Radio and Computing Resource Allocation in Co-Located Edge Computing: A Generalized Nash Equilibrium Model

Mobile Network Operators (MNO) can reduce their Capital and Operational Expenditure (CAPEX) and (OPEX) with the help of tower sharing approach by utilizing the physical infrastructure equipped by a third party tower provider to expand their network coverage. Moreover, Computing Resource Providers (CRP) are also setting up their micro-datacenters at tower stations to provide the Multi-access Edge Computing (MEC) services by cooperating with tower providers. Since both the communication and computing services contribute to the task offloading in MEC, the resource allocation has become a challenging problem. In this paper, we formulate the joint uplink, downlink, and computing resources allocation problem in which the objectives of both MNOs and CRP are to minimize their OPEX. The task offloading is modeled as a network of queues where the end-to-end latency is calculated based on the performance of the queue network. Then, the formulated problem is transformed into a Generalized Nash Equilibrium Problem (GNEP) to capture the conflicting interests in the resource allocation among MNOs and CRP. To solve the formulated GNEP efficiently, two decentralized algorithms are proposed by introducing the penalty parameters to the coupling constraints. In addition, the convergence and performance of the algorithms on different parameters are analyzed.

Automated summary

Mobile Network Operators (MNO) can reduce their CAPEX and OPEX by utilizing tower sharing and partnering with Computing Resource Providers (CRP) to expand their network coverage and provide Multi-access Edge Computing services. This paper formulates a resource allocation problem to minimize OPEX for both MNOs and CRP in the task offloading scenario, and proposes decentralized algorithms to solve it efficiently.