A new agent-based method for QoS-aware cloud service composition using particle swarm optimization algorithm

Naseri, Afshin; Navimipour, Nima Jafari

doi:10.1007/s12652-018-0773-8

Cited by 129 publications

(84 citation statements)

References 58 publications

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“…To select the VMs to be migrated from the source node, the load of each VM is calculated on the source node based on Equation (13). The VM with the maximum load value is nominated to be relocated on the destination node, where job j represents the total number of jobs running on the jth VM and ith node.…”

Section: Second Step: Selection Of Vmsmentioning

confidence: 99%

“…Cloud computing includes a wide range of resources: storage, processing, memory, bandwidth, and network . Four types of these virtualized services are regularly recognized: software as a service, infrastructure as a service, platform as a service, and expert as a service …”

Section: Introductionmentioning

confidence: 99%

“…8,9 Four types of these virtualized services are regularly recognized: software as a service, infrastructure as a service, platform as a service, and expert as a service. [10][11][12][13][14][15] On the other hand, virtualization is a technique that hides the physical properties of resources while still making access possible for users. 16 This technique simultaneously creates the possibility of separating or sharing cloud resources between several different environments, which are called virtual machines (VMs), so that these VMs can interact with each other.…”

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confidence: 99%

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A method for virtual machine migration in cloud computing using a collective behavior‐based metaheuristics algorithm

Sha

Ebadi

Mavaluru

et al. 2019

Concurrency and Computation

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Summary Due to the growth of applications and the integration of new customers into the world of computing systems, computing needs to be changed and to become more powerful and flexible than before. Meanwhile, cloud computing is presented as a model beyond a system that is currently capable of answering most request needs. Flexible infrastructure for cloud computing and virtualization technology provide new features to support business activities. Clouds are a very important topic that used secure management tools for storage, security and securing data centers in a flexible manner. One of the important matters in cloud technologies is virtual machine migration (VMM). There are different ways to implement the VMM, but because of the limitation of resources' energy, energy management is also very important and challenging. Due to the NP‐hard nature of this problem, this paper presents an energy‐aware VMM engine for cloud computing using the discrete bacterial foraging algorithm as a new collective behavior‐based metaheuristics algorithm. The CloudSim simulator is employed to investigate the efficiency of this method. The obtained results have shown that the proposed method improves the energy consumption and the migration count.

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Section: Second Step: Selection Of Vmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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A method for virtual machine migration in cloud computing using a collective behavior‐based metaheuristics algorithm

Sha

Ebadi

Mavaluru

et al. 2019

Concurrency and Computation

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“…In latency and location‐sensitive applications, FC provides a great deal of communication, control, storage, management, configuration, and measurement at the edge of a network. That is why FC is proposed as a powerful complement for cloud . To be specific, instead of sending all data collected to the cloud, FC suggests to processing data at the edges.…”

Section: Introductionmentioning

confidence: 99%

Quality of service‐aware approaches in fog computing

Kashani

Rahmani

Navimipour

2020

Int J Communication

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Summary In recent years, fog computing, a novel paradigm, has emerged for location and latency‐sensitive applications. It is a powerful complement for cloud computing that enables provisioning services and resources outside the cloud near the end devices. In a fog system, the existence of several nonhomogenous devices, which are potentially mobile, led to quality of service (QoS) worries. QoS‐aware approaches are presented in various parts of the fog system, and several different QoS factors are taken into account. In spite of the importance of QoS in fog computing, no comprehensive study on QoS‐aware approaches exists in fog computing. Hence, this paper reviews the current research used to guarantee QoS in fog computing. This paper investigates the QoS‐ensuring techniques that fall into three categories: service/resource management, communication management, and application management (published between 2013 and October 2018). Regarding the selected approaches, this paper represents merits, demerits, tools, evaluation types, and QoS factors. Finally, on the basis of the reviewed studies, we suggest some open issues and challenges which are worth further studying and researching in QoS‐aware approaches in fog computing.

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“…The CC is a rather novel notion of introducing on-request ascendable and virtualized resources, software, and hardware to users. 16,17 The CC is an Internet-oriented method offering heterogeneity, trustworthiness, place independence, openness, execution agility, broad network access, flexibility, voluntariness, ambiguity, scalability, dynamicity, quick amenities compliance, less money spending, delivery, and resource pooling for an array of usages. 18,19 The cloud services are divided into three main types, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).…”

Section: Introductionmentioning

confidence: 99%

A comprehensive study on managing strategies in the fog environments

Wang

Panpan

Batiha

2019

Trans Emerging Tel Tech

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Although cloud computing application is rising, some unanswered problems still exist because of its inner issues like untrustworthy inactivity, the absence of movement backing, and place awareness. Therefore, fog computing has appeared as a hopeful infrastructure to supply flexible resources at the edge of the network. Fog supplies processing, data, storing, and application amenities to ultimate operators. The management strategies have a great impact on fog computing, such as monitoring and optimizing, the correlated components for improving the performance, availability, security, and any fundamental operational requirement. However, as far as we know, no organized study exists about analyzing their importance in fog environments. This paper provides a detailed survey for covering the current state‐of‐the‐art in fog management. This paper classifies the management strategies into three main categories: data management, energy, and resource. We also presented a few prospects and problems like the suggestions for the upcoming studies in the associated methods requiring to be investigated in fog computing. Moreover, a new paradigm has been ensured by increasing fog functionality and resource consumption. In general, fog management strategies in computing environments still need improvements in the variety of its setting to convert to an on‐request method, decrease the associated overhead, and improve the performance. Therefore, proper management can maintain the least resource consumption, which will finish the extra decrease in energy usage. Therefore, we contribute to provide strong suggestions for future fog computing studies. This paper can handle the pace of publications and propose the outcomes of study and practice as an upcoming route for decision makers in healthcare. In principle, the increase of researchers, scientists and managers' awareness level would increase the managers' good and knowingly behavioral conduct on managing fog environments.

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A new agent-based method for QoS-aware cloud service composition using particle swarm optimization algorithm

Cited by 129 publications

References 58 publications

A method for virtual machine migration in cloud computing using a collective behavior‐based metaheuristics algorithm

A method for virtual machine migration in cloud computing using a collective behavior‐based metaheuristics algorithm

Quality of service‐aware approaches in fog computing

A comprehensive study on managing strategies in the fog environments

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