2017/03/21 by Nof Abuzainab, Abuzainab, Nof, Walid Saad +5
Computer Science · #Cognitive Science and Mapping #Distributed Sensor Networks and Detection Algorithms #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #Information Theory (cs.IT) #IoT and Edge/Fog Computing
paper · pdf · doi:10.48550/arxiv.1703.07418
openalex publication_date 2017/03/21 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
In this paper, the problem of distributed resource allocation is studied for\nan Internet of Things (IoT) system, composed of a heterogeneous group of nodes\ncompromising both machine-type devices (MTDs) and human-type devices (HTDs).\nThe problem is formulated as a noncooperative game between the heterogeneous\nIoT devices that seek to find the optimal time allocation so as to meet their\nquality-of-service (QoS) requirements in terms of energy, rate and latency.\nSince the strategy space of each device is dependent on the actions of the\nother devices, the generalized Nash equilibrium (GNE) solution is first\ncharacterized, and the conditions for uniqueness of the GNE are derived. Then,\nto explicitly capture the heterogeneity of the devices, in terms of resource\nconstraints and QoS needs, a novel and more realistic game-theoretic approach,\nbased on the behavioral framework of cognitive hierarchy (CH) theory, is\nproposed. This approach is then shown to enable the IoT devices to reach a CH\nequilibrium (CHE) concept that takes into account the various levels of\nrationality corresponding to the heterogeneous computational capabilities and\nthe information accessible for each one of the MTDs and HTDs. Simulation\nresults show that the proposed CHE solution keeps the percentage of devices\nwith satisfied QoS constraints above 96% for IoT networks containing up to\n10,000 devices without considerably degrading the overall system performance.\n