Abstract
Massive computing requirements of mobile applications greatly challenge the limited resources in the cloud. It is observed that parked vehicles (PVs) have redundant computing resources for task execution. Hence, we focus on how to efficiently and economically apply PVs for assisting the cloud. An proposed incentive mechanism, initiated by the cloud, motivates PVs to participate in the offloading of cloud’s computing tasks. We build the utility to characterize a PV’s profits, generated from task execution and socially-aware effects from other PVs. The benefits of the cloud consider many factors, such as computing tasks of mobile users, energy cost, economic compensation for PVs and PVs’ computation delay. The interactions among PVs and the cloud formulate a two-stage Stackelberg game to maximize their profits. The performance of the proposed model is investigated by simulations. Numerical results prove its efficiency for enhancing PVs’ utilities and cloud’s quality of service.
Supported in part by National Natural Science Foundation of China under Grant No. 61802216, National Key Research and Development Plan Key Special Projects under Grant No. 2018YFB2100303, Shandong Province colleges and universities youth innovation technology plan innovation team project under Grant No. 2020KJN011, Program for Innovative Postdoctoral Talents in Shandong Province under Grant No. 40618030001 and Postdoctoral Science Foundation of China under Grant No. 2018M642613.
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References
Chen, J., Kang, H., Qi, W., Sun, Y., Shi, Z., He, S.: Narrowband internet of things: implementations and applications. IoT J. IEEE 4(6), 2309–2314 (2017)
Li, Y., Li, J., Ahmed, M.: A three-stage incentive formation for optimally pricing social data offloading. J. Netw. Comput. Appl. 172, 102816 (2020)
Lin, C., Pan, J., Lian, Z., Shen, X.: Networked electric vehicles for green intelligent transportation. IEEE Commun. Stan. Mag. 1(2), 77–83 (2017)
Lyu, X., Tian, H., Sengul, C., Zhang, P.: Multiuser joint task offloading and resource optimization in proximate clouds. IEEE Trans. Veh. Technol. 66, 3435–3447 (2017)
Qiao, Y., Li, Y., Li, J.: An economic incentive for D2D assisted offloading using Stackelberg game. IEEE Access 8, 136684–136696 (2020)
Xu, C., Lei, J., Li, W., Fu, X.: Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans. Netw. 24(5), 2795–2808 (2016)
Yuan, Q., Zhou, H., Li, J., Liu, Z., Yang, F., Shen, X.S.: Toward efficient content delivery for automated driving services: an edge computing solution. IEEE Netw. 32(1), 80–86 (2018)
Yue, L., Kai, S., Lin, C.: Cooperative device-to-device communication with network coding for machine type communication devices. IEEE Trans. Wireless Commun. 17(1), 296–309 (2017)
Zhang, J., et al.: Energy-latency tradeoff for energy-aware offloading in mobile edge computing networks. IEEE IoT J. 5, 2633–2645 (2017)
Zhang, X., Guo, L., Li, M., Fang, Y.: Motivating human-enabled mobile participation for data offloading. IEEE Trans. Mob. Comput. 17, 1624–1637 (2017)
Zhang, Y., Lan, X., Ren, J., Cai, L.: Efficient computing resource sharing for mobile edge-cloud computing networks. IEEE/ACM Trans. Netw. 28, 1227–1240 (2020)
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Li, Y., Li, Y., Li, J., Liang, Y. (2021). Incentive Cooperation with Computation Delay Concerns for Socially-Aware Parked Vehicle Edge Computing. In: Liu, Z., Wu, F., Das, S.K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2021. Lecture Notes in Computer Science(), vol 12939. Springer, Cham. https://doi.org/10.1007/978-3-030-86137-7_24
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DOI: https://doi.org/10.1007/978-3-030-86137-7_24
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