Deployment of an Energy Efficient Routing Protocol for Wireless Sensor Networks Operating in a Resource Constrained Environment - Imoize, Agbotiname Lucky; Oyedare, Taiwo R; Ezekafor, Chibuike Gerald; Shetty, Sachin (Discoveries in Agriculture and Food Sciences, 2019)
Wireless Sensor Networks often exist in a resource constrained environment and the most critical limitation is energy or battery life. In most cases, the batteries cannot be recharged during operation and cannot be replaced during transmission without interfering with the quality of service. An efficient routing protocol that can prolong the life span of the energy source for mobile wireless sensor network (WSN) is proposed in this paper. Hierarchical routing protocol improved the life span by more than six times compared to direct techniques. Sets of varied parameters were used to obtain simulation results. A sample typical of a hospital layout was used in this paper. Wards were assigned varied sensor range which depicts number of patients that fall into these banded regions of clusters. Service centers were created to ensure that random mobilization of sensors/patient per round is achieved for one of the simulation option. Simulation rounds were carried out for non-hierarchical (direct) and lowenergy adaptive clustering hierarchy (LEACH) based routing protocols. Model validation was done by setting up a real life test using Wi-Fi sensor node module ESP8266 properly distributed, and this was done without mobility. Effect of base station location was also investigated and results tabulated. With improved battery and network life span from both simulation and live validation for hierarchical routing, quality of service is greatly improved in health-care deliveries; cost of replacing energy sources is reduced. Results were also compared with other similar works to support our conclusion. Though results were not exact when compared, parameters used could cause tolerable difference. Furthermore, same result could not be achieved for different locations, varied number of wards, varied number of sensor nodes per wards as well as variations in other modeling parameters.