Introduction to algorithms
Next century challenges: mobile networking for “Smart Dust”
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Wireless integrated network sensors
Communications of the ACM
Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Reverse path forwarding of broadcast packets
Communications of the ACM
Proceedings of the 8th annual international conference on Mobile computing and networking
On deriving the upper bound of α-lifetime for large sensor networks
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks
IEEE Transactions on Mobile Computing
A Minimum Cost Heterogeneous Sensor Network with a Lifetime Constraint
IEEE Transactions on Mobile Computing
DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks
IEEE Transactions on Wireless Communications
Hi-index | 0.24 |
In wireless sensor networks (WSNs), when a stimulus or event is detected within a particular region, data reports from the neighboring sensor nodes (sources) are sent to the sink (destination). Data from these sources are usually aggregated along their way to the sink. The data aggregation via in-network processing reduce communication cost and improves energy efficiency. In this paper, we propose two different tree structures to facilitate data aggregation. We first propose E-Span, which is an energy-aware spanning tree algorithm. In E-span, the source node which has the highest residual energy is chosen as the root. Other source nodes choose their corresponding parent node among their neighbors based on the information of the residual energy and distance to the root. We also propose the Lifetime-Preserving Tree (LPT). In LPT, nodes which have higher residual energy are chosen as the aggregating parents. LPT also includes a self-healing feature by which the tree will be re-constructed again whenever a node is no longer functional or a broken link is detected. By choosing Directed Diffusion [C. Intanagonwiwat, R. Govindan, D. Estrin, Directed diffusion: a scalable and robust communication paradigm for sensor networks, in: Proc. of ACM MobiCom'00, Boston, MA, Aug. 2000, pp. 56-67.] as the underlying routing platform, simulation results show that in a WSN with 250 sensor nodes, the lifetime of sources can be extended significantly when data are aggregated by using either E-Span or LPT algorithms.