We consider a two-tiered Wireless Sensor Network (WSN) consisting of sensor clusters deployed around strategic locations and base-stations (BSs) whose locations are relatively flexible. Within a sensor cluster, there are many small sensor nodes (SNs) that capture, encode and transmit relevant information from the designated area, and there is at least one application node (AN) that receives raw data from these SNs, creates a comprehensive local-view, and forwards the composite bit-stream toward a BS. In practice, both SN and AN are battery-powered and energy-constrained, and their node lifetimes directly affect the network lifetime of WSNs. In this paper, we focus on the topology control process for ANs and BSs, which constitute the upper tier of a two-tiered WSN. We propose approaches to maximize the topological network lifetime of the WSN, by arranging BS location and inter-AN relaying optimally. Based on an algorithm in Computational Geometry, we derive the optimal BS locations under three topological lifetime definitions according to mission criticality. In addition, by studying the intrinsic properties of WSNs, we establish the upper and lower bounds of their maximal topological lifetime. When inter-AN relaying becomes feasible and favorable, we continue to develop an optimal parallel relay allocation to further prolong the topological lifetime of the WSN. An equivalent serialized relay schedule is also obtained, so that each AN only needs to have one relay destination at any time throughout the mission. The experimental performance evaluation demonstrates the efficacy of topology control as a vital process to maximize the network lifetime of WSNs.

https://graphics.stanford.edu/projects/geometry/MobiCom03/a286.pdf

Topology control for wireless sensor networks

Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations and over a long period of time. The results from the real-world experiments demonstrate that 1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability and 2) with online control, ATPC is robust even with environmental changes over time.

/pdf/atpc-adaptive-transmission-power-control-for-wireless-sensor-4hm939kxro.pdf

ATPC: adaptive transmission power control for wireless sensor networks

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

A Realistic Power Consumption Model for Wireless Sensor Network Devices

As new fabrication and integration technologies reduce the cost and size of micro-sensors and wireless interfaces, it becomes feasible to deploy densely distributed wireless networks of sensors and actuators. These systems promise to revolutionize biological, earth, and environmental monitoring applications, providing data at granularities unrealizable by other means. In addition to the challenges of miniaturization, new system architectures and new network algorithms must be developed to transform the vast quantity of raw sensor data into a manageable stream of high-level data. To address this, we propose a tiered system architecture in which data collected at numerous, inexpensive sensor nodes is filtered by local processing on its way through to larger, more capable and more expensive nodes.We briefly describe Habitat monitoring as our motivating application and introduce initial system building blocks designed to support this application. The remainder of the paper presents details of our experimental platform.

Habitat monitoring: Application driver for wireless communications technology

A wireless sensor network with multimedia capabilities typically consists of data sensor nodes, which sense, for instance, sound or motion, and video sensor nodes, which capture video of events of interest. In this survey, we focus on the video encoding at the video sensors and the real-time transport of the encoded video to a base station. Real-time video streams have stringent requirements for end-to-end delay and loss during network transport. In this survey, we categorize the requirements of multimedia traffic at each layer of the network protocol stack and further classify the mechanisms that have been proposed for multimedia streaming in wireless sensor networks at each layer of the stack. Specifically, we consider the mechanisms operating at the application, transport, network, and MAC layers. We also review existing cross-layer approaches and propose a few possible cross-layer solutions to optimize the performance of a given wireless sensor network for multimedia streaming applications.

/pdf/a-survey-of-multimedia-streaming-in-wireless-sensor-networks-50x2szpgry.pdf

A survey of multimedia streaming in wireless sensor networks

In a wireless, multi-hop sensor network, choosing transmission power levels has an important impact on energy efficiency and network lifetime. Two algorithms for dynamically adjusting transmission power level on a per-node basis are proposed here. Network lifetime, convergence speed as well as resulting network connectivity are used as figures of merit for these two algorithms. They have been evaluated in an indoor sensor environment. The network lifetime metrics of these two local algorithms are also benchmarked against power control algorithms using global information. We show that these local algorithms outperform fixed power level assignment and that the lifetime achieved by them is usually within a factor of two of globally computed solution while being scalable.

Distributed algorithms for transmission power control in wireless sensor networks

The common belief is that a multi-hop configuration with rather small per-hop distance is the only viable energy-efficient option for wireless sensor networks. We discuss a single hop configuration, utilizing the asymmetry between lightweight sensor nodes and a more powerful "base station" and demonstrate that such a single hop configuration can actually have lower overall power consumption than a multi-hop counterpart.

/pdf/does-proper-coding-make-single-hop-wireless-sensor-networks-4emtwxp0aw.pdf

Does proper coding make single hop wireless sensor networks reality: the power consumption perspective

In this paper we integrate the energy models of all the components of the data link layer of a wireless sensor network into a single framework, which interacts with the abstracted models of the network layer, the physical layer, and the channel. Such a framework enables intra layer and cross layer optimization. By identifying the important design parameters, it provides the venues and guidelines for energy' reduction and design improvement, as demonstrated in the paper. The validity of the models is verified using OMNET++ network simulations.

/pdf/an-integrated-data-link-energy-model-for-wireless-sensor-4bkt96ixx9.pdf

L.C. Zhong

Papers

Distributed algorithms for transmission power control in wireless sensor networks

Does proper coding make single hop wireless sensor networks reality: the power consumption perspective

An integrated data-link energy model for wireless sensor networks