The Role of Grid Computing Technologies in Cloud Computing

Villegas, David; Rodero, Iván; Fong, Liana; Bobroff, Norman; Liu, Yanbin; Parashar, Manish; Sadjadi, S. Masoud

doi:10.1007/978-1-4419-6524-0_8

Cited by 10 publications

(7 citation statements)

References 47 publications

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“…In the general scheduling problem, given a set of jobs and requirements, a set of resources and the system status, the algorithms should map the jobs to the appropriate resources. In Cloud computing, the factors such as economic considerations and efficient resource provisioning in terms of QoS guarantees, utilization and energy are playing a vital role [5]. Clouds provide the abstraction of nearly unlimited computing resources through the elastic use of consolidated resource pools.…”

Section: Schedulingmentioning

confidence: 99%

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Cloud Scheduling - A Survey

GeorgeAmalarethinam¹,

Beena²

2014

IJCA

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Cloud computing is a new technological trend that supports better utilization of IT infrastructure, services and applications. It follows pay-per-use approach for its services, in which user do not need to own infrastructure, platform or applications but use them at any time wherever they need them. The realization of Cloud computing has become a reality with the support of various paradigms like Distributed Systems, Virtualization, Web 2.0, Service-oriented Computing and Utility Computing. In all these paradigms, scheduling forms an important role. In the last few decades a lot of research has been devoted to scheduling starting from High Performance Computing facilities, still there are lot of issues related to scheduling with respect to cloud scenario. In this paper, existing scheduling algorithms such as online scheduling, cost-effective scheduling, workflow scheduling etc., for cloud scenario were compared. This survey shows the need for new algorithms with energy efficiency, bandwidth usage and power efficiency are to be considered for the better cloud services.

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Section: Schedulingmentioning

confidence: 99%

“…how to dynamically allocate resources among VMs with the goal of optimizing a global utility function[5].…”

mentioning

confidence: 99%

Cloud Scheduling - A Survey

GeorgeAmalarethinam¹,

Beena²

2014

IJCA

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“…Cloud computing is an emerging technology recently, which has numerous novel features, such as large-scale resource sharing, dynamic and flexible resource management, and on-demand resource provisioning [5]. Cloud computing takes advantage of Gird technology which enables integration of resources across distributed heterogeneous dynamic virtual organizations [6]. A grid service is designed to execute a certain task under the control of the resource management system (RMS) [7].…”

Section: Introductionmentioning

confidence: 99%

A Correlated Model for Evaluating Performance and Energy of Cloud System Given System Reliability

Zhang

Zhou

2015

Discrete Dynamics in Nature and Society

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The serious issue of energy consumption for high performance computing systems has attracted much attention. Performance and energy-saving have become important measures of a computing system. In the cloud computing environment, the systems usually allocate various resources (such as CPU, Memory, Storage, etc.) on multiple virtual machines (VMs) for executing tasks. Therefore, the problem of resource allocation for running VMs should have significant influence on both system performance and energy consumption. For different processor utilizations assigned to the VM, there exists the tradeoff between energy consumption and task completion time when a given task is executed by the VMs. Moreover, the hardware failure, software failure and restoration characteristics also have obvious influences on overall performance and energy. In this paper, a correlated model is built to analyze both performance and energy in the VM execution environment given the reliability restriction, and an optimization model is presented to derive the most effective solution of processor utilization for the VM. Then, the tradeoff between energy-saving and task completion time is studied and balanced when the VMs execute given tasks. Numerical examples are illustrated to build the performance-energy correlated model and evaluate the expected values of task completion time and consumed energy.

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“…But transactional applications cannot be deployed in the Cloud due to eventual consistency. Data grid may play an important role in deploying applications in Cloud [3]. Data Grid often keeps data fully or partially as data sets.…”

Section: Introductionmentioning

confidence: 99%

Improving Performance of Cloud based Transactional Applications using In-Memory Data Grid

Arora¹,

Gupta²

2014

IJCA

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Browser based applications are used currently to handle data related requirements of educational institutes. Such applications are not scalable due to limited scalability of database servers. The performance of such applications can be improved with the use of Cloud Computing and In-memory Data Grid (IMDG). IMDG uses the concept of caching to keep frequently used data in memory which is required by an application. This ensures high availability of data to the application. Due to cached data, the performance of the application also increases. This paper proposes the usage of IMDG for deploying transactional applications of educational institutes in the Cloud. This paper also points out performance issues in using IMDG. Then the paper proposes an approach to solve the identified performance issues of transactional applications required by educational institutes in Cloud environment. An analysis of proposed approach with traditional approach highlights better access time, availability and scalability.

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The Role of Grid Computing Technologies in Cloud Computing

Cited by 10 publications

References 47 publications

Cloud Scheduling - A Survey

Cloud Scheduling - A Survey

A Correlated Model for Evaluating Performance and Energy of Cloud System Given System Reliability

Improving Performance of Cloud based Transactional Applications using In-Memory Data Grid

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