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Field Estimation in Wireless Sensor Networks Using Distributed Kriging Field Estimation in Wireless Sensor Networks Using Distributed Kriging

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Date added: 10/28/2012
Date modified: 12/28/2013
Filesize: 398.05 kB
Downloads: 1839

 

In this paper, we tackle the problem of spatial interpolation for distributed estimation in Wireless Sensor Networks by using a geostatistical technique called kriging. We present a novel Distributed Iterative Kriging Algorithm (DIKA) which is composed of two main phases. First, the spatial dependence of the field is exploited by calculating semivariograms in an iterative way. Second, the kriging system of equations is solved by an initial set of nodes in a distributed manner, providing some initial interpolation weights to each node. In our algorithm, the estimation accuracy can be improved by iteratively adding new nodes and updating appropriately the weights, which leads to a reduction in the kriging variance. As a consequence, each cluster is constructed adaptively by the set of nodes that achieves the best estimation over the sub-area covered by them. We analyze the most influential parameters to implement this algorithm. Finally, we evaluate the performance of our algorithm and we also analyze its complexity.

Real-time scheduling in LTE for smart grids Real-time scheduling in LTE for smart grids

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Date added: 02/06/2013
Date modified: 12/28/2013
Filesize: 286 Bytes
Downloads: 1826

 

The latest wireless network, 3GPP Long Term Evolution (LTE), is considered to be a promising solution for smart grids because it provides both low latency and large bandwidth. However, LTE was not originally intended for smart grids applications, where data generated by the grid have specific delay requirements that are different from traditional data or voice communications. In this paper, the specific requirements imposed by a smart grids on the LTE communication infrastructure is first determined. The latency offered by the LTE network to smart grids components is investigated and an empirical mathematical model of the distribution of the latency is established. It is shown by experimental results that with the current LTE up-link scheduler, smart grid latency requirements are not always satisfied and that only a limited number of components can be accommodated. To overcome such a deficiency, a new scheduler of the LTE medium access control is proposed for smart grids. The scheduler is based on a mathematical linear optimization problem that considers simultaneously both the smart grid components and common user equipments. An algorithm for the solution to such a problem is derived based on a theoretical analysis. Simulation results based on this new scheduler illustrate the analysis. It is concluded that LTE can be effectively used in smart grids if new schedulers are employed for improving latency.

Analytical Modeling of Multi-hop IEEE 802.15.4 Networks Analytical Modeling of Multi-hop IEEE 802.15.4 Networks

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Date added: 02/06/2013
Date modified: 02/07/2014
Filesize: 286 Bytes
Downloads: 1749

 

Many of the existing analytical studies of the IEEE 802.15.4 medium access control (MAC) protocol are not adequate because they are often based on assumptions such as homogeneous traffic and ideal carrier sensing, which are far from the reality for multi-hop networks, particularly in the presence of mobility. In this paper, a new generalized analysis of the unslotted IEEE 802.15.4 MAC is presented. The analysis considers the effects induced by heterogeneous traffic due to multi-hop routing and different traffic generation patterns among the nodes of the network, and the hidden terminals due to reduced carrier sensing capabilities. The complex relation between MAC and routing protocols is modeled and novel results on this interaction are derived. For various network configurations, it is studied under which conditions routing decisions based on packet loss probability or delay lead to an unbalanced distribution of the traffic load across multi-hop paths. It is shown that these routing decisions tend to direct traffic toward nodes with high packet generation rates, with potential catastrophic effects for the node’s energy consumption. It is concluded that heterogeneous traffic and limited carrier sensing range play an essential role on the performance and that routing should account for the presence of dominant nodes to balance the traffic distribution across the network.

Rate Allocation for Quantized Control Over Binary Symmetric Channels Rate Allocation for Quantized Control Over Binary Symmetric Channels

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Date added: 01/29/2013
Date modified: 08/03/2013
Filesize: 286 Bytes
Downloads: 1714

 

Utility maximization in networked control systems (NCSs) is difficult in the presence of limited sensing and communication resources. In this paper, a new communication rate optimization method for state feedback control over a noisy channel is proposed. Linear dynamic systems with quantization errors, limited transmission rate, and noisy communication channels are considered. The most challenging part of the optimization is that no closed-form expressions are available for assessing the performance and the optimization problem is nonconvex. The proposed method consists of two steps: (i) the overall NCS performance measure is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize a weighted quadratic objective function is solved. The proposed method is applied to the problem of state feedback control and the problem of state estimation. Monte Carlo simulations illustrate the performance of the proposed rate allocation. It is shown numerically that the proposed method has better performance when compared to arbitrarily selected rate allocations. Also, it is shown that in certain cases nonuniform rate allocation can outperform the uniform rate allocation, which is commonly considered in quantized control systems, for feedback control over noisy channels.

Decentralized Indoor Wireless Localization Using Compressed Sensing of Signal-Strength Fingerprints Decentralized Indoor Wireless Localization Using Compressed Sensing of Signal-Strength Fingerprints

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Date added: 02/25/2013
Date modified: 08/03/2013
Filesize: 286 Bytes
Downloads: 1693

This paper combines recent developments in sparse approximation and distributed consensus theory to efficiently perform decentralized localization in wireless networks. To this goal, we exploit the Compressed Sensing (CS) framework, which provides a new paradigm for recovering signals being sparse in some basis by means of a limited amount of random incoherent projections. In particular, we propose a novel decentralized technique that considers the spatial correlations among the received measurements at the base stations (BSs) to provide global accurate position estimation, while reducing significantly the amount of measurements exchanged among the BSs and required for accurate positioning. We exploit the common structure of the received measurements to design a gossip-based algorithm in order to alleviate the effects of radio channel-induced signal variations on the estimation accuracy. Experimental evaluation with real data demonstrates the superiority of the proposed decentralized CS-based localization technique over traditional fingerprinting methods in terms of the achieved positioning accuracy.

Asymmetric average consensus under SINR-based interference Asymmetric average consensus under SINR-based interference

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Date added: 07/07/2013
Date modified: 07/07/2013
Filesize: 286 Bytes
Downloads: 1668

Consensus algorithms are a family of distributed processes that are based on exchanging local information in order to obtain some particular global information. An example of these algorithms is the average consensus, in which the value to be obtained is the average of some initial data. Most of the existing consensus techniques assume unrealistic models of communications that require complex control mechanisms in practice. In contrast, we consider the average consensus algorithm under a realistic asynchronous and asymmetric scheme of communications, where the interferences constrain the information exchanged among the nodes. To ensure a correct operation in this scheme, we propose a link scheduling protocol that satisfies certain convergence conditions and maximizes the number of simultaneous links in each iteration of the consensus algorithm. This increase in the number of communications per iteration improves the performance of the consensus algorithm. Simulation results are presented to verify and clearly show the efficiency of our approach.

Optimal topology design for energy efficient consensus in broadcast Wireless Sensor Networks Optimal topology design for energy efficient consensus in broadcast Wireless Sensor Networks

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Date added: 02/12/2015
Date modified: 02/12/2015
Filesize: 286 Bytes
Downloads: 1638

Average consensus algorithms are an essential tool in wireless sensor networks for multiple estimation tasks, being the convergence time and the energy consumption of these algorithms critical for their usability. Most existing work in the related literature focuses on improving these two parameters, assuming generally unicast communications, which are neither realistic nor efficient given the wireless nature of these networks. Instead, broadcast communications allow a greater instantaneous exchange of information between the network nodes, accelerating the consensus and saving energy in communications. In this work, we propose two methods that optimize the network topology to simultaneously improve the total power consumption per iteration, the maximum power consumption per node and the convergence time in a broadcast scenario. The first method is applied to continuous systems, while the second one is more suitable for discrete systems. Numerical results are presented to show the validity and efficiency of the proposed methods.

On Some Extensions of Fast-Lipschitz Optimization for Convex and Non-convex Problems On Some Extensions of Fast-Lipschitz Optimization for Convex and Non-convex Problems

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Date added: 08/15/2012
Date modified: 02/06/2013
Filesize: 235.03 kB
Downloads: 1546

 

 

Fast-Lipschitz optimization has been recently proposed as a new framework with numerous computational advantages for both centralized and decentralized convex and non-convex optimization problems. Such a framework generalizes the interference function optimization, which plays an essential role distributed radio power optimization over wireless networks. The characteristics of Fast-Lipschitz methods are low computational and coordination complexity compared to Lagrangian methods, with substantial benefits particularly for distributed optimization. These special properties of Fast-Lipschitz optimization can be ensured through qualifying conditions, which allow the Lagrange multipliers to be bound away from zero. In this paper, the Fast-Lipschitz optimization is substantially extended by establishing new qualifying conditions. The results are a generalization of the old qualifying conditions and a relaxation of the assumptions on problem structure so that the optimization framework can be applied to many more problems than previously possible. The new results are illustrated by a non-convex optimization problem, and by a radio power optimization problem which cannot be handled by the existing Fast-Lipschitz theory.

Non-cooperative power allocation game with imperfect sensing information for cognitive radio Non-cooperative power allocation game with imperfect sensing information for cognitive radio

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Date added: 07/07/2013
Date modified: 12/28/2013
Filesize: 286 Bytes
Downloads: 1501

In this paper, we consider a sensing-based spectrum sharing scenario and present an efficient decentralized algorithm to maximize the total throughput of the cognitive radio users by optimizing jointly both the detection operation and the power allocation, taking into account the influence of the sensing accuracy. This optimization problem can be formulated as a distributed non-cooperative power allocation game, which can be solved by using an alternating direction optimization method. The transmit power budget of the cognitive radio users and the constraint related to the rate-loss of the primary user due to the interference are considered in the scheme. Finally, we use variational inequality theory in order to find the existence and uniqueness of the Nash equilibrium for our proposed distributed non-cooperative game.

Wireless Sensor Network for Spectrum Cartography Based on Kriging Interpolation Wireless Sensor Network for Spectrum Cartography Based on Kriging Interpolation

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Date added: 08/30/2013
Date modified: 08/30/2013
Filesize: 286 Bytes
Downloads: 1476

Dynamic spectrum access with Cognitive Radio (CR) network is a promising approach to increase the efficiency of spectrum usage. To allow the optimization of resource allocation and transmission adaptation techniques, each CR terminal needs to acquire awareness of the state of the time-frequency-location varying radio spectrum. In this paper we present a Spectrum Cartography (SC) approach where CR terminals are supported by a fixed wireless sensor network (WSN) to estimate and update the Power Spectral Density (PSD) over the area of interest. The wireless sensors collaborate to estimate the spatial distribution of the received power at a given frequency using either a centralized or a distributed Kriging (DK) algorithm. We present an analysis of the semivariogram models used to estimate the spatial statistics of wireless PSD distributions. The performance of the centralized and DK algorithms are evaluated by simulating different realizations of the PSD and the results are compared with classical interpolating schemes varying the density of nodes in the area and the number of nodes used for local estimation.