SCHEDULING TECHNIQUE OF DATA INTENSIVE APPLICATION WORKFLOWS IN CLOUD COMPUTING

Abstract

Cloud computing is a highly scalable distributed computing platform in which computing resources are offered 'as a service° leveraging virtualization. Cloud Computing distributes the computational tasks on the resource pool which consists of massive computers so that the service consumer can gain maximum computation strength, more storage space and software services for its application according to its need. A huge amount of data moves from user to host, hosts to user and host to host in the cloud environment. Based on the above three considerations, how to select appropriate hosts for accessing resources and creating a virtual machine(VM) to execute applications so that execution becomes more efficient and access cost becomes low as far as possible simultaneously is a challenging task. In this dissertation entitled "SCHEDULING TECHNIQUE OF DATA INTENSIVE APPLICATION WORKFLOWS IN CLOUD COMPUTING", a host selection model based on minimum network delay is proposed, the objective is to minimize propagation time of input and output data by selecting nearest host into the network. And finally it minimizes the execution time of cloudlet. It select data host and compute host optimally so that overall cost should minimize.