Data-flow in mobile edge computing networks: end-to-end performance analysis using stochastic network calculus

Mobile edge computing (MEC) networks can provide a variety of services for different applications. End-to-end performance analysis of these services serves as a benchmark for the efficient planning of network resource allocation and routing strategies. In this paper, a performance analysis framework is proposed for the end-to-end data-flows in MEC networks based on stochastic network calculus (SNC). Due to the random nature of routing in MEC networks, probability parameters are introduced in the proposed analysis model to characterize this randomness into the derived expressions. Taking actual communication scenarios into consideration, the end-to-end performance of three network data-flows is analyzed, namely, voice over Internet protocol (VoIP), video, and file transfer protocol (FTP). These network data-flows adopt the preemptive priority scheduling scheme. Based on the arrival processes of these three data-flows, the effect of interference on their performances and the service capacity of each node in the MEC networks, closed-form expressions are derived for showing the relationship between delay, backlog upper bounds, and violation probability of the data-flows. Analytical and simulation results show that delay and backlog performances of the data-flows are influenced by the number of hops in the network and the random probability parameters of interference-flow (IF). © 2022, Beijing University of Posts and Telecommunications. All rights reserved.