Balanced task allocation in the on-demand computing-basedrntransaction processing system using social spider optimization

摘要

Balanced task allocation is one of the methods that can be used to maximize the performance andrnreliability in the on-demand computing-based transaction processing system. On-demand computingrnis an increasingly popular enterprise model. It provides computing resources to the userrnas needed, which may be maintained within the user's enterprise, or made available by a servicernprovider. The balanced task allocation in such environment is known to be an NP hard. Thernreliability is a measure of trustworthiness of the system while executing the task. So we derivernthe reliability formula for the on-demand computing-based transaction processing system consideringrnresource availability. We propose the balanced task allocation based on social spiderrnoptimization (LBTA_SSO) method for this problem. The LBTA_SSO is based on the cooperativernbehavior of social-spiders to find a collectionof task allocation solutions.Wemodified five existingrnalgorithms to obtain the task allocation algorithms; Honey Bee Optimization (HBO), Ant ColonyrnOptimization (ACO), Hierarchical Load Balanced Algorithm (HLBA), Dynamic and DecentralizedrnLoad Balancing (DLB), and Randomized Algorithm respectively. Then,we compared the proposedrnalgorithmwith these modified algorithms. The results show that our algorithmworks better thanrnthemodified existing algorithms.