By Shlomi Dolev (auth.), Thomas Erlebach, Sotiris Nikoletseas, Pekka Orponen (eds.)
This ebook 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 provided including invited keynote talks have been rigorously reviewed and chosen from 31 submissions. The papers are equipped in tracks: sensor networks, overlaying subject matters corresponding to localization, lifetime maximization, interference keep watch over, neighbor discovery, self-organization, detection, and aggregation; and advert hoc instant and cellular structures together with the subjects: routing, scheduling and potential optimization within the SINR version, non-stop tracking, and broadcasting.
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Additional resources 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 this manner load imbalances are averaged out over the k levels of the algorithm. Nevertheless, a Chernoﬀ bound analogous to the one used above for k-RoundRobin will show that √ for k < ln n, with high probability Ni will deviate from its mean of 2nk by O( n ln n). 4 n n Theorem 2. 869-approximation ratio with high probability. 4 Optimizations Still, it is clear from Figure 4 that eﬃciency is highest in Γk (1) and lowest in Γk (k). We can show that in fact, the relative eﬃciency of Γk (k) is the constant 4 The inequality is justiﬁed by the preceding argument that in practice, the actual load balancing will work at least this well.
For this reason we report the variance but focus most of our attention on the expected average lifetime of each algorithm. Theorem 1. 693-approximation ratio in the average case. 2 A. Bar-Noy and B. Baumer k-RoundRobin A natural extension of RoundRobin is to partition U into k equally-spaced subintervals, and run it independently on each of those. Somewhat surprisingly, the performance is no better in either the worst or the average case. , k deﬁne a partition of U . We deﬁne k-RoundRobin to be the algorithm that runs RoundRobin independently on each subinterval Uk (i); maintaining k parallel queues.
Facility location: distributed approximation. In: Proceedings of the 24th Annual ACM Symposium on Principles of Distributed Computing (PODC), pp. 108–117 (2005) 17. : Group strategy proof mechanisms via primal-dual algorithms. 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.
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 by Shlomi Dolev (auth.), Thomas Erlebach, Sotiris Nikoletseas, Pekka Orponen (eds.)