By Sandor P. Fekete
This publication constitutes the reviewed complaints of the Fourth overseas Workshop on Algorithmic features of instant Sensor Networks, ALGOSENSORS 2008, held in Reykjavik, Iceland, Wroclaw, Poland, July 12, 2008. The workshops aimed toward bringing jointly study contributions regarding diversified algorithmic and complexity-theoretic facets of instant sensor networks. the subjects comprise yet aren't restricted to optimization difficulties, noise and likelihood, robots and excursions.
Read or Download Algorithmic Aspects of Wireless Sensor Networks: Fourth International Workshop, Algosensors 2008, Reykjavik, Iceland, July 2008. Revised Selected Pape ... Computer Science Computer Communication N) PDF
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Additional resources for Algorithmic Aspects of Wireless Sensor Networks: Fourth International Workshop, Algosensors 2008, Reykjavik, Iceland, July 2008. Revised Selected Pape ... Computer Science Computer Communication N)
22] add to the basic binary sensing model by considering mobile binary sensors and show that even then the problem is hard. Counting targets is also addressed in , the sensors considered are proximity sensors and sense the amplitude only. The target counting is then represented as peak counting problem in the aggregate sensor network, but the framework assumes that the targets are well separated. In , the authors look at the problem of counting the number of people in a crowd using image sensors.
Theorem 2. Let ∈ (0, 1). Unless P=NP, no polynomial time algorithm can approximate F-Wgp within a ratio better than Ω(m1− ). Proof. 2 in . As shown in , it is possible to construct in polynomial time, given an IBM instance I, an instance I of Wgp with an arbitrary number m of packets such that the following hold: 1. if I has an induced matching of size k, then there is a schedule for I with maximum ﬂow time 2k + 1; 2. if all induced matchings of I are of size at most k/α, then in every schedule for I there will be a round in which Θ(m/k) packets have been released but not yet collected at the sink.
Proof. Notice that the analysis of the above theorem also yields that Cj∗ , Cj ≤ j∈J j∈J where Cj is the completion time of packet j in the schedule generated by 5ISRPT. We can now simulate the schedule generated by 5-ISRPT by running it at a lower speed: whatever 5-ISRPT does at time t, a unit-speed algorithm can do at time 5t. The schedule can be constructed online and clearly it respects the release dates. If Cj is the completion time of packet j in the new schedule, we obtain Cj = 5 · Cj ≤ 5 Cj∗ .