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Determining the Strength of Barrier Coverage in Wireless Sensor Networks

Momtazian Fard, Zahra | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 50209 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Ghodsi, Mohammad
  7. Abstract:
  8. Given a set of obstacles as an arrangement of geometric shapes in the plane, we would like to find a path from the initial point s to the target point t that crosses the minimum number of obstacles. In other words, the goal is to determine the minimum number of obstacles that need to be removed to exist a collision-free path between s and t.On one hand, this problem can be used for measuring the strength of barrier coverage which is a fundamental concept in wireless sensor networks (WSNs), and on the other hand, it has been considered as a robot motion-planning problem. The objective of barrier coverage is to guarantee that any path from the start point to the target point, will intersect at least one sensor region. Since sensors have limited energy, determining the minimum number of sensors whose removal permits a free path from s to t, is a method for measuring the robustness of the barrier coverage. Also, determining the existence of a collision-free path between two points is one of the most fundamental problems in robotics. In some situations, crossing an obstacle is costly but not impossible. Therefore, if no collision-free path exists, it may be appropriate to ask for a path that crosses the fewest obstacles.In this research, we define a new version of the problem where each obstacle is associated with a color from a color set and each color has a non-zero weight. The weight of a path is defined as the sum of weights of the colors that at least one of the obstacles with that color is crossed by the path. The goal is to find a path between s and t with the minimum total weight.We show that the problem for disk obstacles is NP-hard to approximate within a factor of O(log n), by reduction from the set cover problem. Then, we present a polynomial time O(√n)-approximation algorithm for the problem in general case. In addition, we consider a restricted version of the problem where for each color, there exist at most k ⩾ 3 disks with that color. We show that the problem in this special case remains NP-hard, but there is a polynomial-time 2k-approximation algorithm for it
  9. Keywords:
  10. Computational Geometry ; Approximate Algorithm ; Sensor Network ; Path Planning ; Barrier Coverage

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