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IEEE Transactions on Cloud Computing (TCC)(Energy-efficient Adaptive Resource Management for Real-time Vehicular Cloud Services)
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posted on 2017-04-21, 12:39 authored by Mohammad ShojafarMohammad Shojafar, Nicola Cordeschi, Enzo BaccarelliProviding 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.
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Italian MIUR named GAUChO (A Green Adaptive Fog Computing and Networking Architecture)
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- Networking and communications
- Distributed computing and systems software not elsewhere classified
- Distributed systems and algorithms
- Energy generation, conversion and storage (excl. chemical and electrical)
- Electrical engineering not elsewhere classified
- Cyberphysical systems and internet of things
- Other information and computing sciences not elsewhere classified
Keywords
Energy-efficiencyAdaptive Resource ManagementVirtualized Fog CentersCognitive ComputingTCP/IP-based Vehicular Cloud ComputingDistributed Computing Systemnetwork algorithmNetworking and CommunicationsComputer Communications NetworksDistributed ComputingDistributed and Grid SystemsDistributed Computing not elsewhere classifiedEnergy Generation, Conversion and Storage EngineeringPower and Energy Systems Engineering (excl. Renewable Power)Ubiquitous ComputingInformation and Computing Sciences not elsewhere classified
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