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Wireless sensor networks (WSNs) are widely used in battle fields, logistic applications, healthcare, habitat monitoring, environmental monitoring, home security, and variety of other areas. The existing routing algorithms focus on the delivery of data packets to the sink using the shortest path; however, calculating the shortest path is not a cost-effective solution while disseminating datasets of interest to the nearest sink node. The approach presented in this paper extends the existing PBR (priority-based routing) protocol by providing a new fault-tolerant multipath priority-based routing (FT-MPPBR) scheme, which not only balances the energy consumption while selecting multiple paths but also balances the workload of the node closest to the sink. The nodes closer to the sink dissipate more energy and can become the source of a communication bottleneck. Simulation results for the proposed routing scheme are encouraging and clearly show that the FT-MPPBR has outperformed the existing PBR schemes in terms of prolonging the network lifetime and reliability. In healthcare sensor networks, timely dissemination of datasets is critical for the well-being of a patient. This research further extends the PBR architecture for supporting computational intensive analysis by transferring datasets of interest to the sensor grid node for improved communication and better throughput.

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Continuous Queries (CQ) help users to retrieve results as soon as they become available. The CQ keeps track of two important events. If there is any change in the source information, it immediately notifies the user about that particular change. Secondly, it also keeps track of the timer-based events, in case information is required after a fixed period of time. Existing techniques such as OpenCQ[1] and NiagaraCQ[2] are inadequate to optimise Continuous Queries. These techniques focus on defining the semantics for execution of CQ and much less effort was spent to define the tradeoffs required for evaluating the specific condition and generating a cost-effective query evaluation plan (QEP). The optimising scheme used in [1],[2] for information retrieval is not appropriate for an environment like the Internet. This paper also provides a new architecture and group optimisation strategy for the efficient retrieval of CQ on the web.