A Novel Algorithm for Optimizing Multiple Services Resource Allocation

Resource provisioning becomes more and more challenging problem in cloud computing environment since cloud-based services become more numerous and dynamic. The problem of scheduling multiple tasks for multiple users on a given number of resources is considered NP-Complete problem, and therefore, several heuristic based research methods were proposed, yet, there are still many improvements can be done, since the problem has several optimization parameters. In addition, most proposed solutions are built on top of several assumptions and simplifications by applying computational methods such as game theory, fuzzy logic, or evolutionary computing. This paper presents an algorithm to address the problem of resource allocation across a cloud-based network, where several resources are available, and the cost of computational service depends on the amount of computation. The algorithm is applicable without restrictions on cost vector or compaction time matrix as opposed to methods in the literature. In addition, the execution of the algorithm shows better utility compared to methods applied on similar problems.