期刊
IEEE INTERNET OF THINGS JOURNAL
卷 7, 期 6, 页码 5386-5400出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.2977606
关键词
Internet of Things; Optimization; Cellular networks; Resource management; Quality of service; Interference; Data aggregation; Coalition game theory; data aggregation; Internet of Things (IoT); resource allocation; user association
资金
- Natural Sciences and Engineering Research Council (NSERC) of Canadian FloodNet
Node clustering and data aggregation help extend the coverage of cellular networks and increase the number of supported devices, while meeting the various service quality requirements and reducing energy consumption, making them suitable for enabling the future massive cellular Internet-of-Things (IoT) applications. Consequently, we propose to overlay the cellular network with a layer of data aggregators (DAs) to act as relays. DAs use cellular backhauling, and thus, the network provides both single- and two-hop routes; however, DAs share radio resources with single-hop devices, creating a dependency between the two routes. Thus, the proper design of the DA-enabled network becomes critical for cost effectiveness and efficient radio resource utilization. In this article, we formulate a joint access point association, resources utilization, and energy-efficient communication optimization problem that takes into account various networking factors, such as the number of devices, the number of DAs, the number of available resource units, interference, the transmission power limitation of the devices, DA transmission performance, and channel conditions. The objective is to show the usefulness of data aggregation and shed light on the importance of network design when the number of devices is massive. We propose a coalition game theory-based algorithm PAUSE to transform the optimization problem into a simpler form that can be successfully solved in polynomial time. Different network scenarios are simulated to showcase the effectiveness of PAUSE and to draw observations on cost-effective network design with DAs.
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