Load Balancing Techniques in Cloud Computing

As Cloud Computing is growing rapidly and clients are demanding more services and better results, load balancing for the Cloud has become a very interesting and important research area. The top challenges and Issues faced by cloud Computing is Security, Availability, Performance etc. The issue availability is mainly related to efficient load balancing, resource utilization & live migration of data in the server. In clouds, load balancing, as a method, is applied across different data centres to ensure the network availability by minimizing use of computer hardware, software failures and mitigating recourse limitations. Load Balancing is essential for efficient operations in distributed environments. Hence this paper presents the various existing load balancing Technique in Cloud Computing based on different parameters

Bio-Inspired Load Balancing In Large-Scale WSNs Using Pheromone Signalling

Wireless sensor networks (WSNs) consist of multiple, distributed nodes each with limited resources. With their strict resource constraints and application-specific characteristics, WSNs contain many challenging tradeoffs. This paper proposes a bioinspired load balancing approach, based on pheromone signalling mechanisms, to solve the tradeoff between service availability and energy consumption. We explore the performance consequences of the pheromone-based load balancing approach using (1) a system-level simulator, (2) deployment of real sensor testbeds to provide a competitive analysis of these evaluation methodologies. The effectiveness of the proposed algorithm is evaluated with different scenario parameters and the required performance evaluation techniques are investigated on case studies based on sound sensors

Dynamic Load Balancing Algorithms For Cloud Computing

In cloud computing, the load balancing is one of the major requirment. Load is nothing but the of the amount of work that a system performs. Load can be classified as CPU load, memory size and network load. Load balancing is the process of dividing the task among various nodes of a distributed system to improve both resource utilization and job response time. Also avoiding a situation where some of the nodes are heavily loaded and others are idle. Load balancing ensures that every node in the network having equal amount of work (as per their capacity) at any instant of time. In This paper we survey the existing load balancing algorithms for a cloud based environment. DOI: 10.17762/ijritcc2321-8169.150612

Journal of Telecommunications and Information Technology, Load Balancing Based on Optimization Algorithms: An Overview, 2019, nr 4

Combinatorial optimization challenges are rooted in real-life problems, continuous optimization problems, discrete optimization problems and other significant problems in telecommunications which include, for example, routing, design of communication networks and load balancing. Load balancing applies to distributed systems and is used for managing web clusters. It allows to forward the load between web servers, using several scheduling algorithms. The main motivation for the study is the fact that combinatorial optimization problems can be solved by applying optimization algorithms. These algorithms include ant colony optimization (ACO), honey bee (HB) and multi-objective optimization (MOO). ACO and HB algorithms are inspired by the foraging behavior of ants and bees which use the process to locate and gather food. However, these two algorithms have been suggested to handle optimization problems with a single-objective. In this context, ACO and HB have to be adjusted to multiobjective optimization problems. This paper provides a summary of the surveyed optimization algorithms and discusses the adaptations of these three algorithms. This is pursued by a detailed analysis and a comparison of three major scheduling techniques mentioned above, as well as three other, new algorithms (resulting from the combination of the aforementioned techniques) used to efficiently handle load balancing issue

Load Balancing in Cloud Computing Systems

Cloud computing" is a term, which involves virtualization, distributed computing, networking, software and web services. A cloud consists of several elements such as clients, datacenter and distributed servers. It includes fault tolerance, high availability, scalability, flexibility, reduced overhead for users, reduced cost of ownership, on demand services etc. Central to these issues lies the establishment of an effective load balancing algorithm. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. This technique can be sender initiated, receiver initiated or symmetric type (combination of sender initiated and receiver initiated types). Our objective is to develop an effective load balancing algorithm using Divisible load scheduling theorm to maximize or minimize different performance parameters (throughput, latency for example) for the clouds of different sizes (virtual topology depending on the application requirement)

Comparative Analysis of Load Balancing Algorithms for Efficient Task Scheduling in Cloud Computing

Abstract: In the field of information technology cloud computing is a recently developed technology. In such a complicated system, an effective load balancing scheme is critical in order to meet peak user demands and deliver high-quality services. Load balancing is a way of distributing workload among several nodes over network links in order to maximize resource utilization, decrease data processing and response time, and avoid overload. There have been a number of load balancing algorithms suggested that concentrate on important factors including processing time, response time, and processing costs. These techniques, however, ignore cloud computing scenarios. At the same time, there is a few research works that focuses on the subject of load balancing in cloud computing. Motivated by this issue, this study addresses the load balancing challenge in cloud computing by comparing natural inspired Load Balancing Algorithms based on the resource utilization metric. The chosen load balancing methods will next be tested and assessed using the CloudSim simulator to choose the proper natural inspired Load balancing algorithms that solves the problem of load balancing in cloud computing, according to the result of the simulation it can be concluded that the LBA_HB is better than the HBB_LB based on the results for the response time, MakeSpan, and the degree of imbalance. Keywords: Load Balancing, Cloud Computing, Algorithms, CloudSim, HBB-LB, LBA_HB. Title: Comparative Analysis of Load Balancing Algorithms for Efficient Task Scheduling in Cloud Computing Author: Sawsan Rabaya, Yazeed Al Moayed International Journal of Computer Science and Information Technology Research ISSN 2348-1196 (print), ISSN 2348-120X (online) Vol. 11, Issue 3, July 2023 - September 2023 Page No: 160-171 Research Publish Journals Website: www.researchpublish.com Published Date: 18-September-2023 DOI: https://doi.org/10.5281/zenodo.8355059 Paper Download Link (Source) https://www.researchpublish.com/papers/comparative-analysis-of-load-balancing-algorithms-for-efficient-task-scheduling-in-cloud-computingInternational Journal of Computer Science and Information Technology Research, ISSN 2348-1196 (print), ISSN 2348-120X (online), Research Publish Journals, Website: www.researchpublish.co