scholarly journals Efficient Load Balancing Algorithm over Heterogeneous Wireless Packet Networks

2011 ◽  
Vol 1 (1) ◽  
Author(s):  
Quoc-Thinh Nguyen-Vuong ◽  
Nazim Agoulmine
Keyword(s):  
Load Balancing ◽  
Link Quality ◽  
Radio Link ◽  
Packet Networks ◽  
New Approach ◽  
Network Load ◽  
Radio Resources ◽  
Load Balancing Algorithm ◽  
Load Balancer ◽  
Wireless Packet

The paper aims at improving the load balancing algorithm in wireless packet cellular networks and particularly in coordinated heterogeneous wireless packet networks. Our main contributions are two-fold. First, we introduce a new approach to compute the network load metric based on the radio link quality and scheduling information, which can be applied to any wireless packet system. This load metric hides the radio resources heterogeneity of different access technologies from the load balancer. Secondly, we propose a new practical load balancing algorithm which provides a more efficient way to manage the scarce radio resources. The proposed approach has been compared with different existing schemes and the results show the superiority of the proposed solution.

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 Software Defined Network: Load Balancing Algorithm Design and Analysis

2021 ◽  
Vol 18 (3) ◽  
Author(s):  
Senthil Prabakaran ◽  
Ramalakshmi Ramar
Keyword(s):  
Load Balancing ◽  
Algorithm Design ◽  
Threshold Value ◽  
Critical Issue ◽  
Software Defined Network ◽  
Traffic Pattern ◽  
Negative Impacts ◽  
Load Balancing Algorithm ◽  
Load Balancer ◽  
The Cost

Software Defined Network (SDN) cut down the monopolies of producing network devices and their applications. It allows the use of an omniscient controller that manages the overall network and promises for simplifying the configuration and management burden of the traditional Internet Protocol (IP) network. The use of hardware load balancer is a critical issue in conventional IP networks that creates many negative impacts such as the cost affordability, features customization, and availability. Also, the existing load balancing algorithm does not consider the flow size generated by the client nodes. Further, flows are not classified based on the threshold value of the dynamic flow size. The paper proposes to compare the performance of two load balancing algorithms such as flow-based load balancing algorithm and traffic pattern-based load balancing algorithm with distributed controllers' architecture. The result shows that the flow-based load balancing algorithm minimizes response time by 94%, enhances transaction rate by 14% and Traffic pattern-based load balancing algorithm has improved availability by 2.69%.

scholarly journals Enhanced Weighted Round Robin Load Balancing Algorithm in Cloud Computing

2019 ◽  
Vol 8 (9S2) ◽  
pp. 148-151
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Task Assignment ◽  
Round Robin ◽  
Utility Computing ◽  
Distributed Environment ◽  
Dynamic Task ◽  
Computing Model ◽  
Network Load ◽  
Load Balancing Algorithm

The cloud/utility computing model requires a dynamic task assignment to cloud sites with the goal that the performance and demand handling is done as effectively as would be prudent. Efficient load balancing and proper allocation of resources are vital systems to improve the execution of different services and make legitimate usage of existing assets in the cloud computing atmosphere. Consequently, the cloud-based infrastructure has numerous kinds of load concerns such as CPU load, server load, memory drain, network load, etc. Thus, an appropriate load balancing system helps in realizing failures, reducing backlog problems, adaptability, proper resource distribution, expanding dependability and client fulfillment and so forth in distributed environment. This thesis reviewed various popular load balancing algorithms. Modified round robin algorithms are popularly employed by various giant companies for scheduling issues and load balancing. An enhanced weighted round robin algorithm is discussed in this paper concentrating on efficient load balancing and effective task scheduling and resource management.

scholarly journals An Efficient Novel Load Balancing Algorithm to Improve the Performance of the System in Cloud Environment

2019 ◽  
Vol 8 (S3) ◽  
pp. 105-108
Author(s):  
P. Neelima ◽  
A. Rama Mohan Reddy
Keyword(s):  
Load Balancing ◽  
Fitness Function ◽  
Dynamic Environment ◽  
Computing System ◽  
Dragonfly Algorithm ◽  
Main Challenge ◽  
Cloud Computing System ◽  
Load Balancing Algorithm ◽  
Load Balancer ◽  
Is Design

Distribution of workload in a balanced manner is a main challenge in cloud computing system. It distributes workload among multiple nodes, hence resources are properly utilized. This is an optimization problem and a good load balancer should be involved for this strategy to the types of tasks and dynamic environment. To overcome load balancing problem here a Novel Load balancing Algorithm is develop i.e. Dragonfly Algorithm is design and developed, to execute the entire task with shortest completion time and load balanced. Our algorithm will be presented with efficient solution representation, derivation of efficient fitness function (or multi-objective function) along with the usual Dragonfly operators. The performance of the algorithm will be analyzed based on the different evaluation measures. The algorithms like particle swarm optimization (PSO) and Genetic algorithm (GA) will be taken for the comparative analysis.

scholarly journals METHOD FOR ORGANIZING MULTIPATH ROUTING IN SDN NETWORKS

2019 ◽  
pp. 18-28
Author(s):  
Oleksandr Kaliuzhnyi
Keyword(s):  
Comparative Analysis ◽  
Load Balancing ◽  
Routing Algorithm ◽  
Multipath Routing ◽  
Network Resources ◽  
Equal Distribution ◽  
Network Load ◽  
Optimal Load ◽  
Routing Method ◽  
Load Balancing Algorithm

In this work we propose a method for organizing multipath routing for SDN networks. It have two main parts. The fisrt one is a routing method based on modified wave algorithm for finding paths, and second one is load balancing method based on ECMP algorithm. Combination of these methods can optimize using of network resources and provide a more optimal load balancing of network. The basis of routing algorithm is the search and use partially-overlapping routes. The basis of load balancing algorithm is equal distribution network load between all found routes. A comparative analysis with an existing algorithms for routing and load balancing was conducted and the advantages of this development are presented.

scholarly journals Resilience enhancement of container-based cloud load balancing service

2018 ◽  
Author(s):  
Dongsheng Zhang
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Real Time ◽  
Significant Role ◽  
Current Load ◽  
Web Traffic ◽  
Computing Environments ◽  
Load Balancing Algorithm ◽  
Load Balancer ◽  
Computing Infrastructure

Web traffic is highly jittery and unpredictable. Load balancer plays a significant role in mitigating the uncertainty in web environments. With the growing adoption of cloud computing infrastructure, software load balancer becomes more common in recent years. Current load balancer services distribute the network requests based on the number of network connections to the backend servers. However, the load balancing algorithm fails to work when other resources such as CPU or memory in a backend server saturates. We experimented and discussed the resilience evaluation and enhancement of container-based software load balancer services in cloud computing environments. We proposed a pluggable framework that can dynamically adjust the weight assigned to each backend server based on real-time monitoring metrics.

scholarly journals Simulation and performance assessment of a modified throttled load balancing algorithm in cloud computing environment

2022 ◽  
Vol 12 (2) ◽  
pp. 2087
Author(s):  
Noha G. Elnagar ◽  
Ghada F. Elkabbany ◽  
Amr A. Al-Awamry ◽  
Mohamed B. Abdelhalim
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Processing Time ◽  
Virtual Machines ◽  
Active Monitoring ◽  
Load Fluctuation ◽  
Load Balancing Algorithm ◽  
And Performance ◽  
Load Balancer

<span lang="EN-US">Load balancing is crucial to ensure scalability, reliability, minimize response time, and processing time and maximize resource utilization in cloud computing. However, the load fluctuation accompanied with the distribution of a huge number of requests among a set of virtual machines (VMs) is challenging and needs effective and practical load balancers. In this work, a two listed throttled load balancer (TLT-LB) algorithm is proposed and further simulated using the CloudAnalyst simulator. The TLT-LB algorithm is based on the modification of the conventional TLB algorithm to improve the distribution of the tasks between different VMs. The performance of the TLT-LB algorithm compared to the TLB, round robin (RR), and active monitoring load balancer (AMLB) algorithms has been evaluated using two different configurations. Interestingly, the TLT-LB significantly balances the load between the VMs by reducing the loading gap between the heaviest loaded and the lightest loaded VMs to be 6.45% compared to 68.55% for the TLB and AMLB algorithms. Furthermore, the TLT-LB algorithm considerably reduces the average response time and processing time compared to the TLB, RR, and AMLB algorithms.</span>

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