Abstract
Resource allocation draws much attention from various areas and it is a hot topic to explore trustful allocation mechanisms. In this paper, we study the problem in a centralized resource system where a controller allocates appropriate resources to other nodes according to their demands. The max-min fair allocation enables fairness among the nodes and we explore whether the allocation is trustful when a node behaves strategically. We first introduce a simple but efficient algorithm to generate the max-min fair allocation, and then we analyze how the allocated resources vary when a new node is added to the system. To discuss about the trustfulness of the allocation, we propose two strategic behaviors: misreporting strategy which the new node misreports its resource demand and spitting strategy which the node misrepresents itself by creating several fictitious nodes but keeps the sum of their resource demands the same. Surprisingly, we show that the allocation is trustful against the misreporting strategy while it is not trustful against the spitting strategy. Specifically, we present some illustrative examples to verify the results, and we show that a node can achieve 1.83 times resource if it misrepresents itself as two nodes.
This work was supported in part by the National Natural Science Foundation of China under Grant No. U1636215, the Guangdong Province Key Research and Development Plan under Grant No. 2019B010136003, and the National Key Research and Development Program of China 2018YFB1004003.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Adsul, B., Babu, C.S., Garg, J., Mehta, R., Sohoni, M.: Nash equilibria in fisher market. In: Kontogiannis, S., Koutsoupias, E., Spirakis, P.G. (eds.) SAGT 2010. LNCS, vol. 6386, pp. 30–41. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16170-4_4
Aloui, C., Hkiri, B., Hammoudeh, S., Shahbaz, M.: A multiple and partial wavelet analysis of the oil price, inflation, exchange rate, and economic growth nexus in Saudi Arabia. Emerg. Mark. Finance Trade 54(4), 935–956 (2018)
Bertsekas, D., Gallager, R.: Data Networks, 2nd edn. Prentice-Hall Inc., Upper Saddle River (1992)
Blot, M., Cord, M., Thome, N.: Max-min convolutional neural networks for image classification. In: IEEE International Conference on Image Processing, pp. 3678–3682 (2016)
Brams, S.J., Taylor, A.D.: Fair division: from cake-cutting to dispute resolution. Soc. Justice Res. 12(2), 149–162 (1999)
Charny, A.: An algorithm for rate allocation in a packet. Massachusetts Institute of Technology (1994)
Chen, L., Liu, S., Li, B., Li, B.: Scheduling jobs across geo-distributed datacenters with max-min fairness. In: INFOCOM 2017 - IEEE Conference on Computer Communications, pp. 1–9. IEEE (2017)
Chen, N., Deng, X., Zhang, H., Zhang, J.: Incentive ratios of fisher markets. In: Czumaj, A., Mehlhorn, K., Pitts, A., Wattenhofer, R. (eds.) ICALP 2012. LNCS, vol. 7392, pp. 464–475. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31585-5_42
Chen, N., Deng, X., Zhang, J.: How profitable are strategic behaviors in a market? In: Demetrescu, C., Halldórsson, M.M. (eds.) ESA 2011. LNCS, vol. 6942, pp. 106–118. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23719-5_10
Chen, Y., Lai, J.K., Parkes, D.C., Procaccia, A.D.: Truth, justice, and cake cutting. Games Econ. Behav. 77(1), 284–297 (2013)
Chen, Z., Cheng, Y., Deng, X., Qi, Q., Yan, X.: Agent incentives of strategic behavior in resource exchange. In: International Symposium on Algorithmic Game Theory, pp. 227–239 (2017)
Cheng, Y., Deng, X., Pi, Y., Yan, X.: Can bandwidth sharing be truthful? In: Hoefer, M. (ed.) SAGT 2015. LNCS, vol. 9347, pp. 190–202. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-48433-3_15
Cheng, Y., Deng, X., Qi, Q., Yan, X.: Truthfulness of a proportional sharing mechanism in resource exchange. In: International Joint Conference on Artificial Intelligence (IJCAI), pp. 187–193 (2016)
Cretch, P., Michielsens, J., Taeymans, J.: Data network (2002)
Feldman, M., Lai, K., Stoica, I., Chuang, J.: Robust incentive techniques for peer-to-peer networks. In: ACM Conference on Electronic Commerce, pp. 102–111 (2004)
Gamow, G., Stern, M.: Puzzle-Math. The Viking Press, New York (1958)
Ghumman, N.S., Kaur, R.: Dynamic combination of improved max-min and ant colony algorithm for load balancing in cloud system. In: International Conference on Computing, Communication and NETWORKING Technologies, pp. 1–5 (2016)
Hahne, E.L.: Round-robin scheduling for max-min fairness in data networks. IEEE J. Sel. Areas Commun. 9(7), 1024–1039 (1991)
Hurwicz, L.: On Informationally Decentralized Systems (1972)
Jia, Y., Zhao, M., Zhou, W.: Joint user association and eICIC for max-min fairness in HetNets. IEEE Commun. Lett. 20(3), 546–549 (2016)
Khamse-Ashari, J., Kesidis, G., Lambadaris, I., Urgaonkar, B., Zhao, Y.: Constrained max-min fair scheduling of variable-length packet-flows to multiple servers. Ann. Telecommun. 73(3–4), 219–237 (2018)
Menon, V., Larson, K., Menon, V., Larson, K., Menon, V., Larson, K.: Deterministic, strategyproof, and fair cake cutting (2017)
Pham, T.V., Pham, A.T.: Max-min fairness and sum-rate maximization of MU-VLC local networks. In: IEEE GLOBECOM Workshops, pp. 1–6 (2016)
Roughgarden, T., Tardos, E.: How bad is selfish routing? J. ACM (JACM) 49(2), 236–259 (2002)
Segal-Halevi, E.: Cutting a cake with both good and bad parts (2017)
Segal-Halevi, E., Nitzan, S.: Envy-free cake-cutting among families (2016)
Steinhaus, H.: The problem of fair division. Econometrica 16, 101–104 (1948)
Wahlen, S., Laamanen, M.: Collaborative consumption and sharing economies (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Chen, Z., Gu, Z., Wang, Y. (2020). Can the Max-Min Fair Allocation Be Trustful in a Centralized Resource System?. In: Yu, D., Dressler, F., Yu, J. (eds) Wireless Algorithms, Systems, and Applications. WASA 2020. Lecture Notes in Computer Science(), vol 12384. Springer, Cham. https://doi.org/10.1007/978-3-030-59016-1_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-59016-1_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-59015-4
Online ISBN: 978-3-030-59016-1
eBook Packages: Computer ScienceComputer Science (R0)