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Mobile devices are supporting a wide range of applications irrespective of their configuration. There is a need to make the mobile applications executable on mobile devices without concern of battery life. For optimizing mobile applications computational offloading is highly preferred. It helps to overcome the severity of scarce resources constraint mobile devices. In offloading, which part of the application to be offloaded, on which processor and what is available bandwidth rate are the main crucial issues. As subtasks of mobile applications are interdependent, efficient execution of application requires research of favorable wireless network conditions before to take the offloading decision. Broadly in mobile cloud computing the applications is either delay sensitive or delay tolerant. For delay sensitive applications completion time has the highest priority whereas for delay tolerant type of applications depending on the network conditions decision of offloading can be taken. Sometimes, computation time on a cloud server is less but it consumes high communication time which ultimately gives inefficient offloading results. To address this issue, we have proposed a heuristic based level wise task offloading (HTLO). It includes computation time, communication time and maximum energy available on the mobile device to take the decision of offloading. For simulation study, a mobile application is considered as a directed graph and all the tasks are executed on the basis of their levels. The overall results of the proposed heuristic approach are compared with state-of-the-art K-M LARAC algorithm and results show the improvement in execution time, communication time, mobile device energy consumption and total energy consumption.

Constraints Based Heuristic Approach for Task Offloading In Mobile Cloud Computing