A Distributed Fault Tolerant Algorithm for Load Balancing in Cloud Computing Environments

Cloud computing is a promising paradigm that provides users with higher computing benefits in terms of cost, availability and flexibility. Nevertheless, with potentially thousands of connected machines, faults become more frequent and may have an adverse effect on the application. Consequently, fault-tolerant load balancing becomes necessary in order to optimize resource utilization while ensuring the reliability of the system. Different approaches have been proposed in the literature for fault tolerance in cloud computing. However, they suffer from several shortcomings: some fault tolerance techniques use task replication which reduce the cloud’s efficiency in terms of resource utilization. While other models rely on checkpoint recovery to tolerate failures, resulting in an increase in the mean response time. To address these shortcomings, an efficient and adaptive fault tolerant algorithm for load balancing is proposed. Based on the CloudSim simulator, some series of test-bed scenarios are considered to assess the behavior of the proposed algorithm

A survey of load balancing in distributed systems

International audienceWith the technological progress, distributed systems are widely used for parallel processing of computationally intensive applications with heterogeneous computing needs. Such environments require effective load balancing (LB) strategies that consider both algorithmic and architectural constraints. Indeed, the efficient load balancing of applications is crucial in order to reach high performance in parallel and distributed systems. By and large, the objective of load balancing is to find a judicious and suitable workload distribution in order to reduce as much as possible the load difference between the computational resources of the network. The proposed work presents a rigorous survey of the relevant existing load balancing techniques in several types of distributed systems. A detailed classification, the strengths and weaknesses of these techniques have been investigated according to the general characteristics of the underlying systems. We also present the main issues and features of fault tolerance and reliability for load balancing in distributed systems

Load balancing in cloud computing environments based on adaptive starvation threshold

International audienceClouds provide to users on‐demand access to large computing and storing resources and offer over on premise IT infrastructures many advantages in terms of cost, flexibility, and availability. However, this new paradigm still faces many challenges, and in this paper, we address the load balancing problem. Even though many approaches have been proposed to balance the load among the servers, most of them are too sensitive to the fluctuation in the clouds load and produce unstable systems. In this paper, we propose a new distributed load balancing algorithm, based on adaptive starvation threshold. It tries to balance the load between the servers while minimizing the response time of the cloud, maximizing the utilization rate of the servers, decreasing the overall migration cost, and maintaining the stability of the system. The performance of the proposed algorithm was compared to a well‐known load balancing algorithm, inspired from the honey bee behavior (HBB). The experimental results showed that the application of the proposed load balancing algorithm gives considerable performance gains and a significant reduction in number of migrations when compared to the performance of the HBB algorithm

A New Fault-Tolerant Algorithm Based on Replication and Preemptive Migration in Cloud Computing

International audience<span id="ctl00_ctl00_cphMain_cphSection_lblAbstract" class="margin-bottom-10"&gtCloud computing is a promising paradigm thatprovides users higher computation advantages in terms of cost,flexibility, and availability. Nevertheless, with potentiallythousands of connected machines, faults become more frequent.Consequently, fault-tolerant load balancing becomes necessary inorder to optimize resources utilization while ensuring thereliability of the system. Common fault tolerance techniques incloud computing have been proposed in the literature. However, theysuffer from several shortcomings: some fault tolerance techniquesuse checkpoint-recovery which increases the average waiting timeand thus the mean response time. While other models rely on taskreplication which reduces the cloud's efficiency in terms ofresource utilization under variable loads. To address thesedeficiencies, an efficient and adaptive fault tolerant algorithmfor load balancing is proposed. Based on the CloudSim simulator,some series of test-bed scenarios are considered to assess thebehavior of the proposed algorithm.</span&g