Transparent Computing (TC) is becoming a promising paradigm in network computing era. Although many researchers believe that TC model has a high requirement for the communication bandwidth, there is no research on the communication bandwidth boundary or resource allocation, which impedes the development of TC. This paper focuses on studying an efficient transparent computing resource allocation model in an economic view. First, under the quality of experiments (QoE) ensured, the utility function of clients and transparent computing providers (TCPs) is constructed. After that, the demand boundary of communication bandwidth is analyzed under the ideal transparent computing model. Based on the above analyses, a resource allocation scheme based on double-sided combinational auctions (DCA) is proposed so that the resource can be shared by both the service side and the client side with the welfare of the whole society being maximized. Afterward, the results scheduled in different experimental scenarios are given, which verifies the effectiveness of the proposed strategy. Overall, this work provides an effective resource allocation model for optimizing the performance of TC.
Transparent computing Communication bandwidth boundary Double-sided auctions Resources optimization
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This work was supported in part by the National Natural Science Foundation of China (61572528, 61379110, 61073104, 61272494, 61572526), The National Basic Research Program of China (973 Program)(2014CB046305).
Kim SH, Kang DK, Kim WJ, Chen M., & Youn CH (2016) A science gateway cloud with cost adaptive VM management scheme for computational scientific applications. IEEE Syst J doi:10.1109/JSYST.2015.2501750
Hoang DT, Niyato D, Wang P (2012) Optimal admission control policy for mobile cloud computing hotspot with cloudlet ∥WCNC 2012. IEEE Press, Atlanta, pp 3145–3149Google Scholar
Liu X, Dong M, Ota K, Hung P, Liu A (2016) Service pricing decision in cyber-physical systems: insights from game theory. IEEE Trans Serv Comput 9(2):186–198CrossRefGoogle Scholar
He S, Chen J, Li X, Shen XS, Sun Y (2014) Mobility and intruder prior information improving the barrier coverage of sparse sensor networks. IEEE Trans Mob Comput 13(6):1268–1282CrossRefGoogle Scholar
He S, Chen J, Jiang F, Yau DK, Xing G, Sun Y (2013) Energy provisioning in wireless rechargeable sensor networks. IEEE Trans Mob Comput 12(10):1931–1942CrossRefGoogle Scholar
Gui J, & Zhou K (2016) Flexible adjustments between energy and capacity for topology control in heterogeneous wireless multi-hop networks. Journal of Network and Systems Management 1-24Google Scholar
Liu Y, Dong M, Ota K, Liu A (2016) ActiveTrust: secure and trustable routing in wireless sensor networks. IEEE Trans Inf Forensic Secur 11:2013–2027CrossRefGoogle Scholar
Xu Q, Su Z, Guo S (2016) A game theoretical incentive scheme for relay selection services in mobile social networks. IEEE Trans Veh Technol 65(8):6692–6702CrossRefGoogle Scholar
Li H, Lin X, Yang H, Liang X, Lu R, Shen X (2014) EPPDR: an efficient privacy-preserving demand response scheme with adaptive key evolution in smart grid. IEEE Trans Parallel Distrib Syst 25(8):2053–2064CrossRefGoogle Scholar
Long J, Dong M, Ota K, Liu A (2015) Green TDMA scheduling algorithm for prolonging Lifetime in wireless sensor networks. IEEE Syst J doi:10.1109/JSYST.2015.2448355.
Chen M, Ma Y, Song J, Lai C, Hu B (2016) Smart clothing: connecting human with clouds and big data for sustainable health monitoring. ACM/Springer Mob Netw Appl 21(5):825–845CrossRefGoogle Scholar
Deng X, Li G, Dong M, Ota K (2017) Finding overlapping communities based on Markov chain and link clustering. Peer-to-Peer Netw Appl 10(2):411–420CrossRefGoogle Scholar
Stojmenovic I, Wen S, Huang X, Luan H (2015) An overview of fog computing and its security issues. Concurr Comput: Pract Experience 28(10):2991–3005CrossRefGoogle Scholar
Al Faruque MA, Vatanparvar K (2016) Energy management-as-a-service over fog computing platform. IEEE Internet Things J 3(2):161–169CrossRefGoogle Scholar
Samimi P, Teimouri Y, Mukhtar M (2016) A combinatorial double auction resource allocation model in cloud computing. Inf Sci 357:201–216CrossRefGoogle Scholar
Baranwal G, Vidyarthi DP (2015) A fair multi-attribute combinatorial double auction model for resource allocation in cloud computing. J Syst Softw 108:60–76CrossRefGoogle Scholar
Dong M, Liu X, Qian Z et al (2015) QoE-ensured price competition model for emerging mobile networks. IEEE Wirel Commun 22(4):50–57CrossRefGoogle Scholar
Samaan N (2014) A novel economic sharing model in a federation of selfish cloud providers. IEEE Trans Parallel Distrib Syst 25(1):12–21CrossRefGoogle Scholar