Abstract — We propose new algorithms to achieve k-coverage in dense sensor networks. In such networks, covering sensor locations approximates covering the whole area. However, it has been shown before that selecting the minimum set of sensors to activate from an already deployed set of sensors is NP-hard. We propose an efficient approximation algorithm which achieves a solution of size within a logarithmic factor of the optimal. We prove that our algorithm is correct and analyze its complexity. We implement our algorithm and compare it against two others in the literature. Our results show that the logarithmic factor is only a worst-case upper bound and the solution size is close to the optimal in most cases. A key feature of our algorithm is that it can be implemented in a distributed manner with local information and low message complexity. We design and implement a fully distributed version of our algorithm. Our distributed algorithm does not require that sensors know their locations. Comparison with two other distributed algorithms in the literature indicates that our algorithm: (i) converges much faster than the others, (ii) activates near-optimal number of sensors, and (iii) significantly prolongs (almost doubles) the network lifetime because it consumes much less energy than the other algorithms. I.

Abstract not found

Abstract not found

Abstract. Automatic fire detection is important for early detection and promptly extinguishing fire. There are ample studies investigating the best sensor combinations and appropriate techniques for early fire detection. In the previous studies fire detection has either been considered as an application of a certain field (e.g., event detection for wireless sensor networks) or the main concern for which techniques have been specifically designed (e.g., fire detection using remote sensing techniques). These different approaches stem from different backgrounds of researchers dealing with fire, such as computer science, geography and earth observation, and fire safety. In this report we survey previous studies from three perspectives: (1) fire detection techniques for residential areas, (2) fire detection techniques for forests, and (3) contributions of sensor networks to early fire detection. 1

In this paper, we are concerned with en- area [1],[2]. Energy is consumed in the sensor nodes ergy efficient area monitoring using information cov- for the purpose of sensing as well as communication. erage in wireless sensor networks, where collaboration Several studies in the literature have addressed the isamong multiple sensors can enable accurate sensing sue of minimizing the energy spent for the purpose of of a point in a given area-to-monitor even if that communication (e.g., energy efficient routing [3]). In point falls outside the physical coverage of all the sen- this paper, we address the energy spent for the pursors. We refer to any set of sensors that can collec- pose of sensing, focusing on energy efficient algorithms tively sense all points in the entire area-to-monitor for scheduling the sensing activity of sensor nodes usas a full area information cover. We first propose a ing Information Coverage [4], instead of the often used low-complexity heuristic algorithm to obtain full area physical coverage. information covers. Using these covers, we then ob- Sensor nodes in the network have the task of senstain the optimum schedule for activating the sensing ing/monitoring an area-to-sense/monitor and sending activity of various sensors that maximizes the sensing the sensed information to a sink. Not all nodes in the lifetime. The scheduling of sensor activity using the network may be needed to adequately cover (sense) optimum schedules obtained using the proposed algo- the entire area-to-monitor. By intelligently switchrithm is shown to achieve significantly longer sensing ing the redundant sensor nodes to low power operalifetimes compared to those achieved using physical tion, the energy spent in sensing can be reduced, and coverage. Relaxing the full area coverage requirement hence the overall lifetime of the network can be into a partial area coverage (e.g., 95 % of area coverage creased. Redundant nodes can be deactivated as long as adequate instead of 100 % area coverage) further

Abstract—Various sensor types, e.g., temperature, humidity, and acoustic, sense physical phenomena in different ways, and thus are expected to have different sensing models. Even for the same sensor type, the sensing model may need to be changed in different environments. Designing and testing a different coverage protocol for each sensing model is indeed a costly task. To address this challenging task, we propose a new probabilistic coverage protocol (denoted by PCP) that could employ different sensing models. We show that PCP works with the common disk sensing model as well as probabilistic sensing models, with minimal changes. We analyze the complexity of PCP and prove its correctness. In addition, we conduct an extensive simulation study of large-scale sensor networks to rigorously evaluate PCP and compare it against other deterministic and probabilistic protocols in the literature. Our simulation demonstrates that PCP is robust, and it can function correctly in presence of random node failures, inaccuracies in node locations, and imperfect time synchronization of nodes. Our comparisons with other protocols indicate that PCP outperforms them in several aspects, including number of activated sensors, total energy consumed, and network lifetime.

Email: ivan @ site.uottawa.ca Abstract- Wireless sensor networks are composed of hundreds of small and low power devices deployed over a field to monitor. Energy consumption is balanced by taking advantage of the redundancy induced by the random deployment of nodes. Some nodes are active while others are in sleep mode. Area coverage protocols aim at turning off redundant sensor nodes while preserving satisfactory monitoring by the set of active nodes. The problem addressed here consists in building k distinct subsets of active nodes (layers), in a fully decentralized manner, so that each layer covers the area. In our protocol, each node selects a waiting timeout, listening to messages from neighbors. Activity messages include the layer at which a node has decided to be active. Depending on the physical layer used for sensing modeling, any node can evaluate if the provided coverage is sufficient for each layer. If so, node can sleep, otherwise it selects a layer to be active. Here, we describe a localized area coverage protocol able to maintain an area k-covered under realistic physical layer assumptions for both sensing and communicating modules. I.

Abstract: In this paper, we are concerned with algorithms for deployed sensor nodes over a long period of time (e.g., monischeduling the sensing activity of sensor nodes that are deployed toring the radiation level or temperature of a source at a given to sense/measure point-targets in wireless sensor networks using location in a remote/inaccessible area). The intensity of such a information coverage. Defining a set of sensors which collectively physical quantity to monitor typically decays with distance. A can sense a target accurately as an information cover, we propose target is said to be 'covered ' if a sensor individually (or a set of an algorithm to obtain Disjoint Set of Information Covers (DSIC), sensors collectively) can measure (i.e., sense) the target with which achieves longer network life compared to the set of certain acceptable accuracy. A set of nodes which collectively covers obtained using an Exhaustive-Greedy-Equalized Heuristic can sense a target in the network with acceptable accuracy is (EGEH) algorithm proposed recently in the literature. We also referred to as a cover for that target. In the case of multiple present a detailed complexity comparison between the DSIC and targets in the network, a set of nodes which together can EGEH algorithms. sense all the targets in the network with acceptable accuracy

Abstract—In wireless sensor networks, multiple-coverage, in which each point is covered by more than one sensor, is often required to improve detection quality and achieve high fault tolerance. However, finding optimal patterns that achieve multiplecoverage in a plane remains a long-lasting open problem. In this paper, we first derive the optimal deployment density bound for two-coverage deployment patterns where Voronoi polygons generated by sensor nodes are congruent. We then propose optimal two-coverage patterns based on the optimal bound. We further extend these patterns by considering the connectivity requirement and design a set of optimal patterns that achieve two-coverage and one-, two-, and three-connectivity. We also study optimal patterns under practical considerations. To our knowledge, our work is the very first that proves the optimality of multiplecoverage deployment patterns.

In wireless sensor networks (WSNs), energy source is usually battery cell, which is impossible to recharge while WSNs are working. Therefore, one of the main issues in wireless sensor networks is how to prolong the network lifetime of WSNs with certain energy source as well as how to maintain coverage and connectivity. In this paper, we consider the wireless sensor networks satisfying that each node monitors one target or just for connection. Assume the wireless sensor network has l targets, and each is monitored by k sensor nodes. If k = 2 and the graph G corresponding to the wireless sensor network is (l + max{1,l − 4})-connected, or k ≥ 3 and G is (l(k − 1) + 1)-connected, then we can find k (the maximum number) disjoint sets each of which completely covers all the targets and remains connected to one of the central processing nodes. The disjoint sets are activated successively, and only the sensor nodes from the active set are responsible for monitoring the targets and connectivity, all other nodes are into a sleep mode. And we also give the related algorithms to find the k disjoint sets.