TY - JOUR
T1 - A Cyclic Game for Service-Oriented Resource Allocation in Edge Computing
AU - Ma, Shiheng
AU - Guo, Song
AU - Wang, Kun
AU - Jia, Weijia
AU - Guo, Minyi
N1 - Funding Information:
This research was financially supported by the General Research Fund of the Research Grants Council of Hong Kong (PolyU 152221/19E); the National Natural Science Foundation of China (Grants 61872310, 61832006, 61872240, 61872195, 61532013, and 61872239); 0007/2018/A1, 0060/2019/A1, DCT-MoST Joint-project No. 025/2015/AMJ of Science and Technology Development Fund, Macao S.A.R (FDCT), China; and University of Macau Grant Nos: MYRG2018-00237-RTO, CPG2019-00004-FST, and SRG2018-00111-FST.
Publisher Copyright:
© 2008-2012 IEEE.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Existing works adopt the Edge-Oriented Resource Allocation (EORA) scheme, in which edge nodes cache services and schedule user requests to distribute workloads over cloud and edge nodes, so as to achieve high-quality services and low latency. Unfortunately, EORA does not fully take into account the fact that service providers are sometimes independent from the edge operators with their own objectives. To deal with the conflict and cooperation between service providers and edge nodes, we devise a service-oriented resource allocation (SORA) scheme, where edge nodes and service providers adjust their resource allocations to provide requested services. We first prove that such resource allocation problem is NP-hard. We then propose a three-sided cyclic game (3CG) involving users, edge nodes, and service providers who make their individual decisions by choosing respectively high-quality services, high-value users, and cost-effective edge nodes for service deployment. Based on 3CG, we prove the existence and approximation ratio of pure-strategy Nash equilibriums (NEs). We also develop both centralized and distributed approximate algorithms for resource allocation. Finally, extensive experimental results validate the effectiveness and convergence of the proposed algorithms.
AB - Existing works adopt the Edge-Oriented Resource Allocation (EORA) scheme, in which edge nodes cache services and schedule user requests to distribute workloads over cloud and edge nodes, so as to achieve high-quality services and low latency. Unfortunately, EORA does not fully take into account the fact that service providers are sometimes independent from the edge operators with their own objectives. To deal with the conflict and cooperation between service providers and edge nodes, we devise a service-oriented resource allocation (SORA) scheme, where edge nodes and service providers adjust their resource allocations to provide requested services. We first prove that such resource allocation problem is NP-hard. We then propose a three-sided cyclic game (3CG) involving users, edge nodes, and service providers who make their individual decisions by choosing respectively high-quality services, high-value users, and cost-effective edge nodes for service deployment. Based on 3CG, we prove the existence and approximation ratio of pure-strategy Nash equilibriums (NEs). We also develop both centralized and distributed approximate algorithms for resource allocation. Finally, extensive experimental results validate the effectiveness and convergence of the proposed algorithms.
KW - Edge computing
KW - game theory
KW - resource allocation
UR - http://www.scopus.com/inward/record.url?scp=85083694035&partnerID=8YFLogxK
U2 - 10.1109/TSC.2020.2966196
DO - 10.1109/TSC.2020.2966196
M3 - Journal article
AN - SCOPUS:85083694035
SN - 1939-1374
VL - 13
SP - 723
EP - 734
JO - IEEE Transactions on Services Computing
JF - IEEE Transactions on Services Computing
IS - 4
M1 - 8960300
ER -