A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks

Abstract

We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.

Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

“…Vajdi et al [84] investigate the problems of hostile environment applications or eventdriven wireless sensor networks (EWSNs) such as forest and fire detection events. In these applications, data harvesting is a big challenge to handle from sensor nodes in the field.…”

“…In Table 2, various healthcare applications are used in the query-driven model in terms of data delivery delay, and scheduling algorithms are used to save energy in WSNs [78][79][80]94,95]. If an unexpected event occurs in the WSNs environment such as fire, temperature, or a road accident, then emergency applications are used in the event-driven model [81][82][83][84][85]. Sensor nodes use the shortest minimal hop routing path for data while analyzing the reliability and true or fault probability-based events that occur.…”