scholarly journals Numerical Estimation of the Impact of Interferences on the Localization Problem in Sensor Networks

2006 ◽  
pp. 13-23
Author(s):  
Matthieu Bouget ◽  
Pierre Leone ◽  
Jose Rolim
Keyword(s):  
Sensor Networks ◽  
Localization Problem ◽  
Numerical Estimation ◽  
The Impact

scholarly journals Energy-Efficient Packet Forwarding Scheme Based on Fuzzy Decision-Making in Underwater Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4368
Author(s):  
Jitander Kumar Pabani ◽  
Miguel-Ángel Luque-Nieto ◽  
Waheeduddin Hyder ◽  
Pablo Otero
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Real Life ◽  
Base Station ◽  
Fuzzy Decision Making ◽  
Underwater Sensor Networks ◽  
Packet Forwarding ◽  
Node Number ◽  
The Impact

Underwater Wireless Sensor Networks (UWSNs) are subjected to a multitude of real-life challenges. Maintaining adequate power consumption is one of the critical ones, for obvious reasons. This includes proper energy consumption due to nodes close to and far from the sink node (gateway), which affect the overall energy efficiency of the system. These wireless sensors gather and route the data to the onshore base station through the gateway at the sea surface. However, finding an optimum and efficient path from the source node to the gateway is a challenging task. The common reasons for the loss of energy in existing routing protocols for underwater are (1) a node shut down due to battery drainage, (2) packet loss or packet collision which causes re-transmission and hence affects the performance of the system, and (3) inappropriate selection of sensor node for forwarding data. To address these issues, an energy efficient packet forwarding scheme using fuzzy logic is proposed in this work. The proposed protocol uses three metrics: number of hops to reach the gateway node, number of neighbors (in the transmission range of a node) and the distance (or its equivalent received signal strength indicator, RSSI) in a 3D UWSN architecture. In addition, the performance of the system is also tested with adaptive and non-adaptive transmission ranges and scalable number of nodes to see the impact on energy consumption and number of hops. Simulation results show that the proposed protocol performs better than other existing techniques or in terms of parameters used in this scheme.

scholarly journals On the Impact of Local Processing for Motor Monitoring Systems in Industrial Environments Using Wireless Sensor Networks

2013 ◽  
Vol 9 (7) ◽  
pp. 471917 ◽  
Author(s):  
Ruan Delgado Gomes ◽  
Marcéu Oliveira Adissi ◽  
Abel Cavalcante Lima-Filho ◽  
Marco Aurélio Spohn ◽  
Francisco Antônio Belo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Local Processing ◽  
Monitoring Systems ◽  
Industrial Environments ◽  
The Impact

scholarly journals Graph Theoretic Techniques in the Analysis of Uniquely Localizable Sensor Networks

2009 ◽  
pp. 146-173 ◽  
Author(s):  
Bill Jackson ◽  
Tibor Jordán
Keyword(s):  
Graph Theory ◽  
Sensor Networks ◽  
Optimization Problems ◽  
Partial Information ◽  
Two Dimensions ◽  
Localization Problem ◽  
Graph Theoretic ◽  
Network Localization ◽  
Exact Location ◽  
The Given

In the network localization problem the goal is to determine the location of all nodes by using only partial information on the pairwise distances (and by computing the exact location of some nodes, called anchors). The network is said to be uniquely localizable if there is a unique set of locations consistent with the given data. Recent results from graph theory and combinatorial rigidity made it possible to characterize uniquely localizable networks in two dimensions. Based on these developments, extensions, related optimization problems, algorithms, and constructions also became tractable. This chapter gives a detailed survey of these new results from the graph theorist’s viewpoint.

scholarly journals Convex hull as a heuristic

2018 ◽  
Author(s):  
Naama Katzin
Keyword(s):  
Computer Simulation ◽  
Convex Hull ◽  
Physical Properties ◽  
Spatial Data ◽  
Good Predictor ◽  
Numerical Cognition ◽  
Numerical Estimation ◽  
Geometrical Properties ◽  
Numerical Discrimination ◽  
The Impact

Recent studies in the field of numerical cognition quantify the impact of physical properties of an array on its enumeration, demonstrating that enumeration relies on the perception of these properties. This paper marks a shift in reasoning as it changes the focus from demonstrating this effect to explaining it. Interestingly, we were inspired by one of the very first articles in the field, “The power of numerical discrimination” by Stanley Jevons that was published in Nature in 1871. In his report, Jevons attempts to answer the question of how many objects can be perceived in “a single mental beat of attention”. We relate directly to Jevons’s records, putting forward a plausible heuristic mechanism that relies on the physical geometrical properties of the arrays to be enumerated. We use a mathematical theorem and computer simulation to show that the shape of the convex hull, the smallest polygon containing all dots in an array, is a good predictor of numerosity. We show that convex hull downsamples the spatial data, allowing quick and fairly accurate numerical estimation. Moreover, convex hull predictability changes as numerosity grows, corresponding to the psychophysical curve of enumeration shown by Jevons and many others that followed.

scholarly journals Solving Minimum Cost Three-Dimensional Localization Problem in Ocean Sensor Networks

2014 ◽  
Vol 10 (5) ◽  
pp. 452718 ◽  
Author(s):  
Chao Zhang ◽  
Yingjian Liu ◽  
Zhongwen Guo ◽  
Yu Wang
Keyword(s):  
Sensor Networks ◽  
Three Dimensional ◽  
Minimum Cost ◽  
Localization Problem ◽  
Ocean Sensor Networks

Adaptive Modeling of Routing Algorithms for Wireless Sensor Networks

2012 ◽  
pp. 73-92
Author(s):  
Marcello Cinque ◽  
Catello Di Martino
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Algorithms ◽  
Experimental Results ◽  
Wireless Sensor ◽  
Adaptive Modeling ◽  
Modeling Approach ◽  
Viable Solution ◽  
The Impact

Recent years have witnessed a proliferation of routing algorithms for Wireless Sensor Networks (WSNs), hence complicating the choice of the proper algorithm to be used for a given application. Simulation frameworks represent a viable solution to anticipate crucial choices, however existing solutions do not encompass the impact of changes (e.g., route updates, node crashes) on the nodes behavior and vice-versa. This article proposes a novel adaptive modeling approach to master the complexity of the thorough simulation of routing algorithms for WSN. Experimental results are provided showing the effectiveness of the proposed approach at managing changes, and dealing with detailed aspects, during the simulation and comparison of several routing algorithms.

scholarly journals Performance Evaluation and Interference Characterization of Wireless Sensor Networks for Complex High-Node Density Scenarios

Proceedings ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 28
Author(s):  
Mikel Celaya-Echarri ◽  
Leyre Azpilicueta ◽  
Peio Lopez-Iturri ◽  
Erik Aguirre ◽  
Francisco Falcone
Keyword(s):  
Wireless Sensor Networks ◽  
Wave Propagation ◽  
Sensor Networks ◽  
Radio Wave ◽  
Radio Wave Propagation ◽  
Outdoor Environment ◽  
Wireless Sensor ◽  
5 Ghz ◽  
The Impact ◽  
Indoor And Outdoor

The uncontainable future development of smart regions, as a set of smart cities’ assembled networks, is directly associated with a growing demand of full interactive and connected ubiquitous smart environments. To achieve this goal of global connection, a large number of transceivers and multiple wireless systems will be involved to provide user services and applications (i.e., Ambient Assisted Living, emergency situations, e-health monitoring, or Intelligent Transportation Systems) anytime and anyplace, regardless of the devices, networks, or systems used. Adequate, efficient, and effective radio wave propagation tools, methodologies, and analyses in complex environments (indoor and outdoor) are crucial to prevent communication limitations such as coverage, capacity, speed, or channel interferences due to nodes’ density or channel restrictions. In this work, radio wave propagation characterization in an urban indoor and outdoor environment, at ISM 2.4 GHZ and 5 GHz Wireless Sensor Networks (WSNs), has been assessed. The selected scenario is an auditorium placed in a free open area surrounded by inhomogeneous vegetation. User density within the scenario, in terms of inherent transceivers density, poses challenges to the overall system operation, given by multiple node operation which increases overall interference levels. By means of an in-house developed 3D ray launching algorithm, the impact of variable density wireless sensor network operation within this complex scenario is presented. This analysis and the proposed simulation methodology can lead in an adequate interference characterization, considering conventional transceivers as well as wearables, which provide suitable information for the overall network performance in complex crowded indoor and outdoor scenarios.

scholarly journals A Robust Diffusion Minimum Kernel Risk-Sensitive Loss Algorithm over Multitask Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2339 ◽  
Author(s):  
Xinyu Li ◽  
Qing Shi ◽  
Shuangyi Xiao ◽  
Shukai Duan ◽  
Feng Chen
Keyword(s):  
Sensor Networks ◽  
Gaussian Noise ◽  
Impulsive Noise ◽  
Estimation Algorithm ◽  
Distributed Estimation ◽  
Superior Performance ◽  
Mean Square ◽  
Unknown Parameters ◽  
Risk Sensitive ◽  
The Impact

Distributed estimation over sensor networks has attracted much attention due to its various applications. The mean-square error (MSE) criterion is one of the most popular cost functions used in distributed estimation, which achieves its optimality only under Gaussian noise. However, impulsive noise also widely exists in real-world sensor networks. Thus, the distributed estimation algorithm based on the minimum kernel risk-sensitive loss (MKRSL) criterion is proposed in this paper to deal with non-Gaussian noise, particularly for impulsive noise. Furthermore, multiple tasks estimation problems in sensor networks are considered. Differing from a conventional single-task, the unknown parameters (tasks) can be different for different nodes in the multitask problem. Another important issue we focus on is the impact of the task similarity among nodes on multitask estimation performance. Besides, the performance of mean and mean square are analyzed theoretically. Simulation results verify a superior performance of the proposed algorithm compared with other related algorithms.

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