Inspired by current challenges in data-intensive and energy-limited sensor networks, we formulate a coverage optimization problem for mobile sensors as a (constrained) repeated multiplayer game. Each sensor tries to optimize its own coverage while minimizing the processing/energy cost. The sensors are subject to the informational restriction that the environmental distribution function is unknown a priori. We present two distributed learning algorithms where each sensor only remembers its own utility values and actions played during the last plays. These algorithms are proven to be convergent in probability to the set of (constrained) Nash equilibria and global optima of a certain coverage performance metric, respectively. Numerical examples are provided to verify the performance of our proposed algorithms.

/pdf/distributed-coverage-games-for-energy-aware-mobile-sensor-32amcbwbaw.pdf

Distributed Coverage Games for Energy-Aware Mobile Sensor Networks

On efficient sensor scheduling for linear dynamical systems

Coverage in mobile wireless sensor networks (M-WSN)

Game theory for energy efficiency in Wireless Sensor Networks

Recently, wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and become one of the enabling technologies for disaster early-warning systems. Event detection functionality of WSNs can be of great help and importance for (near) real-time detection of, for example, meteorological natural hazards and wild and residential fires. From the data-mining perspective, many real world events exhibit specific patterns, which can be detected by applying machine learning (ML) techniques. In this paper, we introduce ML techniques for distributed event detection in WSNs and evaluate their performance and applicability for early detection of disasters, specifically residential fires. To this end, we present a distributed event detection approach incorporating a novel reputation-based voting and the decision tree and evaluate its performance in terms of detection accuracy and time complexity.

/pdf/distributed-event-detection-in-wireless-sensor-networks-for-1wzutmphfe.pdf

Distributed Event Detection in Wireless Sensor Networks for Disaster Management

Sensor networks can be used for event alarming applications. To date, in most of the proposed schemes, the raw or aggregated sensed data is periodically sent to a data consuming center. However, with this scheme, the occurrence of an emergency event such as a fire is hardly reported in a timely manner which is a strict requirement for event alarming applications. In sensor networks, it is also highly desired to conserve energy so that the network lifetime can be maximized. Furthermore, to ensure the quality of surveillance, some applications require that if an event occurs, it needs to be detected by at least k sensors where k is a user-defined parameter. In this work, we examine the timely energy-efficient k-watching event detection problem (TEKWEO). A topology-and-routing-supported algorithm is proposed which constructs a set of detection sets that satisfy the short notification time, energy conservation, and tunable quality of surveillance requirements for event alarming applications. Simulation results are shown to validate the proposed algorithm.

Composite Event Detection in Wireless Sensor Networks

The complete area coverage problem in Wireless Sensor Networks (WSNs) has been extensively studied in the literature. However, many applications do not require complete coverage all the time. For such applications, one effective method to save energy and prolong network lifetime is to partially cover the area. This method for prolonging network lifetime recently attracts much attention. However, due to the hardness of verifying the coverage ratio, all the existing centralized or distributed but nonparallel algorithms for partial coverage have very high time complexities. In this work, we propose a framework which can transform almost any existing complete coverage algorithm to a partial coverage one with any coverage ratio by running a complete coverage algorithm to find full coverage sets with virtual radii and converting the coverage sets to partial coverage sets via adjusting sensing radii. Our framework can preserve the characteristics of the original algorithms and the conversion process has low time complexity. The framework also guarantees some degree of uniform partial coverage of the monitored area.

Transforming Complete Coverage Algorithms to Partial Coverage Algorithms for Wireless Sensor Networks

Wireless sensor networks can be used for event warning applications. Till date, in most of the proposed schemes, the raw or aggregated sensed data are periodically sent to a data consuming center. However, with those schemes, the occurrence of an emergency event such as a fire is hardly reported timely, which is a strict requirement for event warning applications. In wireless sensor networks, it is also highly desired to conserve energy so that network lifetime can be maximized. Furthermore, to ensure the quality of surveillance, some applications require that if an event occurs, it needs to be detected by at least k sensors, where k is a user-defined parameter. In this work, we examine the Timely Energy-efficient k-Watching Event Monitoring (TEKWEM) problem and propose a scheme, which involves an event detection model and a warning delivery model, for monitoring composite events and delivering warnings to users. Theoretical analysis and simulation results are shown to validate the proposed scheme.

Delay-Bounded and Energy-Efficient Composite Event Monitoring in Heterogeneous Wireless Sensor Networks

In sensor networks, it is desired to conserve energy so that the network lifetime can be maximized. An efficient approach to prolong the network lifetime is to identify a schedule for all the sensors, indicating which subset of the sensors can be active during the current time slot. Furthermore, to ensure the quality of surveillance, some applications require k-coverage of the monitored area. In this paper, we first define the Sensor Energy-efficient Scheduling for k-coverage (SESK) problem. We further resolve it by proposing a scheduling approach named Distributed Energy-efficient Scheduling for k-coverage DESK such that the energy consumption among all the sensors is balanced while still assuring the k-coverage requirement. This approach is completely distributed as well as localized, which is more practical than centralized ones in wireless sensor networks.

Distributed Energy-Efficient Scheduling Approach for K-Coverage in Wireless Sensor Networks

Some sensor network applications require k-coverage to ensure the quality of surveillance. Meanwhile, energy is another primary concern for sensor networks. In this paper, we investigate the Sensor Scheduling for k-Coverage (SSC) problem which requires to efficiently schedule the sensors, such that the monitored region can be k-covered throughout the whole network lifetime with the purpose of maximizing network lifetime. The SSC problem is NP-hard and we propose a heuristic algorithm for it. In addition, we develop a guideline for users to better design a sensor deployment plan to save energy by employing density control. Simulation results are presented to evaluate our proposed algorithm.

Chinh T. Vu

Papers

Composite Event Detection in Wireless Sensor Networks

Transforming Complete Coverage Algorithms to Partial Coverage Algorithms for Wireless Sensor Networks

Delay-Bounded and Energy-Efficient Composite Event Monitoring in Heterogeneous Wireless Sensor Networks

Distributed Energy-Efficient Scheduling Approach for K-Coverage in Wireless Sensor Networks

Sensor scheduling for k-coverage in wireless sensor networks