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Mobile systems are gaining more and more importance, and new promising paradigms like Mobile Cloud Computing are emerging. Mobile Cloud Computing provides an infrastructure where data storage and processing could happen outside the mobile node. Specifically, there is a major interest in the use of the services obtained by taking advantage of the di...
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... The lack of distributed election algorithms designed to operate in highly dynamic environments is the motivation for proposing, as part of previous work, the algorithm presented in [19]. This is referred to here as Consensus, which is a distributed LE algorithm based on an approach where an agreement or consensus is reached to elect the most suitable node or leader to perform a task. ...
... Additionally, the VOELA algorithm is compared with the previously proposed Consensus election algorithm [19]. ...
Novel approaches are needed to better facilitate dynamic service replication management in mobile ad-hoc networks (MANETs) and to use and apply them within current and emerging autonomous intelligent systems and the Internet of Things (IoT) paradigm. Such approaches should address the context-awareness and self-adaptation of service replication, while paying special attention to quality attributes (e.g. availability, reliability, etc.) under specific runtime changes and adverse conditions with unstable communications and network partitions. The dynamic election for a node to host a service replica in MANETs can be based on the use of leader election (LE) algorithms. In this research work, a new voting-based election algorithm for managing dynamic service replication in MANETs (namely, VOELA) is proposed. This algorithm is based upon a utility function to score node resources and features (i.e., battery level and topology position) to decide where the service replica will be activated. VOELA is compared to a previously proposed consensus-based algorithm and three other well-known leader election algorithms in terms of service availability, election algorithm reliability, coordination message usage, and network lifetime. For this comparative analysis, the ns-3 network simulator is used together with three different mobility models, namely Manhattan Grid Mobility (MGM), Random Walk Mobility (RWM) and Reference Point Group Mobility (RPGM). The VOELA algorithm demonstrates in balance the most promising results.
... Tacit knowledge exchange and coclimbing is a collaborative network support platform for self-directed professional development. In the construction of a CET resource data bank, some teachers pay more attention to the technical level of PPT courseware production and ignore the design of actual teaching content, according to reference [23]. The courseware is, to some extent, an "empty shell without pulp." ...
Chinese students began learning English during compulsory education, have a long history of English learning, and focus on vocabulary, grammar, and other aspects of the language in middle school. Teaching resources include a variety of teaching conditions, such as materials. In a broad sense, they also include educational policies and other contents. They typically include teaching materials, cases, films and television, pictures, courseware, teacher resources, teaching aids, and infrastructure. In this case, cloud computing provides a good technical platform for solving the problems mentioned above in college English teaching (CET). Cloud computing enables the desktop use of Internet resources while reducing personal computer performance. In this paper, we will create a data resource data bank based on the cloud computing concept, making the most of existing resources, avoiding repeated development, and achieving curriculum content sharing. Reduce the cost of developing online courses, shorten the development cycle, and ensure that they are of high quality. This paper investigates the use of cloud computing to build a CET resource data bank. The cloud computing platform enables multiperson collaboration, document creation, editing, and sharing, all of which are characteristics of constructivism and collaborative learning theory.
... Other places with different environmental factors may experience different outcomes. Garrido et al. (2016) presented a context-aware architecture that provides an adaptable and reusable avenue for the availability of cloud-based mobile services using an election algorithm. A service replication scheme together with a self-configuration method was adopted for the activation/hibernation of the replicas of the service depending on user context information from the mobile system. ...
... Thus, developing a good cloud service recommendation method is an urgent research problem. Cloud computing's service architecture is generally composed of three layers: cloud service providers, application programming interfaces, and cloud service users [15,16]. This is illustrated in Figure 1. ...
Cloud computing is the on-demand availability of internet-based computing services, especially software, large amounts of data storage, operating systems, and other computing resources. Service Level Agreement (SLA) violation is the most critical problem in cloud computing. SLA violation creates many problems for cloud service providers and cloud customers. Due to this, cloud customer gets low-quality cloud service. Thus, designing an effective cloud service recommendation algorithm is a critical research problem in cloud computing. The primary objective of this research is to determine the optimal cloud service from functionally equivalent cloud services that better fit the user's requirements (latency, throughput, response time, and cost). The efficiency of cloud services varies according to the time and location of the virtual machine. First, this proposed method determines the correlation between active user requirements and cloud services. Second, strongly correlated services are separated into two clusters based on the virtual machine's location and the cloud service's data transmission rate. For this purpose, two lightweight clustering algorithms have been proposed. A modified multilayer perceptron algorithm has been developed to recommend the optimal cloud service to the active user from the two clusters. The open-source WS-Dream dataset is used to train and validate the proposed MLP. The training efficiency, prediction accuracy, and performance of the proposed MLP-based cloud service recommendation system are experimentally compared to the existing cloud service recommendation systems analysed in the literature study [20, 2, 22, 23]. Compared to existing cloud service recommendation approaches, the MAE and RMSE values of the proposed cloud service recommendation system are less than one. In terms of accuracy, the suggested method obtains a precession of 94 %, a recall of 97 %, and an F1-Measure of 96 %, all of these are significantly better than the existing cloud service recommendation methods. Finally, experimental results prove that the overall performance of the proposed method's throughput (increase 10 MBPS), latency (reduce 10 ms), the response time (reduce 17 ms) and service recommendation time (reduce 5ms) is more robust than existing methods.
... Local Mobile Cloud is required in domains where mobile applications also need to be supported by data storage and processing services provided by the mobile platform itself in a transparent and flexible way, such as rescue teams, security forces, tourism [1]. The nodes could be turned off or disconnected (temporarily or permanently), Since these networks are generally multi-hop, this normally entails connection failures, path changes, or even network partitions, all of which could have a significant effect on the network's service availability. ...
Mobile systems are becoming increasingly important, and new promising paradigms such as Mobile Cloud Computing. Mobile Cloud Computing is an application that allows data to be stored and processed outside of the mobile node. There is a lot of interest in using the resources that can be accessed by transparently using distributed resource pooling offered by nearby mobile nodes. This type of device is used in emergency, education, and tourism. Systems basically use dynamic network topologies in which network partitions and disconnection occurs frequently, so the availability of the services has been compromised. In this paper proposes the context aware architecture to provide availability of the services deployed in mobile and dynamic network environments which provides better response time, the services need not be migrated at real time, so the bandwidth and energy used has been more efficient.
... The drawback in, the paper is that it did not introduce a comparative study to compare and calculate energy consumption and computation percentages with its related work. Fig. 4: The framework of MCC system model [6] Another solution proposed by Gabriel et al. in [7] in case of emergencies, like when internet connection cannot be established. They proposed a context-aware software architecture to support the availability of the services and increase the efficiency of battery. ...
... The drawback of the proposed solution is that it can be used on small and medium networks because the replicas will cause heavy load on nodes and they will lose the concurrency of the services. The elements that make up the context-aware architecture for availability [7]. ...
... Very few approaches aim at enabling IoT systems to self-adapt to dynamic changes in their deployment topologies [90,91]. Contreras et al. [92] introduced an architecture to support the availability of services in mobile and dynamic Edge environments. When an Edge node becomes unavailable, the service consumers automatically elect another node to run a service replica. ...
The Internet of Things (IoT) is a fast-spreading technology that enables new types of services in several domains, such as transportation, health, and building automation. To exploit the potential of the IoT effectively, several challenges have to be tackled, including the following ones that we study in this thesis. First, the proposed IoT visions provide a fragmented picture, leading to a lack of consensus about IoT systems and their constituents.
To piece together the fragmented picture of IoT systems, we systematically identified their characteristics by analyzing existing taxonomies. More specifically, we identified seventeen characteristics of IoT systems and grouped them into two categories, namely, elements and quality aspects of IoT systems. Moreover, we conducted a survey to identify the factors that drive the deployment decisions of IoT systems in practice. A second set of challenges concerns the environment of IoT systems that is often dynamic and uncertain. For instance, due to the mobility of users and things, the set of things available in users' environment might change suddenly. Similarly, the status of IoT systems’ deployment topologies (i.e., the deployment nodes and their interconnections) might change abruptly. Further, environmental conditions monitored and controlled through IoT devices, such as ambient temperature and oxygen levels, might fluctuate suddenly.
The majority of existing approaches to engineer IoT systems rely on predefined processes to achieve users’ goals.
... ing [4], [5], web servers [6], [7] and wireless networks [8], [9], where faults and failures are ubiquitous and costly [10]- [12], few existing solutions operate in environments with constrained resources and/or where complete system information is not current and reliable. Constrained resources and unreliable information sources can be found in military landbased operations, where the potential benefits of using selfadaptive systems are significant [13], [14]. ...
... Existing self-adaptive and autonomic approaches may inform the development of self-adaptive software systems for military applications, but the majority of literature on this topic does not consider the military domain explicitly. Existing works either consider perfect environments [25] or lack evaluation of key system properties [26] such as scalability [13], [14], [27], [28] or security [29], [30] among others. However, several approaches have been proposed in crisis management situations, where scenarios may include similar environmental complexity such as unreliable communication performance [25], and limited battery performance [31]. ...
Self-adaptive approaches are a promising to address the dynamic and uncertain nature of the environments where today’s complex systems operate. In particular, systems operating in military environments, during crises or under unexpected conditions need to address critical concerns related to resource sparsity and the unstable and uncertain nature of exchanged information. Despite a plethora of self-adaptive and autonomic approaches proposed in the last decade, very few have been designed for or evaluated in contested environments, where adversarial action in the communications domain leads to stale or incomplete information, or in resource-constrained environments, where resources are either limited or required by a large number of components. These conditions are where self-adaptability to aid human operators is needed the most. To better understand self-adaptation in contested and resource-constrained environments, we conducted a systematic literature review of publications over the last decade. We conduct our review through the lens of a military environment, where contention, both physical and from a resource, be it computational or communication based is at its peak. We followed the systematic literature review methodology and analysed 238 primary studies. We identified that the most frequent application domains are those where failures are frequent and costly, namely, cloud computing, web services and applications, and servers. Despite this, less than 3% of the papers considered constrained resources and stale or incomplete information and a significant focus was on developing centralised solutions instead of distributed ones throughout all papers. Very few papers (4.6%) considered environments where the information about the system components was not readily available. No papers evaluated the systems running in contested and resource-constrained environments. We present an analysis of the self-adaptive systems that consider incomplete or stale information and constrained resources, discuss their limitations and identify future areas of research. Critical research gaps include the lack of evaluation of self-adaptive approaches, including the lack of standards or formalisms to allow for the comparison of various approaches. In addition, there is a need to consider more self-* properties and non-functional requirements in order to make sure the designed system is resilient. This paper presents our review findings in detail, examines how self-adaptation happens in contested and resource-constrained environments, and discusses the identified research gaps.
... In mobile cloud computing (MCC), by offloading the computational tasks to the distant cloud for execution, the system performance, e.g., energy consumption and latency, is able to be improved [1]. Among all different types of MCC technologies, fog/edge computing system, emerges as a proximity solution to provide pervasive and distributed computation services for the MDs, and especially for the Internet-of-Things (IoT) applications with stringent requirement of latency and reliability [2]. ...
In this work, we propose a dynamic optimization scheme for an edge computing system with multiple users, where the radio and computational resources, and offloading decisions, can be dynamically allocated with the variation of computation demands, radio channels and the computation resources. Specifically, with the objective to minimize the energy consumption of the considered system, we propose a joint computation offloading, radio and computational resource allocation algorithm based on Lyapunov optimization. Through minimizing the derived upper bound of the Lyapunov drift-plus-penalty function, the main problem is divided into several sub-problems at each time slot and are addressed separately. The simulation results demonstrate the effectiveness of the proposed scheme.
... In the literature, very few works aim at enabling IoT systems to self-adapt to dynamic changes in their deployment topologies [10], [28]. Contreras et al. [20] propose an architecture for supporting the availability of services in mobile and dynamic Edge environments. When an Edge node (e.g., a laptop) that provides a service moves, becomes unreachable, or is about to run out of battery, the service consumers elect another node that runs a replica of the service. ...
Engineering Internet of Things (IoT) systems is a challenging task partly due to the dynamicity and uncertainty of the environment including the involvement of the human in the loop. Users should be able to achieve their goals seamlessly in different environments, and IoT systems should be able to cope with dynamic changes. Several approaches have been proposed to enable the automated formation, enactment, and self-adaptation of goal-driven IoT systems. However, they do not address deployment issues. In this paper, we propose a goal-driven approach for deploying self-adaptive IoT systems in the Edge-Cloud continuum. Our approach supports the systems to cope with the dynamicity and uncertainty of the environment including changes in their deployment topologies, i.e., the deployment nodes and their interconnections. We describe the architecture and processes of the approach and the simulations that we conducted to validate its feasibility. The results of the simulations show that the approach scales well when generating and adapting the deployment topologies of goal-driven IoT systems in smart homes and smart buildings.
