Overbook in Advance, Trade in Future: Computing Resource Provisioning in Hybrid Device-Edge-Cloud Networks

• Published in: IEEE network Vol. 37; no. 5; pp. 105 - 113
• Main Authors: Liwang, Minghui, Wang, Xianbin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Big Data; Cloud computing; Constraint handling; Contracts; Cost benefit analysis; Data assimilation; Data processing; Distributed processing; Dynamic scheduling; Edge computing; Forward contracts; Hybrid intelligent systems; Internet of Things; Mathematical analysis; Network architecture; Provisioning; Resource allocation; Resource management; Resource utilization; Risk management; Servers; Uncertainty
• ISSN: 0890-8044; 1558-156X
• DOI: 10.1109/MNET.125.2200187

The big data processing in distributed Internet of Things (IoT) systems calls for innovative computing architectures and resource provisioning techniques to support real-time and cost-effective computing services. This article introduces a novel overbooking-promoted forward trading mechanism named Overbook in Advance, Trade in Future (OATF), where computing resources can be traded across three parties, i.e. end-users, an edge server and a remote cloud server, under a hybrid device-edge-cloud network with uncertainties (e.g., "no shows"). More importantly, OATF encourages a feasible overbooking rate that allows the edge server to overbook resources to multiple end-users (e.g., exceed the resource supply), while purchasing backup resources from the cloud server, by determining rights and obligations associated with forward contracts in advance via analyzing historical statistics (e.g., network, resource dynamics). Such a mechanism can greatly improve time efficiency and resource utilization thanks to overbooking and pre-signed forward contracts. Critical issues such as overbooking rate design and risk management are carefully investigated in this article, while an interesting case study is proposed with mathematical analysis. Comprehensive simulations demonstrate that OATF achieves mutually beneficial utilities for different parties (cloud, edge, and end-users), as well as substantial resource usage and commendable time efficiency, in comparison with conventional trading methods.