Name
Abstract | ||
|---|---|---|
The routing energy efficiency of a wireless sensor network is a crucial issue for the network lifetime. In this article, we
propose MICRO (MInimum Cost Routing with Optimized data fusion), an energy-efficient routing protocol for event-driven dense
wireless sensor networks. The proposed routing protocol is an improvement over the formerly proposed LEACH and PEGASIS protocol,
which is designed to be implemented mainly with node computations rather than mainly with node communications. Moreover, in
the routing computation the proposed scheme exploits a new cost function for energy balancing among sensor nodes, and uses
an iterative scheme with optimized data fusions to compute the minimum-cost route for each event-detecting sensor node. Compared
to the PEGASIS routing protocol, MICRO substantially improves the energy-efficiency of each route, by optimizing the trade-off
between minimization of the total energy consumption of each route and the balancing of the energy state of each sensor node.
It is demonstrated that the proposed protocol is able to outperform the LEACH and the PEGASIS protocols with respect to network
lifetime by 100–300% and 10–100%, respectively. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s10776-009-0101-5 | IJWIN |
Keywords | Field | DocType |
event-driven dense wireless sensor networks � energy efficient routing algorithmenergy balanced routingnetwork lifetime optimization,routing protocol,wireless sensor network,energy efficient,data fusion,energy balance,cost function | Link-state routing protocol,Dynamic Source Routing,Computer science,Enhanced Interior Gateway Routing Protocol,Path vector protocol,Computer network,Wireless Routing Protocol,Real-time computing,Routing Information Protocol,Routing protocol,Distributed computing,Zone Routing Protocol | Journal |
Volume | Issue | ISSN |
16 | 3 | 15728129 |
Citations | PageRank | References |
1 | 0.35 | 18 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liuguo Yin | 1 | 77 | 18.20 |
| Changmian Wang | 2 | 8 | 2.36 |
| Geir E. Øien | 3 | 381 | 43.38 |