Load Balancing Approaches: Recent Computing Trends

Abstract

This paper presents thorough survey of work addressing on load balancing in recent computing trends. There are many issues whose solutions lead to the need for load balancing. The objective of load balancing is to increase the performance of parallel and distributed system by distributing the load among the processors. Load balancing is a major factor for achieving high performance. It affects the execution time significantly by expediting it. Load imbalance is a wellknown problem in the areas involving parallelism. However, offering load balancing is a difficult and challenging task. Various algorithms have been proposed for load balancing. These algorithms have distinguished features and each uses different mechanisms. Various Load balancing algorithms like biased sampling, honey bee, active clustering, and join idle queue have been studied. General TermsParallel and distributed computing.

Load Balancing in Multicore Systems using Heuristics Based Approach

“…Many researchers have proposed different strategies to schedule the tasks and balance the workload of the system considering different areas of application . Some application areas are load balancing in parallel computing [4], fog computing [5], cloud computing [6,7] and real time environment [8][9][10][19][20][21][22][23][24]. An efficient load balancing real time algorithm is one in which the tasks are schedulable, their deadlines are met and the load is balanced after task assignment such that the resources are effectively used with no overload or under load constraints.…”