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With the emergence of millimeter-Wave (mmWave) communication technology, thecapacity of mobile backhaul networks can be significantly increased. On theother hand, Mobile Edge Computing (MEC) provides an appropriate infrastructureto offload latency-sensitive tasks. However, the amount of resources in MECservers is typically limited. Therefore, it is important to intelligentlymanage the MEC task offloading by optimizing the backhaul bandwidth and edgeserver resource allocation in order to decrease the overall latency of theoffloaded tasks. This paper investigates the task allocation problem in MECenvironment, where the mmWave technology is used in the backhaul network. Weformulate a Mixed Integer NonLinear Programming (MINLP) problem with the goalto minimize the total task serving time. Its objective is to determine anoptimized network topology, identify which server is used to process a givenoffloaded task, find the path of each user task, and determine the allocatedbandwidth to each task on mmWave backhaul links. Because the problem isdifficult to solve, we develop a two-step approach. First, a Mixed IntegerLinear Program (MILP) determining the network topology and the routing paths isoptimally solved. Then, the fractions of bandwidth allocated to each user taskare optimized by solving a quasi-convex problem. Numerical results illustratethe obtained topology and routing paths for selected scenarios and show thatoptimizing the bandwidth allocation significantly improves the total servingtime, particularly for bandwidth-intensive tasks.

A Generic Framework for Task Offloading in mmWave MEC Backhaul Networks