The breakthrough of wireless power transfer technology provides an effective solution to the problem of energy depletion in Wireless Rechargeable Sensor Networks (WRSNs). Most existing work focuses on charging between a mobile charger and a requested sensor, such as NJNP and SAMER, under the assumption that sensors have the same battery capacity and energy consumption rate. In reality, it is more general that a WRSN consists of different types of sensors where they have different battery capacity and energy consumption rate, which is referred as Heterogeneous Wireless Rechargeable Sensor Network (HWRSN). We propose a novel online charging algorithm called VTMT to solve the charging problem in HWRSN. First, we propose the concept of Virtual Time, which is positively correlated with the waiting time of the requested sensor. Then selects the next charging sensor primarily based on the Virtual Time (VT) of the sensor and the Moving Time (MT) of the mobile charger to the node. Simulation results show that VTMT outperforms other charging schemes, which effectively reduce the failure rate of nodes and ensure the scheduling fairness.

Barrier coverage is an important coverage model for intrusion detection, which requires a chain of sensors across the deployment area with the adjacent sensors’ sensing areas overlapping. Directional sensors are often dispersed from an airplane following a predetermined line. However, barrier coverage cannot be guaranteed after initial sensor deployment due to the sensors’ random offsets and random orientations. Fortunately, directional sensors can rotate to mend the barrier gaps using this line-based sensor deployment model. Existing work proposed a greedy heuristic approach to mend the gaps by rotating sensors, but it cannot answer whether there exists a barrier. We fill in this gap by presenting an exact algorithm which can determine whether there exists a barrier. We first introduce the notion of feasible orientation range and then try to calculate each sensor’s feasible orientation starting from the leftmost sensor. We also propose a fast algorithm of choosing the sensors’ orientations from their feasible orientation ranges to form a barrier if there exists a barrier, or form a set of sub-barriers if there does not exist a barrier. Simulation results show that our algorithm outperforms the distributed algorithm in the existing work.

Border surveillance for intrusion detection is an important application of wireless sensor networks. Given a set of mobile sensors and their initial positions, how to move these sensors to a region border to achieve barrier coverage energy-efficiently is challenging. In this paper, we study the 2-D MinMax barrier coverage problem of moving n sensors in a two-dimensional plane to form a barrier coverage of a specified line segment in the plane while minimizing the maximum sensor movement for the sake of balancing battery power consumption. Previously, this problem was shown to be NP-hard for the general case. It was an open problem whether the problem is polynomial-time solvable for the case when sensors have a fixed number of sensing ranges. We study a special case of great practical significance that the sensors have the same sensing range and present an O(n3log n) time algorithm. Our algorithm computes a permutation of the left and right endpoints of the moving ranges of all the sensors forming a barrier coverage and minimizes the maximum sensor movement distance by characterizing permutation switches that are critical. To the best of our knowledge, this is the first result for solving the 2-D MinMax barrier coverage problem for the case that all sensors have a uniform sensing range.