Information Processing in Sensor Networks 

About: Information Processing in Sensor Networks is an academic conference. The conference publishes majorly in the area(s): Wireless sensor network & Key distribution in wireless sensor networks. Over the lifetime, 1394 publications have been published by the conference receiving 69426 citations.

Telos: enabling ultra-low power wireless research

Abstract: We present Telos, an ultra low power wireless sensor module ("mote") for research and experimentation. Telos is the latest in a line of motes developed by UC Berkeley to enable wireless sensor network (WSN) research. It is a new mote design built from scratch based on experiences with previous mote generations. Telos' new design consists of three major goals to enable experimentation: minimal power consumption, easy to use, and increased software and hardware robustness. We discuss how hardware components are selected and integrated in order to achieve these goals. Using a Texas Instruments MSP430 microcontroller, Chipcon IEEE 802.15.4-compliant radio, and USB, Telos' power profile is almost one-tenth the consumption of previous mote platforms while providing greater performance and throughput. It eliminates programming and support boards, while enabling experimentation with WSNs in both lab, testbed, and deployment settings.

A scheme for robust distributed sensor fusion based on average consensus

Abstract: We consider a network of distributed sensors, where where each sensor takes a linear measurement of some unknown parameters, corrupted by independent Gaussian noises. We propose a simple distributed iterative scheme, based on distributed average consensus in the network, to compute the maximum-likelihood estimate of the parameters. This scheme doesn't involve explicit point-to-point message passing or routing; instead, it diffuses information across the network by updating each node's data with a weighted average of its neighbors' data (they maintain the same data structure). At each step, every node can compute a local weighted least-squares estimate, which converges to the global maximum-likelihood solution. This scheme is robust to unreliable communication links. We show that it works in a network with dynamically changing topology, provided that the infinitely occurring communication graphs are jointly connected.

The Sybil attack in sensor networks: analysis & defenses

Abstract: Security is important for many sensor network applications. A particularly harmful attack against sensor and ad hoc networks is known as the Sybil attack based on J.R. Douceur (2002), where a node illegitimately claims multiple identities. This paper systematically analyzes the threat posed by the Sybil attack to wireless sensor networks. We demonstrate that the attack can be exceedingly detrimental to many important functions of the sensor network such as routing, resource allocation, misbehavior detection, etc. We establish a classification of different types of the Sybil attack, which enables us to better understand the threats posed by each type, and better design countermeasures against each type. We then propose several novel techniques to defend against the Sybil attack, and analyze their effectiveness quantitatively.

Health monitoring of civil infrastructures using wireless sensor networks

Abstract: A Wireless Sensor Network (WSN) for Structural Health Monitoring (SHM) is designed, implemented, deployed and tested on the 4200 ft long main span and the south tower of the Golden Gate Bridge (GGB). Ambient structural vibrations are reliably measured at a low cost and without interfering with the operation of the bridge. Requirements that SHM imposes on WSN are identified and new solutions to meet these requirements are proposed and implemented. In the GGB deployment, 64 nodes are distributed over the main span and the tower, collecting ambient vibrations synchronously at 1 kHz rate, with less than 10 mus jitter, and with an accuracy of 30 muG. The sampled data is collected reliably over a 46-hop network, with a bandwidth of 441 B/s at the 46th hop. The collected data agrees with theoretical models and previous studies of the bridge. The deployment is the largest WSN for SHM.

TinyECC: A Configurable Library for Elliptic Curve Cryptography in Wireless Sensor Networks

Abstract: Public key cryptography (PKC) has been the enabling technology underlying many security services and protocols in traditional networks such as the Internet. In the context of wireless sensor networks, elliptic curve cryptography (ECC), one of the most efficient types of PKC, is being investigated to provide PKC support in sensor network applications so that the existing PKC-based solutions can be exploited. This paper presents the design, implementation, and evaluation of TinyECC, a configurable library for ECC operations in wireless sensor networks. The primary objective of TinyECC is to provide a ready-to-use, publicly available software package for ECC-based PKC operations that can be flexibly configured and integrated into sensor network applications. TinyECC provides a number of optimization switches, which can turn specific optimizations on or off based on developers' needs. Different combinations of the optimizations have different execution time and resource consumptions, giving developers great flexibility in integrating TinyECC into sensor network applications. This paper also reports the experimental evaluation of TinyECC on several common sensor platforms, including MICAz, Tmote Sky, and Imotel. The evaluation results show the impacts of individual optimizations on the execution time and resource consumptions, and give the most computationally efficient and the most storage efficient configuration of TinyECC.