Energy-efficient Scheduling for Leakage Detection in Long-distance Pipeline

Background: The convergence of wireless technologies, ad hoc networks and sensing devices has ushered to the concept of Wireless Sensor Network (WSN) that has the potential to improve a wide range of applications relating to healthcare, environment, transportation, cities, military and disaster management. WSN allows a set of sensor nodes to measure, process and report specific parameters. More recently, some research interests have been focusing on detecting water leakage in a long pipeline using WSN. Furthermore, water leakage significantly affects the human lives and environment and designing a reliable leak detection technique is a crucial task. Method: Our design is mainly based on mobile sensor nodes that either use water velocity or localize themselves through range-based localization techniques. Our idea consists to schedule a set of mobile sensor nodes and allow them to switch their states from active to idle and vice versa such that we can achieve two objectives: localizing water leakage in a long-distance pipeline and minimizing energy consumption. We propose, simulate, evaluate and compare the energy consumption of three non-real time scheduling techniques. The first one investigates water velocity for predicting the movement of sensor nodes. The second technique localizes sensor nodes through a range-based method. However, the third technique merges the features of interrupt-driven and water velocity scheduling. Results: Our results demonstrate that interrupt-driven/water velocity-based scheduling outperforms all the other tested scheduling techniques and leads to an energy consumption which is an exponential function that depends on the number of nodes. In addition, the energy consumption of interruptdriven/ water velocity-based scheduling demonstrates a good performance according to the pipe length. Conclusion: Our simulation and analysis results demonstrate the energy-efficiency and scalability of interrupt-driven/water velocity-based scheduling according to the number of sensor nodes and the length of the pipe. This work may be improved by conducting in the future an experimental study to prove its performance.