Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

A wireless body area network(WBAN)consists of tiny healthmonitoring sensors implanted in or placed on the human body.These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things(IoT)systems.WBANs are connected to medical servers that monitor patients’health.This type of network can protect critical patients’lives due to the ability to monitor patients’health continuously and remotely.The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely.However,during patient movement,the WBAN patient nodes may become out of range of a remote base station.Hence,to handle this problem,an efficient method for inter-WBAN communication is needed.In this study,a method using a cluster-based routing technique is proposed.In the proposed method,a cluster head(CH)acts as a gateway between the cluster members and the external network,which helps to reduce the network’s overhead.In clustering,the cluster’s lifetime is a vital parameter for network efficiency.Thus,to optimize the CH’s selection process,three evolutionary algorithms are employed,namely,the ant colony optimization(ACO),multi-objective particle swarm optimization(MOPSO),and the comprehensive learning particle swarm optimization(CLPSO).The performance of the proposed method is verified by extensive experiments by varying values of different parameters,including the transmission range,node number,node mobility,and grid size.A comprehensive comparative analysis of the three algorithms is conducted by extensive experiments.The results show that,compared with the other methods,the proposed ACO-based method can form clusters more efficiently and increase network lifetime,thus achieving remarkable network and energy efficiency.The proposed ACO-based technique can also be used in other types of ad-hoc networks as well.

Lightweight Key Management Scheme Using Fuzzy Extractor for Wireless Mobile Sensor Network

The mature design of wireless mobile sensor network makes it to be used in vast verities of applications including from home used to the security surveillance.All such types of applications based on wireless mobile sensor network are generally using real time data,most of them are interested in real time communication directly from cluster head of cluster instead of a base station in cluster network.This would be possible if an external user allows to directly access real time data from the cluster head in cluster wireless mobile sensor network instead of accessing data from base station.But this leads to a serious security breach and degrades the performance of any security protocol available in this domain.Most existing schemes for authentication and cluster key management for external users,exchange a number of messages between cluster head and base station to allow external to access real time data from the base station instead of cluster head.This increase communication cost and delay in such real time access information.To handle this critical issue in cluster wireless mobile sensor network,we propose a lightweight authentication and key management scheme using a fuzzy extractor.In this scheme,any external user can access data directly from the cluster head of any cluster without the involvement of the base station.The proposed scheme only uses the one-way hash functions and bitwise XOR operations,apart from the fuzzy extractor method for the user biometric verification at the login phase.The presented scheme supports scalability for an increasing number of nodes using polynomials.The proposed scheme increases the life-time of the network by decreasing the key pool size.