Optimizing Detection Quality and Transmission Quality of Barrier Coverage in Heterogeneous Wireless Sensor Networks
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This paper proposes an algorithm, called the Optimized Barrier Coverage Algorithm (OBCA), to optimize the quality of the barrier coverage formed by a wireless sensor network (WSN). OBCA aims at optimizing the barrier coverage quality in terms of the detection degree, the detection quality, and the transmission quality (i.e., the expected transmission time). This paper also proposes a model to formulate the minimum detection probability between two WSN sensors with different sensing ranges. With the model, OBCA can be applied to heterogeneous WSNs whose sensors have various sensing ranges. OBCA’s optimization is proved, and its time complexity is analyzed. The performance of OBCA is simulated and compared with those of two related algorithms.
KeywordsWireless sensor network Internet of things Cloud system Barrier coverage Minimum cost maximum flow algorithm Expected transmission time Optimization
This work was supported in part by the Ministry of Science and Technology (MOST), Taiwan, under Grant Nos. 104-2221-E-008-017-, 105-2221-E-008-078- and 105-2218-E-008-008-.
- 1.Ball MG, Qela B and Wesolkowski S (2016) A review of the use of computational Intelligence in the design of military surveillance networks. Recent Advances in Computational Intelligence in Defense and Security, Springer, pp 663–693Google Scholar
- 2.Suri N, Tortonesi M, Michaelis J, Budulas P, Benincasa G, Russell S and Winkler R (2016) Analyzing the applicability of Internet of Things to the battlefield environment. In: Proc. of IEEE International Conference on Military Communications and Information Systems (ICMCIS), pp 1–8Google Scholar
- 6.Oppermann FJ, Boano CA, Römer K (2014) A decade of wireless sensing applications: survey and taxonomy. Springer, The Art of Wireless Sensor Networks, pp 11–50Google Scholar
- 7.Kumar S, Lai T-H and Arora A (2005) Barrier coverage with wireless sensors. In: Proc. of the 11th ACM annual international conference on Mobile computing and networking (MobiCom05), pp. 284–298Google Scholar
- 8.Yang G and Qiao D (2009) Barrier information coverage with wireless sensors. In: Proc. of IEEE INFOCOMGoogle Scholar
- 9.Chen A, Kumar S and Lai TH (2007) Designing localized algorithms for barrier coverage. In: Proc. of ACM Mobicom07, pp. 63–74Google Scholar
- 10.Chen A, Kumar S and Lai TH (2010) Local barrier coverage in wireless sensor networks. IEEE Transactions on Mobile Computing (TMC) 9(4);491–504Google Scholar
- 11.Saipulla A, Westphal C, Liu B and Wang J (2009) Barrier coverage of line-based deployed wireless sensor networks. In: Proc. of IEEE INFOCOMGoogle Scholar
- 12.He S, Gong X, Zhang J, Chen J and Sun Y (2013) Barrier coverage in wireless sensor networks: from lined-based to curve-based deployment. In: Proc. of IEEE INFOCOMGoogle Scholar
- 13.Saipulla A, Liu B and Wang J (2010) Finding and mending barrier gaps in wireless sensor networks, in Proc. of IEEE GlobecomGoogle Scholar
- 14.Saipulla A, Liu B, Xing G, Fu X, and Wang J (2010) Barrier coverage with sensors of limited mobility. In: Proc. of ACM MobiHoc, pp. 201–210Google Scholar
- 15.Chen J, Wang B, Liu W, Yang LT and Deng X (2014) Rotating directional sensors to mend barrier gaps in a line-based deployed directional sensor network, IEEE Systems Journal. PP(99):1–12Google Scholar
- 16.Tao D, Tang S, Zhang H, Mao X, Li X, Ma H (2013) Strong barrier coverage detection and mending algorithm for directional sensor networks ad hoc sensor. Wirel Netw 18(1–2):17Google Scholar
- 18.Kumar S, Lai TH, Posner ME, Sinha P (2010) Maximizing the lifetime of a barrier of wireless sensors. IEEE Trans Mob Comput 9(8)Google Scholar
- 19.Luo H, Du H, Kim D, Ye Q, Zhu R and Jia J (2014) Imperfection Better Than Perfection: Beyond Optimal Lifetime Barrier Coverage in Wireless Sensor Networks. In: Proc. of 10th IEEE International Conference on Mobile Ad-hoc and Sensor Networks (MSN 2014)Google Scholar
- 20.DeWitt J and Shi H (2014) Maximizing lifetime for k-barrier coverage in energy harvesting wireless sensor networks. In Proc. of 2014 GlobecomGoogle Scholar
- 21.Balister P, Bollobas B, Sarkar A and Kumar S (2007) Reliable density estimates for coverage and connectivity in thin strips of finite length. In: Proc. of ACM Mobicom, pp 75–86Google Scholar
- 23.Cormen TH, Leiserson CE, Rivest RL and Stein C (2001) Introduction to algorithms. MIT PressGoogle Scholar
- 24.Elfes A (1991) Occupancy grids: A stochastic spatial representation for active robot perception. In: Proc. of the 6th Annual Conference on Uncertainty in Artificial Intelligence (UAI-90), pp 60–70Google Scholar
- 25.Draves R, Padhye J and Zill B (2004) Routing in multi-radio, multi-hop wireless mesh networks. In: Prof. of ACM MobiComGoogle Scholar
- 27.Texas Instruments (2016) CC2420 datasheet, URL: www.ti.com/lit/ds/symlink/cc2420.pdf, last accessed in August 2016.
- 28.Google, An introduction to or-tools, Google's software suite for combinatorial optimization, URL: https://developers.google.com/optimization/, last accessed in December 2016.
- 29.Panasonic. PIR motion sensors (Passive Infrared or Pyroelectric) from Panasonic for optimal usability and reliability. URL: http://www3.panasonic.biz/ac/cdn/e/control/sensor/human/catalog/bltn_eng_papirs.pdf, last accessed in December 2016.