Abstract
Cloud computing is characterized by strong computing and storage capabilities, and edge computing has the advantages of low latency and low power consumption. Many service providers have begun to combine the advantages of cloud and edge computing to provide better quality of service, but the heterogeneity of cloud and edge computing represents a challenge for service deployment and resource allocation. This paper proposes a framework for cloud-edge collaboration based on live video webcast services and transforms the resource allocation problem into a constrained integer programming (IP) model. Additionally, we introduce an auction mechanism to solve the problem of resource competition among the anchor users in live services. By solving the IP resource allocation problem and Vickrey–Clarke–Groves mechanism, we obtain the optimal resource allocation mechanism. Based on the dominant resource proportion and matching model, we design a resource allocation mechanism for the online environment. These mechanisms can be used for reservation and live webcast scenarios. Furthermore, we prove that the two mechanisms have individual rationality and truthfulness. Our approach is characterized by high social welfare, high resource utilization and a short execution time.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Availability of data and material
The datasets used or analysed during the current study are available from the corresponding author on reasonable request.
References
Alibaba (2020) Alibaba Live [Online]. https://www.aliyun.com/product/live
Angelelli E, Filippi C (2011) On the complexity of interval scheduling with a resource constraint. Theoret Comput Sci 412(29):3650–3657
Angelelli E, Bianchessi N, Filippi C (2014) Optimal interval scheduling with a resource constraint. Comput Oper Res 51:268–281
Bharti S, Pattanaik K (2014) Dynamic distributed flow scheduling for effective link utilization in data center networks. J High Speed Netw 20(1):1–10
Carvalho G, Cabral B, Pereira V, Bernardino J (2021) Edge computing: current trends, research challenges and future directions. Computing 103:993–1023
Chen M, Hao Y (2018) Task offloading for mobile edge computing in software defined ultra-dense network. IEEE J Sel Areas Commun 36(3):587–597
Chen X, Hu X, Liu T, Ma W, Qin T, Tang P, Wang C, Zheng B (2016) Efficient mechanism design for online scheduling. J Artif Intell Res 56(1):429–461
Deng S, Xiang Z, Zhao P, Taheri J, Gao H, Yin J, Zomaya AY (2020) Dynamical resource allocation in edge for trustable internet-of-things systems: a reinforcement learning method. IEEE Trans Ind Inf 16(9):6103–6113
Deng S, Xiang Z, Taheri J, Khoshkholghi MA, Yin J, Zomaya AY, Dustdar S (2021) Optimal application deployment in resource constrained distributed edges. IEEE Trans Mob Comput 20(5):1907–1923
Duan Q, Wang S, Ansari N (2020) Convergence of networking and cloud/edge computing: Status, challenges, and opportunities. IEEE Netw 34(6):148–155
Guo H, Liu J, Qin H (2018) Collaborative mobile edge computation offloading for iot over fiber-wireless networks. IEEE Netw 32(1):66–71
Iimedia (2019) 2019q3 china online live broadcast industry development research report [Online]. https://www.iimedia.cn/c400/66897.html
Jiao Y, Wang P, Niyato D, Xiong Z (2018) Social welfare maximization auction in edge computing resource allocation for mobile blockchain. In: IEEE international conference on communications, pp 1–6
Li K (2019) How to stabilize a competitive mobile edge computing environment: a game theoretic approach. IEEE Access 7:69960–69985
Liu C, Li K, Liang J, Li K (2019) Cooper-match: job offloading with a cooperative game for guaranteeing strict deadlines in mec. IEEE Trans Mobile Comput. https://doi.org/10.1109/TMC.2019.2921713
Liu C, Li K, Liang J, Li K (2019) Cooper-sched: a cooperative scheduling framework for mobile edge computing with expected deadline guarantee. IEEE Trans Parallel Distrib Syst 1
Liu X, Li W, Zhang X (2018) Strategy-proof mechanism for provisioning and allocation virtual machines in heterogeneous clouds. IEEE Trans Parallel Distrib Syst 29(7):1650–1663
Mashayekhy L, Fisher N, Grosu D (2016) Truthful mechanisms for competitive reward-based scheduling. IEEE Trans Comput 65(7):2299–2312
Mashayekhy L, Nejad M, Grosu D, Vasilakos A (2016) An online mechanism for resource allocation and pricing in clouds. IEEE Trans Comput 65(4):1172–1184
Nejad M, Mashayekhy L, Grosu D (2015) Truthful greedy mechanisms for dynamic virtual machine provisioning and allocation in clouds. IEEE Trans Parallel Distrib Syst 26(2):594–603
Nguyen DT, Le LB, , Bhargava V (2018) Price-based resource allocation for edge computing: a market equilibrium approach. IEEE Trans Cloud Comput 9(1):302–317
Nisan T, Roughgarden E, Tardos E, Vazirani V (2007) Algorithmic game theory. Cambridge Univ. Press, Cambridge
Ren J, Yu G, He Y, Li GY (2019) Collaborative cloud and edge computing for latency minimization. IEEE Trans Veh Technol 68(5):5031–5044
Shi W, Pallis G, Xu Z (2019) Edge computing [scanning the issue]. Proc IEEE 107(8):1474–1481
Song B, Hassan MM, Alamri A, Alelaiwi A, Tian Y, Pathan M, Almogren A (2016) A two-stage approach for task and resource management in multimedia cloud environment. Computing 98(1–2):119–145
Sun W, Liu J, Yue Y, Zhang H (2018) Double auction-based resource allocation for mobile edge computing in industrial internet of things. IEEE Trans Ind Inf 14(10):4692–4701
Tran Tuyen X, Pompili D (2018) Joint task offloading and resource allocation for multi-server mobile-edge computing networks. IEEE Trans Veh Technol 68(1):856–868
Wang Y, Sheng M, Wang X, Wang L, Li J (2016) Mobile-edge computing: partial computation offloading using dynamic voltage scaling. IEEE Trans Commun 64(10):4268–4282
Wu Q, Hao J (2016) A clique-based exact method for optimal winner determination in combinatorial auctions. Inf Sci 334:103–121
Xiang Z, Deng S, Jiang F, Gao H, Tehari J, Yin J (2020) Computing power allocation and traffic scheduling for edge service provisioning, pp 394–403
You C, Huang K, Chae H, Kim BH (2016) Energy-efficient resource allocation for mobile-edge computation offloading. IEEE Trans Wirel Commun 16(3):1397–1411
Zafari F, Li J, Leung KK, Towsley D, Swami A (2018) A game-theoretic approach to multi-objective resource sharing and allocation in mobile edge clouds. In: Technologies for the wireless edge workshop, pp 9–13
Zhang H, Guo F, Ji H, Zhu C (2015) Combinational auction-based service provider selection in mobile edge computing networks. IEEE Access 5:13455–13464
Zhang J, Xie N, Zhang X, Li W (2018) An online auction mechanism for cloud computing resource allocation and pricing based on user evaluation and cost. Future Gener Comput Syst 89:286–299
Zhang J, Xie N, Zhang X, Yue K, Li W, Kumar D (2018) Machine learning based resource allocation of cloud computing in auction. Comput Mater Contin 56(1):123–135
Zhang J, Yang X, Xie N, Zhang X, Athanasios V, Li W (2020) An online auction mechanism for time-varying multidimensional resource allocation in clouds. Future Gener Comput Syst 111:27–38
Zhao H, Deng S, Liu Z, Xiang Z, Yin J, Dustdar S, Zomaya A (2021) Dpos: decentralized, privacy-preserving, and low-complexity online slicing for multi-tenant networks. IEEE Trans Mobile Comput. https://doi.org/10.1109/TMC.2021.3074934
Zhou H, Bai G, Deng S (2019) Optimal interval scheduling with nonidentical given machines. Clust Comput 22(5):1007–1015
Funding
This work is supported in part by the National Natural Science Foundation of China (Nos. 62062065, 61762091, 61662088, 12071417 and 11663007), the Project of the Natural Science Foundation of Yunnan Province of China (2019FB142 and 2018ZF017), and the Program for Excellent Young Talents, Yunnan University, China.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
Not applicable
Code availability
The codes generated or used during the study are available from the corresponding author on reasonable request.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zhang, J., Chi, L., Xie, N. et al. Strategy-proof mechanism for online resource allocation in cloud and edge collaboration. Computing 104, 383–412 (2022). https://doi.org/10.1007/s00607-021-00962-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00607-021-00962-6