Dynamic energy efficient load balancing strategy for computational grid

2021 ◽  
Author(s):  
Babar Nazir ◽  
Zulfiqar Ahmad
Keyword(s):  
Load Balancing ◽  
Energy Efficient ◽  
Computational Grid

Energy-efficient user association with load-balancing for cooperative IIoT network within B5G era

2021 ◽  
pp. 103110
Author(s):  
Xin Jian ◽  
Langyun Wu ◽  
Keping Yu ◽  
Moayad Aloqaily ◽  
Jalel Ben-Othman
Keyword(s):  
Load Balancing ◽  
Energy Efficient ◽  
User Association

scholarly journals A Survey on Investigating the Need for Intelligent Power-Aware Load Balanced Routing Protocols for Handling Critical Links in MANETs

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
B. Sivakumar ◽  
N. Bhalaji ◽  
D. Sivakumar
Keyword(s):  
Load Balancing ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Ad Hoc ◽  
Recent Literature ◽  
Mobile Nodes ◽  
Critical Nodes ◽  
Mobile Ad Hoc ◽  
Critical Links ◽  
Hoc Networks

In mobile ad hoc networks connectivity is always an issue of concern. Due to dynamism in the behavior of mobile nodes, efficiency shall be achieved only with the assumption of good network infrastructure. Presence of critical links results in deterioration which should be detected in advance to retain the prevailing communication setup. This paper discusses a short survey on the specialized algorithms and protocols related to energy efficient load balancing for critical link detection in the recent literature. This paper also suggests a machine learning based hybrid power-aware approach for handling critical nodes via load balancing.

HEROS: Energy-Efficient Load Balancing for Heterogeneous Data Centers

2015 ◽  
Author(s):  
Mateusz Guzek ◽  
Dzmitry Kliazovich ◽  
Pascal Bouvry
Keyword(s):  
Load Balancing ◽  
Energy Efficient ◽  
Data Centers ◽  
Heterogeneous Data

Energy-Efficient Virtualized Scheduling and Load Balancing Algorithm in Cloud Data Centers

2021 ◽  
Vol 11 (3) ◽  
pp. 34-48
Author(s):  
J. K. Jeevitha ◽  
Athisha G.
Keyword(s):  
Quality Of Service ◽  
Load Balancing ◽  
Energy Efficient ◽  
Data Centers ◽  
Scheduling Algorithm ◽  
Cloud Data ◽  
The Third ◽  
Cloud Data Centers ◽  
Load Balancing Algorithm

To scale back the energy consumption, this paper proposed three algorithms: The first one is identifying the load balancing factors and redistribute the load. The second one is finding out the most suitable server to assigning the task to the server, achieved by most efficient first fit algorithm (MEFFA), and the third algorithm is processing the task in the server in an efficient way by energy efficient virtual round robin (EEVRR) scheduling algorithm with FAT tree topology architecture. This EEVRR algorithm improves the quality of service via sending the task scheduling performance and cutting the delay in cloud data centers. It increases the energy efficiency by achieving the quality of service (QOS).

scholarly journals ENERGY EFFICIENT LOAD BALANCING FOR CLOUD DATA CENTER

2017 ◽  
Vol 10 (13) ◽  
pp. 162
Author(s):  
Amey Rivankar ◽  
Anusooya G
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Energy Efficient ◽  
Large Scale ◽  
Virtual Machines ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Efficient Resource ◽  
Cloud Data Centers ◽  
Near Future

Cloud computing is the latest trend in large-scale distributed computing. It provides diverse services on demand to distributive resources such asservers, software, and databases. One of the challenging problems in cloud data centers is to manage the load of different reconfigurable virtual machines over one another. Thus, in the near future of cloud computing field, providing a mechanism for efficient resource management will be very significant. Many load balancing algorithms have been already implemented and executed to manage the resources efficiently and adequately. The objective of this paper is to analyze shortcomings of existing algorithms and implement a new algorithm which will give optimized load balancingresult.

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