Abstract
Fog computing is considered as a promising technology to meet the ever-increasing computation requests from a wide variety of mobile applications. By offloading the computation-intensive requests to the fog node or the central cloud, the performance of the applications, such as energy consumption and delay, are able to be significantly enhanced. Meanwhile, utilizing the recent advances of social network and energy harvesting techniques, the system performance could be further improved. In this paper, we take the social relationships of the energy harvesting MDs into the design of computational offloading scheme in fog computing. With the objective to minimize the social group execution cost, we advocate game theoretic approach and propose a dynamic computation offloading scheme designing the offloading process in fog computing system with energy harvesting MDs. Different queue models are applied to model the energy cost and delay performance. It can be seen that the proposed problem can be formulated as a Generalized Nash Equilibrium Problem (GNEP) and we can use exponential penalty function method to transform the original GNEP into a classical NEP and address it with semi-smooth Newton method with Armijo line search. The simulation results demonstrate the effectiveness of the proposed scheme.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cardellini, V., Valerio, V.D., Facchinei, F., Presti, F.L., Piccialli, V.: A game-theoretic approach to computation offloading in mobile cloud computing. Math Program. 157(2), 421–449 (2015)
Jia, M., Cao, J., Liang, W.: Optimal cloudlet placement and user to cloudlet allocation in wireless metropolitan area networks. IEEE Trans. Serv. Comput. 5(4), 725–737 (2017)
Lazar, A.: The throughput time delay function of an M/M/1 queue (Corresp.). IEEE Trans. Inf. Theory 29(6), 914–918 (1983)
Deng, R., Lu, R., Lai, C., Luan, T.H., Liang, H.: Optimal workload allocation in fog-cloud computing towards balanced delay and power consumption. IEEE Internet Things J. 3(6), 1171–1181 (2016)
Jiang, L., Tian, H., Xing, Z., Wang, K., Zhang, K., Maharjan, S., Gjessing, S., Zhang, Y.: Social-aware energy harvesting device-to-device communications in 5G networks. IEEE Wirel. Commun. 23(4), 20–27 (2016)
Zhang, W., Wen, Y., Guan, K., Kilper, D., Luo, H., Wu, D.O.: Energy-optimal mobile cloud computing under stochastic wireless channel. IEEE Trans. Wirel. Commun. 12(9), 4569–4581 (2013)
Liu, L., Chang, Z., Guo, X.: Socially aware dynamic computation offloading scheme for fog computing system with energy harvesting devices. IEEE Internet Things J. 5(3), 1869–1879 (2018)
Machol, R.E.: Queue theory. IRE Trans. Educ. E-5(2), 99–105 (2007)
Xu, J., Hou, J., Tan, Y., Feng, E.: Exponential penalty function method for generalized nash equilibrium problem. Oper. Res. Manag. Sci. 24(1), 81–89 (2015)
Xie, L.: The general convex smoothing problem solved by a semismooth newton algorithm. Math. Numerica Sinica. 27(3), 257–266 (2005)
Sardellitti, S., Scutari, G., Barbarossa, S.: Joint optimization of radio and computational resources for multicell mobile-edge computing. IEEE Trans. Signal Inf. Process. Netw. 1(2), 89–103 (2015)
Mao, Y., Zhang, J., Letaief, K.B.: Dynamic computation offloading for mobile-edge computing with energy harvesting devices. IEEE J. Sel. Area Commun. 34(12), 3590–3605 (2016)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Zhou, Z., Chang, Z., Liao, H. (2021). Dynamic Computation Offloading Scheme for Fog Computing System with Energy Harvesting Devices. In: Green Internet of Things (IoT): Energy Efficiency Perspective. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-64054-5_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-64054-5_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-64053-8
Online ISBN: 978-3-030-64054-5
eBook Packages: Computer ScienceComputer Science (R0)