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Proceedings ArticleDOI

A Realistic Power Consumption Model for Wireless Sensor Network Devices

Qin Wang, +2 more
- Vol. 1, pp 286-295
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TLDR
A realistic power consumption model of wireless communication subsystems typically used in many sensor network node devices is presented and it is shown that whenever single hop routing is possible it is almost always more power efficient than multi-hop routing.
Abstract
A realistic power consumption model of wireless communication subsystems typically used in many sensor network node devices is presented. Simple power consumption models for major components are individually identified, and the effective transmission range of a sensor node is modeled by the output power of the transmitting power amplifier, sensitivity of the receiving low noise amplifier, and RF environment. Using this basic model, conditions for minimum sensor network power consumption are derived for communication of sensor data from a source device to a destination node. Power consumption model parameters are extracted for two types of wireless sensor nodes that are widely used and commercially available. For typical hardware configurations and RF environments, it is shown that whenever single hop routing is possible it is almost always more power efficient than multi-hop routing. Further consideration of communication protocol overhead also shows that single hop routing will be more power efficient compared to multi-hop routing under realistic circumstances. This power consumption model can be used to guide design choices at many different layers of the design space including, topology design, node placement, energy efficient routing schemes, power management and the hardware design of future wireless sensor network devices

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Citations
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Journal ArticleDOI

Deployment of Distributed Applications in Wireless Sensor Networks

TL;DR: Simulation results show that the framework results in considerable energy conservation with respect to sink-oriented or cluster-oriented deployment approaches, particularly for networks with high node densities, non-uniform energy consumption and initial energy, and complex actions.
Journal ArticleDOI

Modulation and SNR Optimization for Achieving Energy-Efficient Communications over Short-Range Fading Channels

TL;DR: This paper presents a model that determines the energy consumed per payload bit transferred without error over fading channels of various statistics and finds that each modulation scheme has a single optimal signal-to-noise ratio (SNR) at which the energy consumption is minimized.
Journal ArticleDOI

Lifetime Maximization in Cognitive Sensor Networks Based on the Node Selection

TL;DR: This paper proposes two methods for maximizing the lifetime of the cognitive sensor networks by focusing on node selection criteria for spectrum sensing in such networks by relaxing the method to a more tractable form.
Book ChapterDOI

Analyzing mobile application software power consumption via model-driven engineering

TL;DR: The System Power Optimization Tool (SPOT) is described, which is a model-driven tool that automates power consumption emulation code generation and simplifies analysis and empirically demonstrates how SPOT can estimate power consumption to within ∼3-4% of actual power consumption for representative smartphone applications.
Proceedings ArticleDOI

Discrete Radio Power Level Consumption Model in Wireless Sensor Networks

TL;DR: This work combines realistic radio consumption models, signal strength estimation and that reception cost may be more than the transmission cost into a single model for estimating radio power costs.
References
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Proceedings ArticleDOI

Energy-efficient communication protocol for wireless microsensor networks

TL;DR: The Low-Energy Adaptive Clustering Hierarchy (LEACH) as mentioned in this paper is a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network.

Energy-efficient communication protocols for wireless microsensor networks

TL;DR: LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network, is proposed.
Journal ArticleDOI

An application-specific protocol architecture for wireless microsensor networks

TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
Journal Article

The design of CMOS radio-frequency integrated circuits, 2nd edition

TL;DR: This expanded and thoroughly revised edition of Thomas H. Lee's acclaimed guide to the design of gigahertz RF integrated circuits features a completely new chapter on the principles of wireless systems.
Book

The Design of CMOS Radio-Frequency Integrated Circuits

TL;DR: In this article, the authors present an expanded and thoroughly revised edition of Tom Lee's acclaimed guide to the design of gigahertz RF integrated circuits, which is packed with physical insights and design tips, and includes a historical overview of the field in context.
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