http://www.eecs.ucf.edu/~dcm/Teaching/COT4810-Spring2011/Literature/SensorNetworksSurvey.pdf

Wireless sensor networks: a survey

Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose 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. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.

/pdf/energy-efficient-communication-protocol-for-wireless-4vhuagusz2.pdf

Energy-efficient communication protocol for wireless microsensor networks

Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have signicant impact on the overall energy dissipation of these networks. Based on our ndings that the conventional protocols of direct transmission, minimum-transmission-energy, multihop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster base stations (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show that LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional routing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.

Energy-efficient communication protocols for wireless microsensor networks

Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze 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. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.

/pdf/an-application-specific-protocol-architecture-for-wireless-1s7y9fiv40.pdf

An application-specific protocol architecture for wireless microsensor networks

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

This paper describes a method for learning coordination policies in body sensor networks. The learning of a compact coordination policy is important for implementing the policy in sensor nodes with limited memory. We present a novel algorithm, Reinforcement Learning Average Approximation (RLAA), to learn local coordination policies for each sensor node from globally joint rewards. These local policies are obtained by reinforcement learning and averaging state-action tables under a stochastic process model. We show results on a simulation of an existing body sensor network interfaced with transdermal sensors that demonstrate the performance of this learning scheme. Experimental results show that the performance of the RLAA algorithm is significantly better than a random policy and is close to the optimal policy that can be obtained from solving a global Markov Decision Process while the learning step is fast. The results also show that the RLAA algorithm is scalable to networks represented by large state spaces (in terms of number s of sensors and degree of discretization).

Learning a Policy for Coordinated Sampling in Body Sensor Networks

Adaptive array antennas have the ability to respond automatically to an unknown interference environment, in real time, by steering nulls and reducing side lobe levels in the direction of interference, while retaining some desired signal beam characteristics. We present a protocol (ADAPT) that enables nodes in an ad hoc network to utilize adaptive array antennas efficiently to communicate. We compare our adaptive antenna configuration {ADAPT, adaptive array antennas} to both an omni-directional setting {802.11, omni-directional antennas} and a directional one {DMAC protocol, directional antennas} in terms of network throughput and end-to-end delay. The DMAC protocol is described by M. Takai et al. (see Proc. ACM MobiHoc, 2002) and R. Roychoudhury et al. (see Proc. MOBICOM 2002). Our protocol achieves up to a 60% throughput and 2-3 times delay improvement over the omni-directional case and up to a 40% throughput and 55% delay improvement over the directional one, in most scenarios considered.

/pdf/adapt-a-media-access-control-protocol-for-mobile-ad-hoc-4o8nmb28r9.pdf

ADAPT: a media access control protocol for mobile ad hoc networks using adaptive array antennas

Wireless microsensor networks have gained great momentum due to collaborative research efforts on various disciplines. It has made many useful applications possible. In a typical sensor network application, in order to operate for a long period of time, sensor nodes need to conserve energy. In this paper, a multi-hop tripwire detection and cueing scheme is proposed for energy conservation in wireless sensor networks. It uses a cueing protocol and a detection algorithm to enable a two-tier sensor network for energy conservation. The proposed scheme overcomes the false alarm problem and the exposed alarm problem in sensor network applications. For a typical application scenario of sensor networks, our simulation results show that a two-tier sensor network employing the proposed scheme can reduce energy consumption by about 55% when compared to a homogeneous sensor network.

/pdf/power-aware-wireless-sensor-networks-using-tripwire-37v993jeol.pdf

Power Aware Wireless Sensor Networks Using Tripwire Detection and Cueing

Dynamic Relibility Modeling and Analysis of Computer Networks.

The reliability of a distributed system depends on the reliabilities of its communication links and computing elements, as well as on the distribution of its resources, such as programs and data files. A useful measure of reliability in distributed systems is the terminal reliability between a pair of nodes which is the probability that at least one communication path exists between these nodes. An interesting optimization problem is that of maximizing the terminal reliability between a pair of computing elements under a given budget constraint. Analytical techniques to solve this problem are applicable only to special forms of reliability expressions. In this paper, three iterative algorithms for terminal reliability maximization are presented. The first two algorithms require the computation of terminal reliability expressions, and are therefore efficient for only small networks. The third algorithm, which is developed for large distributed systems, does not require the computation of terminal reliability expressions; this algorithm maximizes approximate objective functions and gives accurate results. Several examples are presented to illustrate the approximate optimization algorithm and an estimation of the error involved is also given.

Cauligi S. Raghavendra

Papers

Learning a Policy for Coordinated Sampling in Body Sensor Networks

ADAPT: a media access control protocol for mobile ad hoc networks using adaptive array antennas

Power Aware Wireless Sensor Networks Using Tripwire Detection and Cueing

Dynamic Relibility Modeling and Analysis of Computer Networks.

Reliability optimization in the design of distributed systems.