Abstract
The main aim of this research is to design the hybrid evolutionary algorithm for minimizing multiple problems of dynamic resource allocation in cloud computing. The resource allocation is one of the big problems in the distributed systems when the client wants to decrease the cost for the resource allocation for their task. In order to assign the resource for the task, the client must consider the monetary cost and computational cost. Allocation of resources by considering those two costs is difficult. To solve this problem in this study, we make the main task of client into many subtasks and we allocate resources for each subtask instead of selecting the single resource for the main task. The allocation of resources for the each subtask is completed through our proposed hybrid optimization algorithm. Here, we hybrid the Binary Particle Swarm Optimization (BPSO) and Binary Cuckoo Search algorithm (BCSO) by considering monetary cost and computational cost which helps to minimize the cost of the client. Finally, the experimentation is carried out and our proposed hybrid algorithm is compared with BPSO and BCSO algorithms. Also we proved the efficiency of our proposed hybrid optimization algorithm.
Highlights
With the rapid development of processing and storage technologies and the success of the Internet, computing resources have become cheaper, more powerful and more ubiquitously available than ever before
We proposed a hybrid optimization algorithm for dynamic resource allocation in cloud computing
The Binary Cuckoo Search algorithm (BCSO) algorithm generates the initialization matrix as per the number of subtasks and resources. It calculates the fitness value for each particle of the initialization matrix based on the monetary cost and computational cost
Summary
With the rapid development of processing and storage technologies and the success of the Internet, computing resources have become cheaper, more powerful and more ubiquitously available than ever before. In a cloud computing environment, an Infrastructure-as-a-Service (IaaS) provider packages its physical resources (e.g., CPU, memory disk) into distinct types of Virtual Machines (VMs) in terms of their sizes and features and offers them as services to the general public (Zhang et al, 2011). It delivers an infrastructure, platform and software (applications) as Services that are made available to consumers in a pay-as-you-go model. Examples include digital services and functions required by the various industrial sectors, ranging from manufacturing to housing, from transportation to banking (Goudarzi and Pedram, 2011)
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