Event-driven field estimation for wireless sensor networks

This paper introduces and analyzes a field estimation scheme for wireless sensor networks. Our scheme imitates the response of living beings to the surrounding events. The sensors define their periphery of attention based on their own readings. Readings differing from the expected behavior are considered events of interest and trigger the data transmission to the sink. The presented scheme is evaluated with real-site-collected data and the tradeoff between the amount of data sent to the sink and the reconstruction error is analyzed. Results show that signifcant reduction in the data transmission and, as a consequence, in the energy consumption of the network is achievable while keeping low the average reconstruction error.8th IFIP/IEEE International conference on Mobile and Wireless CommunicationRed de Universidades con Carreras en Informática (RedUNCI

Event-driven field estimation for wireless sensor networks

This paper introduces and analyzes a field estimation scheme for wireless sensor networks. Our scheme imitates the response of living beings to the surrounding events. The sensors define their periphery of attention based on their own readings. Readings differing from the expected behavior are considered events of interest and trigger the data transmission to the sink. The presented scheme is evaluated with real-site-collected data and the tradeoff between the amount of data sent to the sink and the reconstruction error is analyzed. Results show that signifcant reduction in the data transmission and, as a consequence, in the energy consumption of the network is achievable while keeping low the average reconstruction error.8th IFIP/IEEE International conference on Mobile and Wireless CommunicationRed de Universidades con Carreras en Informática (RedUNCI

Event-driven field estimation for wireless sensor networks

This paper introduces and analyzes a field estimation scheme for wireless sensor networks. Our scheme imitates the response of living beings to the surrounding events. The sensors define their periphery of attention based on their own readings. Readings differing from the expected behavior are considered events of interest and trigger the data transmission to the sink. The presented scheme is evaluated with real-site-collected data and the tradeoff between the amount of data sent to the sink and the reconstruction error is analyzed. Results show that signifcant reduction in the data transmission and, as a consequence, in the energy consumption of the network is achievable while keeping low the average reconstruction error.8th IFIP/IEEE International conference on Mobile and Wireless CommunicationRed de Universidades con Carreras en Informática (RedUNCI

Predictive Duty Cycle Adaptation for Wireless Camera Networks

Wireless sensor networks (WSN) typically employ dynamic duty cycle schemes to efficiently handle different patterns of communication traffic in the network. However, existing duty cycling approaches are not suitable for event-driven WSN, in particular, camera-based networks designed to track humans and objects. A characteristic feature of such networks is the spatially-correlated bursty traffic that occurs in the vicinity of potentially highly mobile objects. In this paper, we propose a concept of indirect sensing in the MAC layer of a wireless camera network and an active duty cycle adaptation scheme based on Kalman filter that continuously predicts and updates the location of the object that triggers bursty communication traffic in the network. This prediction allows the camera nodes to alter their communication protocol parameters prior to the actual increase in the communication traffic. Our simulations demonstrate that our active adaptation strategy outperforms TMAC not only in terms of energy efficiency and communication latency, but also in terms of TIBPEA, a QoS metric for event-driven WSN

Autonomous monitoring framework for resource-constrained environments

Acknowledgments The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub, reference: EP/G066051/1. URL: http://www.dotrural.ac.uk/RemoteStream/Peer reviewedPublisher PD

mTOSSIM: A simulator that estimates battery lifetime in wireless sensor networks

Knowledge of the battery lifetime of the wireless sensor network is important for many situations, such as in evaluation of the location of nodes or the estimation of the connectivity, along time, between devices. However, experimental evaluation is a very time-consuming task. It depends on many factors, such as the use of the radio transceiver or the distance between nodes. Simulations reduce considerably this time. They allow the evaluation of the network behavior before its deployment. This article presents a simulation tool which helps developers to obtain information about battery state. This simulator extends the well-known TOSSIM simulator. Therefore it is possible to evaluate TinyOS applications using an accurate model of the battery consumption and its relation to the radio power transmission. Although an specific indoor scenario is used in testing of simulation, the simulator is not limited to this environment. It is possible to work in outdoor scenarios too. Experimental results validate the proposed model.Junta de Andalucía P07-TIC-02476Junta de Andalucía TIC-570

Distributed Object Tracking Using a Cluster-Based Kalman Filter in Wireless Camera Networks

Local data aggregation is an effective means to save sensor node energy and prolong the lifespan of wireless sensor networks. However, when a sensor network is used to track moving objects, the task of local data aggregation in the network presents a new set of challenges, such as the necessity to estimate, usually in real time, the constantly changing state of the target based on information acquired by the nodes at different time instants. To address these issues, we propose a distributed object tracking system which employs a cluster-based Kalman filter in a network of wireless cameras. When a target is detected, cameras that can observe the same target interact with one another to form a cluster and elect a cluster head. Local measurements of the target acquired by members of the cluster are sent to the cluster head, which then estimates the target position via Kalman filtering and periodically transmits this information to a base station. The underlying clustering protocol allows the current state and uncertainty of the target position to be easily handed off among clusters as the object is being tracked. This allows Kalman filter-based object tracking to be carried out in a distributed manner. An extended Kalman filter is necessary since measurements acquired by the cameras are related to the actual position of the target by nonlinear transformations. In addition, in order to take into consideration the time uncertainty in the measurements acquired by the different cameras, it is necessary to introduce nonlinearity in the system dynamics. Our object tracking protocol requires the transmission of significantly fewer messages than a centralized tracker that naively transmits all of the local measurements to the base station. It is also more accurate than a decentralized tracker that employs linear interpolation for local data aggregation. Besides, the protocol is able to perform real-time estimation because our implementation takes into consideration the sparsit- - y of the matrices involved in the problem. The experimental results show that our distributed object tracking protocol is able to achieve tracking accuracy comparable to the centralized tracking method, while requiring a significantly smaller number of message transmissions in the network

Adaptive Duty Cycling MAC Protocols Using Closed-Loop Control for Wireless Sensor Networks

The fundamental design goal of wireless sensor MAC protocols is to minimize unnecessary power consumption of the sensor nodes, because of its stringent resource constraints and ultra-power limitation. In existing MAC protocols in wireless sensor networks (WSNs), duty cycling, in which each node periodically cycles between the active and sleep states, has been introduced to reduce unnecessary energy consumption. Existing MAC schemes, however, use a fixed duty cycling regardless of multi-hop communication and traffic fluctuations. On the other hand, there is a tradeoff between energy efficiency and delay caused by duty cycling mechanism in multi-hop communication and existing MAC approaches only tend to improve energy efficiency with sacrificing data delivery delay. In this paper, we propose two different MAC schemes (ADS-MAC and ELA-MAC) using closed-loop control in order to achieve both energy savings and minimal delay in wireless sensor networks. The two proposed MAC schemes, which are synchronous and asynchronous approaches, respectively, utilize an adaptive timer and a successive preload frame with closed-loop control for adaptive duty cycling. As a result, the analysis and the simulation results show that our schemes outperform existing schemes in terms of energy efficiency and delivery delay