An Energy-Aware Virtual Machine Scheduling Method for Cloudlets in Wireless Metropolitan Area Networks

Xu, Xiaolong; Li, Yuancheng; Yuan, Yuan; Peng, Kai; Yu, Wenbin; Dou, Wanchun; Liu, Alex X.

doi:10.1109/cybermatics_2018.2018.00110

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…There are many kinds of edge servers [43]. Cloudlet is a type of edge server, which has been widely used in LAN and WMAN [25][26][27][44][45][46]. Computation offloading was originally studied in MCC [28][29][30][31][32][33].…”

Section: Related Workmentioning

confidence: 99%

An energy- and cost-aware computation offloading method for workflow applications in mobile edge computing

Peng

Zhu

Zhang

et al. 2019

J Wireless Com Network

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Mobile edge computing is becoming a promising computing architecture to overcome the resource limitation of mobile devices and bandwidth bottleneck of the core networks in mobile cloud computing. Although offloading applications to the cloud can extend the performance for the mobile devices, it may also lead to greater processing latency. Usually, the mobile users have to pay for the cloudlet resource or cloud resource they used. In this paper, we bring a thorough study on the energy consumption, time consumption, and cost of using the resource of cloudlet and cloud for workflow applications in mobile edge computing. Based on theoretical analysis, a multi-objective optimization model is established. In addition, a corresponding multi-objective computation offloading method based on non-dominated sorting genetic algorithm II is proposed to find the optimal offloading strategy for all the workflow applications. Finally, extensive experimental evaluations are performed to show that our proposed method is effective and energy-and cost-aware for workflow applications in MEC.

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Section: Related Workmentioning

confidence: 99%

An energy- and cost-aware computation offloading method for workflow applications in mobile edge computing

Peng

Zhu

Zhang

et al. 2019

J Wireless Com Network

Self Cite

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A systematic literature review on contemporary and future trends in virtual machine scheduling techniques in cloud and multi-access computing

Rana,

Jeribi,

Khan

et al. 2024

Front. Comput. Sci.

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IntroductionThe migration of business and scientific operations to the cloud and the surge in data from IoT devices have intensified the complexity of cloud resource scheduling. Ensuring efficient resource distribution in line with user-specified SLA and QoS demands novel scheduling solutions. This study scrutinizes contemporary Virtual Machine (VM) scheduling strategies, shedding light on the complexities and future prospects of VM design and aims to propel further research by highlighting existing obstacles and untapped potential in the ever-evolving realm of cloud and multi-access edge computing (MEC).MethodImplementing a Systematic Literature Review (SLR), this research dissects VM scheduling techniques. A meticulous selection process distilled 67 seminal studies from an initial corpus of 722, spanning from 2008 to 2022. This critical filtration has been pivotal for grasping the developmental trajectory and current tendencies in VM scheduling practices.ResultThe in-depth examination of 67 studies on VM scheduling has produced a taxonomic breakdown into three principal methodologies: traditional, heuristic, and meta-heuristic. The review underscores a marked shift toward heuristic and meta-heuristic methods, reflecting their growing significance in the advancement of VM scheduling.ConclusionAlthough VM scheduling has progressed markedly, the focus remains predominantly on metaheuristic and heuristic approaches. The analysis enlightens ongoing challenges and the direction of future developments, highlighting the necessity for persistent research and innovation in this sector.

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Issues and Challenges (Privacy, Security, and Trust) in Blockchain-Based Applications

Nair

Ramesh

Tyagi

2022

Research Anthology on Convergence of Blockchain, Internet of Things, and Security

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The major issues and challenges in blockchain over internet of things are security, privacy, and usability. Confidentiality, authentication, and control are the challenges faced in security issue. Hence, this chapter will discuss the challenges and opportunities from the prospective of security and privacy of data in blockchain (with respect to security and privacy community point of view). Furthermore, the authors will provide some future trends that blockchain technology may adapt in the near future (in brief).

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An Energy-Aware Virtual Machine Scheduling Method for Cloudlets in Wireless Metropolitan Area Networks

Cited by 4 publications

References 16 publications

An energy- and cost-aware computation offloading method for workflow applications in mobile edge computing

An energy- and cost-aware computation offloading method for workflow applications in mobile edge computing

A systematic literature review on contemporary and future trends in virtual machine scheduling techniques in cloud and multi-access computing

Issues and Challenges (Privacy, Security, and Trust) in Blockchain-Based Applications

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