It has been well established that the lifetime of a Wireless Sensor Network (WSN) depends on the energy of the sensor nodes which is limited by the battery capacity of the nodes. This challenge has led to research efforts towards developing a more efficient energy based routing algorithms and architectures. One of such popular algorithm is the Low-Energy Adaptive Clustering Hierarchy (LEACH). The LEACH approach adopts randomized rotation of local base stations (or cluster-heads (CH)) to evenly distribute energy load amongst the sensors in the network. A variant of LEACH known as Vice-LEACH (V-LEACH) introduces the concept of a vice-CH that takes over the role of the main CH in the event of CH death. Random selection of cluster- head node in both LEACH and V-LEACH ignore node's residual energy and the optimal number and distribution of cluster head is not ensured in all rounds. This work presents an enhanced cluster-based routing algorithm which took into consideration the residual energy of nodes in the network while maintaining the optimal number of CHs throughout the network lifetime. A sensor network was developed on OPNET Modeler software tool and simulation tests were performed to evaluate the performance of the enhanced routing algorithm on the network. Simulation results showed that this enhanced routing algorithm distributed network energy consumption across the network nodes hence significantly improving the lifetime of the sensor network. 

Proxy Mobile IPv6 (PMIPv6) is a promising IP mobility protocols that is being deployed in emerging wireless technologies. This however has a non-optimal packet route as a result of the triangular routing problem. This creates a bottle neck at the Local Mobility Anchor (LMA) thereby increasing packet delays. This paper presents the implementation of a locator-based route switching scheme on OPNET Modeler. The Mobility Access Gateway (MAG) and the LMA were enhanced by making them intelligent. This enables them to be able to check the position of the Corresponding Node (CN) with respect to the Mobile Node (MN) and also determine the available bandwidth on each link. From the checks made, a three-stage decision process is used to switch routing to the most optimal route that guarantees the best QoS. Node Models were developed for the MAG and LMA, network models were deployed and simulation tests were carried out. The results show that the developed scheme switched packets to a more optimal route according to the designed algorithm. The impact of this switching on differences between transmitted throughput at MN and the received throughput at CN was also evaluated. The receiver activity result shows a reduction in the bottleneck at the LMA-MAG link. The end-to-end delay results show over 50 milliseconds drop in packet delay as a result of the switching to a more optimal route. This shows that the packet delays result from the congestion at the LMA-MAG interface due to suboptimal routing.