Energy Efficient Approach for Surveillance Applications Based on Self Organized Wireless Sensor Networks

AbstractSurveillance applications based on Wireless Sensor Networks (WSNs) are energy consumption sensitive. Such applications require low energy consumption in order to extend network lifetime. In this paper, we are interested in event detection around strategic sites (e.g., oil or military sites). We propose energy efficient approach which consists of identifying and using network boundary nodes as sentries, i.e., they are always in active mode and are responsible of detecting events, sending and relaying alert messages to the sink. Remaining nodes are used as relay nodes only. They alternate between active and sleep modes in order to reduce energy consumption. Simulation results show that our approach increases significantly network lifetime and provides an acceptable percentage of alerts delivered to the sink

On realistic target coverage by autonomous drones

Low-cost mini-drones with advanced sensing and maneuverability enable a new class of intelligent sensing systems. To achieve the full potential of such drones, it is necessary to develop new enhanced formulations of both common and emerging sensing scenarios. Namely, several fundamental challenges in visual sensing are yet to be solved including (1) fitting sizable targets in camera frames; (2) positioning cameras at effective viewpoints matching target poses; and (3) accounting for occlusion by elements in the environment, including other targets. In this article, we introduce Argus, an autonomous system that utilizes drones to collect target information incrementally through a two-tier architecture. To tackle the stated challenges, Argus employs a novel geometric model that captures both target shapes and coverage constraints. Recognizing drones as the scarcest resource, Argus aims to minimize the number of drones required to cover a set of targets. We prove this problem is NP-hard, and even hard to approximate, before deriving a best-possible approximation algorithm along with a competitive sampling heuristic which runs up to 100× faster according to large-scale simulations. To test Argus in action, we demonstrate and analyze its performance on a prototype implementation. Finally, we present a number of extensions to accommodate more application requirements and highlight some open problems

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network

Barrier coverage has been widely used to detect intrusions in wireless sensor networks (WSNs). It can fulfill the monitoring task while extending the lifetime of the network. Though barrier coverage in WSNs has been intensively studied in recent years, previous research failed to consider the problem of intrusion in transversal directions. If an intruder knows the deployment configuration of sensor nodes, then there is a high probability that it may traverse the whole target region from particular directions, without being detected. In this paper, we introduce the concept of crossed barrier coverage that can overcome this defect. We prove that the problem of finding the maximum number of crossed barriers is NP-hard and integer linear programming (ILP) is used to formulate the optimization problem. The branch-and-bound algorithm is adopted to determine the maximum number of crossed barriers. In addition, we also propose a multi-round shortest path algorithm (MSPA) to solve the optimization problem, which works heuristically to guarantee efficiency while maintaining near-optimal solutions. Several conventional algorithms for finding the maximum number of disjoint strong barriers are also modified to solve the crossed barrier problem and for the purpose of comparison. Extensive simulation studies demonstrate the effectiveness of MSPA

TỐI ƯU HÓA VÙNG PHỦ SÓNG CỦA MẠNG CẢM BIẾN KHÔNG DÂY BẰNG THUẬT TOÁN VORONOI TRONG MÔI TRƯỜNG 3D

In recent years, wireless sensor networks (WSN) has appeared interesting to many authors. Some methods to optimize the coverage of wireless sensor networks is proposed to improve the efficiency of deploying sensor networks, thus increasing the coverage; howerver, most are built on 2D model, which are often hard to implement in reality. In this paper we extend Voronoi algorithm to deploy sensors in 3D environments where there are obstacles which affect the ability of coverage of wireless sensor networks.Trong những năm gần đây mạng cảm biến không dây (WSN) được nhiều nhóm tác giả quan tâm. Một số phương pháp tối ưu hóa vùng phủ sóng của mạng cảm biến không dây được đề xuất để nâng cao hiệu quả triển khai mạng cảm biến do đó làm tăng độ phủ sóng, nhưng hầu hết được xây dựng trên mô hình 2D, mà thường xa rời với thực tế. Trong bài báo này chúng tôi mở rộng thuật toán Voronoi để triển khai các cảm biến trong môi trường 3D mà ở đó có nhiều vật cản làm ảnh hưởng đến khả năng phủ sóng của mạng cảm biến không dây

Full-View Coverage Problems in Camera Sensor Networks

Camera Sensor Networks (CSNs) have emerged as an information-rich sensing modality with many potential applications and have received much research attention over the past few years. One of the major challenges in research for CSNs is that camera sensors are different from traditional scalar sensors, as different cameras from different positions can form distinct views of the object in question. As a result, simply combining the sensing range of the cameras across the field does not necessarily form an effective camera coverage, since the face image (or the targeted aspect) of the object may be missed. The angle between the object\u27s facing direction and the camera\u27s viewing direction is used to measure the quality of sensing in CSNs instead. This distinction makes the coverage verification and deployment methodology dedicated to conventional sensor networks unsuitable. A new coverage model called full-view coverage can precisely characterize the features of coverage in CSNs. An object is full-view covered if there is always a camera to cover it no matter which direction it faces and the camera\u27s viewing direction is sufficiently close to the object\u27s facing direction. In this dissertation, we consider three areas of research for CSNS: 1. an analytical theory for full-view coverage; 2. energy efficiency issues in full-view coverage CSNs; 3. Multi-dimension full-view coverage theory. For the first topic, we propose a novel analytical full-view coverage theory, where the set of full-view covered points is produced by numerical methodology. Based on this theory, we solve the following problems. First, we address the full-view coverage holes detection problem and provide the healing solutions. Second, we propose $k$-Full-View-Coverage algorithms in camera sensor networks. Finally, we address the camera sensor density minimization problem for triangular lattice based deployment in full-view covered camera sensor networks, where we argue that there is a flaw in the previous literature, and present our corresponding solution. For the second topic, we discuss lifetime and full-view coverage guarantees through distributed algorithms in camera sensor networks. Another energy issue we discuss is about object tracking problems in full-view coverage camera sensor networks. Next, the third topic addresses multi-dimension full-view coverage problem where we propose a novel 3D full-view coverage model, and we tackle the full-view coverage optimization problem in order to minimize the number of camera sensors and demonstrate a valid solution. This research is important due to the numerous applications for CSNs. Especially some deployment can be in remote locations, it is critical to efficiently obtain accurate meaningful data