TaSRD: Task Scheduling Relying on Resource and Dependency in Mobile Edge Computing

Offloading computation-intensive tasks from mobile to nearby resource-rich surrogates, called edge servers, is proposed recently because traditional mobile cloud computing has a bottleneck of bandwidth and resource limitation for devices. The primary performance concern of offloading is how to maximize energy saving under task delay and task dependency limitation. Besides, edge servers that mobile perceived are changeable and heterogeneous in the process of offloading. In this paper, we formalize this problem, reduce it into knapsack problem and propose a task scheduling scheme, named TaSRD, including independent sub-task scheduling for tasks without dependencies and dependent sub-task scheduling for dependent tasks. We implement TaSRD and evaluate it by case study and simulation on CloudSim framework developed by Melbourne University. We use time model and energy model to measure results and recommend suitable parameters for TaSRD. The experimental results demonstrate that TaSRD can effectively save energy and reduce makespan for mobile while offloading tasks to edge servers.