Abstract-Cloud computing is the latest emerging trend in distributed computing, where shared resources are provided to end-users in an on demand fashion that brings many advantjuages, including data ubiquity, flexibility of access, high availability of resources, and flexibility. The task scheduling problem in Cloud computing is an NP-hard problem. Therefore, many heuristics have been proposed, from low level execution of tasks in multiple processors to high level execution of tasks. In this paper, a new evolutionary algorithm is proposed which named CSA to schedule the tasks in Cloud computing. CSA algorithm is based on the obligate brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fruit flies. The simulation results demonstrated that when the value of Pa is low, the speed and coverage of the algorithm become very high.
I. INTRODUCTIONCloud computing evolved through the recent advancements in hardware, virtualization technology, distributed computing, and service delivery over the Internet. While Cloud computing may not involve a lot of new technologies, it certainly represents a new way of managing IT. In many cases, this will not only change the workflow within the IT organization, it will often result in a complete reorganization of the IT department. Cost savings and scalability can be highly achieved from cloud computing [1]. The "Cloud" metaphor is a reference to the ubiquitous availability and accessibility of computing resources via Internet technologies [2]. Generally, cloud computing services can be categorized into three main types of services: Infrastructure as a Service, Platform as a Service and Software as a Service. These services can then be accessed through a cloud client, which could be a web browser, mobile app, and so on [3]. Cloud computing provides implementation agility, lower capital expenditure, location independence, resource pooling, broad network access, reliability, scalability, elasticity, and ease of maintenance [4]. The scheduling of a task workflow in a distributed computing platform is a well-known NP-hard problem [5]. The problem is even more complex and challenging when the virtualized clusters are used to execute a large number of Manuscript received June 3, 2014; revised October 9, 2014. tasks in a Cloud computing platform [6]. For this reason, many heuristics have been proposed, from low level execution of tasks in multiple processors to high level execution of tasks in Grid and Cloud environments [7]. Recently, many papers are published which used evolutionary algorithms like genetic, ant colony, bee colony and PSO for optimization problems. Due to the advantages of Cuckoo Search Algorithm (CSA) [8], this paper addresses a task scheduling problem in a homogeneous Cloud infrastructure considering the minimization of the total waiting time of the tasks based on the CSA. CSA is based on the obligate brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fru...
