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135
A line in the sand: a wireless sensor network for target detection, classification, and tracking
- COMPUTER NETWORKS
, 2004
"... Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a de ..."
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Cited by 272 (41 self)
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Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called ‘‘A Line in the Sand’ ’ and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability on application performance. Our work includes multiple experimental deployments of over 90
Vigilnet: An Integrated Sensor Network System for Energy-Efficient Surveillance
- ACM Transaction on Sensor Networks
, 2006
"... This article describes one of the major efforts in the sensor network community to build an integrated sensor network system for surveillance missions. The focus of this effort is to acquire and verify information about enemy capabilities and positions of hostile targets. Such missions often involve ..."
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Cited by 159 (36 self)
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This article describes one of the major efforts in the sensor network community to build an integrated sensor network system for surveillance missions. The focus of this effort is to acquire and verify information about enemy capabilities and positions of hostile targets. Such missions often involve a high element of risk for human personnel and require a high degree of stealthiness. Hence, the ability to deploy unmanned surveillance missions, by using wireless sensor networks, is of great practical importance for the military. Because of the energy constraints of sensor devices, such systems necessitate an energy-aware design to ensure the longevity of surveillance missions. Solutions proposed recently for this type of system show promising results through simulations. However, the simplified assumptions they make about the system in the simulator often do not hold well in practice, and energy consumption is narrowly accounted for within a single protocol. In this article, we describe the design and implementation of a complete running system, called VigilNet, for energyefficient surveillance. The VigilNet allows a group of cooperating sensor devices to detect and track the positions of moving vehicles in an energy-efficient and stealthy manner. We evaluate VigilNet middleware components and integrated system extensively on a network of 70 MICA2 motes. Our results show that our surveillance strategy is adaptable and achieves a significant extension of
Atpc: Adaptive transmission power control for wireless sensor networks
- In Proceedings of the Fourth International Conference on Embedded Networked Sensor Systems (SenSys
, 2006
"... Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmissi ..."
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Cited by 146 (10 self)
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Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations and over a long period of time. The results from the real-world experiments demonstrate that 1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability and 2) with online control, ATPC is robust even with environmental changes over time.
Macro-programming Wireless Sensor Networks using Kairos
"... The literature on programming sensor networks has, by and large, focused on providing higher-level abstractions for expressing local node behavior. Kairos is a natural next step in sensor network programming in that it allows the programmer to express, in a centralized fashion, the desired global b ..."
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Cited by 134 (3 self)
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The literature on programming sensor networks has, by and large, focused on providing higher-level abstractions for expressing local node behavior. Kairos is a natural next step in sensor network programming in that it allows the programmer to express, in a centralized fashion, the desired global behavior of a distributed computation on the entire sensor network. Kairos’ compile-time and runtime subsystems expose a small set of programming primitives, while hiding from the programmer the details of distributed code generation and instantiation, remote data access and management, and inter-node program flow coordination. Kairos ’ runtime is greatly simplified by assuming eventual consistency in node state; this assumption underlies many practical distributed computations proposed for sensor networks. In this paper, we describe Kairos ’ programming model, and the flexibility and robustness it affords programmers. We demonstrate its suitability, through actual implementation, for a variety of distributed programs—both infrastructure services and signal processing tasks—typically encountered in sensor network literature: routing tree construction, localization, and object tracking. Our experimental results suggest that Kairos does not adversely affect the performance or accuracy of distributed programs, while our implementation experiences suggest that it greatly raises the level of abstraction presented to the programmer.
Collaborative Signal and Information Processing: An Information Directed Approach
- Proceedings of the IEEE
, 2003
"... This article describes information-based approaches to processing and organizing spatially distributed, multi-modal sensor data in a sensor network. Energy constrained networked sensing systems must rely on collaborative signal and information processing (CSIP) to dynamically allocate resources, mai ..."
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Cited by 125 (2 self)
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This article describes information-based approaches to processing and organizing spatially distributed, multi-modal sensor data in a sensor network. Energy constrained networked sensing systems must rely on collaborative signal and information processing (CSIP) to dynamically allocate resources, maintain multiple sensing foci, and attend to new stimuli of interest, all based on task requirements and resource constraints. Target tracking is an essential capability for sensor networks and is used as a canonical problem for studying information organization problems in CSIP. After formulating a CSIP tracking problem in a distributed constrained optimization framework, the paper describes IDSQ and other techniques for tracking individual targets as well as combinatorial tracking problems such as counting targets. Results from simulations and experimental implementations have demonstrated that these information based approaches are scalable and make efficient use of scarce sensing and communication resources.
Distributed Group Management for Track Initiation and Maintenance in Target Localization Applications
- In Proc. of 2nd workshop on Information Processing in Sensor Networks (IPSN
, 2003
"... The tradeoff between performance and scalability is a fundamental issue in distributed sensor networks. In this paper, we propose a novel scheme to efficiently organize and utilize network resources for target localization. Motivated by the essential role of geographic proximity in sensing, sens ..."
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Cited by 86 (4 self)
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The tradeoff between performance and scalability is a fundamental issue in distributed sensor networks. In this paper, we propose a novel scheme to efficiently organize and utilize network resources for target localization. Motivated by the essential role of geographic proximity in sensing, sensors are organized into local collaborative groups.
Entropy-based Sensor Selection Heuristic for Target Localization
- in Proceedings of the third international symposium on Information processing in sensor networks
, 2004
"... We propose an entropy-based sensor selection heuristic for localization. Given 1) a prior probability distribution of the target location, and 2) the locations and the sensing models of a set of candidate sensors for selection, the heuristic selects an informative sensor such that the fusion of the ..."
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Cited by 84 (1 self)
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We propose an entropy-based sensor selection heuristic for localization. Given 1) a prior probability distribution of the target location, and 2) the locations and the sensing models of a set of candidate sensors for selection, the heuristic selects an informative sensor such that the fusion of the selected sensor observation with the prior target location distribution would yield on average the greatest or nearly the greatest reduction in the entropy of the target location distribution. The heuristic greedily selects one sensor in each step without retrieving any actual sensor observations. The heuristic is also computationally much simpler than the mutual-information-based approaches. The e#ectiveness of the heuristic is evaluated using localization simulations in which Gaussian sensing models are assumed for simplicity. The heuristic is more e#ective when the optimal candidate sensor is more informative.
The Sensor Selection Problem for Bounded Uncertainty Sensing Models
- IEEE Tran. Automation Science and Engineering
, 2005
"... We address the problem of selecting sensors so as to minimize the error in estimating the position of a target. We consider a generic sensor model where the measurements can be interpreted as polygonal, convex subsets of the plane. This model applies to a large class of sensors including cameras. We ..."
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Cited by 73 (3 self)
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We address the problem of selecting sensors so as to minimize the error in estimating the position of a target. We consider a generic sensor model where the measurements can be interpreted as polygonal, convex subsets of the plane. This model applies to a large class of sensors including cameras. We present an approximation algorithm which guarantees that the resulting error in estimation is within a factor 2 of the least possible error. In establishing this result, we formally prove that a constant number of sensors suffice for a good estimate -- an observation made by many researchers. In the second part of the paper, we study the scenario where the target's position is given by an uncertainty region and present algorithms for both probabilistic and online versions of this problem.
Information-directed routing in ad hoc sensor networks
- IEEE Journal on Selected Areas in Communications
, 2005
"... In a sensor network, data routing is tightly coupled to the needs of a sensing task, and hence the application semantics. This paper introduces the novel idea of information-directed routing, in which routing is formulated as a joint optimization of data transport and information aggregation. The ro ..."
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Cited by 51 (2 self)
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In a sensor network, data routing is tightly coupled to the needs of a sensing task, and hence the application semantics. This paper introduces the novel idea of information-directed routing, in which routing is formulated as a joint optimization of data transport and information aggregation. The routing objective is to minimize communication cost while maximizing information gain, differing from routing considerations for more general ad hoc networks. The paper uses the concrete problem of locating and tracking possibly moving signal sources as an example of information generation processes, and considers two common information extraction patterns in a sensor network:routing a user query from an arbitrary entry node to the vicinity of signal sources and back, or to a prespecified exit node, maximizing information accumulated along the path. We derive information constraints from realistic signal models, and present several routing algorithms that find near-optimal solutions for the joint optimization problem. Simulation results have demonstrated that information-directed routing is a significant improvement over a previously reported greedy algorithm, as measured by sensing quality such as localization and tracking accuracy and communication quality such as success rate in routing around sensor holes.
State-Centric Programming for Sensor-Actuator Network Systems
, 2003
"... This article describes a state-centric, agent-based design methodology to mediate between a system developer's mental model of physical phenomena and the distributed execution of DSAN applications. Building on the ideas of data-centric networking, sensor databases, and proximity-based gro ..."
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Cited by 45 (0 self)
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This article describes a state-centric, agent-based design methodology to mediate between a system developer's mental model of physical phenomena and the distributed execution of DSAN applications. Building on the ideas of data-centric networking, sensor databases, and proximity-based group formation, 3 we introduce the notion of collaboration groups, which abstracts common patterns in application-specific communication and resource allocation. An application developer specifies computations as the creation, aggregation, and transformation of states, which naturally map to the vocabulary used by signal processing and control engineers. More specifically, programmers write applications as algorithms for state update and retrieval, with input supplied by dynamically created collaboration groups. As a result, programs written in the state-centric framework are more invariant to system configuration changes, making the resulting software more modular and portable across multiple platforms. Using a distributed tracking application with sensor networks, we'll demonstrate how state-centric programming can raise the abstraction level for application developers
