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Nature-Inspired Algorithms for Reliable, Low-Latency Communication in Wireless Sensor Networks for Pervasive Healthcare Applications

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Nature Inspired Computing for Wireless Sensor Networks

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

Abstract

With the growing popularity of IoT paradigms, the number of connected medical equipment is on the rise and includes a variety of products ranging from simple devices such as thermometers to more complex machinery like smart infusion pumps, patient monitoring systems, and MRI scanners, to name a few. The advantages of such interconnected architectures are manifold, enabling better access to patients’ electronic health records, and improving the quality of care through real-time monitoring systems. However, a healthcare facility packed with medical appliances could face issues such as dropped network connections, power loss, and failure in the transmission of critical alarms. In pervasive healthcare applications, such incidents could result in disastrous consequences and are non-negotiable. Wireless sensor networks for healthcare have emerged in the recent years due to advances in sensor technology and the pressing need for the design of reliable, low-power networks. The most important key in WSN design is the task of finding the optimal path for transmission of sensor data to achieve energy efficiency and reduce costs, while catering to the needs of the application. Nature is arguably the best coach and extracting eccentric elements of biological network design proves useful in solving complex problems. Computations using nature-inspired algorithms have emerged as a new epoch in computing, serving a varied range of applications. This paper explores the need of optimization in WSN design for pervasive healthcare systems, while studying the existing class of bio-inspired algorithms and routing protocols for reliable communication in such architectures. Further, a detailed study is conducted to identify the challenges in routing sensitive data over a cluster of light, portable sensing motes, and application-specific nature-inspired models are suggested based on the observations.

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Authors and Affiliations

  1. Computer Science and Engineering, Institute of Engineering and Management, Salt Lake City, 700091, India

    Prateeti Mukherjee

  2. Department of Nanoscience and Nanotechnology, University of Siegen, Siegen, Germany

    Ankur Das

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  1. Prateeti Mukherjee
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  2. Ankur Das
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Correspondence to Prateeti Mukherjee .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University, Kolkata, West Bengal, India

    Debashis De

  2. Department of Computer Science and Engineering, Institute of Engineering and Management, Kolkata, West Bengal, India

    Amartya Mukherjee

  3. School of Computer Science and Engineering, National Institute of Science and Technology, Berhampur, Odisha, India

    Santosh Kumar Das

  4. Department of Information Technology, Techno India College of Technology, Kolkata, India

    Nilanjan Dey

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Mukherjee, P., Das, A. (2020). Nature-Inspired Algorithms for Reliable, Low-Latency Communication in Wireless Sensor Networks for Pervasive Healthcare Applications. In: De, D., Mukherjee, A., Kumar Das, S., Dey, N. (eds) Nature Inspired Computing for Wireless Sensor Networks. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-2125-6_14

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  • DOI: https://doi.org/10.1007/978-981-15-2125-6_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2124-9

  • Online ISBN: 978-981-15-2125-6

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