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Heuristics for QoS-aware Web Service Composition
Abstract
This paper discusses the quality of service (QoS)-aware composition of Web services. The work is based on the assumption that for each task in a workflow a set of alternative Web services with similar functionality is available and that these Web services have different QoS parameters and costs. This leads to the general optimization problem of how to select Web services for each task so that the overall QoS and cost requirements of the composition are satisfied. Current proposals use exact algorithms or complex heuristics (e.g. genetic algorithms) to solve this problem. An actual implementation of a workflow engine (like our WSQoSX architecture), however, has to be able to solve these optimization problems in real-time and under heavy load. Therefore, we present a heuristic that performs extremely well while providing excellent (almost optimal) solutions. Using simulations, we show that in most cases our heuristic is able to calculate solutions that come as close as 99% to the optimal solution while taking less than 2% of the time of a standard exact algorithm. Further, we also investigate how much and under which circumstances the solution obtained by our heuristic can be further improved by other heuristics
... The time and cost aspects of service compositions have been investigated by several prior works -see for instance the overviews in [8,19,20,26]. In particular the temporal aspect is recognized as crucial for designing service compositions, orchestrations and workflows and defining temporal SLAs [5,9,15,16,21,22,27,29]. Examples of prior work towards design and verification of temporal aspects are [2,4,11,17,18,24]. These approaches rely on formalisms such as timed transition systems, interval temporal logic, and temporal constraint networks, and focus on verifying the existence of schedules or absence of conflicting constraints. ...
... Cost of service invocation in isolation has been considered in several prior works, especially aimed at maximizing Quality of Service of Web service compositions. For instance, in [4], authors propose a heuristic approach for service selection to maximize Quality of Service. The approach proposed in [4] may indeed include cost as one of the non-functional aspects. ...
... For instance, in [4], authors propose a heuristic approach for service selection to maximize Quality of Service. The approach proposed in [4] may indeed include cost as one of the non-functional aspects. ...
Time and cost are crucial criteria in Service Level Agreements. Frequently, the time when and how long a service can be provided or used and the cost for utilizing a service are related and hence users are confronted with a trade-off between time and cost. Besides the fundamental direct and indirect proportional relationship between time and cost, composed services might also have more complex non-monotonic relationships. We introduce a novel way of expressing the trade-offs between time and cost in form of TC-Maps as a set of piece-wise linear functions. For calculating the duration, cost and their relation for service compositions, we introduce specific operations used in a bottom-up procedure resulting in an overall TC-Map. The proposed structure allows us to derive the minimum cost of a composed service given a duration limit, or for analyzing possible durations for a provided budget. TC-Maps offer the basis for optimizing the utilization of composed services according to user preferences, resources and objectives.
... A number of prior works such as [3], [4], [5], [6], considered the temporal, resp. cost dimension in Web service compositions. ...
... We call each [f, t) a duration interval in T . [5,15) is a duration interval in the case of the Data Storing Service. If for a tuple c = null, then this time interval is considered impossible (not offered) -following the semantics of NULL in databases. ...
... The range of time-cost Table I is [5,30) and [10,40) is the range of time-cost Table II. A time-cost table is dense, if all durations within its range are covered by a duration interval, i.e. there are no gaps between the duration intervals. ...
... Others [11,12] handled the discovery of mobile and dynamic services but neglected the existence of static ones. Also, many approaches addressed service selection [5,[13][14][15][16]. Some works [5,13,15,17] considered Quality of Services (QoS) to select the most appropriate ones based on user constraints, without dealing with I/O matching between the related services and service dynamicity. ...
... The solution uses a skyline-based algorithm to reduce the number of candidates resources having identical task. In [14], a QoS-aware Web service composition problem is solved by proposing a heuristic. In the approach, a backtracking algorithm is applied to the results calculated using a Linear Program relaxation, and user constraints, which are defined to the overall service composition, are considered. ...
... Our QoR model is designed in a way that it can support any number and type of QoR attributes, as long as these attributes can be added to the resource description. Therefore, we do not consider the number or the type of QoR taken into account when highlighting our contribution with respect to related work [5,[13][14][15]. ...
In the Web of Things (WoT) context, an increasing number of stationary and mobile objects provide functions as RESTful services, also called resources, that can be combined with other existing Web resources, to create value-added processes. However, nowadays resource discovery and selection are challenging, due to (1) the growing number of resources providing similar functions, making Quality of Resource (QoR) essential to select appropriate resources, (2) the transient nature of resource availability due to sporadic connectivity, and (3) the location changes of mobile objects in time. In this paper, we first present a location-aware resource discovery that relies on a 3-dimensional indexing schema, which considers object location for resource identification. Then, we present a QoR-driven resource selection approach that uses a Selection Strategy Adaptor (SSA) to form i-compositions (with i ∈N*) offering different implementation alternatives. The defined SSA allows forming resource compositions while considering QoR constraints and Inputs/Outputs matching of related resources, as well as resource availability and users different needs (e.g., optimal and optimistic compositions obtained using a scoring system). Analyses are made to evaluate our service quality model against existing ones, and experiments are conducted in different environments setups to study the performance of our solution.
... The approach uses a set of quality attributes incorporated into each resource description expressed with Hydra, and implements a skyline-based algorithm that reduces the set of candidates for a given task. In [4], a heuristic is proposed to solve QoSaware Web service composition problem. It uses a backtracking algorithm on the results computed by a Linear Program relaxation, while considering user constraints given to the overall composition. ...
... The comparison between our QoR model against the QoS model of existing works [2,4,14], is done independently of the number and type of the QoS used, since our work supports various attributes as long as they are presented in resources descriptions. The work in [2] uses 3 attributes: Performance: [0-10], Availability: [0-100], and Reputation: [0-5]. ...
... Also, and besides neglecting I/O matching of the linked services, by applying our threshold formula, a service with a high attribute value (Availability = 90) and a very low value for another one (Performance = 2) is selected over a service with acceptable values for both attributes (Availability = 70 and Performance = 6), as QoS are not normalized. In [4], several QoS are used to describe the services as Response Time and Availability. Contrary to our work, user constraints are given to the global composition (e.g., the overall response time should be < 50s) and not to each service, thus, aggregation functions are used for every QoS parameter. ...
In the Web of Things (WoT) context, an increasing number of objects provide functions as RESTful services (resources), that can be composed with other existing resources, to create value-added processes (compositions). However, to form a composition, selecting the suitable resources is becoming more challenging, due to: (1) the growing number of resources providing identical functions, which calls for the use of Quality of Resource (QoR) to distinguish between them, and (2) the transient nature of resource availability as a result of objects’ sporadic connectivity in the WoT environments. In this chapter, we present a QoR-driven resource selection approach that forms i-compositions (with i \(\in \mathbb {N}^{*}\)) offering different implementation alternatives. This is done using a selection strategy adaptor that considers QoR constraints and Inputs/Outputs matching of related resources, as well as resource availability and users’ different needs (e.g., optimal compositions having the highest scores, and optimistic compositions having acceptable scores but obtained in more satisfactory delays). Analysis are made to evaluate our resource quality model against existing ones, and experiments are conducted in different environments setups to study the performance of our work.
... In the literature, many approaches (i.e., REST-based and SOAP-oriented) addressed service selection [22,25,114,96]. Some works [22,114,120] were based on Quality of Services (QoS) to select the most suitable ones according to user constraints or preferences, without taking into account I/O service matching and service dynamicity. Others [96,66] dealt with the service selection problem as an AI planning problem aiming at finding a sequence of services starting from given inputs and leading to the desired outputs, without considering service matching on the functional level, their QoS, and dynamicity. ...
... In [25], a heuristic-based approach is proposed to solve the QoS-aware Web Service composition problem. The solution aims at maximizing the QoS of the overall Web Service composition, while considering preferences and constraints defined by the user. ...
... In this section, we analyze QoS model of existing works [22,25,114,120], and compare them to our QoR model. This is done independently from the number and type of the quality attributes used, since our solution can support various attributes as long as they are presented in resource descriptions. ...
Nowadays, a plethora of Web-based environments (Web applications, Web platforms, etc.), publish their functions as RESTful services, i.e., self-contained and self-describing resources that follow the REpresentational State Transfer (REST) architectural style principles. As the Web has become a major medium of communication, integrating objects (e.g., smart devices) into the Web and taking advantage of its open popular standards has created an emerging trend: the Web of Things (WoT). In the WoT, objects expose their functions also as resources respecting the REST principles. Each resource provides well defined functions that meet specific users’ requests. However, there are cases in which a single resource is not sufficient to answer users’ requests, and often, combining two or more resources forming a resource composition, achieves the desired output. Nevertheless, several challenges are to be addressed when composing resources.In this thesis, we address three challenges. The first one consists on verifying the behavior of static resource compositions built manually by the user, as several design errors may occur (e.g., end-loops preventing other resources to run, and datatype mismatch between the Inputs/Outputs of the linked resources). For the other two challenges, the targeted Web environments are hybrid providing: (i) dynamic resources (connected to/removed from the environment at different instances), and (ii) static resources (established to be always available). The challenges focus respectively on the automatic resource discovery, while considering resource location (whenever exposed by objects), and the automatic selection of the appropriate resources to form suitable compositions satisfying users’ requests. To cope with these challenges, we first propose a formal model based on Colored Petri Nets (CPN) that maps resources behavior with their composition to CPN. This allows to use CPN behavioral properties to verify the correctness of static compositions behavior. Then, we propose a formal graph representation linking static resource to dynamic ones, allowing adapted graph algorithms to explore the semantically annotated descriptions of the traversed graph resources, in order to identify automatically the required resources. The resource discovery process uses an original defined indexing schema that allows identifying the resources based on their location (if exposed by objects), and enhancing resource search in large Web environments connecting many resources. As for automatic resource selection, we present a Selection Strategy Adaptor that selects the suitable resources to form several compositions with different implementation alternatives, taking into account Quality of Resource (QoR), Inputs/Outputs matching of related resources, as well as resource availability. Our proposal is generic as it can be applicable in Web environments belonging to different application domains. However, in this thesis, it has been illustrated inthe smart buildings domain, more particularly, in projects for managing buildings’ energy behavior.
... To address this issue, many research efforts have proposed computationally efficient, albeit suboptimal, solutions to the service selection problem. Since a MMKP problem can be formally expressed with an IP formulation, a common approach [16,54] is to relax the integer restriction on the variables of the IP problem, thus obtaining a LP problem that can be efficiently solved in polynomial time. The caveat is however that a solution to the relaxed problem does not necessarily solve the original problem. ...
... Therefore, solutions based on a LP formulation are more suited to address the selection problem at per-flow granularity level, where the QoS constraints are evaluated in the long-term and for a flow of requests, rather than the per-request granularity, where individual executions could violate the constraints. The work in [16] proposes an algorithm for finding a sub-optimal solution to the original IP problem by enumerating the solutions of the LP problem in a clever way, until the IP problem constraints are not violated. ...
... Several solutions have been proposed for the self-adaptation of SOSs (e.g. [4,6,9,11,12,16,47,54,58], but very few frameworks and platforms have been realized and To the best of our knowledge, besides MOSES, realized and evaluated platforms are: MUSIC [89], SASSY [66,68], VieDAME [74] and VRESCo [70]. In this section we review the characteristics and features of the aforementioned brokers according to the taxonomy presented in Section 2.3 and compare them to MOSES. ...
Service Oriented Systems (SOSs) based on the SOA paradigm are becoming popular thanks to a widely deployed internetworking infrastructure. They are composed by a possibly large number of heterogeneous third-party subsystems and usually operate in a highly varying execution environment, that make challenging to provide applications with Quality of Service (QoS) guarantees. A well-established approach to face the heterogeneous and varying operating environment is to design a SOS as a runtime self-adaptable software system, so that a prospective enterprise willing to realize a SOA application can dynamically choose the component services that best fit its requirements and the environment in which the application operates. These SOSs are commonly architected as self-adaptive systems following the MAPE-K (Monitor, Analyze, Plan, Execute, and Knowledge) reference model for autonomic computing.
In this thesis we will first present a taxonomy of self-adaptive SOSs and then we
will present the methodology, the design and architecture, and the performance evaluation of MOSES: a QoS-driven autonomic framework for service oriented systems. This framework, which is freely available with an opensource license at http://uniroma2-moses.sourceforge.net, fully implements the MAPE-K reference model by providing a platform for developing, testing and running different adaptation mechanisms exploited by autonomic SOSs. Specifically, we will focus on the methodologies at the core of the Plan phase that support QoS-driven adaptation. To this end, we will propose two policies that follow a different perspective in the request management, by optimizing either each single request or a flow of requests. The design and architecture of MOSES will be discussed according to the layered view of the Cloud Computing stack: we will start from the design and realization of an Infrastructure as a Service (IaaS) on which we deployed the Platform as a Service (PaaS) which acts as a container for MOSES, that in its turn resides at the Software as a Service (SaaS) layer. Finally, we will present the results of an extensive performance evaluation, which takes into account both the effectiveness of the proposed QoS-driven adaptation methodologies and the scalability of the framework.
Thanks to the modular architecture of MOSES, we are confident that its public release will allow the experimentation of alternative approaches to QoS-driven adaptation of Service Oriented Systems.
... The linear programming approach discussed by , and confirmed by Canfora et al. (2005) and Yu et al. (2007), suggested that the approach is not scalable with the number of candidate services and activities in the business process. Genetic algorithms proposed by Canfora et al. (2005Canfora et al. ( , 2008 and a heuristic approach presented by Berbner et al. (2006) for service composition with sequential execution is an improvement over the linear programming approach as they demonstrate the heuristics are very fast and perform significantly better than linear programming based approaches. Menascé et al. (2008) described optimal service selection in SOAs for BPEL-compliant business processes, which allows constructs such as sequence, switch, and flow. ...
... doi:10.1287/ mnsc.42.11.1515Berbner, R., Spahn, M., Repp, N., Heckmann, O., & Steinmetz, R. (2006 Heuristics for QoS-aware Web Service Composition. Proceedings of the IEEE Conference on Web Services (ICWS'06), 72-82. ...
When deployed as infrastructure components of real-time business processes, service computing applications we rely on for our daily activities elicit the proper addressing of performance and dependability issues. While recent developments in service-oriented architectures have come a long way in many aspects, ranging from semantics and ontologies to frameworks and design processes, performance and dependability remains a research demanding field.
Performance and Dependability in Service Computing: Concepts, Techniques and Research Directions highlights current technological trends and related research issues in dedicated chapters without restricting their scope. This book focuses on performance and dependability issues associated with service computing and these two complementary aspects, which include concerns of quality of service (QoS), real-time constraints, security, reliability and other important requirements when it comes to integrating services into real-world business processes and critical applications.
... How to generate optimized composite services by using evaluation conditions of QoS solution. Considering QoS multidimensional attribute characteristics value in service composition, at present, there are main research methods including integer programming [1][2][3], mixed-integer programming [4][5][6], heuristic search algorithm [7][8][9][10][11][12][13][14][15], intelligent algorithm [16][17][18][19][20][21][22][23], etc. ...
... en, Wang et al. proposed an effective optimal service composition method [6] by using mixed-integer programming method from perspective of user trust and preference characteristics. Berbner et al. [7] proposed a heuristic search method considering constraints from QoSaware service composition driven by workflow model. ey used backtracking algorithm to generate effective service composition solution and selected optimal solution of service composition through branch limit method. ...
Edge services are transferred data processing, application running, and implementation of some functional services from cloud central server to network edge server to provide services. Combined edge service can effectively reduce task computation in the cloud, shorten transmission distance of processing data, quickly decompose task of service request, and select the optimal edge service combination to provide service for users. BAS is an efficient intelligent optimization algorithm, which can achieve efficient optimization and neither need to know the specific form of function nor need gradient information. This paper designs an edge service composition model based on edge computing and proposes a method about edge service composition by BAS optimization algorithm. Our proposed method has obvious advantages in service composition efficiency compared with service composition method based on PSO or WPA heuristic algorithm. Compared with cloud service composition method, our proposed method has advantages of shorter service response time, low cost, and high quality of user experience.
... Other approaches have focused on QoS-aware composition of Web Services [2,3,20,53,65] showing a level of similarity with security-aware composition. Aggarwal et al. [2] present a semantic web-based approach for achieving constraint-driven Web service composition. ...
... The tool allows process designers to bind Web Services to an abstract process described as BPEL4WS, based on business and process constraints, and generate an executable process. Berbner et al. [20] present an heuristic approach with the goal of selecting Web Services so that the overall QoS and cost requirements of the composition are satisfied. More recently, Alrifai et al. [3] propose a hybrid solution that combines global optimization with local selection techniques, to produce composite services addressing user constraints on end-to-end QoS. ...
The diffusion of service-based and cloud-based systems has created a scenario where software is often made available as services, offered as commodities over corporate networks or the global net. This scenario supports the definition of business processes as composite services, which are implemented via either static or runtime composition of offerings provided by different suppliers. Fast and accurate evaluation of services’ security properties becomes then a fundamental requirement and is nowadays part of the software development process. In this article, we show how the verification of security properties of composite services can be handled by test-based security certification and built to be effective and efficient in dynamic composition scenarios. Our approach builds on existing security certification schemes for monolithic services and extends them towards service compositions. It virtually certifies composite services, starting from certificates awarded to the component services. We describe three heuristic algorithms for generating runtime test-based evidence of the composite service holding the properties. These algorithms are compared with the corresponding exhaustive algorithm to evaluate their quality and performance. We also evaluate the proposed approach in a real-world industrial scenario, which considers ENGpay online payment system of Engineering Ingegneria Informatica S.p.A. The proposed industrial evaluation presents the utility and generality of the proposed approach by showing how certification results can be used as a basis to establish compliance to Payment Card Industry Data Security Standard.
... To achieve this efficiently, various heuristic approaches are developed. There are two prominent strands: Integer Programming (IP) (e.g., [43], [46], [47]) and Genetic Algorithm (GA) (e.g., [48], [49], [50], [51]) based solutions. ...
... The authors propose to address the complexity problem of global planning by introducing an IP-based solution with a Simple Additive Weighting (SAW) based utility function to determine the desirability of an execution plan. This approach is extended in [47] with more heuristics to promote efficiency. In [43] a hybrid approach of local and global optimization is proposed, in which global constraints are delegated to local tasks, and the constraint delegation is modeled as an IPbased optimization problem. ...
An increasing number of cities are confronted with challenges resulting from the rapid urbanisation and new demands that a rapidly growing digital economy imposes on current applications and information systems. Smart city applications enable city authorities to monitor, manage and provide plans for public resources and infrastructures in city environments, while offering citizens and businesses to develop and use intelligent services in cities. However, providing such smart city applications gives rise to several issues such as semantic heterogeneity and trustworthiness of data sources, and extracting up-to-date information in real time from large-scale dynamic data streams. In order to address these issues, we propose a novel framework with an efficient semantic data processing pipeline, allowing for real-time observation of the pulse of a city. The proposed framework enables efficient semantic integration of data streams and complex event processing on top of real-time data aggregation and quality analysis in a Semantic Web environment. To evaluate our system, we use real-time sensor observations that have been published via an open platform called Open Data Aarhus by the City of Aarhus. We examine the framework utilising Symbolic Aggregate Approximation to reduce the size of data streams, and perform quality analysis taking into account both single and multiple data streams. We also investigate the optimisation of the semantic data discovery and integration based on the proposed stream quality analysis and data aggregation techniques.
... The above mentioned semantic service discovery and composition takes into account only the functional aspects of services. QoS aware service composition and optimisation is NP-hard [31]. Various techniques, e.g., [32,31,[33][34][35], have proposed different heuristics to solve the problem efficiently. ...
... QoS aware service composition and optimisation is NP-hard [31]. Various techniques, e.g., [32,31,[33][34][35], have proposed different heuristics to solve the problem efficiently. ...
... Constraint Programming has been proposed in [6], while Integer Programming and Mixed Linear Integer Programming has been used in [7,8,9] in order to optimize composite service execution plans. Authors of [10] propose a workflow engine (namely "WSQoSX") that builds on top of [7] and [9] to construct a feasible solution based on a backtracking algorithm. A heuristic method to identify services that meet local QoS parameters (resulted by the decomposition of end-to-end QoS constraints) using integer linear programming is introduced in [11,12], while following such a decomposition method and applying fuzzy logic control to support dynamic service selection with the lowest cost is proposed in [13]. ...
... Within the algorithm, the user's preferences are expressed with the weights ) ( n s w for the corresponding parameters (obtained by the relevance feedback mechanism). These values express how important each parameter is considered to be by the user and are expressed through the weight factor of equation (10). ...
Cloud computing is essentially changing the way services are built, provided and consumed. As a paradigm building on a set of combined technologies, it enables service provision through the commoditization of IT assets and on-demand usage patterns. In the emerging era of the Future Internet, clouds aim at facilitating applications that move away from the monolithic approach into an Internet-scale one, thus exploiting information, individual offerings and infrastructures as composite services. In this paper we present an approach for selecting the services (that comprise the composite ones) in order to meet the end-to-end Quality of Service (QoS) requirements. The approach is enhanced with a relevance feedback mechanism that provides additional information with respect to the importance of the content and the service. The latter is performed in an automated way, allowing for user preferences to be considered during the service selection process. We also demonstrate the operation of the implemented approach and evaluate its effectiveness using a real-world scenario, based on a computer vision application.
... There are several ways for implementing SOA, but the most famous and most popular way are run by Web Service technology [2] that depends on infrastructure of World Wide Web and use of open XML standards such as SOAP, WSDL. Another benefit of using web services is their interoperability between different heterogeneous organizations or units [3]. ...
... Many works have been conducted on service changes management area which [16] can be an example. In [3] using intelligent solution for finding optimal solution is suggested. In Table 1 part of works on service composition area is shown. ...
The application of service-orientated architecture in organizations for implementation of complicated workflows in electronic way using composite web services has become widespread. Thus, challenging research issues have also been raised in this regard. One of these issues is constructing composite web services by workflows. These workflows are composed of existing web services. Selections of a web service for each of workflow activities and fulfilling users’ conditions is still regarded as a major challenge. In fact, selection of a web service out of many such web services with identical function is a critical task which generally depends on composite evaluation tool of QoS. Previously proposed approaches do not consider exchange restrictions on the composition process and internal processes of architecture and previous experiences, and they ignore the fact that value of many of QoSs depends on the time of implementation. Selection of web services only based on QoS does not bring about optimal composite web service. Thus, till now, no solution has been proposed that performs composition process automatically or semi-automatically in optimal manner Objective: identification of existing concerns on composition of services and then designing a framework to provide a solution which consider all concerns and finally performing tests in order to examine and evaluate proposed framework Method: in the proposed framework, elements affecting management of service-oriented architecture processes are organized according to a logical procedure. This framework identifies processes of this style of architecture based on requirements in service-oriented architecture processes management and according to qualitative features in this area. In the proposed framework, in addition to using existing data in the problem area, existing structure and patterns in the area of software architecture are also utilize, and management processes in service-orientated architecture are improved based on propriety of available requirements. QWV are qualitative weighted dynamic features which indicate priority of users, and QF is quality factor of service at the time of implementation which is weighted in the framework. These factors are used for constructing composite web service. Multifactor computing is known as a natural computational system for automating the interaction between services. The factors in multi-agent systems can be used as the main reliable mechanism for the control which usually use data exchange for accelerating their evaluations. For identification of all concerns in the solution space, many aspects should be examined. To this end, classes of agents are defined which investigate these aspects in the form of four components using repository data. Results: proposed framework was simulated by Arena software and results showed this framework can be useful in automatic generation of needed services and meet all concerns at the same time. Results support that using agents in the model increased speed of accountability and satisfaction of users as well as system efficiency.
... Therefore, this category is inappropriate for problems where the search space increases exponentially with the size of the problem. The second category is based on heuristic approaches that are too specific and difficult to reuse and apply to other problems [19][20][21][22][23][24]. The third category, meta-heuristic-based approaches provides a near-optimal composition with a reasonable response time and shows high performance [25][26][27][28][29]. ...
In an Internet of Things (IoT) environment, multiple objects usually interact with one another to meet a complex user’s request. This involves the composition of several atomic IoT services. Given a large number of functionally equivalent services with different Quality of Service (QoS) values, the service composition problem remains one of the main challenges in IoT environments. This paper presents a Discrete Adaptive Lion Optimization Algorithm (DALOA) to select IoT services in a composition process while considering global user QoS constraints. DALOA is based on the Lion Optimization Algorithm (LOA) and developed by combining several LOA operators, such as roaming, mating, and migration. First, DALOA divides the initial population into two sub-populations: pride and nomad, and each sub-population has its search strategies. Second, the roaming nomad process follows a random searching mode (strong exploration) to avoid being trapped in local optima. Third, the roaming pride searching mode represents strong local research, ensuring more efficient exploitation. Four, mating (mating pride, mating nomad) allows for information sharing between members of the same population. Finally, the migration operator is used to ensure population diversity by allowing information sharing between the pride and the nomad. The simulation results show that DALOA obtains the best compositional optimality and finds the near-optimal composition of the IoT services in a reasonable execution time compared to other approaches. Indeed, the combination of the previous operators provides a good trade-off between exploration and exploitation.
... In this category of approaches there are heuristic-based algorithms and meta-heuristicbased algorithms [17]. The heuristic-based algorithms (see e.g., [19][20][21]) support limited size workflows and do not find optimal composition [22]. Unlike heuristics, metaheuristics are adapted to various kinds of problems without deeply changes, require less computation time and handle large size workflows with global constraints. ...
The democratization of smart devices over the last decade has given rise what is called the Internet of Thing (IoT). In view of the multitude of functionally equivalent services that have different quality of service (QoS) levels, the services composition is one of the main challenges in the IoT environments where several devices interact with each other to perform a user’s complex task. This paper proposes a QoS-aware services composition approach that exploits a novel bat algorithm (QC-NBA) to compose the best IoT services while considering user’s constraints related to the QoS properties. Unlike most existing bio-inspired services composition approaches, the NBA method includes mechanisms that improve the exploration and exploitation of the composition search space. The bats habitat selection, the Doppler Effect compensation and the self-adaptive local search strategy of the NBA method speed-up the convergence and avoid the local optimum, enhancing therefore the performance of the QC-NBA algorithm in term of execution time and composition quality. The results obtained through the simulation scenarios, show that the QC-NBA approach achieves a good composition in terms of QoS utility and converges faster compared to other services composition baselines.
... Articles included through snowballing[68,69,70,71,72,73,74,75,76,77,78,79] Articles included ad-hoc by us[80,81,82,83, 84, 85, 86, 87] ...
Search-Based Software Engineering (SBSE) is widely used in different fields of Software Engineering, notoriously, in Enterprise Application Integrations (EAIs). EAI encompasses methodologies, techniques and tools that a software engineer can use to create integration solutions. SBSE is currently an active research topic of increasing interest. The number and diversity of publications produced yearly are large to the extent that it is hard to identify the active research groups, their locations, techniques used and research topics that have not received enough attention. To answer these questions categorically, we have conducted systematic mapping study of the literature. In this paper, we report our methodology and findings. In our study, we used systematic search strategies that resulted in the retrieval of 560 articles, of which we first selected 25. Second, on the basis of the authors’ experience, we included eight additional articles. Finally, we used a snowballing sample technique to include another 12 articles. The results demonstrate that during the last two decades (1999–2020) EAI has benefited from the use of Search-Based Software Engineering techniques.
... In [18], the authors analyzed quality of service (QoS) in composition of web services. Their work is based on the assumption that for each task in a set of web services with similar functionalities, they have different QoS, parameters and costs, so this leads to an optimization problem when selecting web services for each task. ...
Web development, machine ubiquity, and the availability of communication networks impacted device design, replacing the idea of an isolated personal computer with one of distributed and connected computers. A web service is a component of software which provides a specific functionality that can be accessed over the Internet. Software development through the assembly of independent services follows the Service-Oriented Computing (SOC) paradigm. One key in the SOC model is that third parties provide resources by presenting only external access interfaces. In this context, the analysis of issues related to the quality of service (QoS) becomes crucial for several development activities related to web services, spanning the discovery of services, their selection, composition and their adaptation in client systems. As far as we know, little has been done in terms of estimation of unknown quality attribute levels when those attributes have high priority in client systems. In this study, a linear regression-based statistical approach is explored to evaluate the relationship between the quality attributes provided by Web services and the metrics related to their interfaces defined in WSDL. This issue is a cornerstone in web service composition for verifying and ascertaining the levels of quality attributes provided by candidate services when QoS data is missing. Finally, we illustrate the approach by performing experiments with public QoS web service datasets and service interface metrics, explore its limitations, and delineate future steps.
... Therefore, it is not surprising that research about QoS-aware Service Composition started just a few years after the service composition concept itself was proposed. This is true for automatic composition, but QoS adds significant complexity even to manual composition (for example, see the work of [Ber+06]). ...
The automatic composition of web services refers to how services can be used in a complex and aggregate manner, to serve a specific and known functionality. Given a list of services described by the input and output parameters, and a request of a similar structure: the initially known and required parameters; a solution can be designed to automatically search for the set of web services that satisfy the request, under certain constraints. We first propose two very efficient algorithms that solve the problem of the automatic composition of the web services as it was formulated in the competitions organized in 2005 and 2008. The algorithms obtain much better results than the rest of the participants with respect to execution time and even composition size. Evaluation consists of running the previous and the proposed solutions on given benchmarks and generated tests. Further, we design two new models to match service's parameters, extending the semantic expressiveness of the 2008 challenge. The initial goal is to resolve some simple and practical use-cases that cannot be expressed in the previous models. We also adhere to modern service description languages, like OpenAPI and especially schema.org. Algorithms for the new models can solve instances of significant size. Addressing a wider and more realistic perspective, we define the online version of the composition problem. In this regard, we consider that web services and compositions requests can be added and removed in real-time, and the system must handle such operations on the fly. It is necessary to maintain the workflows for users who actively run the compositions over time. As for the newly semantic model algorithms, we propose new algorithms and provide comprehensive evaluation by generating test cases that simulate all corner cases.
... When the candidate service solution set is small, most of the existing methods can effectively solve the problem of service composition. However, when the scale becomes larger, the fast-growing time consumption will not meet the needs of real-time tasks (Berbner et al. 2006). Moreover, with the emerging of information overload problem, to a certain extent, the new introduced services are invoked by requests are limited in the service pool. ...
Owing to the rapid proliferation of service technologies in cross-enterprise manufacturing collaborations, manufacturing service composition (MSC) has attracted much attention from both academia and industries. However, the existing service composition is often constructed by the combination of off-line and on-line services, quality of service (QoS) attributes are not appropriate for satisfying the specific demands of MSC. Moreover, there are very few historical QoS invocations of manufacturing service, leading to difficulty in recommending appropriate service composition to a target user. In order to find the personalized MSC mode from a complex service network more accurately, we combine combinatorial optimization with collaborative filtering in this paper to figure out two questions: (1) how to construct a QoS description model of manufacturing service composition; (2) how to enhance the effectiveness of personalized QoS-aware service composition recommendations. First, the new QoS model of MSC is proposed by considering both traditional characteristics (e.g. availability, performance and reliability), variability of service composition and enterprise dimensional QoS attributes. Second, the service combination optimization is constructed based on combinatorial optimization method. Third, the collaborative filtering is employed to calculate the missing QoS values of the candidate manufacturing services. Finally, with both available objective functions and predicted QoS values, optimal service composition recommendation can be generated by using combinatorial optimization model with QoS constraints.
... Dans [12], les auteurs proposent une méthode heuristique pour résoudre le problème de composition. Dans ce travail, les auteurs utilisent une fonction d'agrégation afin de calculer l'utilité de l'ensemble du service composite. ...
Nowadays, service composition is one of the major problems in the Cloud due to the exceptional growth number of service deployed by providers. Recently, atomic services cannot deal with all client requirements. Traditional service composition gives the clients a composite service without non-functional parameters. To respond to both functional and non-functional parameters, we need a service composition. Since web services cannot communicate with each other or participate dynamically in service composition, this issue led us to use a dynamic entity represented by an agent. This work proposes an agent-based architecture with a new cooperation protocol that can offer an automatic and adaptable service composition by giving composite service with a maximum number of quality of service (QoS). As the provider uses the cloud to deploy their services, which this process needs to be handled well to make the service operate in best conditions according to QoS values. In order to deploy services in the Cloud, each one needs some combination of services model. When we mentioned combination problems, service composition represents the solution to this issue. Besides, each service provider looks for the best service deployment that gives his service the best conditions through the quality of service. The present thesis transforms the service deployment problem into an optimization problem. Moreover, in this thesis, we proposed a service description model that assists in the service discovery process.
... Moreover, it uses coefficients based on user preferences to prioritize or other requirements. Heuristic approach [15] divides QoS parameters into three groups: additive parameters, multiplicative parameters and attributes aggregated by Min-operator. Also this approach provides SLA monitoring and reconfiguration. ...
Web Service Composition (WSC) is a process that helps to save much programming and cost effort by reusing existing components – web services. This process consists of two major stages – Web Service Discovery and Selection (WSD, WSS). This paper presents an overview of current state-of-the-art WSD and WSS methods. It also provides an analysis and highlighting of major problems like lack of support of the syntactical description in fuzzy logic algorithms in WSD and complex approach shortage in WSS problem. Moreover WSC approach and SLA-Aware WSC System are presented.
... They use a GA-based approach on a synthetic process and compare the performance to an integer programming approach, utilizing execution time and overall fitness as the basis for comparison. Berbner et al. (2006) utilized three heuristics involving backtracking, swapping, and annealing. Using generic QoS measures on a synthetic process, they assessed the heuristics on computation time and approximation ratio. ...
The need to create and deploy business application systems rapidly has sparked interest in using web services to compose them. When creating mission-critical business applications through web service compositions, in addition to ensuring that functional requirements are met, designers need to consider the end-to-end reliability, security, performance, and overall cost of the application. As the number of available coarse-grain business services grows, the problem of selecting appropriate services quickly becomes combinatorially explosive for realistic-sized business applications. This article develops a business-process-driven approach for composing service-oriented applications. We use a combination of weights to explore the entire QoS criteria landscape through the use of a multi-criteria genetic algorithm (GA) to identify a Pareto-optimal multidimensional frontier that permits managers to trade off conflicting objectives when selecting a set of services. We illustrate the effectiveness of the approach by applying it to a real-world drop-ship business application and compare its performance to another GA-based approach for service composition.
... Hill climbing, BFS and A * algorithms are few examples of heuristic approaches. for the detailed exposition of heuristic approaches, please refer to the [15], [16], [17], [18], [19]. ...
Web services are application software which can be remotely accessed through the Internet. Due to the proliferate the growth of web services of the same functionality, the user goes into a dilemma to select suitable service for him. In this paper, we study the web service selection problem (WSS) in a sequential composition model. We formulated the WSS as a constrained optimization problem. To solve the problem we suggest, a modified artificial bee colony (mABC) algorithm, which uses a chaotic based opposition learning method to generate a better initial population. To improve the exploration capability of mABC, a new search equation for employee bee phase is suggested. On the other hand, to improve the exploitation capacity of mABC, a new search strategy, inspired by differential evolution (DE), is adopted in the onlooker bee phase. We test mABC on synthetic web service selection problem taken from QWS dataset. To asses the relative performance of mABC, we compare it against five other state-of-the-art algorithms. The experimental results show that mABC is better than other existing approaches in terms of response time, latency, availability and reliability.
... Bonatti et al. [26] have proven that the problem of service composition with global QoS constraints is NP-complete. Various heuristic algorithms have been proposed to reduce the search space, such that the service requester can efficiently obtain a near-optimal solution [27]. Huat et al. [28] proposed probabilistic ranking and hierarchical refinement that enable smart exploration of the search space by leveraging the information of global constraints for the service providers. ...
... According to ITU E.800 [8] and ISO/IEC 20000 [7], QoS include nonfunctional attributes such as reliability, availability, throughput, latency, cost etc. Berbner et al. [5] pointed out that mathematically QoS properties' values should be real numbers together with precise interpretations. Nevertheless, the mandatory constraint is not usually suitable for describing QoS attributes in current applications, as QoS data is estimated from a large amount of historical data and is hard to obtain in some particular enterprises due to certain restraints, such as economic and time constraints, so that the confidence level of data lies in the interval [0, 1]. ...
The quality of service (QoS)-aware service composition problem is a lively topic of debate because of the fuzziness in the quality data and the user-oriented specific QoS requirements. The aim of this paper is to develop a model to select the most suitable service composition in a way that maximizes solutions expressed as functions over fuzzy/crisp QoS attributes, while satisfying user’s QoS requirements. In this paper, based on fuzzy set theory (FST) and genetic algorithm (GA), a triangular fuzzy genetic algorithm (TGA) is proposed for solving the service composition problem. The following set of strategies are presented: a quality model including crisp and fuzzy properties represented by triangular fuzzy numbers, a feasible method of normalizing the QoS matrix, aggregating formulas of each control structure for eight properties, a practicable method of defuzzification, a global best strategy with a fitness function which calculates the QoS priority vector and is considered as an objective evaluation criterion for selecting an optimal solution that meets user’s preferences best. Empirical comparisons with two algorithms on different scales of composite service indicate that TGA is highly competitive in regards to search capability, especially when the problem size is large. The results may be helpful to designers in selecting the best services for building a service-oriented system.
... One possibility to reduce the complexity of the problem is to aim for finding near optimal solutions using heuristic approaches, rather than optimal solutions. Many heuristics have already been proposed to solve composite service selection [32], [34], [35] or for combinatorial auctions [33]. However, it's not possible to apply any of these heuristics directly to a composite service selection problem based on combinatorial auctions. ...
Composite service selection refers to the process of selecting an optimal set of web services out of a pool of available candidates based on their quality of service and price. The goal is to logically compose these atomic web services and create value-added composite services which in turn can be used to develop service-based systems. Existing approaches to composite service selection are mostly based on optimization and negotiation techniques. In this paper, we study an emerging trend of composite service selection approaches based on auction models. These techniques benefit from the dynamic pricing of auction models compared to a fixed pricing approach and have the potential to incorporate the dependencies that exist between services constituting a composition. We propose a design framework that introduces two components which need to be addressed when developing an auction-based model for composite service selection: the elements in an auction-based model and a set of design decisions associated with those elements.
... Although there is a large body of work related to assembling selected services for web service compositions based on QoS parameters in SLAs, we are not aware of any work that attempts to provision services or demands across a network using SLAs that have the ability to provide resiliency from geographic challenges in the network. With respect to provisioning based on SLAs, most of the research is related to composing web services to meet a particular QoS level as proposed in [7] and [4]. These works assume that the number of web services to choose from are large and, therefore, present a difficult problem. ...
During disasters and other geographically correlated failures, the local telecommunications infrastructure undergoes a unique set of challenges. First, the telecommunications infrastructure is typically damaged reducing the capability to sustain the normal level of demands on the networks. Second, the demands on the telecommunications infrastructure increase typically by an order of magnitude. This is both for critical demands and non-critical demands. Third, critical demands, which may now be used to support disaster first responder and recovery efforts take on a crucial role. In this work, we propose multi-situational linear programming techniques to create disaster modes that take advantage of the non-coincidence of disasters in different geographic areas simultaneously reducing cost and improving restoration of demands during disasters. We also propose efficient heuristics to provision for disasters at a lower cost than standard provisioning with 1 + 1 redundancy. Additionally, we use diverse routing techniques to reduce the likelihood of damage to critical services. The restoration of demands during disasters also presents challenges for network provisioners. We present both heuristic and linear programming methods to assist with restoration of services in stressed network environments giving critical demands priority. Finally, service level agreements (SLAs) are used to provide a framework for these concepts. © 2018 This is a U.S. Government work and not under
... Furthermore, in real world settings, a greedy approach may negatively affect the runtime of the pipeline. Hence, to provide a more efficient framework for creating QA pipelines, we plan to replace the greedy approach with concepts similar to web service composition [2], where we assign cost metrics (e.g., precision, runtime, or memory consumption) to select components using a pipeline optimiser in an automatic way. ...
Modern question answering (QA) systems need to flexibly integrate a number of components specialised to fulfil specific tasks in a QA pipeline. Key QA tasks include Named Entity Recognition and Disambiguation, Relation Extraction, and Query Building. Since a number of different software components exist that implement different strategies for each of these tasks, it is a major challenge to select and combine the most suitable components into a QA system, given the characteristics of a question. We study this op-timisation problem and train Classifiers, which take features of a question as input and have the goal of optimising the selection of QA components based on those features. We then devise a greedy algorithm to identify the pipelines that include the suitable components and can effectively answer the given question. We implement this model within Frankenstein a QA framework able to select QA components and compose QA pipelines. We evaluate the effectiveness of the pipelines generated by Frankenstein using the QALD and LC-QuAD benchmarks. These results not only suggest that Frankenstein precisely solves the QA optimisation problem, but also enables the automatic composition of optimised QA pipelines, which outperform the static Baseline QA pipeline. Thanks to this flexible and fully automated pipeline generation process, new QA components can be easily included in Frankenstein thus improving the performance of the generated pipelines.
The problem of service composition is the process of assigning resources to services from a pool of available ones in the shortest possible time so that the overall quality of service is maximized. This article provides solutions for the composition problem that takes into account its scalability, services' locations, and users' restrictions, which are key for the management of applications using state‐of‐the‐art technologies. The provided solutions use different techniques, including genetic algorithms and heuristics. We provide an extensive experimental evaluation, which shows the pros and cons of each of them, and allows us to characterize the preferred option for each specific problem. Since no solution dominates the others, we propose a decision tree, based on our results, to select the best composition algorithm in each situation.
Offering services maintaining the requested QoS-levels is the main concern of service discovery approaches. The efficiency of such approaches can be measured often in terms of execution time. Most of the existing works focus on the low execution time but do not consider the provision of closer alternatives in case of “unsuccessful search” . Search method becomes unsuccessful if the query fails to discover services having necessary QoS metrics with desired levels. Available alternatives with a minimum compromise in case of “unsuccessful search” may enhance the efficiency. Method of query relaxation is a well-accepted approach for enhancing customer satisfaction. All the existing works on query relaxation concentrate on relaxing strategy while compromising execution time. Moreover, often the inputs from users regarding preference on QoS metrics are needed for offering a solution. These intermediate interventions increase execution time, and the solution highly depends on the domain knowledge of the consumers. Here, we have proposed an approach, capable of offering a set of alternative solution through query relaxation in a fully automated way without compromising in terms of execution time. A lattice-based meta-model with a subsequent discovery mechanism is presented that relaxes the query in terms of QoSs for providing possible alternatives. Moreover, the solution exhibits well with execution time complexity of (O(klogn)) that is comparable to the best solution in the service discovery domain.
The Web service composition refers to the aggregation of Web services to meet customers' needs in the construction of complex applications. The selection among a large number of Web services that provide the desired functionalities for the composition is generally driven by QoS (Quality of Service) attributes, and formulated as a constrained multi-objective optimization problem. However, many equally important QoS attributes exist and in this situation the performance of the multi-objective algorithms can be degraded. To deal properly with this problem we investigate in this chapter a solution based in many-objective optimization algorithms. We conduct an empirical analysis to measure the performance of the proposed solution with the following preference relations: Controlling the Dominance Area of Solutions, Maximum Ranking and Average Ranking. These preference relations are implemented with NSGA-II using five objectives. A set of performance measures is used to investigate how these techniques affect convergence and diversity of the search in the WSC context.
As more web services that implement core functions of business are delivered to customers with service charges, an open and competitive business web services market must be established. However, the qualities of these business web services are unknown without real experiences and users are unable to make decisions on service selection. To address this problem, the authors adopt insurance into business web services composition. In this paper, the authors propose three insurance models for business web services. Based on the insurance models, the authors propose an approach to compute the expected profit of composite business web services, which can be used as a criterion for business web services composition. The insurance of business web services and the criterion for business web services composition will help service competition and boost the development of more business web services and the software industry.
Web services technologies promise to create new business applications by composing existing services and to publish these applications as services for further composition. The business logic of applications is described by abstract processes consisting of tasks which specify the required functionality. Web services provision refers to assigning concrete Web services to perform the constituent tasks of abstract processes. It describes a promising scenario where Web services are dynamically chosen and invoked according to their up-to-date functional and non-functional capabilities. It introduces many challenging problems and has therefore received much attention. In this article, the authors provide a comprehensive overview of current research efforts. The authors divide the lifecycle of Web services provision into three steps: service discovery, service selection, and service contracting. They also distinguish three types of Web services provision according to the functional relationship between services and tasks: independent provision, cooperative provision and multiple provision. Following this taxonomy, we investigate existing works in Web services provision, discuss open problems, and shed some light on potential research directions.
Semantic web service compositions must be aligned with requirements from the target users in terms of quality requirements. Given a set of quality requirements, one can choose to either find the optimal composition or a “good enough” composition, which satisfies these requirements. Since optimizing compositions of semantic services under quality constraints is known to be NP-hard, it is unsuitable for realistic problems within large search spaces. The authors address the issue by using the “good enough” approach, selecting the first composition that passes their quality threshold. Firstly, this paper defines quality constraints within an innovative and extensible model designed to balance semantic fit (or functional quality) with quality of service (QoS) metrics. The semantic fit criterion evaluates the quality of semantic links between the semantic descriptions of Web services parameters, while QoS focuses on non-functional criteria of services. User quality requirements are met by selecting a valid composition. To allow the use of this model with a large number of candidate services as foreseen by the strategic EC-funded project SOA4All the authors formulate the selection problem as a Constraint Satisfaction Problem and test the use of a stochastic search method.
An important area of services research gathering momentum is the ability to take a generic business process and instantiate it by selecting services that meet both the functional and non-functional requirements of the process owner. These non-functional or quality-of-service (QoS) requirements may describe essential performance and dependability requirements and apply across different logical layers of the application, from business-related details to system infrastructure; i.e., they are cross-cutting and considered multidimensional. Configuring an abstract business process with the “best” services to meet the process owner’s multidimensional end-to-end QoS requirements is a challenging task as there may be many services that match to the functional requirements but provide differentiated QoS characteristics. In this chapter we explore an approach to discover services, differentiated by their QoS attributes, to configure an abstract business process by selecting an optimal configuration of the “best” QoS combinations. The approach considered takes into account the optimal choice of multi-dimensional QoS variables. We present and compare two solutions based on heuristic algorithms to illustrate how this approach would work practically.
The use of Service Oriented Architectures (SOA) enables the existence of a market of service providers delivering functionally equivalent services at different Quality of Service (QoS) and cost levels. The QoS of composite applications can typically be described in terms of metrics such as response time, availability, and throughput of the services that compose the application. A global utility function of the various QoS metrics is the objective function used to determine a near-optimal selection of service providers that support the composite application. This chapter describes the architecture of a QoS Broker that manages the performance of composite applications. The broker continually monitors the utility of the applications and triggers a new service selection when the utility falls below a pre-established threshold or when a service provider fails. A proof-of-concept prototype of the QoS broker demonstrates how it maintains the average utility of the composite application above the threshold in spite of service provider failures and performance degradation.
With the on-going trends of the telecom services, the number of service providers with similar functionalities is undergoing a rapid growth. The customers face the difficulty to decide which service provider can satisfy their needs and full their requirements. Negotiating contracts between involved parts, and hiding heterogeneity in the distributed network environment has been challenging for telecom operators and service providers. Different languages exist to describe the Service Level Agreement (SLA), which is a contract between a service provider and a customer. However, since each service provider expresses his SLA in his own way, it disrupts the customer's choice of the best service provider, and leads to a bad contract management. In this respect, we propose a novel architecture for service selection, and SLA management between different stakeholders in our network architecture. The idea is to set up a smart broker where we implemented a Multi-Criteria Decision Making (MCDM) method to maximize utility function so that the customer can choose services with required QoS performances. We also came up with the idea of settling a negotiation model for the SLA, and a context based SLA contract ontology in IP Multimedia Subsystem (IMS) network is also proposed to provide users with a clear model to express their requirements and preferences. Moreover, we used the New Generation Operations Systems and Software (NGOSS) Framework to model and analyze networks and services actions. To better understand the relationship and the projection of NGOSS Framework and IMS platform, we introduce an SLA management and monitoring architecture in IMS network.
Most state-of-the-art service selection approaches assume user preferences can be provided by the target user with sufficient precision and ignore historical service usage data for all users. It is desirable for ordinary users to possess a new service selection approach that can recommend satisfactory services to them even when their service selection preferences are specified imprecisely in terms of vagueness, inaccuracy, and incompleteness. This paper proposes a novel service selection approach that resolves the imprecise characteristics of user preferences and can recommend satisfactory services for users with varying cognitive levels in terms of service experience. The proposed service selection approach comprises of four major tasks: 1) employ user-friendly linguistic variables to collect apparent user preferences (AUP) and convert the linguistic variables to standardized fuzzy weights as AUP weights; 2) evaluate all users’ respective cognitive levels for the target service type and obtain the cognitive level threshold for that type of services; 3) adjust the AUP weights based on the calculated cognitive levels and the threshold, and supplement the potential user preferences (PUP) weights; and 4) prioritize candidate services per a user satisfaction maximization objective. In-depth comparative experimental evaluations were performed using two real-world datasets. The results show that our service selection model outperforms three other representative ones and could provide a stable and reliable selection of services for the users with low service cognitive levels.
This paper introduces an approach that allows Web services to handle user requests where the price that the users are willing to pay is fixed. In such cases, a user search for the highest quality of service based on the submitted fixed price. Instead of searching for individual Web services, the user finds it more convenient to send requests to middlemen (or brokers) who act on behalf of a group of Web services. These middlemen then select a Web service within the group to handle the request. In this paper we demonstrate how fixed price requests can be included into the operation of a community of Web services. Our approach introduces auction theory into the selection process. Experiments using real world values are conducted to demonstrate the effectiveness of the approach.
QoS-Aware service selection seeks to find the optimal service providers to achieve the optimization goal of a service requester, such as the maximization of utility, while satisfying global QoS requirements. Service providers are usually self-interested and have some private information, such as minimum prices, that would significantly factor into the decision making of the service requester. Thus, service requesters face a decision making dilemma with incomplete information. Recent work has used iterative combinatorial auctions to address this problem. However, such studies do not sufficiently consider that the service requester can elicit the private information from service providers by observing their actions. This can help the service selection process achieve better outcomes. In this paper, we propose a type of incentive contract that can motivate the service providers to offer the QoS and prices that the service requester prefers. Based on the incentive contracts, we propose an incentive mechanism for effective service selection. In the mechanism, a service requester offers a set of incentive contracts to the service providers and then elicits their private information based on their responses to the incentive contracts. The process is iterated until the service requester finally obtains a solution that fulfills the global QoS requirements. Experimental results show that the incentive contracts have a positive impact on both service requesters and providers and that the incentive mechanism outperforms the existing combinatorial auction-based approaches in finding optimal solutions.
The proliferation of sensor devices and services along with the advances in event processing brings many new opportunities as well as challenges. It is now possible to provide, analyze and react upon real-time, complex events in urban environments. When existing event services do not provide such complex events directly, an event service composition maybe required. However, it is difficult to determine which event service candidates (or service compositions) best suit users' and applications' quality-of-service requirements. A sub-optimal service composition may lead to inaccurate event detection, lack of system robustness etc. In this paper, the authors address these issues by first providing a quality-of-service aggregation schema for complex event service compositions and then developing a genetic algorithm to efficiently create near-optimal event service compositions. The authors evaluate their approach with both real sensor data collected via Internet-of-Things services as well as synthesised datasets.
Service composition is a key enabling technology in service-oriented computing for developing versatile applications by integrating various existing interoperable services. Although actively studied, most existing works on service composition neglect the existence of complementarity among candidate services within a service class, so-called internal complementarity. In fact, complementary candidate services within a service class can be composed to form a composite candidate service which may yield better service utility than that provided by any existing candidate service within that service class. This work focuses on web service composition where internal complementarity is more likely to happen. Specifically, we aim at addressing the problem of QoS-aware web service selection with internal complementarity (WSS-IC). We first transform this problem into a multi-choice multi-dimensional knapsack problem (MMKP) and prove such a transformation per se has non-polynomial time complexity in the worse case.Then, we perform complexity analysis to demonstrate that existing approaches to MMKPs are not computationally feasible to resolve QoS-aware WSS-IC. This fact motivates us to propose an iteratively improving framework for deriving the solution iteration by iteration while taking into account both solution structure and QoS constraints. At each iteration, the current solution gets improved by solving a disjunctively constrained knapsack problem. To verify the effectiveness of the proposed framework, two heuristic approaches are implemented under this framework. Experimental results demonstrate that our approaches outperform the compared methods in terms of both solution quality and computation time.
Software as a service is a well accepted software deployment and distribution model that has grown exponentially in the last few years. One of the biggest benefits of SaaS is the automated composition of different services in a composite system. It allows users to automatically find and bind these services (to maximize the productivity), meeting both functional and non-functional requirements. In this paper, we present a framework for modeling the dependency relationships among different Quality of Service parameters of the component services. Our proposed approach considers the different invocation patterns of component services, and presents a service composition framework to model the dependencies and uses the global QoS for service selection. We evaluate the efficiency of our proposed technique on the WSDream-QoS Dataset [1].
We discuss possible Web Service Management (WSM) and Web Service Composition Management (WSCM) applications of the Web Service
Offerings Language (WSOL) and how the language supports these applications. WSOL is a novel language for the formal specification
of classes of service, various constraints (functional constraints, Quality of Service — QoS, and access rights), and management
statements (subscription and pay-per-use prices, monetary penalties, and management responsibilities) for Web Services. Describing
a Web Service in WSOL, in addition to the Web Services Description Language (WSDL), enables monitoring, metering, and management
of Web Services. Metering of QoS metrics and evaluation of constraints can be the responsibility of the provider Web Service,
the consumer, and/or one or more mutually trusted third parties (SOAP intermediaries or probes). Further, manipulation of
classes of service (switching, deactivation/reactivation, and dynamic creation) can be used for dynamic (i.e., run-time) adaptation
and management of Web Service compositions.
Organizations have been aware of the importance of quality of service (QoS) for competitiveness for some time. It has been widely recognized that workflow systems are a suitable solution for managing the QoS of processes and workflows. The correct management of the QoS of workflows allows for organizations to increase customer satisfaction, reduce internal costs, and increase added value services. In this paper we show a novel method, composed of several phases, describing how organizations can apply data mining algorithms to predict the QoS for their running workflow instances. Our method has been validated using experimentation by applying different data mining algorithms to predict the QoS of workflow
Run-time service discovery and late-binding constitute some of the most challenging issues of service-oriented software engineering. For late-binding to be effective in the case of composite services, a QoS-aware composition mechanism is needed. This means determining the set of services that, once composed, not only will perform the required functionality, but also will best contribute to achieve the level of QoS promised in service level agreements (SLAs). However, QoS-aware composition relies on estimated QoS values and workflow execution paths previously obtained using a monitoring mechanism. At run-time, the actual QoS values may deviate from the estimations, or the execution path may not be the one foreseen. These changes could increase the risk of breaking SLAs and obtaining a poor QoS. Such a risk could be avoided by replanning the service bindings of the workflow slice still to be executed. This paper proposes an approach to trigger and perform composite service replanning during execution. An evaluation has been performed simulating execution and replanning on a set of composite service workflows.
Flexible business processes are a key success factor for enterprises to succeed in globalised markets. The Service-oriented Architecture (SoA) concept is very well suited to support flexible business processes and application systems because capabilities (in form of services) can be composed in the most efficient way to achieve a high level of agility. However, the management of SoA-founded application systems is often neglected. Thus, we present an approach that enhances the traditional SoA concept by additional management functionality, e.g. monitoring mechanisms and SLA management. As a validation of our concept we introduce WSQoSX, a prototypical implementation based on Web Services.
Web services are rapidly changing the landscape of software engineering. One of the most interesting challenges introduced by web services is represented by Quality Of Service (QoS)--aware composition and late--binding. This allows to bind, at run--time, a service--oriented system with a set of services that, among those providing the required features, meet some non--functional constraints, and optimize criteria such as the overall cost or response time. In other words, QoS--aware composition can be modeled as an optimization problem.We propose to adopt Genetic Algorithms to this aim. Genetic Algorithms, while being slower than integer programming, represent a more scalable choice, and are more suitable to handle generic QoS attributes. The paper describes our approach and its applicability, advantages and weaknesses, discussing results of some numerical simulations.
Our Web Service Offerings Language (WSOL) enables formal specification of important management information - classes of service (modeled as service offerings), various types of constraint (functional, QoS, access rights), and management statements (e.g., prices, penalties, and management responsibilities) - for XML (Extensible Markup Language) Web services. To demonstrate the usefulness of WSOL for the management of Web services and their compositions, we have developed a corresponding management infrastructure, the Web Service Offerings Infrastructure (WSOI). WSOI enables monitoring and accounting of WSOL service offerings and their dynamic manipulation. To support monitoring of WSOL service offerings, we have extended the Apache Axis open-source SOAP engine with WSOI-specific modules, data structures, and management ports. To support dynamic manipulation of WSOL service offerings, we have developed appropriate algorithms, protocols, and management port types and built into WSOI modules and data structures for their implementation. Apart from provisioning of WSOL-enabled Web services, we are using WSOI to perform experiments comparing dynamic manipulation of WSOL service offerings and alternatives.
The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online business-to-business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different quality of service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming.
In times of globalisation and internationalisation enterprises have to establish flexible business processes to react to dynamically changing markets and to satisfy sophisticated customers. IT architectures that support the integration of legacy systems as well as the collaboration with business partners are a key success factor for flexible business processes. Thus, we present an approach to support flexible business processes by the means of a Service-oriented Architecture (SoA). Web Services as a realization of a Service-oriented Architecture gain more and more in importance to implement business processes. We address Quality of Service (QoS) as crucial for a sustainable success of Web Service based workflows. Thus, we designed and implemented a Web Service architecture with comprehensive QoS support. The selection of a particular Web Service depends on its QoS properties that must be guaranteed in Service Level Agreements (SLAs). The compliance with such SLAs is monitored by a component of the architecture as well.
Workflow management systems (WfMSs) have been used to support various types of business processes for more than a decade now. In workflows or Web processes for e-commerce and Web service applications, suppliers and customers define a binding agreement or contract between the two parties, specifying quality of service (QoS) items such as products or services to be delivered, deadlines, quality of products, and cost of services. The management of QoS metrics directly impacts the success of organizations participating in e-commerce. Therefore, when services or products are created or managed using workflows or Web processes, the underlying workflow engine must accept the specifications and be able to estimate, monitor, and control the QoS rendered to customers. In this paper, we present a predictive QoS model that makes it possible to compute the quality of service for workflows automatically based on atomic task QoS attributes. We also present the implementation of our QoS model for the METEOR workflow system. We describe the components that have been changed or added, and discuss how they interact to enable the management of QoS.
One of the promises of the service-oriented architecture (SOA) is that complex services can be easily composed using individual services from various service providers. Individual services can be selected and in- tegrated either statically or dynamically based on the service functionali- ties and performance constraints. For many distributed applications, the runtime performance (e.g. end-to-end delay, overall cost, service reliabil- ity and availability) of complex services are very important. In our earlier work, we have studied the service selection problem for complex services with only one QoS constraint. This paper extends the service selection problem to multiple QoS constraints. The problem can be modelled in two ways: the combinatorial model and the graph model. The combina- torial model deflnes the problem as the multi-dimension multi-choice 0-1 knapsack problem (MMKP). The graph model deflnes the problem as the multi-constraint optimal path (MCOP) problem. We propose algo- rithms for both models and study their performances by test cases. We also compare the pros & cons between the two models.
Emerging Web services standards enable the development of large-scale applications in open environments. In particular, they enable services to be dynamically bound. However, current techniques fail to address the critical problem of selecting the right service instances. Service selection should be determined based on user preferences and business policies, and consider the trustworthiness of service instances. We propose a multiagent approach that naturally provides a solution to the selection problem. This approach is based on an architecture and programming model in which agents represent applications and services. The agents support considerations of semantics and quality of service (QoS). They interact and share information, in essence creating an ecosystem of collaborative service providers and consumers. Consequently, our approach enables applications to be dynamically configured at runtime in a manner that continually adapts to the preferences of the participants. Our agents are designed using decision theory and use ontologies. We evaluate our approach through simulation experiments.
Web services technology has generated a lot interest, but its adoption rate has been slow. This paper discusses issues related to this slow take up and argues that quality of services is one of the contributing factors. The paper proposes a new Web services discovery model in which the functional and non-functional requirements (i.e. quality of services) are taken into account for the service discovery. The proposed model should give Web services consumers some confidence about the quality of service of the discovered Web services.
Web services are modular web applications that can be independently deployed and invoked by other software or services on the web. This offers enterprises the capability to integrate in-house business services with external Web services to conduct complex business transactions. The integration efficiency and flexibility are critical for services composition. For Web services providing a similar functionality, Quality of Service (QoS) is the main factor to differentiate them. The overall QoS of a business process must meet a user's requirement. In this paper, we propose a broker-based framework to facilitate dynamic integration and adaptation of QoS-aware Web services with end-to-end QoS constraints. The key functions of a dynamic broker include service collection, selection, composition and adaptation. Our study considers both functional and QoS characteristics of Web services to identify the optimal business process solutions.
Creating Web processes using Web service technology gives us the opportunity for selecting new services, which best suit our need at the moment. Doing this automatically requires us to quantify our criteria for selection. In addition, there are challenging issues of correctness and optimality. We present a constraint driven Web service composition tool in METEOR-S, which allows the process designers to bind Web services to an abstract process, based on business and process constraints and generate an executable process. Our approach is to reduce much of the service composition problem to a constraint satisfaction problem. It uses a multiphase approach for constraint analysis. This work was done as part of the METEORS framework, which aims to support the complete lifecycle of semantic Web processes.
QoS (quality of service) support in Web services is an important issue. We present a QoS-capable Web service architecture, QCWS, by introducing a QoS broker module between service clients and providers (servers). The functions of the QoS broker module include collecting QoS information about servers, making selection decisions for clients, and negotiating with servers to get QoS commitments. We propose two resource allocation algorithms (HQ and RQ) used by QoS broker when broker acts as the front-end of a server. The goals of algorithms are to maximize the server resource usage while minimizing the QoS instability for each client. The QoS performance and instability tradeoffs of both algorithms are studied by simulation.
As the exceptional potential of Web services for unleashing the full power of Web-accessible service content and application-to-application integration in business-critical contexts is becoming increasingly evident, management information is mainly modelled in high-level specifications on top of the basic protocol stack. After reviewing relevant work, we present a simple approach to model certain Web service management attributes such as QoS and provision price, and discuss how this information can be accommodated within basic specification standards such as WSDL and exploited within the Web service deployment and application life-cycle.
Web Services Offerings Infrastructure (WSOI) - A Management Infrastructure for XML Web Services
- V Tosic
- W Ma
- B Pagurek
- B Esfandiari