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Issue No. 09 - Sept. (2012 vol. 23)
ISSN: 1045-9219
pp: 1752-1761
Shao-Yu Lien , National Taiwan University, Taipei
Shin-Ming Cheng , National Taiwan University, Taipei
Sung-Yin Shih , National Taiwan University, Taipei
Kwang-Cheng Chen , National Taiwan University, Taipei
The recent deployment of Cyber-Physical Systems (CPS) has emerged as a promising approach to provide extensive interaction between computational and physical worlds. For a large-scale distributed CPS comprising of numerous machines, sharing radio resource efficiently with the existing wireless networks while maintaining sufficient quality of service (QoS) for machine-to-machine (M2M) communications becomes an essential and challenging requirement. By clustering CPS machines as a swarm with the cluster head managing radio resources inside the swarm, spectrum sharing among numerous machines can be achieved in a distributed and scalable fashion. Specifically, we apply the recent innovation, cognitive radio, and a special mode in cognitive radio, interweave coexistence, to leverage machines to collect radio resource usage information for autonomous and interference-free radio resource management in the CPS. To reduce the communication overheads of channel sensing feedbacking from machines, we apply compressive sensing to construct a spectrum map indicating the radio resource availability on any given locations within the CPS coverage. Such spectrum map resource management (SMRM) only utilizes a small portion of machines to perform channel sensing but enables distributed cluster-based spectrum sharing in an efficient way. Through the concept of effective capacity, the SMRM controls available resources to guarantee the QoS for communications of CPS. By evaluating the performance of the proposed SMRM in the most promising realization of CPS based on LTE-Advanced machine-type communications coexisting with LTE-Advanced Macrocells to utilize identical spectrum, the simulation results show effective QoS guarantees of CPS by SMRM in the realistic environments.
Sensors, Macrocell networks, Resource management, Quality of service, Interference, Compressed sensing, Delay, effective capacity, Sensors, Macrocell networks, Resource management, Quality of service, Interference, Compressed sensing, Delay, radio resource management., Cyber-physical systems (CPS), cognitive radio (CR), spectrum map, compressive sensing, machine-to-machine (M2M) communication, quality of service (QoS)

S. Cheng, S. Shih, K. Chen and S. Lien, "Radio Resource Management for QoS Guarantees in Cyber-Physical Systems," in IEEE Transactions on Parallel & Distributed Systems, vol. 23, no. , pp. 1752-1761, 2012.
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