Energy Efficient Node Deployment in Wireless Ad-hoc Sensor Networks

We study a wireless ad-hoc sensor network (WASN) where $N$ sensors gather data from the surrounding environment and transmit their sensed information to $M$ fusion centers (FCs) via multi-hop wireless communications. This node deployment problem is formulated as an optimization problem to make a trade-off between the sensing uncertainty and energy consumption of the network. Our primary goal is to find an optimal deployment of sensors and FCs to minimize a Lagrange combination of the sensing uncertainty and energy consumption. To support arbitrary routing protocols in WASNs, the routing-dependent necessary conditions for the optimal deployment are explored. Based on these necessary conditions, we propose a routing-aware Lloyd algorithm to optimize node deployment. Simulation results show that, on average, the proposed algorithm outperforms the existing deployment algorithms.Comment: 7 pages, 6 figure

Introducing Connected Dominating Set as Selection Feature of Cluster Heads in Hierarchical Protocols of Wireless Sensor Networks

It has been found that almost all routing protocols do suffer from efficiency of its operation regarding data transfer from one point to another. To overcome this process algorithm regarding the choice of nodes as cluster heads has to be done with utmost care. Failing of this leads to unnecessary dissipation of energy such as generating excess ‘Hello’ messages and less useful data transfer. In this communication we show that the introduction of connected dominating set as one of the metric regarding the choice of cluster head leads to better data transfer and energy consumption. Moreover we implemented this concept in LEACH protocol and found acceptable improvement in the performance parameters of the protocol

Localización de fallas en sistemas de transmisión eléctrica usando sensado comprimido

In the present investigation, we develop a methodology that refers to the location of faults in transmission systems using compressed sensing (CS). A model is develop with the advantages of the algorithm Least Squares (LS), Basic Pursuit (BP) and Orthogonal Matching Pursuit (OMP), which provides a sufficiently dispersed vector by convex optimization, making it possible to recover many more dispersed in a stable manner, solving the problem by iterative approaches. To do this, we use the information provided by the phasor measurement units (PMU), intelligent electronic devices that allow us to measure synchrophasors of sine waves of voltage and current deployed in the power electrical system, which, with this method will allow us to find the estimated location of the failure in a timely manner and maximize the observability of the electrical system.. The proposed method is test in the IEEE 9 transmission bus system, is estimated finding the line with problems and the distance at which the failure.En la Presente investigación, se desarrolló una metodología que hace referencia a la localización de fallas en sistemas de transmisión usando Sensado Comprimido (CS), se desarrolló un modelo con las ventajas del algoritmo Least Squares (LS), Basic Pursuit (BP) y Orthogonal Matching Pursuit (OMP), el cual nos proporciona un vector lo suficientemente disperso por optimización convexa, haciendo posible recuperar señales mucho más dispersas de manera estable, resolviendo el problema mediante aproximaciones iterativas. Para ello, se utiliza la información que nos proporciona las unidades de medición fasorial (PMU), dispositivos electrónicos inteligentes que nos permiten medir sincrofasores de ondas sinusoidales de voltaje y corriente desplegadas en el sistema eléctrico de potencia, el cual, con dicho método nos permitirá encontrar la localización estimada de la falla de manera oportuna y maximizar la observabilidad del sistema eléctrico. El método propuesto fue probado en el sistema de 9 barras de la IEEE, encontrando la línea con problemas y la distancia a la que se estima ocurre la falla

Wireless Sensor Networks (WSN): An Overview

The plethora of research and development efforts on Wireless Sensor Networks is an indication that the technology has emerged an active research area in recent times. In this paper, a review of this intelligent technology is undertaken. Its working mechanisms, merits, challenges, transmission technologies, simulating tools and applications are considered. The paper concludes with a clear conviction that a sound knowledge of the basics of this technology is a sine qua non to research and development of the technology

Energy Efficiency in Two-Tiered Wireless Sensor Networks

We study a two-tiered wireless sensor network (WSN) consisting of $N$ access points (APs) and $M$ base stations (BSs). The sensing data, which is distributed on the sensing field according to a density function $f$, is first transmitted to the APs and then forwarded to the BSs. Our goal is to find an optimal deployment of APs and BSs to minimize the average weighted total, or Lagrangian, of sensor and AP powers. For $M=1$, we show that the optimal deployment of APs is simply a linear transformation of the optimal $N$-level quantizer for density $f$, and the sole BS should be located at the geometric centroid of the sensing field. Also, for a one-dimensional network and uniform $f$, we determine the optimal deployment of APs and BSs for any $N$ and $M$. Moreover, to numerically optimize node deployment for general scenarios, we propose one- and two-tiered Lloyd algorithms and analyze their convergence properties. Simulation results show that, when compared to random deployment, our algorithms can save up to 79\% of the power on average.Comment: 11 pages, 7 figure

Wireless energy harvesting for Internet of Things

Internet of Things (IoT) is an emerging computing concept that describes a structure in which everyday physical objects, each provided with unique identifiers, are connected to the Internet without requiring human interaction. Long-term and self-sustainable operation are key components for realization of such a complex network, and entail energy-aware devices that are potentially capable of harvesting their required energy from ambient sources. Among different energy harvesting methods such as vibration, light and thermal energy extraction, wireless energy harvesting (WEH) has proven to be one of the most promising solutions by virtue of its simplicity, ease of implementation and availability. In this article, we present an overview of enabling technologies for efficient WEH, analyze the life-time of WEH-enabled IoT devices, and briefly study the future trends in the design of efficient WEH systems and research challenges that lie ahead

MAXIMUM CONNECTED LOAD BALANCING COVER TREE ALGORITHM FOR WIRELESS SENSOR NETWORK

In wireless sensor network the main problem is in the network lifetime, power transmission, energy consumption, speed and bandwidth for transmitting the packets and another problem is that the sink node can connect only with the limited nodes if more number of nodes is connected means then there may be occurrence of traffic and the data information can be eliminated. In order to overcome this problem maximum connected load balancing cover tree (MCLCT) algorithm is used. In various studies it is observed that the MCLCT has more network lifetime, power transmission and energy consumption when compared to the other methods and also to solve the optimization problem simulated annealing algorithm is used to transmit the data which form minimum movement in wireless sensor network and which can achieve both target coverage (TCOV) and network connectivity (NCON)

An improved modified LEACH-C algorithm for energy efficient routing in Wireless Sensor Networks

Wireless Sensor Networks (WSN) is mainly characterized by its limited power supply. Hence the need for Energy efficient infrastructure is becoming increasingly more important since it impact in network lifetime. Here the focus of this paper on Hierarchy clustering because multi-hope short range communication between wireless sensor nodes is energy efficient compared to Single-hope long range communication. In Hierarchy clustering, there are many Protocols but this paper talk about the well-known Low-Energy Adaptive Clustering Hierarchy (LEACH)[1].Centralized Low-Energy Adaptive Clustering Hierarchy (LEACH-C) and Advanced Low-Energy Adaptive Clustering Hierarchy(ALEACH) are energy efficient clustering routing protocol and they are belonging to hierarchy routing. In this paper we proposed Modified LEACH-C to upgrade the execution of existing Leach-C in such sort of Topology where Leach-C not performs so well. By Applying Method of Distance calculation between CH (cluster-head) to Member node and BS (base-station) to Member node. Making non-overlapping cluster using assigning proper ID while creating clusters. This makes the routing protocol more energy effective and delays life-time of a wireless sensor network. Simulation results demonstrate that Modified LEACH-C enhances network life-time contrasted with LEACH-C algorithm