LBDP: localized boundary detection and parametrization for 3-D sensor networks

摘要: Many applications of wireless sensor networks involve monitoring a time-variant event (e.g., radiation pollution in the air). In such applications, fast boundary detection is crucial function, as it allows us to track variation timely fashion. However, problem becomes very challenging demands highly efficient algorithm cope with dynamics introduced by evolving event. Moreover, many physical events occupy volumes rather than surfaces again), has work for 3-D cases. Finally, boundaries network can be complicated 2-manifolds, functionalities routing) may fail face boundaries. To this end, we propose Localized Boundary Detection and Parametrization (LBDP) tackle these challenges. The first component LBDP UNiform Fast On-Line (UNFOLD). It applies an inversion node coordinates that “notched” surface “unfolded” into convex one, which turn reduces localized convexity test. We prove correctness efficiency UNFOLD; also use simulations implementations evaluate its performance, demonstrates UNFOLD two orders magnitude more time- energy-efficient most up-to-date proposal. Another Sphericalization (LBS). Through purely operations, LBS maps arbitrary genus-0 unit sphere, supports distinguishing inter from external ones distributed coordinations on boundary. implement TOSSIM show effectiveness.