Dynamic Optical Data Center Network Load Balancing and Resource Allocation

2016 ◽  
Author(s):  
Henna Huang ◽  
Vincent W. S. Chan
Keyword(s):  
Resource Allocation ◽  
Load Balancing ◽  
Data Center ◽  
Optical Data ◽  
Data Center Network ◽  
Network Load ◽  
Network Load Balancing

Development of a Hybrid Algorithm for User Association and Resource Allocation to Improve Load Balancing and Energy Efficiency in 5G HetNet

2020 ◽  
Vol 19 (1) ◽  
pp. 17-25
Author(s):  
Elvis Obi ◽  
Aliyu Danjuma Usman ◽  
Suleiman Muhammad Sani ◽  
Abdoulie Momodou Sunkary Tekanyi
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Load Balancing ◽  
Bandwidth Allocation ◽  
Hybrid Algorithm ◽  
Control Algorithm ◽  
User Association ◽  
Network Load ◽  
Power Control Algorithm ◽  
Network Load Balancing

This paper presents the development and integration of a power control algorithm into the User Association Algorithm with Optimal Bandwidth Allocation (UAAOBA) to form a Hybrid Algorithm for User Association and Resource Allocation (HAUARA). The power control algorithm updates the transmit power of the Base Stations (BSs) towards a minimum transmit power that satisfies the minimum data rate requirement (1 Gbps) of the User Equipment UEs. The power update is achieved using the Newton Rhapson’s method and it adapts the transmit powers of the BSs to the number of their connected UEs. The developed HAUARA provides an optimal solution for user associations, bandwidth allocation, and transmit powers to UEs concurrently. This maximizes the network energy efficiency by coordinating the load fairness of the network while guaranteeing the quality of service requirement of the UEs. The network energy efficiency performance of the developed HAUARA is compared with that of the UAAOBA. The results show that the developed algorithm has network energy efficiency improvement of 12.36%, 10.58%, and 13.44% with respect to UAAOBA for increase number of macro BS antennas, pico BSs, and femto BSs, respectively. Also, the network load balancing performance of the developed HAUARA is compared with that of the UAAOBA. The results show that the developed algorithm has network load balancing improvement of 12.62%, 10.04%, and 10.34% with respect to UAAOBA for increase number of macro BS antennas, pico BSs, and femto BSs, respectively. This implies that the developed algorithm outperforms the UAAOBA in terms of network energy efficiency and load balancing.

scholarly journals A Review on: Network Load Balancing in Dynamic Data Center

IJARCCE ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 88-91
Author(s):  
Prof. Nitin Chopde ◽  
Shrikant Deshmukh
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Dynamic Data ◽  
Network Load ◽  
Network Load Balancing

Study on Network Load Balancing Algorithm Based on Server Cluster System

2012 ◽  
Vol 182-183 ◽  
pp. 1978-1981 ◽  
Author(s):  
Li Lan ◽  
Chu Huan Qi
Keyword(s):  
Load Balancing ◽  
Load Balance ◽  
Cluster System ◽  
Utilization Efficiency ◽  
Server Cluster ◽  
Use Of Resources ◽  
Network Load ◽  
System Resource ◽  
Network Load Balancing ◽  
Load Balancing Algorithm

The utilization efficiency of system resources is a key issue for cluster system while load balance is an important tool to realize the efficient use of resources. Based on server cluster system, this paper puts forwards an improved self-adaptive algorithm for network load balancing. Simulation results show that the algorithm can improve the utilization efficiency of system resource and reduce the server’s response time so as to achieve the request of real time when dealing with tasks and high availability of system.

Sign in / Sign up

Export Citation Format

Share Document