Download Algorithmic Aspects of Wireless Sensor Networks: Fourth by Sandor P. Fekete PDF

By Sandor P. Fekete

This publication constitutes the reviewed complaints of the Fourth overseas Workshop on Algorithmic points of instant Sensor Networks, ALGOSENSORS 2008, held in Reykjavik, Iceland, Wroclaw, Poland, July 12, 2008. The workshops aimed toward bringing jointly study contributions with regards to diversified algorithmic and complexity-theoretic facets of instant sensor networks. the themes comprise yet usually are not constrained to optimization difficulties, noise and chance, robots and excursions.

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P(a + |S| − 1)}; 2. If i ≥ 1 and i ≤ |S| − 1, then Cp(a+i) ≤ Cp(a+i−1) + γ/σ; 3. If a + |S| ≤ m, then Cp(a+|S|) > Cp(a+|S|−1) + γ/σ. That is, a component is a maximal set of packets arriving subsequently at the sink, each within time γ/σ of the previous packet. It follows from the definition 24 V. Bonifaci et al. that the set J of all packets can be partitioned into components T1 , . . , T , for some . Lemma 1. For any component T we have minj∈T Cj = minj∈T (rj + δj /σ). Proof. Consider the partition of the packet set J into components T1 , .

15th Symp. on Discrete Algorithms, pp. 350–358. SIAM, Philadelphia (2004) Target Counting under Minimal Sensing: Complexity and Approximations Sorabh Gandhi, Rajesh Kumar, and Subhash Suri Department of Computer Science, University of California, Santa Barbara, CA-93106 Abstract. We consider the problem of counting a set of discrete point targets using a network of sensors under a minimalistic model. Each sensor outputs a single integer, the number of distinct targets in its range, but targets are otherwise indistinguishable to sensors: no angles, distances, coordinates, or other target-identifying measurements are available.

Partially supported by the German Research Foundation (DFG) within the Research Training Group GRK 1194 “Self-organizing Sensor-Actuator Networks”. Partially supported by the “BW-FIT” project “ZeuS” by the Landesstiftung BadenW¨ urttemberg. S. ): ALGOSENSORS 2008, LNCS 5389, pp. 43–56, 2008. c Springer-Verlag Berlin Heidelberg 2008 44 B. Katz, S. Mecke, and D. Wagner Power consumption in this scenario can be reduced in several ways. First by compressing the data, second by improving the routing tree to prevent that single nodes are overly burdened, and third by avoiding all unnecessary power consumption of the radio.

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