This paper 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 paper, we describe the design and implementation of a complete running system, called VigilNet, for energy-efficient 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 network lifetime. Finally, we share lessons learned in building such an integrated sensor system.

A wide variety of sensors have been incorporated into a spectrum of wireless sensor network (WSN) platforms, providing flexible sensing capability over a large number of low-power and inexpensive nodes. Traditional signal processing algorithms, however, often prove too complex for energy-and-cost-effective WSN nodes. This study explores how to design efficient sensing and classification algorithms that achieve reliable sensing performance on energy-andcost-effective hardware without special powerful nodes in a continuously changing physical environment. We present the detection and classification system in a cutting-edge surveillance sensor network, which classifies vehicles, persons, and persons carrying ferrous objects, and tracks these targets with a maximum error in velocity of 15%. Considering the demanding requirements and strict resource constraints, we design a hierarchical classification architecture that naturally distributes sensing and computation tasks at different levels of the system. Such a distribution allows multiple sensors to collaborate on a sensor node, and the detection and classification results to be continuously refined at different levels of the WSN. This design enables reliable detection and classification without involving high-complexity computation, reduces network traffic, and emphasizes resilience and adaptation to the realistic environment. We evaluate the system with performance data collected from outdoor experiments and field assessments. Based on the experience acquired and lessons learned when developing this system, we abstract common issues and introduce several guidelines which can direct future development of detection and classification solutions based on WSNs.

Abstract-Energy efficiency is a fundamental issue for outdoor sensor network systems. This paper presents the design and implementation of multi-dimensional power management strategies in VigilNet, a major recent effort to support longterm surveillance using power-constrained sensor devices. We integrate a novel tripwire service with an effective sentry and duty cycle scheduling in order to increase the system lifetime, collaboratively. Through extensive system implementation, we demonstrate the feasibility to achieve high surveillance performance and energy efficiency, simultaneously. We invest a fair amount of effort to evaluate our architecture with a network of 200 XSM motes in an outdoor environment, an extensive simulation with 10,000 nodes, as well as an analytical probabilistic model. These evaluations demonstrate the effectiveness of our integrated approach and identify many interesting lessons and guidelines, useful for the future development of energy-efficient sensor systems.

Energy efficiency is a fundamental issue for outdoor sensor network systems. This paper presents the design and implementation of multi-dimensional power management strategies in VigilNet, a major recent effort to support longterm surveillance using power-constrained sensor devices. We integrate a novel tripwire service with an effective sentry and duty cycle scheduling in order to increase the system lifetime, collaboratively. Through extensive system implementation, we demonstrate the feasibility to achieve high surveillance performance and energy efficiency, simultaneously. We invest a fair amount of effort to evaluate our architecture with a network of 200 XSM motes in an outdoor environment, an extensive simulation with 10,000 nodes, as well as an analytical probabilistic model. These evaluations demonstrate the effectiveness of our integrated approach and identify many interesting lessons and guidelines, useful for the future development of energy-efficient sensor systems.

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The problem of localization in wireless sensor networks where nodes do not use ranging hardware, remains a challenging problem, when considering the required location accuracy, energy expenditure and the duration of the localization phase. In this paper we propose a framework, called StarDust, for wireless sensor network localization based on passive optical components. In the StarDust framework, sensor nodes are equipped with optical retro-reflectors. An aerial device projects light towards the deployed sensor network, and records an image of the reflected light. An image processing algorithm is developed for obtaining the locations of sensor nodes. For matching a node ID to a location we propose a constraint-based label relaxation algorithm. We propose and develop localization techniques based on four types of constraints: node color, neighbor information, deployment time for a node and deployment location for a node. We evaluate the performance of a localization system based on our framework by localizing a network of 26 sensor nodes deployed in a 120 × 60f t 2 area. The localization accuracy ranges from 2f t to 5f t while the localization time ranges from 10 milliseconds to 2 minutes.

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 energy-efficient 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 network lifetime. Finally, we share lessons learned in building such an integrated sensor system.

This paper describes a novel group based programming abstraction called a 'Bundle' for cyber physical systems (CPS). Similar to other programming abstractions, a Bundle creates logical collections of sensing devices. However, previous abstractions were focused on wireless sensor networks (WSN) and did not address key aspects of CPS. Bundles elevate the programming domain from a single WSN to complex systems of systems by allowing the programming of applications involving multiple CPSs that are controlled by different administrative domains and support mobility both within and across CPSs. Bundles can seamlessly group not only sensors, but also actuators which constitute an important part of CPS. Bundles support heterogeneous devices, such as motes, PDAs, laptops and actuators according to the applications' requirements. They allow different applications to simultaneously use the same sensors and actuators. Bundles facilitate feedback control mechanisms by dynamic membership update and requirements reconfiguration based on feedback from the current members. The Bundle abstraction is implemented in Java which ensures ease and conciseness of programming. We present the design and implementation details of Bundles as well as a performance evaluation using 32 applications written with Bundles. This set includes across-network applications that have sophisticated sensing and actuation logic, mobile nodes that are heterogeneous, and feedback control mechanisms. Each of these applications is programmed in less than 60 lines of code.