Empowering the invulnerability of wireless sensor networks through super wires and super nodes

Proceedings - 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2013

Volumn , Issue , 2013, Pages 561-568

  Fu, Xiuwen ^a   Li, Wenfeng ^a   Fortino, Giancarlo ^b  

^a WUHAN UNIVERSITY OF TECHNOLOGY   (China)

^b UNIVERSITY OF CALABRIA   (Italy)

Author keywords

Centrality measurement; Invulnerability; Super nodes; Super wires; Wireless sensor networks

Indexed keywords

EFFECTIVE SOLUTION; ENVIRONMENTAL CONDITIONS; GAINING MOMENTUM; INVULNERABILITY; NETWORK CONSTRUCTION; NETWORK INVULNERABILITIES; SIMULATION ANALYSIS; SUPERNODES;

COMPUTER SIMULATION; GRID COMPUTING; OPTIMIZATION; WIRE; WIRELESS SENSOR NETWORKS;

SENSOR NODES;

EID: 84881292157     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCGrid.2013.95     Document Type: Conference Paper

References (21)

1. D. M. Doolin, and N. Sitar, Wireless sensors for wildfire monitoring, SPIE Symposium on Smart Structures & Materials/NDE 2005, March 2005.
2. Martinez de Dios et al. Computer vision techniques for forest fire perception. Image and Vision Computing, 2008, 26( 4).
3. Son B, Her Y., Kim J. A design and implementation of forest-fires surveillance system based on wireless sensor networks for South Korea Mountains. IJCSNS 2006, 6, 124-130.
4. S.W. Taylor, M.E. Alexander, "Science, technology, and human factors in fire danger rating: the Canadian Experience", International Journal of Wildland Fire, 2006, 15, pp121-135.
5. Kewei Sha, Weisong Shi, Watkins, O. Wayne State Univ., Detroit, MI; Using Wireless Sensor Networks for Fire Rescue Applications: Requirements and Challenges, IEEE International Conference on Electro/information Technology, 2006. 239-244.
6. Boesch F, Thomas R. On graphs of invulnerable communication nets. J. Circuit Theory, 1970, 17(2): 183-192.
7. Fratta L, Montanari U. A Boolean algebra method for computing the terminal reliability in a communication network. Circuit Theory, 1973, 20(3): 203-211.
8. Albert R, Jeong H, Barabási A L. Error and attack tolerance of complex networks. Nature,2000, 406: 378-382.
9. Dunne J A, Williams R J, Martinez N D. Network structure and biodiversity loss in food webs: robustness increases with connection. Ecology Letters, 2002, 5: 558-567.
10. Jeong H, Mason S, Barabsi A-L, et al. Lethality and centrality in protein networks. Nature, 2001, 411: 41-42.
11. Qi Xiao-gang, Zhang Cheng-cai, Liu Li-fang. Study on node importance and network invulnerability analysis of wireless sensor network. Systems Engineering-Theory &Practice, 2011, 31(2): 34-37.
12. Lin Li-wei, Xu Li, Ye Xiu-cai. A Novel Method and Its Simulation to Evaluate the Invulnerability of Wireless Sensor Networks. Computer Systems & Application, 2010, 19(4):32-36.
13. Helmy A. Small worlds in wireless networks. IEEE Communications Letters, 2003, 7(10): 490-492.
14. Helmy A. Analysis of wired short cuts in wireless sensor networks. The IEEE/ACS Int Conf on Pervasive Services. Washington DC, 2004: 167-176.
15. Liu Ming. Approach to construction of wireless sensor networks with small world effect. Electronic Measurement Technology, 2007, 30(4): 37-40.
16. Cavalcanti D. Exploiting the small-world effect to increase connectivity in wireless ad hoc networks. Int Conf on Telecommunications. Fortaleza, 2004: 388-393.
17. Meng Anbo, Chen peng. Construction to heterogeneous sensor networks based on effect of small world. Computer & Digital Engineering, 2008, 36(9): 98-100.
18. Wu Jun, Tan Yue-jin. Study on measure of complex network invulnerability. Journal of Systems Engineering, 2005, 20(2):128-131.
19. M. Newman. A measure of betweenness centrality based on random walks. Social Networks, 2005, 27(1):39-54.
20. Wasserman S, Faust K. Social Network Analysis: Methods and Applications. New York: Cambridge University Press, 1994.
21. Freeman L C. Centrality in social networks: conceptual clarification. Social Networks, 1979, (1): 215-239.