Energy-Efficient Adaptive Resource Management for Real-Time Vehicular Cloud Services

• Published in: IEEE transactions on cloud computing Vol. 7; no. 1; pp. 196 - 209
• Main Authors: Shojafar, Mohammad, Cordeschi, Nicola, Baccarelli, Enzo
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE Computer Society 01.01.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; adaptive resource management; Admission control; Clients; Cloud computing; cognitive computing; Computing time; Consolidation; Data centers; Delay; Delays; Energy efficiency; Energy management; Energy transmission; IP (Internet Protocol); Mobile communication; Mobile handsets; Performance evaluation; Quality of service; Real time; Reconfiguration; Resource management; Resource scheduling; TCP/IP (protocol); TCP/IP-based vehicular cloud computing; Traffic control; Vibration; Virtual environments; virtualized fog centers; Wireless communication; Workload
• ISSN: 2168-7161; 2372-0018
• DOI: 10.1109/TCC.2016.2551747

Providing real-time cloud services to Vehicular Clients (VCs) must cope with delay and delay-jitter issues. Fog computing is an emerging paradigm that aims at distributing small-size self-powered data centers (e.g., Fog nodes) between remote Clouds and VCs, in order to deliver data-dissemination real-time services to the connected VCs. Motivated by these considerations, in this paper, we propose and test an energy-efficient adaptive resource scheduler for Networked Fog Centers (NetFCs). They operate at the edge of the vehicular network and are connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. The goal is to exploit the locally measured states of the TCP/IP connections, in order to maximize the overall communication-plus-computing energy efficiency, while meeting the application-induced hard QoS requirements on the minimum transmission rates, maximum delays and delay-jitters. The resulting energy-efficient scheduler jointly performs: (i) admission control of the input traffic to be processed by the NetFCs; (ii) minimum-energy dispatching of the admitted traffic; (iii) adaptive reconfiguration and consolidation of the Virtual Machines (VMs) hosted by the NetFCs; and, (iv) adaptive control of the traffic injected into the TCP/IP mobile connections. The salient features of the proposed scheduler are that: (i) it is adaptive and admits distributed and scalable implementation; and, (ii) it is capable to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rates of the traffic delivered to the vehicular clients, instantaneous rate-jitters and total processing delays. Actual performance of the proposed scheduler in the presence of: (i) client mobility; (ii) wireless fading; and, (iii) reconfiguration and consolidation costs of the underlying NetFCs, is numerically tested and compared against the corresponding ones of some state-of-the-art schedulers, under both synthetically generated and measured real-world workload traces.