Energy-Balanced Optimization on Flying Ferry Placement for Data Gathering in Wireless Sensor Networks

Deploying flying ferries in large-scaled wireless sensor networks can prevent data gathering and distribution from physical communication restrictions on the ground. Ferry-assisted data distribution is straightfoward and manageable, as compared with traditional ad hoc routing over weak and multi-hop wireless networks. Our study exploits the notion of a ferry fleet that conducts teamwork for data gathering in such environments. To maximize the lifetime of a ferry fleet, we propose a fair and energy-balanced ferry fleet placement scheme, named as FEB for brevity, as jointly considering the efficiency, balance, and fairness of energy consumption. This scheme operates two mutual phases. The first phase demarcates service regions in a network using the powered-Voronoi diagram. The second phase decides a shortest-path itinerary across sensors in every service region using a genetic-based alternative of the traveling salesman problem (TSP) algorithm. Thus, this scheme is able to ensure fair task assignment, balance energy consumption, and prolong the lifetime among multiple ferries in teamwork. Performance results show that the proposed scheme outperforms several typical schemes, including Native, K-Means and Spiral, in terms of cumulative energy computation, residual energy distribution, Jain's fairness index on energy utilization, the number of alive ferries, and the total of task execution times during ferry teamwork.