Opportunistic Task Scheduling over Co-Located Clouds in Mobile Environment

Abstract-In data streams limitations on available memory and processing time which leads to arrival and execution time changes. It is important to schedule the task in order to avoid collusion and delay between them. There is many existing algorithms used for task scheduling like remote cloud. But which leads to delay when scheduling. Propose a new mobile cloudlet assisted service mode named Opportunistic task scheduling over Co-located Clouds (OSCC), which achieves flexible cost-delay tradeoffs between conventional remote cloud service mode and mobile cloudlets service mode. The request for virtualized resources is described through a set of parameters detailing the processing, memory and disk. For attaining better resource allocation with load balancing strategy we use VM placement. This can be achieved by allocating the incoming task to a virtual machine (VM) which meets two conditions; number of tasks currently processing by this VM is less than number of tasks currently processing by other VMs and the deviation of this VM processing time from average processing time of all VMs is less than a value. From using our proposed system which distribute workload of multiple network links in the way that avoid underutilization and over utilization of the resources. Simulation result shows our proposed system
provides better energy cost optimized cloud storage compared than other systems