Return
Joint Optimal Software Caching, Computation Offloading and Communications Resource Allocation for Mobile Edge Computing
DOI:10.1109/TVT.2020.2993359.png)
Abstract
En 中文
As software may be used by multiple users, caching popular software at the wireless edge has been considered to save computation and communications resources for mobile edge computing (MEC). However, fetching uncached software from the core network and multicasting popular software to users have so far been ignored. Thus, existing design is incomplete and less practical. In this paper, we propose a joint caching, computation and communications mechanism which involves software fetching, caching and multicasting, as well as task input data uploading, task executing (with non-negligible time duration) and computation result downloading, and mathematically characterize it. Then, we optimize the joint caching, offloading and time allocation policy to minimize the weighted sum energy consumption subject to the caching and deadline constraints. The problem is a challenging two-timescale mixed integer nonlinear programming (MINLP) problem, and is NP-hard in general. We convert it into an equivalent convex MINLP problem by using some appropriate transformations and propose two low-complexity algorithms to obtain suboptimal solutions of the original non-convex MINLP problem. Specifically, the first suboptimal solution is obtained by solving a relaxed convex problem using the consensus alternating direction method of multipliers (ADMM), and then rounding its optimal solution properly. The second suboptimal solution is proposed by obtaining a stationary point of an equivalent difference of convex (DC) problem using the penalty convex-concave procedure (Penalty-CCP) and ADMM. Finally, by numerical results, we show that the proposed solutions outperform existing schemes and reveal their advantages in efficiently utilizing storage, computation and communications resources.
Keywords:
Task analysis
Software
Resource management
Multicast communication
Energy consumption
Wireless communication
Convex functions
Mobile edge computing (MEC)
caching
resource allocation
convex-concave procedure (CCP)
alternating direction method of multipliers (ADMM)
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.1
Papers:
1.8W
Citations:
6.6W
Organization
Cited Papers
Computation Offloading and Content Caching n Wireless Blockchain Networks With Mobile Edge Computing
Mobile Edge Computing Enhanced Adaptive Bitrate Video Delivery With Joint Cache and Radio Resource Allocation
IEEE ACCESS
IF3.6

