Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks

Abstract

We consider the problem of decentralized hypothesis testing in a network of energy harvesting sensors, where sensors make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center. The fusion center makes a decision about the present hypothesis using the aggregate received data during a time interval. We explicitly consider a scenario under which the messages are sent through parallel access channels towards the fusion center. To avoid limited lifetime issues, we assume each sensor is capable of harvesting all the energy it needs for the communication from the environment. Each sensor has an energy buffer (battery) to save its harvested energy for use in other time intervals. Our key contribution is to formulate the problem of decentralized detection in a sensor network with energy harvesting devices. Our analysis is based on a queuing-theoretic model for the battery and we propose a sensor decision design method by considering long term energy management at the sensors. We show how the performance of the system changes for different battery capacities. We then numerically show how our findings can be used in the design of sensor networks with energy harvesting sensors.

Robust distributedH∞filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

“…Remark 6. In this paper, time-varying delay and norm-bounded uncertainties have been considered in the system model (1). Moreover, the measurement model (4) is in the general form and includes the multiple fading measurements and stochastic time-varying delays and norm-bounded uncertainties simultaneously, which make the design of distributed H ∞ filter more intricate.…”

“…A sensor network is composed of a large number of sensor nodes that are spatially distributed and coordinated to perform some particular tasks in a collaborative manner. In recent years, due to the advantages of network systems such as low cost, low power requirements, simple installation and maintenance, and also the rapid developments of communication technologies, the applications of sensor networks have been extensively investigated in a wide range of areas such as environment and habitat monitoring, distributed robotics, industrial automation, health care, and traffic control …”

“…In recent years, due to the advantages of network systems such as low cost, low power requirements, simple installation and maintenance, and also the rapid developments of communication technologies, the applications of sensor networks have been extensively investigated in a wide range of areas such as environment and habitat monitoring, distributed robotics, industrial automation, health care, and traffic control. [1][2][3][4] The distributed filtering or estimation problem over sensor networks has attracted great attention recently. [5][6][7][8] In a distributed filtering scheme over sensor network, each sensor node can receive the measurements not only from its own but also from its neighboring nodes according to the given network topology.…”

Optimal Local Thresholds for Distributed Detection in Energy Harvesting Wireless Sensor Networks

“…The designs of wireless sensor networks to perform the task of distributed detection are often based on the conventional battery-powered sensors, leading into designs with a short lifetime, due to battery depletion [1], [2], [3]. Recently, energy harvesting, which can collect energy from renewable resources in ambient environment (e.g., solar, wind, and geothermal energy) has attracted much attention [4], [5].…”

“…Recently, energy harvesting, which can collect energy from renewable resources in ambient environment (e.g., solar, wind, and geothermal energy) has attracted much attention [4], [5]. Energy harvesting technology in wireless sensor networks promises a selfsustainable system with a lifetime that is not limited by the lifetime of the conventional batteries [2], [6], [7].…”