Joint Cache Placement and NOMA-Based Task Offloading for Multi-User Mobile Edge Computing

Hanzhe Dai, Haifeng Wen, Hong Xing, Zhiguo Ding

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Scopus citations

    Abstract

    One of the emerging computing paradigms, mobile edge computing (MEC, also known as fog computing), has been developed to reduce both energy consumption and computation latency for computation-extensive IoT applications. Further, thanks to advantages brought by non-orthogonal multiple access (NOMA) in increasing the capacity of multiple-access channels (MAC), and by service caching in alleviating the burden of responding to repeated computation requests, this paper considers the joint design of communication, computation, and caching for multi-user MEC systems. Aiming for minimizing the weighted-sum energy consumption of communication and computation, given a finite set of computation services, we jointly optimize the NOMA transmission, the computation resources, and the Boolean-variable modeled cache placement, subject to the computation and caching capacity of the edge server as well as the computation latency constraints. To solve the formulated mixed-integer non-convex problem, first, given the cache placement, we solve the non-differentiable convex problem by Lagrangian dual method leveraging a semi-closed form of NOMA transmission power, followed by a one-dimension search for the optimal common task offloading time. Next, an optimal branch-and-bound (BnB) based caching strategy is proposed. Meanwhile, we also provide a heuristic suboptimal cache placement design to reduce computational complexity. Finally, numerical results show the striking performance of the proposed joint optimization of NOMA-based task offloading and service caching compared to the greedy cache placement and other benchmarks without either NOMA-based task offloading or service caching.

    Original languageBritish English
    Title of host publication2023 IEEE 97th Vehicular Technology Conference, VTC 2023-Spring - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9798350311143
    DOIs
    StatePublished - 2023
    Event97th IEEE Vehicular Technology Conference, VTC 2023-Spring - Florence, Italy
    Duration: 20 Jun 202323 Jun 2023

    Publication series

    NameIEEE Vehicular Technology Conference
    Volume2023-June
    ISSN (Print)1550-2252

    Conference

    Conference97th IEEE Vehicular Technology Conference, VTC 2023-Spring
    Country/TerritoryItaly
    CityFlorence
    Period20/06/2323/06/23

    Keywords

    • Mobile edge computing
    • non-orthogonal multiple access
    • resource allocation
    • service caching

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