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An enhanced energy optimization routing protocol using double cluster heads for wireless sensor network
- Source :
- Cluster Computing. 22:11057-11068
- Publication Year :
- 2017
- Publisher :
- Springer Science and Business Media LLC, 2017.
-
Abstract
- A challenging research topic in wireless sensor network is prolonging the network lifetime by optimizing the network energy expenditure. The paper explores an enhanced energy optimization routing protocol which uses double cluster heads in a clustering wireless sensor network. The double cluster heads which are determined by energy welfare function are referred to as main cluster head and assistant one, respectively. To balance nodes energy, a formula for the energy overhead is presented to make the sensor node join a temporary cluster with low energy consuming during cluster set-up stage. Then, during the routing selection, relay nodes communicate sensory information to the sink by using combining single-hop and multi-hop technology. The selection of relay nodes depends on the weight values involving information of residual energy, the number of nodes in the cluster, selected times as relay nodes, and a distance between two nodes. The improved protocol is evaluated via simulation experiments and compared with some existing protocols. The simulation results demonstrate that the proposed protocol outperforms the relevant protocols in energy utilization efficiency. Especially, the network lifetime is prolonged due to decreasing energy consuming of the cluster head.
- Subjects :
- Routing protocol
Computer Networks and Communications
Computer science
business.industry
ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS
020206 networking & telecommunications
02 engineering and technology
Energy minimization
law.invention
Key distribution in wireless sensor networks
Energy expenditure
Relay
law
Sensor node
Computer Science::Networking and Internet Architecture
0202 electrical engineering, electronic engineering, information engineering
Mobile wireless sensor network
020201 artificial intelligence & image processing
Cluster analysis
business
Wireless sensor network
Software
Computer network
Subjects
Details
- ISSN :
- 15737543 and 13867857
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- Cluster Computing
- Accession number :
- edsair.doi...........8b17c271edc55bae64459515b5b07a0a
- Full Text :
- https://doi.org/10.1007/s10586-017-1297-2