Overlapping layers for prolonging network life time in multi-hop wireless sensor networks

Wireless sensor networks have been proposed as a practical solution for a wide range of applications due to their benefits of low cost, rapid deployment, self-organization capability, and cooperative data-processing. Many applications, such as military surveillance and habitat monitoring, require the deployment of large-scale sensor networks. A highly scalable and fault-tolerant network architecture, the Progressive Multi-hop Rotational Clustered (PMRC) structure has been proposed, which is suitable for constructing large-scale wireless sensor networks. However, similar to other multi-hop structures, the PMRC structure also suffers from the bottleneck problem; This thesis is focused on solving the bottleneck problem existing in the PMRC structure. First, the Overlapping Neighbor Layers (ONL) scheme is proposed to balance the energy consumption among cluster heads at different layers. Further, the Minimum Overlapping Neighbor Layers (MONL) scheme is proposed wherein the overlapped area between neighbor layers is gradually increased through network life time to achieve load balance and energy efficiency in the whole network area. Simulation results show that the MONL scheme significantly prolongs network life time and demonstrates steady performance on sensor networks with uniformly distributed sensor nodes. To further prolong the network life time, traffic-similar sensor nodes distribution combined with the MONL scheme is studied; The proposed overlapped layers schemes are proven to be effective in solving the bottleneck problem and prolonging network life time for PMRC-based networks. They can also be applied for other multi-hop cluster-based sensor networks. The traffic-similar nodes distribution concept can be applied in optimizing sensor network deployment to achieve desired network life time

Robust Communications for Sensor Networks in Hostile Environments

Clustering sensor nodes increases the scalability and energy efficiency of communications among them. In hostile environments, unexpected failures or attacks on cluster heads (through which communication takes place) may partition the network or degrade application performance. In this work, we propose a new approach, REED (Robust Energy Efficient Distributed clustering), for clustering sensors deployed in hostile environments. Our primary objective is to construct a k-fault- tolerant (i.e., k-connected) network, where k is a constant determined by the application. Fault tolerance can be achieved by selecting k independent sets of cluster heads (i.e., cluster head overlays) on top of the physical network, so that each node can quickly switch to other cluster heads in case of failures or attacks on its current cluster head. The independent cluster head overlays also provide multiple vertex-disjoint routing paths for load balancing and security. Network lifetime is prolonged by selecting cluster heads with high residual energy and low communication cost, and periodically re-clustering the network in order to distribute energy consumption among sensor nodes. We prove that REED can asymptotically achieve k-fault tolerance if certain constraints on node density are satisfied. We also investigate via simulations the clustering properties of REED, and show that building multiple cluster head overlays does not consume significant energy

Robust communications for sensor networks in hostile environments

Abstract — Clustering sensor nodes increases the scalability and energy efficiency of communications among them. In hostile environments, unexpected failures or attacks on cluster heads (through which communication takes place) may partition the network or degrade application performance. In this work, we propose a new approach, REED (Robust Energy Efficient Distributed clustering), for clustering sensors deployed in hostile environments. Our primary objective is to construct a k-faulttolerant (i.e., k-connected) network, where k is a constant determined by the application. Fault tolerance can be achieved by selecting k independent sets of cluster heads (i.e., cluster head overlays) on top of the physical network, so that each node can quickly switch to other cluster heads in case of failures or attacks on its current cluster head. The independent cluster head overlays also provide multiple vertex-disjoint routing paths for load balancing and security. Network lifetime is prolonged by selecting cluster heads with high residual energy and low communication cost, and periodically re-clustering the network in order to distribute energy consumption among sensor nodes. We prove that REED can asymptotically achieve k-fault tolerance if certain constraints on node density are satisfied. We also investigate via simulations the clustering properties of REED, and show that building multiple cluster head overlays does not consume significant energy. I