By Shlomi Dolev (auth.), Thomas Erlebach, Sotiris Nikoletseas, Pekka Orponen (eds.)
This booklet constitutes the completely refereed post-conference court cases of the seventh overseas Workshop on Algorithms for Sensor platforms, instant advert Hoc Networks, and self sufficient cellular Entities, ALGOSENSORS 2011, held in Saarbrücken, Germany, in September 2011. The sixteen revised complete papers awarded including invited keynote talks have been rigorously reviewed and chosen from 31 submissions. The papers are prepared in tracks: sensor networks, masking themes similar to localization, lifetime maximization, interference keep watch over, neighbor discovery, self-organization, detection, and aggregation; and advert hoc instant and cellular platforms together with the subjects: routing, scheduling and ability optimization within the SINR version, non-stop tracking, and broadcasting.
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Extra info for Algorithms for Sensor Systems: 7th International Symposium on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities, ALGOSENSORS 2011, Saarbrücken, Germany, September 8-9, 2011, Revised Selected Papers
In: Proceedings of the 24th IEEE International Parallel & Distributed Processing Symposium (IPDPS), pp. 1–10. IEEE (2010) 9. : A distributed O(1)-approximation algorithm for the uniform facility location problem. In: Proceedings of the 18th Annual ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp. 237–243 (2006) 10. : Greedy strikes back: improved facility location algorithms. Journal of Algorithms 31(1), 228–248 (1999) 11. : Greedy facility location algorithms analyzed using dual ﬁtting with factor-revealing LP.
In: Proc. of the 44th Annual IEEE Symposium on Foundations of Computer Science, pp. 584–593 (2003) 18. : Finding Facilities Fast. , Kothapalli, K. ) ICDCN 2009. LNCS, vol. 5408, pp. 11–24. Springer, Heidelberg (2008) 19. : Return of the primal-dual: distributed metric facility location. In: Proceedings of the 28th Annual ACM Symposium on Principles of Distributed Computing (PODC), pp. 180–189 (2009) 20. : Distributed computing: a locality-sensitive approach. Society for Industrial and Applied Mathematics, Philadelphia (2000) Appendix Proof of Claim 1: 1/p 1/p Proof.
In the ﬁrst, given a set of sensors, one wishes to identify a subset of the sensors, which while small in size, captures the essence of the data gathered by the sensors. In the second, one wishes to construct a fused sensor, which utilizes the data from the sensors (possibly after discarding dependent ones) in order to create a single sensor which is more reliable than each of the individual ones. In this work, we rigorously deﬁne the dependence among sensors in terms of joint empirical measures and incremental parsing.