A Soft Computing Approach for Data Routing in Hospital Area Networks (HAN)

A Soft Computing Approach for Data Routing in Hospital Area Networks (HAN)

Rakhee, M. B. Srinivas
DOI: 10.4018/IJBDCN.2016070102
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Abstract

This paper proposes an alternative model to deliver vital signs of patients in a hospital indoor environment where a large number of patients exist and the traffic generated rapidly changes over time using Body Area Network (BAN). The methodology for finding an optimal path includes a meta-heuristic that combines ANT Colony Optimization (ACO). The authors propose an ACO based framework for monitoring data originating from a BAN to improve network life, energy and load balancing of the overall network. Since the traffic generated by BANs on the network changes with time, finding a shortest path is important for Hospital Area Network. In this paper, the authors implemented an ACO based method and have carried out simulations using OMNeT++ to prove that the proposed method can find a better solution than conventional methods.
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Wireless Body Area Networks (WBAN) (Figure 1) together with HAN have created a high impact on the health care because of ageing population due to its sedentary lifestyle and poor diet resulting in an increase in number of people with chronic disease which requires continuous monitoring of the patient. Wireless sensor network technology offers a large scale and cost-effective solutions to this problem. It has become necessity for providing the quality health care timely by using Wireless Body Area Network technology. Authors in (ZK.et.al 2013), for an indoor hospital scenario, it uses centralized and distributed mode of communicating the BAN data packets which are sensitive and critical packets. Communication of the data packets plays a vital role in WBAN, since it consumes energy of the sensor node and that can be optimized by finding the best route to address all important issues concerned with latency, throughput.

Figure 1.

General WBAN architecture

IJBDCN.2016070102.f01

The challenges related to the management of patient’s medical information and an intelligent continuous monitoring of BAN data in hospital environment is discussed (Chen et al. 2010). Many researchers (Wood et al., 2006, Chen et al., 2009; Huang and Fang, 2008; Liang et al., 2008; Razzaque et al., 2008, Curtis et al., 2008; Gao et al., 2007; Agarwal et al., 2010, ZKhan et al., 2013, Ugolotti et al., 2013; Amoretti et al., 2013) have proposed BAN network architecture by combining or splitting the BAN in inter-BAN communication but they failed to address the real time display of BAN data in indoor hospital environment using soft computing approach

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