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Load balanced transaction scheduling using Honey Bee Optimization considering performability in on‐demand computing system
Author(s) -
Mahato Dharmendra Prasad,
Singh Ravi Shankar
Publication year - 2017
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4253
Subject(s) - computer science , ant colony optimization algorithms , mathematical optimization , scheduling (production processes) , database transaction , dynamic priority scheduling , job shop scheduling , load balancing (electrical power) , distributed computing , artificial bee colony algorithm , foraging , algorithm , mathematics , artificial intelligence , embedded system , computer network , quality of service , routing (electronic design automation) , geometry , programming language , grid , ecology , biology
Summary The scheduling of load balanced transactions is an emerging problem in on‐demand computing system. This problem can be studied considering several parameters such as resource availability, performance, and reliability. The existing approaches to find the exact solutions for this problem are limited. This paper presents a Honey Bee Optimization (HBO)–based method to solve the mentioned problem. In this method, first, the load of the system is balanced and then the transactions are scheduled using foraging behavior of honey bees to find the optimal solutions. We also modify four known scheduling algorithms such as Ant Colony Optimization (ACO), Hierarchical Load Balanced Algorithm (HLBA), Dynamic and Decentralized Load Balancing (DLB), and Randomized to obtain transaction scheduling algorithms for the purpose of comparison with our proposed algorithm. The compared results show that the proposed algorithm performs better than the modified existing algorithms.