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Evolution of grid computing architecture and grid adoption models
Abstract
During recent years, we have witnessed a major paradigm shift in distributed computing principles, with a focus towards service orientation, open standards integration, collaboration, and virtualization. One particular area of interest centers on the evolution of grid computing principles into the mainstream of distributed computing and Web services. In this paper, we focus our analysis on this evolution and the significance of achieving some form of standardization of grid-computing architecture principles. This paper presents the technology standards that are driving major grid initiatives and explains in simple terms how these standards and technologies are aligned with the IBM on demand business concepts. In addition, we discuss the recent Web services specifications related to stateful resources (i.e., resources whose behavior is defined with respect to their underlying state) and how these standards relate to grid computing. We conclude with discussions exploring major aspects of grid-computing adoption models and some significant attributes that influence the transformation, collaboration, and virtualization features of these models.
... This merging is also discussed in this paper in detail. The authors illustrates the IBM approach as "It is based on the emergence of open standards platforms to build resource collaboration models, combined with the ability to simply construct dynamic applications that control virtualized resources" [3]. IBM uses this approach for implementation of on demand business model in applications based on grid adoption model. ...
... It is also called utility computing. This concept of commercial on-demand utility grid services adds new, more difficult challenges to the already complicated grid problem list, including service level features, accounting, usage metering, flexible pricing, federated security, scalability, and open-ended integration [3]. ...
... The application layer comprises of the end user applications that operates with in the virtual organization environment. These layers provide the interface to the consumers of the resources based on the collaboration and resource access protocols [3]. ...
This paper discusses the new form of distributed computing, its architecture,
standardization and the future problems which are targeted for research. Today research communities look forward to the open standardizations, integrations, virtualizations and service orientations for the distributed computing. The specific form of the distributed computing is grid computing which provides a more flexible heterogeneous environment for sharing resources. The grid is under the evolutionary stage and different communities’
looks into it in different ways. Many of them provide architecture and principles for the
adoption, for example, Distributed European Infrastructure for Supercomputing
Applications (DEISA) [2], International Business Machine Corporation (IBM), and
Microsoft Inc.
... A vendor must be able to assess the computational resources required by a customer's application and determine, within some reasonable bounds, when the job will be completed. The duration and resources required for a job also play heavily into a vendor's contracted price for the service (Joseph, 2004). ...
... IBM's Architecture for Grid Computing ServicesSource: Joseph 2004 ...
... IBM's Modified Grid Architecture for Business Services.Source: Joseph 2004 ...
... According to Foster, "The real and specific problem that underlies the Grid concept is coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations. The sharing that we are concerned with is not primarily file exchange but rather direct access to computers, software, data, and other resources, as is required by a range of collaborative problem-solving and Virtual Organizations in this definition can be defined as the dynamic group of individuals, groups, or organization who define the conditions and rules for sharing resources (Joseph et al., 2004). Some of the Organizations have also defined the Grid computing with respect to the features. ...
Innovations are necessary to ride the inevitable
tide of change. Most of enterprises are striving
to reduce their computing cost through the
means of virtualization. This demand of
reducing the computing cost has led to the
innovation of Cloud Computing. Cloud
Computing offers better computing through
improved utilization and reduced administration
and infrastructure costs. Cloud Computing is the
sum of Software as a Service (SaaS) and Utility
Computing. Cloud Computing is still at its
infant stage and a very new technology for the
enterprises. Therefore, most of the enterprises
are not very confident to adopt it. This research
paper tackles this issue for enterprises in terms
of cost and security. In this paper we discuss the
benefits and drawbacks an enterprise can have
while they adopt Cloud Computing in terms of
Cost and Security.
In the end, concluding that Cloud Computing is
better for medium and small sized enterprises as
compared to large enterprises in terms of both
cost and data security.
... In the Grid protocol architecture, there are five levels of protocols and services, each of which is denoted by a unique number in the Grid protocol architecture. These are the five levels that make up the grid architecture: fabric layer, connectivity layer, resource layer collective layer, application layer [14], [15]. Song et al. [26] Trusted Grid Resource Allocation ...
Applications that are emerging scientifically and are now developing need for rapid access to enormous volumes of information and comparably speedy processing resources. Grid computing is a cutting-edge registering procedure that consolidates various little and feeble networks to give a huge handling power and capacity asset. Since we mainly use the network, it is important to address the security challenges that we may face and possible solutions to these problems. Keywords: Distributed Computing, Grid Computing, Grid Security
... The main purpose of this kind of grid is to provide an appropriate infrastructure for synthesizing and building new information from distributed data stores in the grid and eliminating bottlenecks (2). The third category is the service grade, the main purpose of them is to provide services that a computer alone cannot provide the services (Joseph, 2004). ...
Grid was a technology that allows us to remotely access various types of resources by using communication infrastructure and computer networks, and by utilizing the limitations of the concepts and features of distributed systems. This study aimed to introduce an algorithm for improving scheduling in grid networks, which in turn results in lower cost. As the results show, the MOPSO algorithm improved the NSGA-II algorithm in all the problems in both the target time function and the target function. This improvement is between 10% and 14%. Generally, this algorithm has achieved a better response by 12.59 percent. Also, according to the objective criteria, other algorithms such as bat algorithm, firefly algorithm and ant colony algorithm have improved in simulation of the algorithm.
... Note that while the shift from infrastructure based computing to cloud computing was based on the economic factors, the shift towards MEC is motivated by low-latency and high bandwidth scenarios that require tighter placement and control of computing and network resources. Although grid computing also shares several common aspects with the MEC including peer to peer computing [9], it cannot fulfill low-latency demands due to its loosely connected compute and network protocols thus creating a lack of availability and trust [10,11]. While MEC promises to fulfill the application QoS, its geographically local, resource constrained design will not be sufficient to handle load surges. ...
This thesis presents the architecture, design, and evaluation of the mobile edge cloud (MEC) system aimed at supporting future low-latency applications. Mobile edge clouds have emerged as a solution for providing low latency services in future generations (5G and beyond) of mobile networks, which are expected to support a variety of real-time applications such as AR/VR (Augmented/Virtual Reality), autonomous vehicles and robotics. Conventional cloud computing implemented at distant large-scale data centers incurs irreducible propagation delays of the order of 50-100ms or more that may be acceptable for current applications but may not be able to support emerging real-time needs. Edge clouds considered here promise to meet the stringent latency requirements of emerging classes of real-time applications by bringing compute, storage, and networking resources closer to user devices. However, edge clouds are intrinsically local and have a smaller scale and are thus subject to significantly larger fluctuations in offered traffic due to factors such as correlated events and user mobility. In addition, edge computing systems by definition are distributed across multiple edge networks and hence are associated with considerable heterogeneity in bandwidth and compute resources. Considering these challenges, this thesis analyzes the requirements posed by the edge clouds and proposes specific techniques for control, network routing, data migration, and dynamic resource assignment which can be employed to support low-latency applications.
The thesis starts by analyzing system-level edge cloud requirements for low-latency by deploying a set of sample AR applications, namely, annotation-based assistance, and smart navigation. A city-scale MEC system is analyzed for achievable latency when running AR applications using existing core clouds as well as the proposed distributed edge cloud infrastructure. Performance evaluation results are presented to understand the trade-offs in key system parameters such as core cloud latency and inter-edge or core-to-edge network bandwidth. The results show that while the core cloud-only system outperforms the edge-only system having low inter-edge bandwidth, a distributed edge cloud selection scheme can approach global optimal assignment when the edge has sufficient compute resources and high inter-edge bandwidth. Adding capacity to an existing edge cloud system without increasing the inter-edge bandwidth contributes to network-wide congestion and can reduce system capacity.
Next, a specific network-assisted cloud resource management technique is described that uses the concept of named-object architecture to create a named-object based virtual network (NOVN) inherently supporting application specific routing specifically designed to enable Quality of Service (QoS) in MEC. The results validate the feasibility of the named-object approach, showing minimal VN processing, control overhead, and latency. The results also validate application specific routing (ASR) functionality for an example latency constrained edge cloud service scenario.
Further, user mobility and edge cloud system load balancing are handled by enabling dynamic service migration. Container migration is emerging as a potential solution that enables dynamic resource migration in virtualized networks and mobile edge cloud (MEC) systems. The orchestrated, lightweight container migration model is designed and evaluated for a real-time application (license plate recognition) using performance metrics such as the average system response time and the migration cost for different combinations of load, compute resources, inter-edge cloud bandwidth, network, and application latency. The concept of NOVN and service migration are then applied to the advanced driver assistance systems (ADAS) geared towards autonomous driving using Augmented Reality (AR). The experiments show that the low-latency ADAS applications with an average system latency of less than 100 ms for the applications can be supported. The key observations from this study are: (1) machine type plays a crucial role in deciding migration, (2) applications requiring higher computation capabilities, for instance, annotation-based assistance should be offloaded to the closest available lightly-loaded edge cloud, (3) the latency of applications requiring pre-fetched data has fewer avenues for optimization, and (4) service migration should consider network bandwidth, system load, and compute capability of the source and the destination.
The work on edge cloud resource assignment and networking motivated the design of a general-purpose control plane that supports the exchange of essential control information (such as compute and network capabilities, current workloads, bandwidth/latency, etc.) between edge cloud domains in a region. The existence of such a control plane enables distributed resource management, application-aware routing, and task assignment algorithms without the requirement of a single point of control. Therefore, the final part of this thesis focuses on creating a lightweight control protocol that can provide neighboring edge clouds with visibility of their computing and network resources along with current load metrics. The proposed design promotes regional awareness of available resources in a heterogeneous multi-tenant environment to enable cooperative techniques such as cluster computing, compute offloading, or service chaining. The design of a specific control plane protocol followed by a system-level evaluation of the performance associated with task assignment and routing algorithms enabled by the framework is presented. The evaluation is based on a prototype system with a heterogeneous network of compute clusters participating in the control plane protocol and executing specified resource sharing algorithms. An application-level evaluation of latency vs. offered load is also carried out for an example time-critical application (image analysis for traffic lane detection) running on the ORBIT testbed confirming that significant performance gains can be achieved through cooperation at the cost of modest complexity and overhead.
... Grid and cloud computing share several common aspects including peer to peer computing [45], [46]. Grid computing cannot fulfill low-latency demands due to its loosely connected compute and network protocols thus creating a lack of availability and trust [47], [48]. Note that while the shift from infrastructure based computing to cloud computing was based on the economic factors, the shift towards MEC is motivated by low-latency and high bandwidth scenarios that require tighter placement and control of computing and network resources. ...
This paper presents a novel control plane protocol designed to enable cooperative resource sharing in heterogeneous edge cloud scenarios. While edge clouds offer the advantage of potentially low latency for time critical applications, computing load generated by mobile users at the network edge can be very bursty as compared with aggregated traffic served by a data center. This motivates the design of a shared control plane which enables dynamic resource sharing between edge clouds in a region. The proposed control plane is designed to exchange key compute and network parameters (such as CPU GIPS, % utilization and network bandwidth) needed for cooperation between heterogeneous edge clouds across network domains. The protocol thus enables sharing mechanisms such as dynamic resource assignment, compute offloading, load balancing, multi-node orchestration, and service migration. A specific distributed control plane (DISCO) based on overlay neighbor distribution with hop-count limit is described and evaluated in terms of control overhead and performance using an experimental prototype running on the ORBIT radio grid testbed. The prototype system implements a heterogeneous network with 18 autonomous systems each with a compute cluster that participates in the control plane protocol and executes specified resource sharing algorithms. Experimental results are given comparing the performance of the baseline with no cooperation to that of cooperative algorithms for compute offloading, cluster computing and service chaining. An application level evaluation of latency vs. offered load is also carried out for an example time-critical application (image analysis for traffic lane detection). The results show significant performance gains (as much as 45% for the cluster computing example) vs. the no cooperation baseline in each case at the cost of relatively modest complexity and overhead.
... Connectivity layer defines basic communication/authentication protocols needed for gridspecific networking services. Resource layer uses communication/ security protocols (defined by connectivity layer) to control initiation, negotiation, monitoring, and payment for function sharing of individual resources [4]. Collective layer, also called protocol layer implements various sharing behaviors using a limited resource and connectivity-layers protocols. ...
Grid computing is gaining ground in academia and commerce moving from scientific-based applications to service oriented problem solving environments. Grid is a distributed large-scale computing infrastructure providing dependable, secure, transparent, pervasive, inexpensive, and coordinated resource sharing. Resource selection and use are necessary to enhance application performance. Grid task scheduling is a most important grid system technology being a NP complete problem to schedule tasks on appropriate grid nodes. This study uses hill-climbing heuristics for optimizing the scheduling. Simulations validate the proposed algorithm's performance, and results are evaluated by Makespan. Makespan values of best solutions are recorded throughout optimization iterations and minimum time cost time for all tasks completed.
... The term "cloud computing" become popular from then on. Beside the web email, the Amazon Elastic Compute Cloud (EC2), Google App Engine [4] and Sales force's CRM [5] largely represent a promising conceptual foundation of cloud services. The services of cloud computing is broadly divided into three categories: Infrastructure-as-a-Service (IaaS), Platforms-a-Service (PaaS), and Software-as-a-Service (SaaS). ...
The drastic increase in the commodity computer and network performance for the last generation has a resultant of faster hardware and more sophisticated software. But, the supercomputers of the current generation are still incapable of solving the current problems in the field of science, engineering, and business. This problem arises as a single machine cannot facilitate the availability of various heterogeneous resources required to resolve the crisis. Numerous experimental studies were conducted by different organizations, such that the topologically distributed resources were connected by the means of internet to act as a single machine. This new approach is coined by different naming as, meta-computing, scalable computing, global computing, Internet computing and recently "Grid Computing". In this research paper, we have discussed about the origin of Grid Computing, need of Grid Computing, followed by the reason of choosing it and several FAQs. The software development kits and application programming interfaces are categorized upon the study of extensible and open Grid architecture. A comparative study between "cloud computing" and "grid computing", as well a brief study of grid and web services has taken into account. Finally we conclude with the benefits and the applications of Grid computing in the current scenario and the upcoming generations.
... It is very natural for these Vos to produce a Grid portal which provides an end-user view of the collected resources available to the members of the VO. By producing a portal with "one-stop shopping" for users who participate in a VO, the VO makes its resource much more useful and accessible for their users (Joseph, et al, 2004). Grid technologies and infrastructures support the sharing and coordinated use of diverse resources in dynamic, distributed virtual organizations. ...
Grid computing has emerged as an important new field, distinguished from conventional distributed computing based on its abilities on large-scale resource sharing and services. And it will even become more popular because of the benefits it can offer over the traditional supercomputers, and other forms of distributed computing. This paper examines these benefits and also discusses why grid computing will continue to
enjoy greater popularity and patronage in many years to come. Finally, we discussed about virtual organization (VO) as one of the key characteristics of Grid computing.
... Following the common architectures of grid computing (e.g., Joseph et al. 2004, Meliksetian et al. 2004), we consider a centralized, software-based grid manager. The grid manager sells idle computing resources to one or more buyers who each have one or more computing jobs. ...
... Processing data integration, reporting and analytical jobs accelerate decision making across the enterprise. Grid lets fully utilize all available computing resources now and cost-effectively scale out as needed, adding capacity in single-processing units to keep IT spending in check (Joseph, 2004). As it can add low-cost commodity hardware resources incrementally, there is no need to size today's environment. ...
... The term "cloud computing" become popular from then on. Beside the web email, the Amazon Elastic Compute Cloud (EC2), Google App Engine [3] and Sales force's CRM [4] largely represent a promising conceptual foundation of cloud services. The services of cloud computing are broadly divided into three categories: Infrastructure-as-a-Service (IaaS), Platforms-a-Service (PaaS), and Software-as-a-Service (SaaS). ...
The drastic increase in the commodity computer and network performance for the last generation has a resultant of faster hardware and more sophisticated software. But, the supercomputers of the current generation are still incapable of solving the current problems in the field of science, engineering, and business. This problems arises as a single machine cannot facilitate the availability of various heterogeneous resources required to resolve the crisis. Numerous experimental studies were conducted by different organizations, such that the topologically distributed resources were connected by the means of internet to act as a single machine. This new approach is coined by different naming as, meta-computing, scalable computing, global computing, Internet computing and recently “Grid Computing”. In this research paper, we have discussed about the origin of Grid Computing, need of Grid Computing, followed by the reason of choosing it and several FAQs. The software development kits and application programming interfaces are categorized upon the study of extensible and open Grid architecture. A comparative study between “cloud computing” and “grid computing”, as well a brief study of grid and web services have taken into account. Finally we conclude with the benefits and the applications of Grid computing in the current scenario and the upcoming generations.
... An important observation from a middleware perspective is that in grid computing the notion of a site (or administrative unit) is common. This prevalence is emphasized by the gradual shift toward a service-oriented architecture in which sites offer access to the various layers through a collection of Web services [33]. This, by now, has lead to the definition of an alternative architecture known as the Open Grid Services Architecture (OGSA) [23]. ...
Distributed systems are by now commonplace, yet remain an often difficult area of research. This is partly explained by the many facets of such systems and the inherent difficulty to isolate these facets from each other. In this paper we provide a brief overview of distributed systems: what they are, their general design goals, and some of the most common types.
... he most emerging technology of current era on which massive investigations and drastic progressions are coming is cloud computing. It is a drastic development in ield of computing which has been emerged by witnessing the development that followed the pathway from distributing computing 1 to parallel computing 2 , followed by cluster computing 3,4 and grid computing 5,6 . herefore, cloud computing is considered as a striking computing model which allows for the provisioning of resources ondemand 7 , which in a layman language can be described as a virtual space in which users are allotted some space for storage which is accessible by the user ID and password that is actually their private space but along with this there is another kind of space, where data present on it has open access to people for its usage. ...
Background/Objectives: Cloud computing is an arena that is ruling the world of information technology. Every user has its own definition for this technology as per their use. This paper is properly discussed document that describes the complete evolution of cloud computing from its beginning. Findings: With the presence of vast literature in field of load balancing, it was found confusion for the new scholars to find the startup point for their research in this field. Therefore, an exhaustive comparison has been made for the superior understanding of cloud evolution through various proposed algorithms from the past many decades, which will make the researchers possible to analyze the existing scenarios and a better way out to overcome the unsolved queries. Application/Improvements: The assessments between the algorithms will help the new researchers to analyze and opt for the parameters those need much more concentration to meet the required targets for better outcomes in the field.
... Virtual organizations in this definition can be defined as the dynamic group of individuals, groups, or organization who define the conditions and rules for sharing resources [13]. Some of the organizations have also defined the Grid computing with respect to the features. ...
Cloud Computing is a concept that has been defined differently by many and there seem not to be a consensus. Despite these views, cloud computing is not a complete new idea as it has intricate connections to technologies or domain such as the Grid Computing paradigm, and the general distributed computing. This overview gives the basic concept of cloud computing, and highlights the relationship between Cloud computing and other cloud enabling technologies by providing their similarities and differences. This insight into the essential characteristics of cloud and its enabling technologies provides a good foundation for understanding and a hint on how to leverage desirable strengths of these technologies in the cloud by way of extension and or inheritance
... According to the grid computing literature, grid adoption depends on the ability of technology to deliver increased business value. The business issues, related to the grid adoption model, include key factors (Joseph et al., 2004;Pacitti, 2007), such as leveraging existing hardware investments and resources; reducing operational expenses; creating a scalable and flexible infrastructure (Jensen et al., 2005); accelerating development time; improving time to market, and increasing customer satisfaction and business productivity in the field of scientific computing (Jimenez-Peris et al., 2007). ...
The main aim of this chapter is to evaluate a Grid technology (GT) for Archive Solutions in terms of relevant features for Health Care Organizations (HCOs), and with particular attention to technical and organizational issues. The method used was a case study approach that was conducted during the months of March, April, and May 2011, applying a mix of random sampling (randomly selected interviewees from our directory) and "snowball" sampling (contacting interviewees through leads). The research shows that the introduction of grid technologies in HCOs maybe is still premature. However, a grid solution unquestionably led to some important benefits, so the author suggests a "progressive and gradual approach" to its implementation, aiming for further research on this topic.
... A set of individuals and/or institutions defined by such sharing rules form a group called virtual organization (VO) [11]. Thus, creating virtual organizations and enterprises as a temporary alliance of enterprises or organizations that come together to share resources and skills, core competencies, or resources can be enhanced (multiplied) in order to better respond to business opportunities or to fulfill large-scale application processing requirements as envisioned in [12]. The cooperation among the VOs is supported by computer networks. ...
In recent years the Internet learners can freely absorb new knowledge without restrictions on time or place. At present, most E-Learning environment architectures use single computers or servers as their structural foundations. Traditional E-Learning systems have major drawback because of their limitations in scalability, availability, distribution of computing power and huge storage systems, as well as sharing information between users. In this context, the use of Grid technology reveals its utility and availability, as scalable, flexible coordinated and secure resource sharing among geographically distributed individuals or institutions, in the perspective of E-Learning system. The major focus of this paper is to design and develop different types of E-Learning services in Computational Grid Environment. This proposed system is able to handle large multimedia learning materials using the features of Grid Technology.
... A set of individuals and/or institutions defined by such sharing rules form a group called virtual organization (VO) [11]. Thus, creating virtual organizations and enterprises as a temporary alliance of enterprises or organizations that come together to share resources and skills, core competencies, or resources can be enhanced (multiplied) in order to better respond to business opportunities or to fulfill large-scale application processing requirements as envisioned in [12]. The cooperation among the VOs is supported by computer networks. ...
This chapter presents how Grid can be used to build an e-learning
framework which is flexible, convenient, cost-effective, and adaptable. Grid technologies
are appealing due to the fact that the requirements for developing such
framework match very closely what a Grid can offer in terms of computational and
storage resources. On the other hand, agent-based technology can make e-learning
Grid more efficient. A few autonomous, co-operative agents with predefined
functionalities and responsibilities provide more powerful and reliable e-learning
system. The objective of this chapter is to accomplish a blended e-learning Grid
framework, where the framework is designed as a multi-agent system integrated
with Grid. This chapter also presents the implementation of an e-learning system as
Grid services and analysis of the benefits of e-learning Grid system.
... In the later 1990s and early 2000s, a major paradigm shift occurred in distributed computing principles towards service orientation, open standards integration, collaboration, and virtualization (Joseph et al. 2004), which has significantly influenced the development of web mapping and GIS. The concepts and/or technologies of web services (WS), grid computing, peer-to-peer (P2P) architecture, and service-oriented architecture (SOA) are among those contributing to this shift. ...
The field of web mapping and GIS has gone through some tremendous changes over the last few years. Driven by the constant updating of web and other related technologies, as well as the significant revolution of web mapping caused by mainstream IT vendors such as Google, Yahoo and Microsoft, we will see more great changes ahead of us. This chapter presents a technical review of web mapping development over the last decade or so and examines the current status of the development. Special emphasis is put on how web mapping or GIS has evolved with the technology revolution and how the newly emerged technologies might reshape the development in the field. The chapter ends with discussions of some important issues and challenges as well as potential directions for future development.
... Figure 2Grid adaption factors[21] ...
It is expected that improved connectivity will enable African Tertiary education and research institutions to generate a proportionate amount of intellectual property goods to achieve parity with the rest of the world. Nevertheless this vision can only be attained through intensive collaborative activities. The emergence of large-scale e-infrastructure projects in Africa reflects a trend toward more complex configurations of scientific collaboration. This paper investigates the concepts of synergizing which denote the active processes of creating and managing relationships among people, organizations, and technologies in the creation of e-infrastructure. The paper also explores how embeddedness is not only an important result of infrastructure development, but is also a precursor that can act as both a constraint and a resource for development activities. The researchers are more interested with the process of creating and maintaining productive socio-technical relationships, which they refer to as synergizing. Human infrastructure posits that complex infrastructures come about through complex interactions among networks, place-based organizations, groups, and consortia. Through a multiple case study approach and integrated literature survey, the research examines how two e-infrastructure initiatives; UNESCO-HP brain gain and HP catalyst projects attempts to make use of these concepts to foster e-research and draws specific lessons for African HEIs. The study revealed that the two dominant e-research projects have adopted approaches that favor synergizing and embeddedness in e-research however despite funding of 24 projects in 21 HEIs, visibility of Africa in e-research world map is still wanting.
... • delivers non-trivial quality of service Nowadays, most of the interest driven toward the grid concept derives from the fact that, stated as it is, a grid can be regarded as a technology with no boundaries.In fact, if one can integrate all its computing resources, no matter what they are, in a single virtual computing environment, such a system would make possible: As Web technologies have changed the way that information in shared all over the world, grid computing aims at being the next technological revolution, integrating and making available not only information, but also computing resources such as computing power and data-storage capacity [18]. Figure 1.1 illustrates the way that a grid can be built by means of computing resources that are somehow interconnected by the Internet but that there is no relation among them. ...
... Whenever large Grid Computing is involved on service sharing then resource collaborative models are created with the help of open standard platform for dynamic applications. The following models are taken from reference [Josef et al., 2004]. ...
To address the solution for problems of e-health systems, the various new algorithms are developed. Today, the parallel and distributed programming concepts have motivated the doctors and technology experts for the development of e-health grid systems. This e-health grid system is expected to provide more efficient patient care system, better security and more dedicated links among patients, pharmaceutical companies and their experts. The chapter discusses the project significance of grid computing with its past, present and future in the perspective of e-health. The interdisciplinary research and development in the field of biochemistry, health care, information technology and biomedical engineering has enabled technologists to develop equipments and systems for patient monitoring at distances. The pharmaceutical companies, doctors and technology experts have been working for platforms with continuous connectivity for the treatment and post operative care for patients in homes and in hospitals. The practical significance of such developments shall be discussed in the Chapter including the exponential growth and exploration of new areas in post operative care systems where Wireless Sensor Network (WSN) is playing a vital role. Moreover, the chapter explains that 'how video conferencing or face to face examination of patient can be performed in the preview of e-learning'. Since, this e-health grid system contains varied parametric input and output and there is a need of data fusion system. The last, but not least, we discuss here the challenges and process of acquisition and retrieval of the abstract data types (medical images and different sonic beats) using web-portal and MIS e-health care systems.
... Recent research highlighted the need for interoperation standards and reference models to support the management of decentralised web services and remote resources [12]. A number of interoperation models already existed in the public domain including; integration middle layer architecture [105], data interchange standards [106,107] providing via serviceware which is an integration layer between systems' managements and managed resources. Hence, Web Services Distributed Management (WSDM) had been proposed and developed to provide a standard for distributed web services management [108]. ...
... Grid Computing focuses on large-scale resource sharing in a flexible, secure, and coordinated way [1]. This dynamic, coordinated and secure resource sharing enables the development of innovative applications [2,3]. ...
Grid computing deals with large scale resource sharing and can be exploited to carry out storage and compute intensive tasks which are otherwise not practical to be executed on a single system. Video encoding is a lengthy, CPU intensive task, involving the conversion of video media from one format to another. Video files can be easily broken down into smaller work-units. This factor makes the distribution and execution of video encoding processes viable on grid. In this paper we have made an attempt to design, implement and evaluate a grid environment for DV to mpeg4 video conversion. A grid environment consisting of 10 nodes has been implemented using GT4. Over this environment, a video conversion process (DV to MPEG4) has been implemented and performance of the grid for this conversion process has been evaluated. The performance evaluation has been done with respect to time and it has been observed that grid provide performance benefit with respect to time, but, in small environments, the effect of increasing the number of nodes does not provide as much speed advantage as is expected theoretically.
... Some major standards organizations (Source: J. Joseph, et al. [26]). ...
... This is achieved by techniques such as virtualization. Resource virtualization [3] minimizes the impact of heterogeneity by providing access to well defined interfaces or to work units in terms of virtual machines. Using this set of abstractions the user can connect several different devices on his network. ...
Grid and Cloud computing technologies are being applied as an affordable method to cluster computational power together. These structures aim to support service applications by grouping devices and shared resources in one large computational unit. However, the management complexity grows proportionally to the number of resources being integrated. The paper claims to address the problems of management, considering the routing problem in a particular context. An experimental assessment of routing for grid and cloud is presented. In addition, it introduces a proof-of-concept implementation and case study scenarios.
... Today, the Grid has moved beyond the pure academic research projects, and the industrial involvement has gained momentum [5,6]. For industrial innovators, the Grid offers a means to fulfill some long-sought dreams, such as charging for service usage, and outsourcing and automating management of high-end resources [7]. ...
In this paper1 we present the requirements of a national computing Grid. In particular we discuss the issues involved in managing complex policies of multiple stakeholders in such a large-scale, dynamic, and heterogeneous Grid. We also propose a Service Level Agreement (SLA) and agent-based architecture to address these issues. This work is a continuation of the work performed and experiences gained when we developed a Grid accounting system for the Swedish national Grid network, called SweGrid, which provides the foundation for the investigation presented here. We conclude that many SLA concepts fit very well within the SweGrid network to address some of the issues of the current system. Future work includes prototyping parts of the SLA framework and running simulations before eventually deploying it in the SweGrid production environment.
The work presents a linear programming-based transportation model approach known as improved modified distribution load balancing algorithm (IMDLBA) to enhance the migration parameters. IMDLBA is a part of reactive load balancing mechanism that relies on the process of migration to deal with workload imbalances across the virtual resources. The important migration parameters considered in this work are migration cost, degree of balance, number of task migrations, and number of machines required for migration. The model has been reviewed with respect to existing meta-heuristics—improved weighted round robin (IWRR), honey bee behavior load balancing (HBB-LB), dynamic load balancing (DLB), and HDLB algorithms, in terms of above cited parameters which come under the class of quality of service (QoS) metrics. Experimental analysis and evaluations from IMDLB algorithm revealed the significant reduction in migration cost and improvement in balance factor—a metric that define the degree of balance if VMs. A balance factor of around 31% has been enhanced compared to the existing methods. The IMDLB algorithm also works by performing one time migration on a given set of tasks. The IMDLB algorithm reduces the number of task migrations by 28.5, 51.25, 58.33, 75.16, and 75.19% with reference to IWRR (time-shared), IWRR (space-shared), HBB-LB, DLB, and HDLB respectively. Further the minimum number of machine combinations required for performing load balancing is also achieved. The research article takes into consideration five UN sustainable development goals namely SDG7, SDG 8, SDG 9, SDG 11, and SDG 12.
OS gives life to the computer system. OS will provide managing all resources inside the computer. It will take care of memory management, process scheduling, device managing, managing files and folders, provide user interface, manage applications, etc. Network OS will provide build-in networking capability, multiple system images one per node, managing the resources, scheduling the processes, and sharing the resources. UNIX and Windows NT are good examples for Network OS. Distributed OS manages a group of autonomous computers and makes them appear to the users of the system as if it were a single computer. Distributed OS will provide transparency and networking capability. DOS has control over all the nodes in the system. It will support load balancing using scheduling policies and sharing the resources.
Cloud Computing is a concept that has been defined differently by many and there seem not to be a consensus. Despite these views, cloud computing is not a complete new idea as it has intricate connections to technologies or domain such as the Grid Computing paradigm, and the general distributed computing. This overview gives the basic concept of cloud computing, and highlights the relationship between Cloud computing and other cloud enabling technologies by providing their similarities and differences. This insight into the essential characteristics of cloud and its enabling technologies provides a good foundation for understanding and a hint on how to leverage desirable strengths of these technologies in the cloud by way of extension and or inheritance.
This paper presents a theoretical approach to complexity engineering by considering the complex thinking framework proposed by Edgar Morin. The main foundations of this approach are an open system design, emergence, randomness inclusion, and Gödel incompleteness, which are contextualized using real-word instructive problems. Considering these concepts, several conjectures related to engineering activity and engineering education are presented taking several Brazilian catastrophes as counterexamples.
The main aim of this chapter is to evaluate a Grid technology (GT) for Archive Solutions in terms of relevant features for Health Care Organizations (HCOs), and with particular attention to technical and organizational issues. The method used was a case study approach that was conducted during the months of March, April, and May 2011, applying a mix of random sampling (randomly selected interviewees from our directory) and “snowball” sampling (contacting interviewees through leads). The research shows that the introduction of grid technologies in HCOs maybe is still premature. However, a grid solution unquestionably led to some important benefits, so the author suggests a “progressive and gradual approach” to its implementation, aiming for further research on this topic.
To address the solution for problems of e-health systems, the various new algorithms are developed. Today, the parallel and distributed programming concepts have motivated the doctors and technology experts for the development of e-health grid systems. This e-health grid system is expected to provide more efficient patient care system, better security and more dedicated links among patients, pharmaceutical companies and their experts. The chapter discusses the project significance of grid computing with its past, present and future in the perspective of e-health. The interdisciplinary research and development in the field of biochemistry, health care, information technology and biomedical engineering has enabled technologists to develop equipments and systems for patient monitoring at distances. The pharmaceutical companies, doctors and technology experts have been working for platforms with continuous connectivity for the treatment and post operative care for patients in homes and in hospitals. The practical significance of such developments shall be discussed in the Chapter including the exponential growth and exploration of new areas in post operative care systems where Wireless Sensor Network (WSN) is playing a vital role. Moreover, the chapter explains that ‘how video conferencing or face to face examination of patient can be performed in the preview of e-learning’. Since, this e-health grid system contains varied parametric input and output and there is a need of data fusion system. The last, but not least, we discuss here the challenges and process of acquisition and retrieval of the abstract data types (medical images and different sonic beats) using web-portal and MIS e-health care systems.
This chapter aims at contributing to a better understanding of generation and simulation problems of the grid. Towards this end, we propose a new graph structure called layered graphs. This approach enables us to use attributed graph grammars as a tool to generate at the same time both a grid structure and its parameters. To illustrate our method an example of a grid generated by means of graph grammar rules is presented. The obtained results allow us to investigate properties of a grid in a more general way.
This chapter demonstrates how Grid technology can be used to support intelligence in emergency response management decision-making processes. It discusses how the open Grid service architecture and data access integration (OGSA-DAI) specification services can facilitate the discovery of and controlled access to data, resources, and other instrumentation to improve the effectiveness and efficiency of emergency response tasks. A core element of this chapter is to discuss the major limitations with information and communication technology (ICT) in use when a natural disaster occurs. Moreover, it describes emergency response stakeholders' requirements and their need to seamlessly integrate all their ICT resources in a collaborative and timely manner. With this in mind, it goes on to describe in detail a Grid-aware emergency response model as the practice to maximize potential and make the best of functionality offered by current ICT to support intelligence in emergency response decision-making.
Nowadays, careful consideration has been given to issue of distributed computing because of its expandable and significant reduction in costs without spending running expenditures. Grid computing environment as a kind of distributed computing environment due to the lack of having a central management and its ability to connect heterogeneous resources, has been possessed a matter of the utmost importance. Grid provides locationindependent access to all kind of computational resources including machines services which are geographically distributed. One of the most important actions that should be taken in supporting location-independent computing is to discover users' on-demand resources. By increasing number of users and resources as well as changing in Grid computing environment, a decentralized resource discovery service will be required. To this end, this study investigates the environment of Grid computing in which a method will be presented to discover in Grid environment based on peer-to-peer networks behavior as well as the natural behavior of the ants. The mobile agents (ants) have made the suggested proposition scalable and in case of problems they will be able to self-organizing. The suggested design decreases the network traffic at the time of searching, so it has no more need of central controller.
In today s dynamic business environment, IT departments are under permanent pressure to meet two divergent requirements: to reduce costs and to support business agility with higher flexibility and responsiveness of the IT infrastructure. Grid and Cloud Computing enable a new approach towards IT. They enable increased scalability and more efficient use of IT based on virtualization of heterogeneous and distributed IT resources. This book provides a thorough understanding of the fundamentals of Grids and Clouds and of how companies can benefit from them. A wide array of topics is covered, e.g. business models and legal aspects. The applicability of Grids and Clouds in companies is illustrated with four cases of real business experiments. The experiments illustrate the technical solutions and the organizational and IT governance challenges that arise with the introduction of Grids and Clouds. Practical guidelines on how to successfully introduce Grids and Clouds in companies are provided.
Implementing a distributed process using object oriented programming is challenging especially for clusters of nodes ensuring the availability. Java happens to be well suited for writing object oriented programs for applications which needs modularity and high degree of cohesion [2]. In this paper our objective is to propose appropriate programming paradigms for loosely coupled distributed and object-oriented systems with a specific focus on parallel programming and client-server object computing. We select a prototype toolmade based on the research outcome as found in [1] for this purpose. This research prototype tool 'Vishwa' provides a very good starting point for graduate students, engineers and scientists in academia, industry and government to present their tasks using the aspects of parallel and distributed computing. The learning curve is shorter in the domain of grid due to the simplicity in deploying and processing with this tool. We also demonstrate with a case study for bringing out the easiness in splitting the given job into subtasks and executed in this type of grid environment.
Many applications of grid computing are appearing to solve a scientific or technical problem by shaping and coordinating computational services across the network. The dynamic and complex interaction of grid computing has been a big challenge in guaranteeing the reliability of services behaviors. This paper focuses on the behavioral correctness of grid computing. In order to unify the expression of grid computing behaviors, we introduce the BPMN (Business Process Modeling Notation) to formally describe the interactions in a visualization way with the basic business process concepts, which creates a standardized bridge for the gap between the business process logic design and implementation. Then we translate BPMN to an extended FSM (Finite-State Machine) automaton. Furthermore, the safety and liveness properties of behavioral requirements are expressed as LTL (Linear Temporal Logic) formulae according to coverage criterions. After that, LTL formulae are automatically verified in model checker tool SMV (Symbolic Model Checker). Finally, the experimental results are discussed. In conclusion, our method affords an underlying guideline for modeling and verifying grid computing.
This paper presents a unified formal model to be used in the grid representation based on hierarchical graph structures. It aims at both helping in a better understanding of grid generation and in grid simulation problems. A new graph structure called layered graphs is proposed. This approach enables one to use attributed graph grammars as a tool to generate both a grid structure and its parameters at the same time. To illustrate the method an example of a grid generated by means of graph grammar rules is presented.
Grid computing is emerging as the foundation upon which virtual collaborations can be built among large organizations with the aim of integrating and sharing computer resources, and thus offering performance speed and resource availability, which is unattainable by any single institutional technology resources. With the level of increase in the number of tertiary institutions in Africa, and the attendant lack of basic information technology resources, the use of grid computing for collaboration purposes would contribute to the enhancement of research, course delivery, course management, and other aspects of institutional development. This paper carries out an empirical study of the possibility of adoption of grid computing as a vehicle for collaboration among tertiary institutions in Nigeria from the perspective of the potential adopters (users) of the systems. This study uncovers challenges to the adoption of grid technology by the tertiary institutions. The key challenges that significantly affect the adoption of grid computing in tertiary institutions are mainly attitudinal (perceived need and perceived benefits). Infrastructural issues (facilitating conditions) also impose limitations on the ability of universities to implement grid computing.
Computational grids have emerged as a new paradigm for solving large complex problems over the recent years. The problem space and data set are divided into smaller pieces that are processed in parallel over the grid network and reassembled upon completion. Typically, resources are logged into a resource broker that is somewhat aware of all of the participants available on the grid. The resource broker scheme can be a bottleneck because of the amount of computational power and network bandwidth needed to maintain a fresh view of the grid. In this paper, we propose to place the load of managing the network resource discovery on to the network itself: inside of the routers. In the proposed protocol, the routers contain tables for resources similar to routing tables. These resource tables map IP addresses to the available computing resource values, which are provided through a scoring mechanism. Each resource provider is scored based on the attributes they provide such as the number of processors, processor frequency, amount of memory, hard drive space, and the network bandwidth. The resources are discovered on the grid by the protocol's discovery packets, which are encapsulated within the TCP/IP packets. The discovery packet visits the routers and look up in the resource tables until a satisfactory resource is found. The protocol is validated by simulations with five different deployment environments.
Application of grid task scheduling based on QoS (Quality of Service) in the on-line examination system are researched, the superior node scheduling algorithm was designed, grid task scheduling based on historical average complete time of job and load of grid node was designed and realized, grid on-line examination system was implemented. The system can provide grid resource access service by grid portal, each grid node can provide remote share of examination database and information service. The system has better QoS.
Grid is a collection of distributed computing resources that performs tasks in co-ordination to achieve high-end computational capabilities by dividing a given task into sub-tasks. Each sub-task could be large and run for several hours or days on a number of grid nodes. If a sub-task fails to complete even on a single site, all the computations should be performed again. In scalable distributed systems, an individual component failure usually does not result in failure of the entire system. The probability of a single component failure rises rapidly with the increase in number of components in the system. As system grows in size, efficient recovery mechanism is most important for highly parallel mission critical and long running applications of grid environment. This paper addresses a recovery mechanism using checkpoints to recover from grid service failure resulting in task or transaction failure in computational or data grid which will prevent computations to be restarted from scratch. This work helps in preserving two main objectives of grid namely optimal resource utilization and speedy computations, which can be achieved by using resources in a better way for improving performance of the system rather than engaging them in tasks like rollbacks resulting from cascading aborts. This work aims to address checkpointing mechanism to recover from system failure leading to failure of running services and computational tasks or transactions being executed. The saved state using checkpoints can also be used for job migration using job schedulers of grid.
Grid technologies are of increasing interest in science and technology all around the world. From the perspective of management, however, there have been very few studies analysing grids. This new phenomenon should be studied as another element in the technological infrastructures of firms, but this requires a clear specification of the content of the term ‘grid’. We also need to understand what types of technology are referred to by this new concept, how they are interrelated and what are the major strategic implications. With the current work we aim to achieve these objectives: we propose a definition for ‘grid information technology’; we establish an integrative classification of the different types of grid technologies and anticipate the strategic implications that grid technologies will exert on governance structures.
"Grid" computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation. In this article, we define this new field. First, we review the "Grid problem," which we define as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources-what we refer to as virtual organizations. In such settings, we encounter unique authentication, authorization, resource access, resource discovery, and other challenges. It is this class of problem that is addressed by Grid technologies. Next, we present an extensible and open Grid architecture, in which protocols, services, application programming interfaces, and software development kits are categorized according to their roles in enabling resource sharing. We describe requirements that we believe any such mechanisms must satisfy, and we discuss the central role played by the intergrid protocols that enable interoperability among different Grid systems. Finally, we discuss how Grid technologies relate to other contemporary technologies, including enterprise integration, application service provider, storage service provider, and peer-to-peer computing. We maintain that Grid concepts and technologies complement and have much to contribute to these other approaches.
"Grid" computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation. In this article, we define this new field. First, we review the "Grid problem," which we define as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources-what we refer to as virtual organizations. In such settings, we encounter unique authentication, authorization, resource access, resource discovery, and other challenges. It is this class of problem that is addressed by Grid technologies. Next, we present an extensible and open Grid architecture, in which protocols, services, application programming interfaces, and software development kits are categorized according to their roles in enabling resource sharing. We describe requirements that we believe any such mechanisms must satisfy, and we discuss the central role played by the intergrid protocols that enable interoperability among different Grid systems. Finally, we discuss how Grid technologies relate to other contemporary technologies, including enterprise integration, application service provider, storage service provider, and peer-to-peer computing. We maintain that Grid concepts and technologies complement and have much to contribute to these other approaches.
The WS-Resource construct has been proposed as a means of expressing the relationship between stateful resources and Web services. We introduce here the WS-Resource framework, a set of proposed Web services specifications that define a rendering of the WS-Resource approach in terms of specific message exchanges and related XML definitions. These specifications allow the programmer to declare and implement the association between a Web service and one or more stateful resources. They describe the means by which a view of the state of the resource is defined and associated with a Web services description, forming the overall type definition of a WS-Resource. They also describe how the state of a WS-Resource is made accessible through a Web service interface, and define related mechanisms concerned with WS-Resource grouping and addressing. This paper provides an architectural overview of the WS-Resource framework. It motivates, introduces, and summarizes the interrelationships among five separate specification documents that provide the normative definition of the framework: WS-ResourceProperties, WS- ResourceLifetime, WS-RenewableReferences, WS-ServiceGroup, and WS-BaseFaults. We also describe how the WS-Resource framework can support the WS-Notification family of specifications for asynchronous notification.
We argue that objects that interact in a distributed system need to be dealt with in ways that are intrinsically different from objects that interact in a single address space. These differences are required because distributed systems require that the programmer be aware of latency, have a different model of memory access, and take into account issues of concurrency and partial failure. We look at a number of distributed systems that have attempted to paper over the distinction between local and remote objects, and show that such systems fail to support basic requirements of robustness and reliability. These failures have been masked in the past by the small size of the distributed systems that have been built. In the enterprise-wide distributed systems foreseen in the near future, however, such a masking will be impossible. We conclude by discussing what is required of both systems-level and application-level programmers and designers if one is to take distribution seriously.
In both e-business and e-science, we often need to integrate services across distributed, heterogeneous, dynamic "virtual organizations" formed from the disparate resources within a single enterprise and/or from external resource sharing and service provider relationships. This integration can be technically challenging because of the need to achieve various qualities of service when running on top of different native platforms. We present an Open Grid Services Architecture that addresses these challenges. Building on concepts and technologies from the Grid and Web services communities, this architecture defines a uniform exposed service semantics (the Grid service); defines standard mechanisms for creating, naming, and discovering transient Grid service instances; provides location transparency and multiple protocol bindings for service instances; and supports integration with underlying native platform facilities. The Open Grid Services Architecture also defines, in terms of Web Services Description Language (WSDL) interfaces and associated conventions, mechanisms required for creating and composing sophisticated distributed systems, including lifetime management, change management, and notification. Service bindings can support reliable invocation, authentication, authorization, and delegation, if required. Our presentation complements an earlier foundational article, "The Anatomy of the Grid," by describing how Grid mechanisms can implement a service-oriented architecture, explaining how Grid functionality can be incorporated into a Web services framework, and illustrating how our architecture can be applied within commercial computing as a basis for distributed system integration--within and across organizational domains.
Web Service Base Notification (WS-BaseNotification)
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WS-Resource Framework—Globus Alliance Perspectives
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I. Foster, WS-Resource Framework—Globus Alliance Perspectives, http://www.globus.org/wsrf/foster_wsrf.pdf.