Self-Organized Routing For Wireless Micro-Sensor Networks

In this paper we develop an energy-aware self-organized routing algorithm for the networking of simple battery-powered wireless micro-sensors (as found, for example, in security or environmental monitoring applications). In these networks, the battery life of individual sensors is typically limited by the power required to transmit their data to a receiver or sink. Thus effective network routing algorithms allow us to reduce this power and extend both the lifetime and the coverage of the sensor network as a whole. However, implementing such routing algorithms with a centralized controller is undesirable due to the physical distribution of the sensors, their limited localization ability and the dynamic nature of such networks (given that sensors may fail, move or be added at any time and the communication links between sensors are subject to noise and interference). Against this background, we present a distributed mechanism that enables individual sensors to follow locally selfish strategies, which, in turn, result in the self-organization of a routing network with desirable global properties. We show that our mechanism performs close to the optimal solution (as computed by a centralized optimizer), it deals adaptively with changing sensor numbers and topology, and it extends the useful life of the network by a factor of three over the traditional approach

Energy Model for the Design of Ultra-Low Power Nodes for Wireless Sensor Networks

AbstractThis article describes the modeling of a microsensor node for wireless sensor network applications. Considering the heterogeneous aspect of a sensor node, the developed model allows comparing different node configurations in order to make the best choice of components according to the specifications of the application. Therefore, our model allows identifying the need to design specific element or to use Components Of the Shelf

Energy managed reporting for wireless sensor networks

In this paper, we propose a technique to extend the network lifetime of a wireless sensor network, whereby each sensor node decides its individual network involvement based on its own energy resources and the information contained in each packet. The information content is ascertained through a system of rules describing prospective events in the sensed environment, and how important such events are. While the packets deemed most important are propagated by all sensor nodes, low importance packets are handled by only the nodes with high energy reserves. Results obtained from simulations depicting a wireless sensor network used to monitor pump temperature in an industrial environment have shown that a considerable increase in the network lifetime and network connectivity can be obtained. The results also show that when coupled with a form of energy harvesting, our technique can enable perpetual network operatio

Power Aware Routing for Sensor Databases

Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensor network databases like TinyDB are the dominant architectures to extract and manage data in such networks. Since sensors have significant power constraints (battery life), and high communication costs, design of energy efficient communication algorithms is of great importance. The data flow in a sensor database is very different from data flow in an ordinary network and poses novel challenges in designing efficient routing algorithms. In this work we explore the problem of energy efficient routing for various different types of database queries and show that in general, this problem is NP-complete. We give a constant factor approximation algorithm for one class of query, and for other queries give heuristic algorithms. We evaluate the efficiency of the proposed algorithms by simulation and demonstrate their near optimal performance for various network sizes

Kinetic energy harvesting

This paper reviews kinetic energy harvesting as a potential localised power supply for wireless applications. Harvesting devices are typically implemented as resonant devices of which the power output depends upon the size of the inertial mass, the frequency and amplitude of the driving vibrations, the maximum available mass displacement and the damping. Three transduction mechanisms are currently primarily employed to convert mechanical into electrical energy: electromagnetic, piezoelectric and electrostatic. Piezoelectric and electrostatic mechanisms are best suited to small size MEMS implementations, but the power output from such devices is at present limited to a few microwatts. An electromagnetic generator implemented with discrete components has produced a power 120 ?W with the highest recorded efficiency to date of 51% for a device of this size reported to date. The packaged device is 0.8 cm3 and weighs 1.6 grams. The suitability of the technology in space applications will be determined by the nature of the available kinetic energy and the required level of output power. A radioactively coupled device may present an opportunity where suitable vibrations do not exist

On the Relevance of Using Open Wireless Sensor Networks in Environment Monitoring

This paper revisits the problem of the readiness for field deployments of wireless sensor networks by assessing the relevance of using Open Hardware and Software motes for environment monitoring. We propose a new prototype wireless sensor network that fine-tunes SquidBee motes to improve the life-time and sensing performance of an environment monitoring system that measures temperature, humidity and luminosity. Building upon two outdoor sensing scenarios, we evaluate the performance of the newly proposed energy-aware prototype solution in terms of link quality when expressed by the Received Signal Strength, Packet Loss and the battery lifetime. The experimental results reveal the relevance of using the Open Hardware and Software motes when setting up outdoor wireless sensor networks

Energy and quality scalable wireless communication

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 165-171).Nodes for emerging, high-density wireless networks will face the dual challenges of continuous, multi-year operation under diverse and challenging operating conditions. The wireless communication subsystem, a substantial consumer of energy, must therefore be designed with unprecedented energy efficiency. To meet this challenge, inefficiencies once overlooked must be addressed, and the system must be designed for energy scalability, the use of graceful energy vs. quality trade-offs in response to continuous variations in operational conditions. Using a comprehensive model framework that unifies cross-disciplinary models for energy consumption and communication performance, this work explores multi-dimensional trade-offs of energy and quality for wireless communication at all levels of the system hierarchy. The circuit-level "knob" of dynamic voltage scaling is implemented on a commercial microprocessor and integrated into a power aware, prototype microsensor node. Power aware abstractions encourage collaboration between the hardware, which fundamentally dissipates the energy, and software, which controls how the hardware behaves. Accurate models of hardware energy consumption reveal inefficiencies of routing techniques such as multihop, and the models are fused with information-theoretic limits on code performance to bound the energy scalability of the hardware platform. An application-specific protocol for microsensor networks is evaluated with a new, interactive Java simulation tool created expressly for energy-conscious, high density wireless networks. Close collaboration between software and hardware layers, and across the research disciplines that compose wireless communication itself, are crucial enablers for energy-efficient wireless communication.by Rex Kee Min.Ph.D

Study of Energy Efficient Clustering Algorithms for Wireless Sensor Network

Energy utilization and network life time are key issues in design of routing protocols for Wireless sensor network. Many algorithms have been proposed for reducing energy consumption and to increase network life time of the WSN. Clustering algorithms have gained popularity in this field, because of their approach in cluster head selection and data aggregation. LEACH (distributed) is the first clustering routing protocol which is proven to be better compared to other such algorithms. TL-LEACH is one of the descendants of LEACH that saves better the energy consumption by building a two-level hierarchy. It uses random rotation of local cluster base stations to better distribute the energy load among the sensors in the network especially when the density of network is higher. As the clusters are adaptive in LEACH and TL-LEACH, poor clustering set-up during a round will affect overall performance. However, using a central control scheme for cluster set-up may produce better clusters by distributing the cluster head nodes throughout the network. LEACH-C is another modification to LEACH that realizes the above idea and provides better results through uniform distribution of cluster heads avoiding redundant creation of cluster heads in a small area. In our project, we propose a centralized multilevel scheme called CML-LEACH for energy efficient clustering that assumes random distribution of sensor nodes which are not mobile. The proposed scheme merges the idea of multilevel hierarchy, with that of the central control algorithm providing uniform distribution of cluster heads throughout the network, better distribution of load among the sensors and improved packet aggregation. This scheme reduces energy consumption and prolongs network life time significantly as compared to LEACH, TL-LEACH and LEACH-C. The simulation results show comparisons of our scheme with the existing LEACH, TL-LEACH and LEACH-C protocols against chosen performance metrics, using Omnet++