Abstract
Master-worker computing is a parallel computing scheme, which makes master and worker collaborate. Due to its high reliability availability and serviceability, it is widely used in scientific computing fields. However, lack of cooperation and malicious attack in Master-worker computing can greatly reduce the efficiency of parallel computing. In this paper, we consider a reputation system based on individual classification to inducing worker nodes returning true answer and separate malicious worker nodes. By introducing reinforcement learning, rational workers are induced to behave cooperatively and auditing rate of the master decreases. Our model is based on evolutionary game theory. Simulation results show that our reputation system can not only effectively guarantee eventual correctness, separate malicious worker nodes, but also save the master node’s auditing cost.
This paper is supported by the Liaoning Provincial National Science Foundation of China under grant No. 2017540158.
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
Korpela, E.J., et al.: SETI@home-massively distributed computing for SETI. Comput. Sci. Eng. 3(1), 78–83 (2001)
Amazonas Mechanical Turk. https://www.mturk.com
Goux, J.P., et al.: An enabling framework for master-worker applications on the computational grid, vol. 4(1), pp. 43–50 (2000)
Anta, A.F., Georgiou, C., Mosteiro, M.A., Pareja, D.: Multi-round master-worker computing: a repeated game approach. In: 2016 IEEE 35th Symposium on Reliable Distributed Systems (SRDS), pp. 31–40. IEEE, September 2016
Christoforou, E., Anta, A.F., Georgiou, C., Mosteiro, M.A.: Algorithmic mechanisms for reliable master-worker internet-based computing. IEEE Trans. Comput. 63(1), 179–195 (2014)
Nguyen, T.T.H., Brun, O., Prabhu, B.J.: Performance of a fixed reward incentive scheme for two-hop DTNs with competing relays: short talk. ACM SIGMETRICS Perform. Eval. Rev. 44(3), 39 (2017)
Seregina, T., Brun, O., El-Azouzi, R., Prabhu, B.J.: On the design of a reward-based incentive mechanism for delay tolerant networks. IEEE Trans. Mob. Comput. 16(2), 453–465 (2017)
Lu, K., Wang, S., Xie, L., Wang, Z., Li, M.: A dynamic reward-based incentive mechanism: reducing the cost of P2P systems. Knowl. Based Syst. 112, 105–113 (2016)
Gupta, R., Somani, A.K.: Game theory as a tool to strategize as well as predict nodes’ behavior in peer-to-peer networks. In: International Conference on Parallel and Distributed Systems (2005)
Orset, J.M., Ana, C.: Security in ad hoc networks. In: Ad Hoc Networking Towards Seamless Communications. Springer Netherlands, pp. 756–775 (2002)
Ciccarelli, G., Cigno, R.L.: Collusion in peer-to-peer systems. Comput. Netw. 55(15), 3517–3532 (2011)
Christoforou, E., Anta, A.F., Georgiou, C., Mosteiro, Miguel A., Sánchez, A.: Reputation-based mechanisms for evolutionary master-worker computing. In: Baldoni, R., Nisse, N., van Steen, M. (eds.) OPODIS 2013. LNCS, vol. 8304, pp. 98–113. Springer, Cham (2013). https://doi.org/10.1007/978-3-319-03850-6_8
Sonnek, J., Chandra, A., Weissman, J.: Adaptive reputation- based scheduling on unreliable distributed infrastructures. IEEE Trans. Parallel Distrib. Syst. 18(11), 1551–1564 (2007)
BONIC reputation platform. http://bonic.berkeley.edu/trac/wiki/
Kondo, D., et al.: Characterizing result errors in internet desktop grids. In: European Conference on Parallel Processing, pp. 361–371 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Lu, K., Yang, J., Gong, H., Li, M. (2018). Classification-Based Reputation Mechanism for Master-Worker Computing System. In: Wang, L., Qiu, T., Zhao, W. (eds) Quality, Reliability, Security and Robustness in Heterogeneous Systems. QShine 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 234. Springer, Cham. https://doi.org/10.1007/978-3-319-78078-8_24
Download citation
DOI: https://doi.org/10.1007/978-3-319-78078-8_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-78077-1
Online ISBN: 978-3-319-78078-8
eBook Packages: Computer ScienceComputer Science (R0)