Resource allocation and network pricing based on double auction in mobile edge computing

Abstract

By transferring power-hungry huge data centers to lightweight Internet of Things (IoT) mobile devices, mobile edge computing (MEC) has completely changed the IoT. For MEC, to optimize economic gains and motivate profit-oriented entities, the joint resource allocation and network economics problem must be solved, and the joint issue is limited by local constraints, namely, the edge server only serves multiple nearby mobile devices, which is restricted by its available energy. The article studies the jointly issue of network economics and energy allocation in MEC, where mobile device apply for offloading at a purported bid and an edge server supplies its restricted serving at an asking price. In particular, this paper puts forward two dynamic pricing double auction strategies in the MEC system, i.e., a double auction according to the break-even mechanism (DABM) and a more practical double auction based on dynamic pricing mechanism (DADPM) to decide the matching between mobile devices and edge servers, and the pricing strategy for high-priced economic profit in the case of local restricts. Theoretical analysis shows that the proposed two algorithms have properties such as budget balance, individual rationality, economic benefit, authenticity. Extensive simulation experiments evaluate the efficiency of the system, and results verify that the proposed two schemes will greatly make better the economic benefits of MEC.