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. 1. Introduction Fault tolerance is particularly important in sensor networks especially when such devices are attached to the patients with serious medical conditions and monitoring of vital signs is crucial for their survival. The existing algorithms [1–7] for disseminating datasets of interests have widely ignored fault tolerance while communicating datasets to the sink node. In-network processing of datasets received from the sensor nodes attached to the patients with cardiovascular problems, Parkinson disease, epilepsy, high blood pressure, carbon-dioxide concentration, oxygen saturation in the blood, and ECG needs to be efficiently monitored for the future forecasting. Any sudden changes will be communicated to the relevant GP soon after the threshold values trigger alarms. The presence of fault at a particular node can easily compromise the quality of information communicated through a malfunctioning node with relevant information which could be life threatening. A fault-tolerant solution for achieving the desired functionality in the presence of fault is important. The issue of fault tolerance has widely been ignored in [3–5], which is crucial for the energy-efficient data
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