Cluster-based service discovery for heterogeneous wireless sensor networks

International Journal of Parallel, Emergent and Distributed Systems

Volumn 23, Issue 4, 2008, Pages 325-346

  Marin Perianu, R S ^a   Scholten, J ^a   Havinga, P J M ^a   Hartel, P H ^a  

^a UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

Clustering; Energy efficiency; Heterogeneous wireless sensor networks; Mobility; Service discovery

Indexed keywords

ADAPTIVE ALGORITHMS; BOOLEAN FUNCTIONS; CLUSTERING ALGORITHMS; CONSERVATION; DETECTORS; ENERGY EFFICIENCY; FLOW OF SOLIDS; HYBRID SENSORS; NETWORK PROTOCOLS; SENSOR NETWORKS; SENSORS; STRUCTURAL PROPERTIES; TELECOMMUNICATION EQUIPMENT; TELECOMMUNICATION SYSTEMS; WIRELESS NETWORKS; WIRELESS TELECOMMUNICATION SYSTEMS;

(PL) PROPERTIES; ADAPTIVE CLUSTERING; CHAIN REACTIONS; CLUSTER HEAD NODES; CLUSTER HEADS (CH); CLUSTER-BASED; CLUSTERING STRUCTURE; COMMUNICATION COSTS; DISTRIBUTED SERVICES; DYNAMIC ENVIRONMENTS; ENERGY EFFICIENT; HETEROGENEOUS WIRELESS; NEIGHBOURHOOD; SENSOR NODE (SN); SERVICE DISCOVERY; SERVICE DISCOVERY PROTOCOLS; TEST-BEDS;

WIRELESS SENSOR NETWORKS;

EID: 46349090471     PISSN: 17445760     EISSN: 17445779     Source Type: Journal    
DOI: 10.1080/17445760801930948     Document Type: Conference Paper

References (40)

1. I. Akyildiz and I. Kasimoglu, Wireless sensor and actor networks: Research challenges, Ad Hoc Netw. 2(4) (2004), pp. 351-367, October.
2. I.F. Akyildiz et al., A survey on sensor networks, IEEE Commun. Mag. 40(8) (2002), pp. 102-114.
3. Ambient systems. Available at http://www.ambient-systems.net.
4. A.D. Amis et al., Max-min d-cluster formation in wireless ad hoc networks, in INFOCOM (1), IEEE Computer Society Press, Los Alamitos, CA, 2000, pp. 32-41.
5. S. Bandyopadhyay and E.J. Coyle, An energy efficient hierarchical clustering algorithm for wireless sensor networks, in INFOCOM, IEEE Computer Society Press, Los Alamitos, CA, 2003, pp. 1713-1723.
6. S. Banerjee and S. Khuller, A clustering scheme for hierarchical control in multi-hop wireless networks, in INFOCOM, IEEE Computer Society Press, Los Alamitos, CA, 2001, pp. 1028-1037.
7. S. Basagni, Distributed clustering for ad hoc networks, in International Symposium on Parallel Architectures, Algorithms and Networks (ISPAN), IEEE Computer Society, Los Alamitos, CA, 1999, pp. 310-315.
8. D. Bertsekas and R. Gallager, Data Networks, 2nd ed., Prentice-Hall, Inc., Upper Saddle River, NJ, 1992.
9. C. Bettstetter, Mobility modeling, connectivity, and adaptive clustering in ad hoc networks, Ph.D. thesis, Technische Universiẗt M̈nchen, Germany, 2003.
10. N. Bulusu, J. Heidemann, and D. Estrin, Gps-less low cost outdoor localization for very small devices, IEEE Pers. Commun. Mag. 7(5) (2000), pp. 28-34, October.
11. T. Camp, J. Boleng, and V. Davies, A survey of mobility models for ad hoc network research, Wireless Commun. Mobile Comput. (WCMC): Spec. Issue Mobile Ad Hoc Networking: Res. Trends Appl. 2(5) (2002), pp. 483-502.
12. A. Cerpa et al., Habitat monitoring: Application driver for wireless communications technology, SIGCOMM Comput. Commun. Rev. 31(2 supplement) (2001), pp. 20-41.
13. D. Chakraborty et al., Toward distributed service discovery in pervasive computing environments, IEEE Trans. Mobile Comput. 5(2) (2006), pp. 97-112, February.
14. M. Chatterjee, S.K. Das, and D. Turgut, WCA: A weighted clustering algorithm for mobile ad hoc networks, J. Cluster Comput. (Spec. Issue Mobile Ad hoc Netw.) 5(2) (2002), pp. 193-204, April.
15. F.C. Delicato et al., A service approach for architecting application independent wireless sensor networks, Cluster Comput. 8(2-3) (2005), pp. 211-221.
16. C. Frank and H. Karl, Consistency challenges of service discovery in mobile ad hoc networks, in International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM). ACM Press, New York, NY, 2004, pp. 105-114.
17. L. Girod et al., Locating tiny sensors in time and space: A case study, in International Conference on Computer Design (ICCD), IEEE Computer Society, Los Alamitos, CA, 2002, pp. 214-219.
18. S. Helal et al., Konark - a service discovery and delivery protocol for ad hoc networks, Wireless Commun. Networking 3 (2003), pp. 2107-2113.
19. A. Helmy, Resource management in wireless networking, chapter Efficient Resource Discovery in Wireless AdHoc Networks: Contacts Do Help, Vol. 16, Springer, Berlin, NY, 2005.
20. T.D. Hodes et al., An architecture for secure wide-area service discovery, Wireless Netw. 8(2/3) (2002), pp. 213-230.
21. M. Horton and J. Suh, A vision for wireless sensor networks, in IEEE MTT-S International Microwave Symposium Digest, IEEE Computer Society, Los Alamitos, CA, 2005, pp. 361-364.
22. D.B. Johnson, and D.A. Maltz, Dynamic source routing in ad hoc wireless networks, in Mobile Computing, Imielinski and Korth, eds., Vol. 353, Kluwer Academic Publishers, Norwall, MA, 1996, pp. 153-181.
23. D. Johnson, D. Maltz, and J. Broch, Ad Hoc Networking, Chapter 5, Addison-Wesley, Boston, MA, 2001, pp. 139-172.
24. M. Klein, B. Konig-Ries, and P. Obreiter, Lanes - a lightweight overlay for service discovery in mobile ad hoc networks, Tech. Rep. 2003-6, University of Karlsruhe, 2003.
25. U.C. Kozat and L. Tassiulas, Service discovery in mobile ad hoc networks: An overall perspective on architectural choices and network layer support issues, Ad Hoc Netw. 2(1) (2003), pp. 23-44.
26. V. Lenders, M. May, and B. Plattner, Service discovery in mobile ad hoc networks: A field theoretic approach, Pervasive Mobile Comput. 1 (2005), pp. 343-370.
27. C.R. Lin and M. Gerla, Adaptive clustering for mobile wireless networks, IEEE J. Selected Areas Commun. 15(7) (1997), pp. 1265-1275.
28. R.S. Marin-Perianu et al., Energy-efficient cluster-based service discovery in wireless sensor networks, Tech. Rep.TR-CTIT-06-43, Enschede, June, 2006.
29. M. Marin-Perianu et al., Decentralized enterprise systems: A multi-platform wireless sensor networks approach, Tech. Rep. TR-CTIT-07-31, Enschede, April, 2007.
30. A. McDonald and T. Znati, A mobility-based framework for adaptive clustering in wireless ad hoc networks, IEEE J. Selected Areas Commun. (JSAC) 17 (1999), August.
31. V.P. Mhatre et al., A minimum cost heterogeneous sensor network with a lifetime constraint1, IEEE Trans. Mobile Comput. 4(1) (2005), pp. 4-15.
32. F.G. Nocetti, J.S. Gonzalez, and I. Stojmenovic, Connectivity based k-hop clustering in wireless networks, Telecommun. Syst. 22(1-4) (2003), pp. 205-220.
33. C. Perkins and P. Bhagwat, Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers, in SIGCOMM, ACM press, New York, NY, 1994, pp. 234-244.
34. C. Perkins and E. Royer, Ad hoc on-demand distance vector routing, in Workshop on Mobile Computing Systems and Applications (WMCSA). IEEE Computer Society, Los Alamitos, CA, 1999, pp. 90-100.
35. R. Robinson and J. Indulska, Superstring: A scalable service discovery protocol for the wide area pervasive environment, in International Conference on Networks (ICON). IEEE Computer Society, Los Alamitos, CA, 2003, pp. 699-704.
36. D. Stoyan, W.S. Kendall, and J. Mecke, Stochastic Geometry and its Applications, John Wiley and Sons, New York, NY, 1995.
37. S. Tilak et al., Dynamic resource discovery for sensor networks, in IFIP International Symposium on Network-Centric Ubiquitous Systems, Vol. 3823, Lecture Notes in Computer Science Springer Verlag, Berlin, NY, 2005, pp. 785-796.
38. L. Van Hoesel, Schedule-based medium access control protocols for wireless sensor networks, Ph.D. thesis, University of Twente, 2007.
39. A. Varga, The OMNeT++ discrete event simulation system, in European Simulation Multiconference (ESM), Prague, Czech Republic, June, 2001.
40. A. Varshavsky, B. Reid, and E. de Lara, A cross-layer approach to service discovery and selection in manets, in Mobile Adhoc and Sensor Systems Conference (MASS), IEEE Computer Society, Los Alamitos, CA, November, 2005.