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In wireless sensor networks with dynamic clustering, the cluster heads are usually not selected on the basis of their locations. This causes irregular distribution of cluster heads and highly variable number of nodes in the clusters. Also, some of the clusters are spread over large areas within the network, causing limited spatial correlation between associated sensor nodes. These irregularities in cluster placements and dimensions negatively impact the efficiency of a wireless sensor network. For example, for a cooperative data aggregation, it necessitates variable or large sized packets while the aggregations, based on spatial correlation of sensor nodes, cannot be exploited easily. In this paper, we have developed a Distributed Uniform Clustering Algorithm (DUCA) for cluster based WSN. In DUCA, cluster formation mechanism is based on a virtual-grid system and sensing ranges of nodes that provide even distribution of clusters, homogenized cluster sizes, and reduced energy consumption. Simulation results show that DUCA improves the distribution of cluster heads by more than 2 times and reduces the energy consumption within a range of 15% to 50% as compared to the existing protocols.

The study has been undertaken to integrate two different aspects of the triple helix model: universities and the industry. Special attention has been paid to the prevailing difference between the two, hampering their working as a coherent unit. Integrating the existing knowledge in the study, we proposed the Academia-Industry Collaboration Plan (AICP) design model. The model comprises processes, methods or approaches, and tools. Processes serve as a road map to third parties for establishing collaboration between academia and the industry. It has all the essential process models and a series of steps that help minimize the organizational complexity of the collaboration process between academia and the industry. Methods or approaches serve the purpose of implementing those processes effectively. Finally, appropriate tools are selected to integrate possible collaboration improvements that lead to innovation.

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