Surface coverage in wireless sensor networks

Abstract—Coverage is a fundamental problem in Wireless Sensor Networks (WSNs). Existing studies on this topic focus on 2D ideal plane coverage and 3D full space coverage. In many real world applications, the 3D surface of a targeted Field of Interest is complex, however, existing studies do not provide promising results. In this paper, we propose a new coverage model called surface coverage. In surface coverage, the targeted Field of Interest is a surface in 3D space and sensors can be deployed only on the surface. We show that existing 2D plane coverage is merely a special case of surface coverage. Simulations point out that existing sensor deployment schemes for a 2D plane cannot be directly applied to surface coverage cases. In this paper, we target two problems assuming surface coverage to be true. One, under stochastic deployment, how many sensors are needed to reach a certain expected coverage ratio? Two, if sensor deployment can be planned, what is the optimal deployment strategy with guaranteed full coverage with the least number of sensors? We show that the latter problem is NP-complete and propose three approximation algorithms. We further prove that these algorithms have a provable approximation ratio. We also conduct comprehensive simulations to evaluate the performance of the proposed algorithms. I

Probabilistic topology control in wireless sensor networks

For a wide spectrum of applications ranging from habitat monitoring to battlefield surveillance, the wireless sensor network (WSN) technology has exhibited revolutionary advantages when compared to traditional solutions. Among all the energy-saving schemes, topology control has been well recognized as an effective one. By providing an appropriate support for routing protocols, topology control enables more energy-efficient transmissions and higher network capacity. In traditional topology control, a wireless network is represented using deterministic model that assumes a pair of nodes is either connected or disconnected. In practice, however, most wireless links are intermittently connected, called lossy links. By successfully leveraging these lossy links, topologies of more energy-efficiency and higher network capacities are available. By traditional deterministic network model, however, WSN topologies can hardly be well characterized. To seize the opportunity of lossy links, I propose a new probabilistic network model. Using this model we are able to quantify the quality of the network connectivity. The key problem in probabilistic topology control is to seek a topology of minimized energy cost, while the quality of network connectivity satisfied certain constraints. In this work, I prove that in general probabilistic topology control is a NP-hard problem. To serve different communication paradigms,I propose two algorithms called CONREAP and BRASP. The former CONREAP is for sink-to-sensor communications and BRASP is for general sensor-to-sensor communications. I prove that both CONREAP and BRASP has guaranteed network reachability for the derived topology. The worst running time is (∣E∣) and the space requirement is O(d). Experimental results show that CONREAP can remarkably reduce the energy cost. It is more appropriate for low requirement and large transitional region environments. In comparison, BRASP construct a topology of more energy cost, while the derived topology can serve for more general communication patterns from sensor to sensors. To show how to efficiently transmit in a probabilistic wireless network with lossy links involved in, I proposed a novel reliability-oriented transmission protocol called proliferation routing. It leverages randomized dispersion and reproductions. The distinctive feature of proliferation routing is its great flexibility and high energy-efficiency. Not only can it be applied with any Medium Access Control (MAC) protocol and routing metrics, but also a desired service quality can be effectively derived by controlling the system parameters. I conduct comprehensive theoretical analysis and confirm it implementation and simulation experiments. In a specific experiment setup, proliferation routing can increase the end-to-end transmission success rate up to 70% compared with the well-known hop-based routing and flooding

A new MAC protocol design for long-term applications in wireless sensor networks

This paper presents the design, implementation and performance evaluation of a new MAC protocol, called AMAC, for wireless sensor networks. A-MAC combines the strengths of TDMA and CSMA to achieve the goal of low power transmissions for long-term surveillance and monitoring applications, where sensor nodes are typically vigilant for a long time and inactive most of the time until some event is detected. A-MAC employs an advertisement mechanism to eliminate collisions and reduce the overhearing and idle listening, which are the major energy wastes in wireless sensor networks. The distinctive feature of A-MAC is that a node needs to be active only when necessary as it is the transmitter or the receiver During other times it can safely turn off its radio. Furthermore, to meet different application requirements, A-MAC supports two operation modes by which nodes can adaptively switch their operation modes according to the instant requirements and conditions of the network. A-MAC is implemented in TinyOS. By comparing A-MAC with existing MAC protocols, we show that A-MAC presents significant improvements in terms of power consumption and throughput