A resource allocation model based on double-sided combinational auctions for transparent computing
- 296 Downloads
- 19 Citations
Abstract
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.
Keywords
Transparent computing Communication bandwidth boundary Double-sided auctions Resources optimizationNotes
Acknowledgements
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).
References
- 1.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
- 2.Liu J, Zhou Y, Zhang D (2016) TranSim: a simulation framework for cache-enabled transparent computing systems. IEEE Trans Comput 65(10):3171–3183MathSciNetCrossRefMATHGoogle Scholar
- 3.Guo K, Xiao Y, Duan G (2016) A cost-efficient architecture for the campus information system based on transparent computing platform. Int J Ad Hoc Ubiquit Comput 21(2):95–103CrossRefGoogle Scholar
- 4.Li Y, Chen M, Dai W, Qiu M (2015) Energy optimization with dynamic task scheduling mobile cloud computing. IEEE Syst J. doi: 10.1109/JSYST.2015.2442994 Google Scholar
- 5.Zhang Y, Zhou Y (2013) Transparent computing: spatio-temporal extension on von neumann architecture for cloud services. Tsinghua Sci Technol 18(1):10–21CrossRefGoogle Scholar
- 6.Xue C, Lin C (2016) Performance modelling for transparent computing using stochastic petri nets. Int J Ad Hoc Ubiquit Comput 21(2):81–94CrossRefGoogle Scholar
- 7.Li H, Yang Y, Luan TH, Liang X, Zhou L, Shen XS (2016) Enabling fine-grained multi-keyword search supporting classified sub-dictionaries over encrypted cloud data. IEEE Trans Dependable Secure Comput 13(3):312–325CrossRefGoogle Scholar
- 8.Su Z, Xu Q, Fei M, Dong M (2016) Game theoretic resource allocation in media cloud with mobile social users. IEEE Trans Multimed 18(8):1650–1660CrossRefGoogle Scholar
- 9.Liu A, Jin X, Cui G, Chen Z (2013) Deployment guidelines for achieving maximal Lifetime and avoiding energy holes in sensor network. Inf Sci 230:197–226CrossRefGoogle Scholar
- 10.Su Z, Xu Q, Qi Q (2016) Big data in mobile social networks: a QoE-oriented framework. IEEE Netw 30(1):52–57CrossRefGoogle Scholar
- 11.Zeng J, Yang LT, Ma J (2016) A system-level modeling and design for cyber-physical-social systems. ACM Trans Embed Comput Syst (TECS) 15(2):35Google Scholar
- 12.Zhang Y, He S, Chen J et al (2013) Distributed sampling rate control for rechargeable sensor nodes with limited battery capacity. IEEE Trans Wirel Commun 12(6):3096–3106CrossRefGoogle Scholar
- 13.Ren J, Zhang Y, Zhang K, Liu A, Chen J, Shen XS (2016) Lifetime and energy hole evolution analysis in data-gathering wireless sensor networks. IEEE Trans Ind Inform 12(2):788–800CrossRefGoogle Scholar
- 14.Chen Z, Liu A, Li Z, Choi YJ, Li J (2017) Distributed duty cycle control for delay improvement in wireless sensor networks. Peer-to-Peer Netw Appl 10(3):559–578CrossRefGoogle Scholar
- 15.Deng X, He L, Li X, Liu Q, Cai L, Chen Z (2016) A reliable QoS aware routing scheme for neighbor area nework in smart grid. Peer-to-Peer Netw Appl 9(4):616–627CrossRefGoogle Scholar
- 16.Mianxiong D, Kimata T, Sugiura K et al (2014) Quality-of-experience (QoE) in emerging mobile social networks. IEICE Trans Inf Syst 97(10):2606–2612Google Scholar
- 17.Platania M, Obenshain D, Tantillo T, Amir Y, Suri N (2016) On choosing server-or client-side solutions for BFT. ACM Comput Surv (CSUR) 48(4):61CrossRefGoogle Scholar
- 18.Li H, Liu D, Dai Y, Luan TH (2015) Engineering searchable encryption of mobile cloud networks: when qoe meets qop. IEEE Wirel Commun 22(4):74–80CrossRefGoogle Scholar
- 19.Aazam M, Huh EN (2015) Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT[C] //. IEEE 29th Int Conf Adv Inf Netw Appl:687–694Google Scholar
- 20.Yaoxue Zhang, Ju Ren, Jiagang Liu, et al (2017) A Survey on Emerging Computing Paradigms for Big Data. Chinese Journal of Electronics 26(1):1–12Google Scholar
- 21.Ren J, Zhang Y, Zhang K, et al (2015) Exploiting mobile crowdsourcing for pervasive cloud services: challenges and solutions[J]. IEEE Communications Magazine 53(3):98–105.Google Scholar
- 22.Choi CR, Jeong HY, Park JH, Jang HJ, Jeong YS (2016) Relative weight comparison between virtual key factors of cloud computing with analytic network process. J Supercomput 72(5):1694–1714CrossRefGoogle Scholar
- 23.Deng X, Peng Q, He L, He T (2016) Interference-aware QoS routing for neighborhood area network in smart grid. IET Commun. doi: 10.1049/iet-com.2016.0860 Google Scholar
- 24.Zhao S, Liu A (2017) High performance target tracking scheme with low prediction precision requirement in WSNs, International Journal of Ad Hoc and Ubiquitous Computing, http://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijahuc
- 25.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
- 26.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
- 27.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
- 28.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
- 29.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
- 30.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
- 31.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
- 32.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
- 33.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.
- 34.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
- 35.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
- 36.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
- 37.Al Faruque MA, Vatanparvar K (2016) Energy management-as-a-service over fog computing platform. IEEE Internet Things J 3(2):161–169CrossRefGoogle Scholar
- 38.Samimi P, Teimouri Y, Mukhtar M (2016) A combinatorial double auction resource allocation model in cloud computing. Inf Sci 357:201–216CrossRefGoogle Scholar
- 39.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
- 40.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
- 41.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