Comprehensive survey on energy-aware server consolidation techniques in cloud computing

2021 ◽  
Author(s):  
Nisha Chaurasia ◽  
Mohit Kumar ◽  
Rashmi Chaudhry ◽  
Om Prakash Verma
Keyword(s):  
Cloud Computing ◽  
Energy Aware ◽  
Server Consolidation ◽  
Comprehensive Survey

A Comprehensive Survey on SLA Compliant Energy Aware Resource Allocation in Cloud Datacenters

2018 ◽  
Vol 6 (6) ◽  
pp. 335
Author(s):  
Anitha R ◽  
C Vidya Raj
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Load Balancing ◽  
Job Scheduling ◽  
Cost Effective ◽  
Service Users ◽  
Energy Aware ◽  
Art Works ◽  
Comprehensive Survey ◽  
Service Agreement

Cloud Computing has achieved immense popularity due to its unmatched benefits and characteristics. With its increasing popularity and round the clock demand, cloud based data centers often suffer with problems due to over-usage of resources or under-usage of capable servers that ultimately leads to wastage of energy and overall elevated cost of operation. Virtualization plays a key role in providing cost effective solution to service users. But on datacenters, load balancing and scheduling techniques remain inevitable to provide better Quality of Service to the service users and maintenance of energy efficient operations in datacenters. Energy-Aware resource allocation and job scheduling mechanisms in VMs has helped datacenter providers to reduce their cost incurrence through predictive job scheduling and load balancing. But it is quite difficult for any SLA oriented systems to maintain equilibrium between QoS and cost incurrence while considering their legal assurance of quality, as there should not be any violations in their service agreement. This paper presents some state-of-the-art works by various researchers and experts in the arena of cloud computing systems and particularly emphasizes on energy aware resource allocations, job scheduling techniques, load balancing and price prediction methods. Comparisons are made to demonstrate usefulness of the mechanisms in different scenarios.

scholarly journals Shadow Replication: An Energy-Aware, Fault-Tolerant Computational Model for Green Cloud Computing

Energies ◽  
2014 ◽  
Vol 7 (8) ◽  
pp. 5151-5176 ◽  
Author(s):  
Xiaolong Cui ◽  
Bryan Mills ◽  
Taieb Znati ◽  
Rami Melhem
Keyword(s):  
Cloud Computing ◽  
Computational Model ◽  
Fault Tolerant ◽  
Energy Aware ◽  
Green Cloud Computing ◽  
Green Cloud

scholarly journals A Survey on Mobile Edge Computing: Focusing on Service Adoption and Provision

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Kai Peng ◽  
Victor C. M. Leung ◽  
Xiaolong Xu ◽  
Lixin Zheng ◽  
Jiabin Wang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Networks ◽  
Edge Computing ◽  
Computation Offloading ◽  
Battery Life ◽  
Mobile Edge Computing ◽  
Service Adoption ◽  
Comprehensive Survey ◽  
And Storage ◽  
Execution Delay

Mobile cloud computing (MCC) integrates cloud computing (CC) into mobile networks, prolonging the battery life of the mobile users (MUs). However, this mode may cause significant execution delay. To address the delay issue, a new mode known as mobile edge computing (MEC) has been proposed. MEC provides computing and storage service for the edge of network, which enables MUs to execute applications efficiently and meet the delay requirements. In this paper, we present a comprehensive survey of the MEC research from the perspective of service adoption and provision. We first describe the overview of MEC, including the definition, architecture, and service of MEC. After that we review the existing MUs-oriented service adoption of MEC, i.e., offloading. More specifically, the study on offloading is divided into two key taxonomies: computation offloading and data offloading. In addition, each of them is further divided into single MU offloading scheme and multi-MU offloading scheme. Then we survey edge server- (ES-) oriented service provision, including technical indicators, ES placement, and resource allocation. In addition, other issues like applications on MEC and open issues are investigated. Finally, we conclude the paper.

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