Abstract
Networked systems are often deployed over a wide area without any centralized managing authority, and rely on distributed coordination among resource-constrained nodes. This chapter presents distributed algorithms for submodular maximization, including distributed implementations of greedy and exchange-based local search algorithms. The optimality guarantees and performance of each scheme are analyzed and compared to the best centralized algorithms. Techniques for submodular maximization by multiple parallel processors, as in a cloud computing scenario, are also discussed.
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
Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Mach. Learn. 47(2–3), 235–256 (2002)
Auer, P., Cesa-Bianchi, N., Freund, Y., Schapire, R.E.: Gambling in a rigged casino: The adversarial multi-armed bandit problem. In: 36th IEEE Annual Symposium on Foundations of Computer Science, pp. 322–331 (1995)
Barbosa, R.d.P., Ene, A., Nguyen, H.L., Ward, J.: A new framework for distributed submodular maximization. arXiv preprint arXiv:1507.03719 (2015)
Cattivelli, F.S., Lopes, C.G., Sayed, A.H.: Diffusion recursive least-squares for distributed estimation over adaptive networks. IEEE Trans. Signal Process. 56(5), 1865–1877 (2008)
Clark, A., Alomair, B., Bushnell, L., Poovendran, R.: Distributed online submodular maximization in resource-constrained networks. In: 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), pp. 397–404 (2014)
Clark, A., Alomair, B., Bushnell, L., Poovendran, R.: Scalable and distributed submodular maximization with matroid constraints. In: 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), pp. 435–442 (2015)
Golovin, D., Faulkner, M., Krause, A.: Online distributed sensor selection. In: Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, pp. 220–231 (2010)
Intel Berkeley Sensor Network Dataset. http://db.csail.mit.edu/labdata/labdata.html
Kaashoek, M.F., Karger, D.R.: Koorde: a simple degree-optimal distributed hash table. Peer-to-peer Systems II, pp. 98–107. Springer, Berlin (2003)
Kang, I., Poovendran, R.: Maximizing static network lifetime of wireless broadcast ad hoc networks. IEEE Int. Conf. Commun. (ICC) 3, 2256–2261 (2003)
Mirzasoleiman, B., Karbasi, A., Sarkar, R., Krause, A.: Distributed submodular maximization: Identifying representative elements in massive data. In: Advances in Neural Information Processing Systems, pp. 2049–2057 (2013)
Nemhauser, G., Wolsey, L., Fisher, M.: An analysis of approximations for maximizing submodular set functions - I. Math. Program. 14(1), 265–294 (1978)
Nguyen, D., Tran, T., Nguyen, T., Bose, B.: Wireless broadcast using network coding. IEEE Trans. Veh. Technol. 58(2), 914–925 (2009)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Clark, A., Alomair, B., Bushnell, L., Poovendran, R. (2016). Distributed Submodular Maximization. In: Submodularity in Dynamics and Control of Networked Systems. Communications and Control Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-26977-1_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-26977-1_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26975-7
Online ISBN: 978-3-319-26977-1
eBook Packages: EngineeringEngineering (R0)