Hyperheuristic Framework with Evolutionary and Deterministic Algorithms for Virtual Machine Placement Problem

Abstract

Virtual machine placement in cloud computing requires to handle issues like energy efficiency, traffic optimization, load balancing, resource management, etc. VMP problem is constrained satisfaction problem belongs to category of NP problems. Hyperheuristic provides more general framework for range of problems and offer optimal solutions. In this paper, we proposed hyperheuristic framework for VMP problem with evolutionary algorithms and deterministic algorithms. Tabu search technique and Warm-up techniques are compared as higher level heuristics. Low level heuristics tested are first fit, best fit, Intelligent Water Drop and Simulated Annealing. Results of proposed hyperheuristic framework are compared with individual evolutionary algorithms for twelve instances. Results shows that hyperheuristic works better for all instances.