Research Article
An OO-Based Approach of Computing Offloading and Resource Allocation for Large-Scale Mobile Edge Computing Systems
@INPROCEEDINGS{10.1007/978-3-030-92638-0_5, author={Yufu Tan and Sikandar Ali and Haotian Wang and Jiwei Huang}, title={An OO-Based Approach of Computing Offloading and Resource Allocation for Large-Scale Mobile Edge Computing Systems}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 17th EAI International Conference, CollaborateCom 2021, Virtual Event, October 16-18, 2021, Proceedings, Part II}, proceedings_a={COLLABORATECOM PART 2}, year={2022}, month={1}, keywords={Mobile Edge Computing (MEC) Computing offloading Resource allocation Ordinal optimization Large-scale MEC systems}, doi={10.1007/978-3-030-92638-0_5} }- Yufu Tan
Sikandar Ali
Haotian Wang
Jiwei Huang
Year: 2022
An OO-Based Approach of Computing Offloading and Resource Allocation for Large-Scale Mobile Edge Computing Systems
COLLABORATECOM PART 2
Springer
DOI: 10.1007/978-3-030-92638-0_5
Abstract
Mobile edge computing (MEC) is an emerging paradigm to meet the increasing real-time performance demands for Internet of Things and mobile applications. By offloading the computationally intensive workloads to edge servers, the quality of service (QoS) could be greatly improved. However, with the growing popularity of MEC, the MEC systems grow extremely large, and thus the QoS optimization suffers from search space explosion problem, making it impractical in real-life scenarios. To attack this challenge, this paper studies the joint optimization of task offloading and computational resource allocation for large-scale MEC systems. We formulate this problem as a cost minimization problem and illustrate the NP-hardness of this problem. In order to solve this problem, we divide the original problem into two sub-problems and introduce the theory of Ordinal Optimization (OO) to search for a near-optimal computing offloading and resource allocation policy within a significantly reduced search space. Finally, the efficacy of our approach is validated by simulation experiments.
