Computation Offloading for Service Workflow in Mobile Cloud Computing PROJECT TITLE :Computation Offloading for Service Workflow in Mobile Cloud ComputingABSTRACT:The event of Cloud Computing and virtualization techniques allows mobile devices to overcome the severity of scarce resource constrained by allowing them to offload computation and migrate several computation components of an application to powerful cloud servers. A mobile device ought to judiciously determine whether to dump computation along with what portion of an application ought to be offloaded to the cloud. This paper considers a mobile computation offloading downside where multiple mobile services in workflows can be invoked to satisfy their complicated necessities and makes decision on whether or not the services of a workflow ought to be offloaded. Due to the mobility of portable devices, unstable connectivity of mobile networks will impact the offloading call. To handle this issue, we propose a unique offloading system to design sturdy offloading decisions for mobile services. Our approach considers the dependency relations among part services and aims to optimize execution time and energy consumption of executing mobile services. To this finish, we have a tendency to conjointly introduce a mobility model and a trade-off fault-tolerance mechanism for the offloading system. A genetic algorithm (GA) based offloading method is then designed and implemented once rigorously modifying components of a generic GA to match our special needs for the stated problem. Experimental results are promising and show close to-optimal solutions for all of our studied cases with nearly linear algorithmic complexity with respect to the problem size. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Classifying Text-Based Computer Interactions for Health Monitoring Magnetoelectric Random Access Memory-Based Circuit Design by Using Voltage-Controlled Magnetic Anisotropy in Magnetic Tunnel Junctions