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

Sensor networks are used in a variety of applications for event monitoring, environmental sensing and outer space exploration. An important application is detecting a target in the field using sensors gathering acoustic data. In this target detection application (ATR), a cluster of wireless sensors collected acoustic data and perform signal processing. In the algorithm used for signal processing, acoustic data collected by the sensors need to be communicated to a designated head node for determining the target direction of bearing. The data collected by geometrically closely distributed sensors show high spatial correlation. In this paper, our focus is on energy efficient coding schemes for wireless sensor networks. First we give an analysis to show why conventional compression scheme give poor performance when energy consumption for encoding and decoding processing overheads are considered. We then describe a new coding scheme called EEADSC, which minimizes the Lagrangian cost function. The proposed scheme fully exploits spatial correlation in wireless sensor network and is adaptive according to tracking signal strength. We evaluated the proposed scheme using datasets from an ATR application, which achieved up to a factor of 8 data compression. EEADSC uses TCQ quantization and trellis encoding to represent a 16 bit data value by as few as 2 bits. With the scheme, we reduce the overall energy cost for communication in this application by a factor of 2.53, including the overhead processing cost in encoding/decoding. The scheme also fits well for general sensor network applications in which some data collection and aggregation are performed.

An energy efficient adaptive distributed source coding scheme in wireless sensor networks

Performance Analysis of a Redundant-Path Interconnection Network.

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. 
In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.

Datacenter Traffic Control: Understanding Techniques and Trade-offs

The reliability analysis of computer communication networks is generally based on Boolean algebra and probability theory. This paper discusses various reliability problems of computer networks including terminal-pair connectivity, tree connectivity, and multi-terminal connectivity. This paper also studies the dynamic computer network reliability by deriving time-dependent expressions for reliability measures assuming Markov behavior for failures and repairs. This allows computation of task and mission related measures such as mean time to first failure and mean time between failures. A detailed analysis of the bridge network is presented.

Reliability Modeling and Analysis of Computer Networks

The authors present self-routing algorithms for realizing the class of linear permutations in various multistage networks such as Benes and 2n-stage shuffle-exchange. Linear permutations are useful in providing fast access of data arrays. In the first half of the network, switches are set by comparing the destination tags at their inputs, and, in the second half, switches are set using the Omega self-routing algorithm. It is shown that the comparison operations can be implemented in bit-serial networks without loss of time. In contrast, with the well-known Benes network self-routing algorithm of D. Nassimi and S. Sahni (1981), switches are set by giving priority to the destination tag at the upper input to them. The algorithms presented are useful in providing fast access of various data patterns using interconnection networks cheaper than crossbars. >

Cauligi S. Raghavendra

Papers

An energy efficient adaptive distributed source coding scheme in wireless sensor networks

Performance Analysis of a Redundant-Path Interconnection Network.

Datacenter Traffic Control: Understanding Techniques and Trade-offs

Reliability Modeling and Analysis of Computer Networks

On Self Routing in Benes and Shuffle Exchange Networks.