24-01-2012, 01:29 PM
Adaptive Data Fusion for Energy Efficient Routing in Wireless Sensor Networksy
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INTRODUCTION
Wireless sensor networks have attracted a plethora of research efforts due to their vast potential
applications [3][4]. In particular, extensive research work has been devoted to providing energy
efficient routing algorithms for data gathering [5–19]. While some of these approaches assume
statistically independent information and have developed shortest path tree based routing strategies
[5, 6], others have considered the more realistic case of correlated data gathering [7–18].
Our Contribution
In this paper, we propose Adaptive Fusion Steiner Tree (AFST), a routing scheme that not
only optimizes over both transmission and fusion costs, but also adaptively adjusts its fusion
decisions for sensor nodes. By evaluating whether fusion is beneficial to the network based on
fusion/transmission costs and network/data structures, AFST dynamically assigns fusion decisions
to routing nodes during the route construction process.
Network Model
We model a sensor network as a graph G = (V;E) where V denotes the node set and E the
edge set representing the communication links between node-pairs. We assume a set S ½ V of n
nodes, are data sources of interests and the sensed data needs to be sent to a special sink node
t 2 V periodically. We refer the period of data gathering as a round in this paper.
