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 rea...