17,547 research outputs found
Optimal data collection in wireless sensor networks with correlated energy harvesting
We study the optimal data collection rate in a hybrid wireless sensor network where sensor data is collected by mobile
sinks. In such networks, there is a trade-off between the cost of data collection and the timeliness of the data. We further
assume that the sensor node under study harvests its energy from its environment. Such energy harvesting sensors ideally operate energy neutral, meaning that they can harvest the necessary energy to sense and transmit data, and have on-board rechargeable batteries to level out energy harvesting fluctuations. Even with batteries, fluctuations in energy harvesting can considerably affect performance, as it is not at all unlikely that a sensor node runs out of energy, and is neither able to sense nor to transmit data. The energy harvesting process also influences the cost vs. timeliness trade-off as additional data collection requires additional energy as well. To study this trade-off, we propose an analytic model for the value of the information that a sensor node brings to decision-making. We account for the timeliness of the data by discounting the value of the information at the sensor over time, we adopt the energy chunk approach (i.e. discretise the energy level) to track energy harvesting and expenditure over time, and introduce correlation in the energy harvesting process to study its influence on the optimal collection rate
Source-Channel Coding under Energy, Delay and Buffer Constraints
Source-channel coding for an energy limited wireless sensor node is
investigated. The sensor node observes independent Gaussian source samples with
variances changing over time slots and transmits to a destination over a flat
fading channel. The fading is constant during each time slot. The compressed
samples are stored in a finite size data buffer and need to be delivered in at
most time slots. The objective is to design optimal transmission policies,
namely, optimal power and distortion allocation, over the time slots such that
the average distortion at destination is minimized. In particular, optimal
transmission policies with various energy constraints are studied. First, a
battery operated system in which sensor node has a finite amount of energy at
the beginning of transmission is investigated. Then, the impact of energy
harvesting, energy cost of processing and sampling are considered. For each
energy constraint, a convex optimization problem is formulated, and the
properties of optimal transmission policies are identified. For the strict
delay case, , waterfilling interpretation is provided. Numerical
results are presented to illustrate the structure of the optimal transmission
policy, to analyze the effect of delay constraints, data buffer size, energy
harvesting, processing and sampling costs.Comment: 30 pages, 15 figures. Submitted to IEEE Transactions on Wireless
Communication
Capacity of Fading Gaussian Channel with an Energy Harvesting Sensor Node
Network life time maximization is becoming an important design goal in
wireless sensor networks. Energy harvesting has recently become a preferred
choice for achieving this goal as it provides near perpetual operation. We
study such a sensor node with an energy harvesting source and compare various
architectures by which the harvested energy is used. We find its Shannon
capacity when it is transmitting its observations over a fading AWGN channel
with perfect/no channel state information provided at the transmitter. We
obtain an achievable rate when there are inefficiencies in energy storage and
the capacity when energy is spent in activities other than transmission.Comment: 6 Pages, To be presented at IEEE GLOBECOM 201
Optimal Energy Management Policies for Energy Harvesting Sensor Nodes
We study a sensor node with an energy harvesting source. The generated energy
can be stored in a buffer. The sensor node periodically senses a random field
and generates a packet. These packets are stored in a queue and transmitted
using the energy available at that time. We obtain energy management policies
that are throughput optimal, i.e., the data queue stays stable for the largest
possible data rate. Next we obtain energy management policies which minimize
the mean delay in the queue.We also compare performance of several easily
implementable sub-optimal energy management policies. A greedy policy is
identified which, in low SNR regime, is throughput optimal and also minimizes
mean delay.Comment: Submitted to the IEEE Transactions on Wireless Communications; 22
pages with 10 figure
Energy Harvesting - Wireless Sensor Networks for Indoors Applications Using IEEE 802.11
AbstractThe paper investigates the feasibility of using IEEE 802.11 in energy harvesting low-power sensing applications. The investigation is based on a prototype carbon dioxide sensor node that is powered by artificial indoors light. The wireless communication module of the sensor node is based on the RTX4100 module. RTX4100 incorporates a wireless protocol that duty-cycles the radio while being compatible with IEEE 802.11 access points. The presented experiments demonstrate sustainable operation but indicate a trade-off between the benefits of using IEEE 802.11 in energy harvesting applications and the energy-efficiency of the system
Flexible Integration of Alternative Energy Sources for Autonomous Sensing
Recent developments in energy harvesting and autonomous sensing mean that it is now possible to power sensors solely from energy harvested from the environment. Clearly this is dependent on sufficient environmental energy being present. The range of feasible environments for operation can be extended by combining multiple energy sources on a sensor node. The effective monitoring of their energy resources is also important to deliver sustained and effective operation. This paper outlines the issues concerned with combining and managing multiple energy sources on sensor nodes. This problem is approached from both a hardware and embedded software viewpoint. A complete system is described in which energy is harvested from both light and vibration, stored in a common energy store, and interrogated and managed by the node
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