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Proceedings ArticleDOI

On optimal information capture by energy-constrained mobile sensor

TLDR
This work analyzes the expected information captured per unit of energy consumption (IPE) as a function of the event type, the event dynamics, and the speed of the mobile sensor using a realistic energy model of motion.
Abstract
A mobile sensor is used to cover a number of points of interest (PoIs) where dynamic events appear and disappear according to given random processes. It has been shown in [1] that for Step and Exponential utility functions, the quality of monitoring (QoM), i.e., the fraction of information captured about all events, increases as the speed of the sensor increases. This work, however, does not consider the energy of motion, which is an important constraint for mobile sensor coverage. In this paper, we analyze the expected information captured per unit of energy consumption (IPE) as a function of the event type, the event dynamics, and the speed of the mobile sensor. Our analysis uses a realistic energy model of motion, and it allows the sensor speed to be optimized for information capture. We present simulation results to verify and illustrate the analytical results.

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Citations
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Journal ArticleDOI

Achieving Source Location Privacy and Network Lifetime Maximization Through Tree-Based Diversionary Routing in Wireless Sensor Networks

TL;DR: A novel tree-based diversionary routing scheme for preserving source location privacy using hide and seek strategy to create diversionary or decoy routes along the path to the sink from the real source, where the end of each diversionary route is a decoy (fake source node), which periodically emits fake events.
Journal ArticleDOI

Extending the lifetime of wireless sensor networks: A hybrid routing algorithm

TL;DR: This paper mathematically analyzes the power consumption of the proposed algorithm, then demonstrates that the proposed scheme is able to extend the network lifetime by alleviating the hotspot problem.
Journal ArticleDOI

Feedback-Based Clock Synchronization in Wireless Sensor Networks: A Control Theoretic Approach

TL;DR: The results indicate that FBS is much more robust than the delay measurement time-synchronization (DMTS) protocol in different synchronization durations and sensor node configurations and consumes fewer resources than FTSP.
Proceedings ArticleDOI

Practical scheduling for stochastic event capture in wireless rechargeable sensor networks

TL;DR: This work investigates the sensor scheduling problem aiming to maximize the overall Quality of Monitoring (QoM) in events capture application of wireless rechargeable sensor networks and designs an approximation algorithm which achieves a factor of 1/2 of the optimum.
Proceedings ArticleDOI

Energy-constrained mobile sensor with motion plans for monitoring stochastic events

TL;DR: The expected information captured per unit of energy consumption is obtained, which is a function of the event type, the event dynamics, and the velocity of the mobile sensor, which can achieve suboptimal motion plans by adopting existing typical approximation algorithm, and thus enable the sensor velocity to be optimized for capturing stochastic events information.
References
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Journal ArticleDOI

Wireless sensor networks: a survey

TL;DR: The concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics is described.
Journal Article

An Energy-Efficient MAC Protocol for Wireless Sensor Networks

TL;DR: S-MAC as discussed by the authors is a medium access control protocol designed for wireless sensor networks, which uses three novel techniques to reduce energy consumption and support self-configuration, including virtual clusters to auto-sync on sleep schedules.
Proceedings ArticleDOI

An energy-efficient MAC protocol for wireless sensor networks

TL;DR: S-MAC uses three novel techniques to reduce energy consumption and support self-configuration, and applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data move through the network.
Proceedings ArticleDOI

Coverage problems in wireless ad-hoc sensor networks

TL;DR: This work establishes the main highlight of the paper-optimal polynomial time worst and average case algorithm for coverage calculation, which answers the questions about quality of service (surveillance) that can be provided by a particular sensor network.
Proceedings ArticleDOI

The coverage problem in a wireless sensor network

TL;DR: This paper presents polynomial-time algorithms, in terms of the number of sensors, that can be easily translated to distributed protocols, and forms a decision problem to determine whether every point in the service area of the sensor network is covered by at least k sensors.
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