Scalable Self-Governance Using Service Communities as Ambients

Randles, Martin; Taleb-Bendiab, A.; Lamb, David J.

doi:10.1109/services-i.2009.93

Cited by 12 publications

(4 citation statements)

References 26 publications

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“…Therefore, cloud computing in terms of infrastructure refers to a type of distributed and parallel system that comprises a set of interconnected virtual computers. These computers are dynamically provided and are offered as one or more integrated computing resources based on service level agreements [8]. These agreements are established during negotiations between service providers and consumers.…”

Section: Theoretical Foundations Of Research Cloud Networkmentioning

confidence: 99%

“…Gradually, these systems became smaller, and by higher processing power, became available to all users as personal computers. Then, it was possible to provide a network with higher processing power through connecting a set of these small systems so that it will meet more and heavier processing needs; but processing needs were increasingly growing and a need for larger and more powerful computing systems was felt [8].…”

Section: Theoretical Foundations Of Research Cloud Networkmentioning

confidence: 99%

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Foundations of Meta-heuristic Algorithms and Cloud Computing

Sharifi¹

2020

IJET

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Cloud computing refers to applications that are delivered as a service over the Internet. The computing model based on high-speed Internet networks is a new model for the delivery and consumption of virtual services. Cloud includes infrastructure, software, platform, and other computing resources using network. One of the problems existing in resource sharing in mobile cloud computing is scheduling the tasks in these cloud networks that are directly related to the issue of efficiency. In order to achieve this goal, scheduling needs to be optimized so that tasks will be implemented on the servers in a balanced way. This makes all servers being optimally used and reduces users' response receiving time. Load balancing is used in mobile cloud networks for this purpose. Load balancing enables tasks to be optimally scheduled on servers and realizes the main goal which is improving resource sharing and increasing network efficiency.

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Section: Theoretical Foundations Of Research Cloud Networkmentioning

confidence: 99%

Section: Theoretical Foundations Of Research Cloud Networkmentioning

confidence: 99%

Foundations of Meta-heuristic Algorithms and Cloud Computing

Sharifi¹

2020

IJET

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“…Cloud computing architecture is a focus of current research [1][2]. Resource allocation of cloud computing under different architectures is studied in literature [3][4] and a kind of resource allocation mechanism of self-protection is proposed and elaborated in literature [5]. Resource allocation system suitable for distributed computing is proposed in literature [6] and it effectively improves the service quality of cloud computing system.…”

Section: Introductionmentioning

confidence: 99%

Research on Cloud Computing Resource Scheduling Based on PSO-MC Algorithm

Xu¹,

Zhe-Jun²

2015

IJGDC

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The reasonable resource scheduling under the cloud computing environment has become the current research focus. Based on the disadvantages of the traditional particle swarm optimization, this paper introduces a membrane computing theory, and proposes a particle swarm optimization based on the membrane computing (PSO-MC). The paper first analyzes the problems of cloud resource scheduling, takes the membrane system as a framework, conducts the particle's local optimization for intramembrane and the particle swarm's global search and optimization for intermembrane, finds the optimal solution of cloud resource scheduling, and finally performs the algorithm simulation experiment via the CloudSim platform. According to the simulation experiment, the PSO-MC algorithm could reduce the average time to complete the task, improve the efficiency of task processing, and enable the cloud computing resource scheduling to be more reasonable.

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“…The virtual machine resource scheduling method presented will contribute to a balanced use of virtual machine resources in the cloud services resource pool. Literature [5] proposed a resource allocation mechanism of self-management, self-adjustment and self-protection in cloud computing resources, which…”

Section: Introductionmentioning

confidence: 99%

Resource Scheduling Simulation Design of Firefly Algorithm Based on Chaos Optimization in Cloud Computing

Miao¹

2014

IJGDC

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The problem of resources under the environment of cloud computing has always been the focus of research. In this paper, the Artificial Firefly Algorithm is studied, on the basis of which the chaos algorithm is introduced to improve the algorithm with regard to the problem of the subsequent search and optimization precision deficiency cause by the lack of initialization of firefly position in the firefly algorithm. Meanwhile, the updating of luciferin is improved. The improved algorithm is enhanced greatly in accuracy and performance. Through the simulation platform Cloudsim, it is found that under the cloud computing model, the algorithm presented in this paper can effectively reduce the average time spent by subtasks in processing request tasks, and thus improve the efficiency of task processing and achieve a rational allocation of resources.

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Scalable Self-Governance Using Service Communities as Ambients

Cited by 12 publications

References 26 publications

Foundations of Meta-heuristic Algorithms and Cloud Computing

Foundations of Meta-heuristic Algorithms and Cloud Computing

Research on Cloud Computing Resource Scheduling Based on PSO-MC Algorithm

Resource Scheduling Simulation Design of Firefly Algorithm Based on Chaos Optimization in Cloud Computing

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