Optimized-Hilbert for Mobility in Wireless Sensor Networks

In wireless sensor networks (WSNs), mobilizing sink node for data collection can minimize communication and maximize network lifetime. Several mobility algorithms have been proposed to control sink node's movement. However, they do not consider mobility for coverage area problem. Hilbert space-filling curves technique is modified to navigate mobile sink in traversing specfiic area of the sensor field. The algorithm is called optimized-Hilbert, which provides mobility pattern of a sink node in covering an ellipsoidal monitoring area during data collection for a specific mission by traversing the entire area from an entry point and finish at an exit point of square grids. The optimized-Hilbert requires less number of steps as compared to conventional Hilbert. Additionally, it is also compared with circular mobility, and result indicates the efficiency of optimized Hilbert.

[1]  Thomas F. La Porta,et al.  Movement-assisted sensor deployment , 2004, IEEE INFOCOM 2004.

[2]  Jernej Polajnar,et al.  Simple and efficient protocols for guaranteed message delivery in wireless ad-hoc networks , 2005, WiMob'2005), IEEE International Conference on Wireless And Mobile Computing, Networking And Communications, 2005..

[3]  Michael D. Dettinger,et al.  Meteorology and Hydrology in Yosemite National Park: A Sensor Network Application , 2003, IPSN.

[4]  Baback Moghaddam,et al.  Space-filling curves for image compression , 1991, Defense, Security, and Sensing.

[5]  Yu-Chee Tseng,et al.  The Coverage Problem in a Wireless Sensor Network , 2005, Mob. Networks Appl..

[6]  Milind Dawande,et al.  Energy efficient schemes for wireless sensor networks with multiple mobile base stations , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[7]  Donald F. Towsley,et al.  Mobility improves coverage of sensor networks , 2005, MobiHoc '05.

[8]  H. L. R. Ong,et al.  Glacial Environment Monitoring using Sensor Networks , 2005 .

[9]  Laveen N. Kanal,et al.  Classification of binary random patterns , 1965, IEEE Trans. Inf. Theory.

[10]  Sanjoy Paul,et al.  Reliable Multicast Transport Protocol (RMTP) , 1997, IEEE J. Sel. Areas Commun..

[11]  Thomas F. La Porta,et al.  Proxy-based sensor deployment for mobile sensor networks , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[12]  Mani Srivastava,et al.  Controlled Mobility for Increased Lifetime in Wireless Sensor Networks , 2004 .

[13]  Luigi Rizzo,et al.  RMDP: an FEC-based reliable multicast protocol for wireless environments , 1998, MOCO.

[14]  Stephan Olariu,et al.  ANSWER: autonomous wireless sensor network , 2005, Q2SWinet '05.

[15]  Stephan Olariu,et al.  Training a Wireless Sensor Network , 2005, Mob. Networks Appl..

[16]  Waylon Brunette,et al.  Data MULEs: modeling a three-tier architecture for sparse sensor networks , 2003, Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, 2003..

[17]  J. Michael Steele,et al.  General Spacefilling Curve Heuristics and Limit Theory for the Traveling Salesman Problem , 1994, J. Complex..

[18]  Eylem Ekici,et al.  Mobility-based communication in wireless sensor networks , 2006, IEEE Communications Magazine.

[19]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[20]  Jun Luo,et al.  Joint mobility and routing for lifetime elongation in wireless sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[21]  Ashutosh Sabharwal,et al.  Using Predictable Observer Mobility for Power Efficient Design of Sensor Networks , 2003, IPSN.

[22]  Hui Zhang,et al.  A case for end system multicast (keynote address) , 2000, SIGMETRICS '00.

[23]  Deborah Estrin,et al.  Intelligent fluid infrastructure for embedded networks , 2004, MobiSys '04.

[24]  Mark Weiser The computer for the 21st century , 1991 .