TY - JOUR
T1 - Cognitive hierarchy theory for distributed resource allocation in the internet of things
AU - Abuzainab, Nof
AU - Saad, Walid
AU - Hong, Choong Seon
AU - Poor, H. Vincent
N1 - Funding Information:
Manuscript received March 1, 2017; revised June 28, 2017 and August 12, 2017; accepted August 12, 2017. Date of publication August 29, 2017; date of current version December 8, 2017. This work was supported in part by the U.S. Office of Naval Research under Grant N00014-15-1-2709 and in part by the U.S. National Science Foundation under Grant OAC-1541105, Grant CNS-1456793, Grant ECCS-1343210, and Grant CNS-1460333. This paper was presented in part at the IEEE International Symposium on Information Theory, Barcelona, Spain, July 2016 [1]. The associate editor coordinating the review of this paper and approving it for publication was C.-H. Lee. (Corresponding author: Nof Abuzainab.) N. Abuzainab is with Wireless@VT, Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA 24061 USA (e-mail: nof@vt.edu).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/12
Y1 - 2017/12
N2 - In this paper, the problem of distributed resource allocation is studied for an Internet of Things (IoT) system, composed of a heterogeneous group of nodes compromising both machine-type devices (MTDs) and human-type devices (HTDs). The problem is formulated as a noncooperative game between the heterogeneous IoT devices which seek to find the optimal time allocation so as to meet their quality-of-service (QoS) requirements in terms of energy, rate, and latency. Since the strategy space of each device is dependent on the actions of the other devices, the generalized Nash equilibrium (GNE) solution is first characterized, and the conditions for uniqueness of the GNE are derived. Then, to explicitly capture the heterogeneity of the devices, in terms of resource constraints and QoS needs, a novel and more realistic game-theoretic approach, based on the behavioral framework of cognitive hierarchy (CH) theory, is proposed. This approach is then shown to enable the IoT devices to reach a CH equilibrium (CHE), a concept that takes into account the various levels of rationality corresponding to the heterogeneous computational capabilities and the information accessible for each one of the MTDs and HTDs. Simulation results show that the CHE solution maintains a stable performance. In particular, the proposed CHE solution keeps the percentage of devices with satisfied QoS constraints above 96% for IoT networks containing up to 10000 devices without considerably degrading the overall system performance in terms of the total utility. Simulation results also show that the proposed CHE solution brings a twofold increase in the total rate of HTDs and deceases the total energy consumed by MTDs by 78% compared with the equal time policy.
AB - In this paper, the problem of distributed resource allocation is studied for an Internet of Things (IoT) system, composed of a heterogeneous group of nodes compromising both machine-type devices (MTDs) and human-type devices (HTDs). The problem is formulated as a noncooperative game between the heterogeneous IoT devices which seek to find the optimal time allocation so as to meet their quality-of-service (QoS) requirements in terms of energy, rate, and latency. Since the strategy space of each device is dependent on the actions of the other devices, the generalized Nash equilibrium (GNE) solution is first characterized, and the conditions for uniqueness of the GNE are derived. Then, to explicitly capture the heterogeneity of the devices, in terms of resource constraints and QoS needs, a novel and more realistic game-theoretic approach, based on the behavioral framework of cognitive hierarchy (CH) theory, is proposed. This approach is then shown to enable the IoT devices to reach a CH equilibrium (CHE), a concept that takes into account the various levels of rationality corresponding to the heterogeneous computational capabilities and the information accessible for each one of the MTDs and HTDs. Simulation results show that the CHE solution maintains a stable performance. In particular, the proposed CHE solution keeps the percentage of devices with satisfied QoS constraints above 96% for IoT networks containing up to 10000 devices without considerably degrading the overall system performance in terms of the total utility. Simulation results also show that the proposed CHE solution brings a twofold increase in the total rate of HTDs and deceases the total energy consumed by MTDs by 78% compared with the equal time policy.
KW - Bounded rationality
KW - Cognitive hierarchy theory
KW - Internet of things
KW - Resource allocation
UR - http://www.scopus.com/inward/record.url?scp=85028725724&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85028725724&partnerID=8YFLogxK
U2 - 10.1109/TWC.2017.2743077
DO - 10.1109/TWC.2017.2743077
M3 - Article
AN - SCOPUS:85028725724
SN - 1536-1276
VL - 16
SP - 7687
EP - 7702
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 12
ER -