Construction Of Decentralized Lifetime Maximizing Tree for Data Aggregation in Wireless Sensor Networks
To meet the demands of wireless sensor networks
(WSNs) where data are usually aggregated at a single source prior to
transmitting to any distant user, there is a need to establish a tree
structure inside any given event region. In this paper , a novel
technique to create one such tree is proposed .This tree preserves the
energy and maximizes the lifetime of event sources while they are
constantly transmitting for data aggregation. The term Decentralized
Lifetime Maximizing Tree (DLMT) is used to denote this tree.
DLMT features in nodes with higher energy tend to be chosen as data
aggregating parents so that the time to detect the first broken tree link
can be extended and less energy is involved in tree maintenance. By
constructing the tree in such a way, the protocol is able to reduce the
frequency of tree reconstruction, minimize the amount of data loss
,minimize the delay during data collection and preserves the energy.
[1] I. Nikolaidis, J. J. Harms, and S. Zhou, "On sensor data aggregation
with Redundancy removal," in Proc. of 22nd Biennial Symposium on
Communications, Ontario, CA, 2004, pp.119- 127.
[2] D. Petrovic, R. C. Shah, K. Ramchandran, and J. Rabaey, "Data
funneling: Routing with aggregation and compression for wireless sensor
networks," in Proc. of IEEE International Workshop on Sensor Network
Protocols and Applications (SNPA-03), Anchorage, AK, 2003, pp. 156-
162.
[3] Q. Fang, F. Zhao, and L. Guibas, "Lightweight sensing and
communication protocols for target enumeration and aggregation," in
Proc. of MobiHoc-03, Annapolis, MD, 2003, pp.165-176.
[4] A. Boulis, S. Ganeriwal, and M. B. Srivastava, "Aggregation in sensor
networks: An energy-accuracy trade-off," in Proc. of IEEE International
Workshop on Sensor Network Protocols and Applications (SNPA-03),
Anchorage, AK, 2003, pp. 128-138.
[5] E. J. Duarte-Melo, M. Liu, and A. Misra, "A modeling framework for
computing lifetime and information capacity in wireless sensor
networks," in Proc. of 2nd WiOpt: Modeling and Optimization in Mobile,
Ad Hoc and Wireless Networks, Cambridge, UK,2004.
[6] K. Dasgupta, K. Kalpakis, and P. Namjoshi, "An efficient clusteringbased
heuristic for data gathering and aggregation in sensor networks," in
Proc. of IEEE Wireless Communications and Networking Conference
(WCNC-03), New Orleans, LA, 2003, pp.1948- 2003.
[7] A. Sankar and Z. Liu, "Maximum lifetime routing in wireless ad-hoc
networks," in Proc. of IEEE Infocom-04, Hong Kong, 2004, 360-367.
[8] E. J. Duarte-Melo and M. Liu, "Analysis of energy consumption and
lifetime of heterogeneous wireless sensor networks," in Proc. of IEEE
Global Telecommunications Conference (GLOBECOM-02), vol. 1,
Germany, 2003, pp. 21-25.
[9] V. Mhatre, C. Rosenberg, D. Kofman, R. Mazumdar, and N. Shroff,
"A minimum cost heterogeneous sensor network with a lifetime
constraint," accepted for publication in IEEE Trans. Mobile Computing,
Jan. 2004.
[10] H. Zhang and J. Hou, "On deriving the upper bound of ifetime f or
large sensor networks," in Proc. of ACM MobiHoc-04, Roppongi Hills,
Tokyo, Japan, 2004, pp. 121-132.
[11] D. M. Blough and P. Santi, "Investigating upper bounds on network
lifetime extension for cell-based energy conservation techniques in
stationary ad hoc networks," in Proc. Of ACM MobiCom-02, Atlanta, GA,
2006, pp. 183-192.
[12] R. Perlman, Interconnections: Bridges, routers, switches, and
internetworking protocol, 2nd ed., Addison-Wesley Professional
Computing Series, Reading, MA, 2005
[1] I. Nikolaidis, J. J. Harms, and S. Zhou, "On sensor data aggregation
with Redundancy removal," in Proc. of 22nd Biennial Symposium on
Communications, Ontario, CA, 2004, pp.119- 127.
[2] D. Petrovic, R. C. Shah, K. Ramchandran, and J. Rabaey, "Data
funneling: Routing with aggregation and compression for wireless sensor
networks," in Proc. of IEEE International Workshop on Sensor Network
Protocols and Applications (SNPA-03), Anchorage, AK, 2003, pp. 156-
162.
[3] Q. Fang, F. Zhao, and L. Guibas, "Lightweight sensing and
communication protocols for target enumeration and aggregation," in
Proc. of MobiHoc-03, Annapolis, MD, 2003, pp.165-176.
[4] A. Boulis, S. Ganeriwal, and M. B. Srivastava, "Aggregation in sensor
networks: An energy-accuracy trade-off," in Proc. of IEEE International
Workshop on Sensor Network Protocols and Applications (SNPA-03),
Anchorage, AK, 2003, pp. 128-138.
[5] E. J. Duarte-Melo, M. Liu, and A. Misra, "A modeling framework for
computing lifetime and information capacity in wireless sensor
networks," in Proc. of 2nd WiOpt: Modeling and Optimization in Mobile,
Ad Hoc and Wireless Networks, Cambridge, UK,2004.
[6] K. Dasgupta, K. Kalpakis, and P. Namjoshi, "An efficient clusteringbased
heuristic for data gathering and aggregation in sensor networks," in
Proc. of IEEE Wireless Communications and Networking Conference
(WCNC-03), New Orleans, LA, 2003, pp.1948- 2003.
[7] A. Sankar and Z. Liu, "Maximum lifetime routing in wireless ad-hoc
networks," in Proc. of IEEE Infocom-04, Hong Kong, 2004, 360-367.
[8] E. J. Duarte-Melo and M. Liu, "Analysis of energy consumption and
lifetime of heterogeneous wireless sensor networks," in Proc. of IEEE
Global Telecommunications Conference (GLOBECOM-02), vol. 1,
Germany, 2003, pp. 21-25.
[9] V. Mhatre, C. Rosenberg, D. Kofman, R. Mazumdar, and N. Shroff,
"A minimum cost heterogeneous sensor network with a lifetime
constraint," accepted for publication in IEEE Trans. Mobile Computing,
Jan. 2004.
[10] H. Zhang and J. Hou, "On deriving the upper bound of ifetime f or
large sensor networks," in Proc. of ACM MobiHoc-04, Roppongi Hills,
Tokyo, Japan, 2004, pp. 121-132.
[11] D. M. Blough and P. Santi, "Investigating upper bounds on network
lifetime extension for cell-based energy conservation techniques in
stationary ad hoc networks," in Proc. Of ACM MobiCom-02, Atlanta, GA,
2006, pp. 183-192.
[12] R. Perlman, Interconnections: Bridges, routers, switches, and
internetworking protocol, 2nd ed., Addison-Wesley Professional
Computing Series, Reading, MA, 2005
@article{"International Journal of Electrical, Electronic and Communication Sciences:58508", author = "Deepali Virmani and Satbir Jain", title = "Construction Of Decentralized Lifetime Maximizing Tree for Data Aggregation in Wireless Sensor Networks", abstract = "To meet the demands of wireless sensor networks
(WSNs) where data are usually aggregated at a single source prior to
transmitting to any distant user, there is a need to establish a tree
structure inside any given event region. In this paper , a novel
technique to create one such tree is proposed .This tree preserves the
energy and maximizes the lifetime of event sources while they are
constantly transmitting for data aggregation. The term Decentralized
Lifetime Maximizing Tree (DLMT) is used to denote this tree.
DLMT features in nodes with higher energy tend to be chosen as data
aggregating parents so that the time to detect the first broken tree link
can be extended and less energy is involved in tree maintenance. By
constructing the tree in such a way, the protocol is able to reduce the
frequency of tree reconstruction, minimize the amount of data loss
,minimize the delay during data collection and preserves the energy.", keywords = "branch energy, decentralized, energy level , lifetime,tree energy, wireless sensor networks.", volume = "3", number = "4", pages = "846-10", }