A Network Load Balancing Algorithm Design Based on Big Data

2021 ◽  
Author(s):  
Lingfang Huang ◽  
Yi Shu
Keyword(s):  
Big Data ◽  
Load Balancing ◽  
Algorithm Design ◽  
Network Load ◽  
Network Load Balancing ◽  
Load Balancing Algorithm

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.

scholarly journals Load balancing algorithm based-SDN for the IoT applications

2021 ◽  
Vol 21 (2) ◽  
pp. 1209
Author(s):  
Hind Sounni ◽  
Najib El kamoun ◽  
Fatima Lakrami
Keyword(s):  
Load Balancing ◽  
Network Information ◽  
Network Load ◽  
Global View ◽  
Communication Devices ◽  
Network Load Balancing ◽  
Iot Devices ◽  
Load Balancing Algorithm ◽  
Unbalanced Network ◽  
Communication Habits

Nowadays, the emergence of IoT devices has wholly revolutionized the customer's communication habits. The information can be collected at anytime and anywhere. However, the mobility of communication devices in a dense network results in an unbalanced network load and an increase in bandwidth demands. To address these issues, this study proposed a load balancing algorithm based on SDN for enhancing the performance of mobile IoT devices communication over a Wi-Fi network. The use of the SDN makes possible the automatic configuration of the network through a centralized controller, it provides programmability, a global view of the network, it also optimizes resource allocation based on real-time network information that helps implement our algorithm. The proposed algorithm is evaluated through simulation using mininet. The results indicate that our proposed method provides an efficient network load balancing and improves the throughput of associated devices.

scholarly journals RHLB: Improved Routing Load Balancing Algorithm Based on Hybrid Policy

2019 ◽  
Vol 27 (1) ◽  
pp. 324-337
Author(s):  
Muna Mohammed Jawad ◽  
Noor Mohammed Mahdi
Keyword(s):  
Load Balancing ◽  
Packet Loss ◽  
Network Performance ◽  
Delivery Ratio ◽  
Network Simulator ◽  
Network Load ◽  
Dynamic Policy ◽  
Network Load Balancing ◽  
Load Balancing Algorithm ◽  
Network Overhead

A network is defined as a set of nodes that are associated with a way to handle and transfer data and messages from source to destination. The congestion in the network occurs when a lot of traffic occurs, leads to delay, packet loss, bandwidth degradation, and high network overhead. Load balancing algorithms have been designed to reduce congestion in the network. Load Balancing is the redistribution of workload between two or more nodes to be executed at the same time. Two policies of load balancing algorithms: static and dynamic load balancing. This paper proposes a load balancing algorithm based on the hybrid (static and dynamic) policy using Network Simulator (version 2). The hybrid policy is used to improve network performance by redistributing the load between overloaded nodes to other nodes that are under loaded when congestion occurs. The simulation results show that the proposed algorithm used performance of the network with regard to throughput, packet delivery ratio, packet loss and the end-to-end delay.

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.

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