TSEP: Threshold-sensitive Stable Election Protocol for WSNs

Wireless Sensor Networks (WSNs) are expected to find wide applicability and increasing deployment in near future. In this paper, we propose a new protocol, Threshold Sensitive Stable Election Protocol (TSEP), which is reactive protocol using three levels of heterogeneity. Reactive networks, as opposed to proactive networks, respond immediately to changes in relevant parameters of interest. We evaluate performance of our protocol for a simple temperature sensing application and compare results of protocol with some other protocols LEACH, DEEC, SEP, ESEP and TEEN. And from simulation results it is observed that protocol outperforms concerning life time of sensing nodes used.Comment: 10th IEEE International Conference on Frontiers of Information Technology (FIT 12), 201

Energy Consumption Rate based Stable Election Protocol (ECRSEP) for WSNs

In recent few yearsWireless Sensor Networks (WSNs) have seen an increased interest in various applications like border field security, disaster management and medical applications. So large number of sensor nodes are deployed for such applications, which can work autonomously. Due to small power batteries in WSNs, efficient utilization of battery power is an important factor. Clustering is an efficient technique to extend life time of sensor networks by reducing the energy consumption. In this paper, we propose a new protocol; Energy Consumption Rate based Stable Election Protocol (ECRSEP). Our CH selection scheme is based on the weighted election probabilities of each node according to the Energy Consumption Rate (ECR) of each node. We compare results of our proposed protocol with Low Energy Adaptive Clustering Hierarchy (LEACH), Distributed Energy Efficient Clustering (DEEC), Stable Election Protocol (SEP), and Enhanced SEP(ESEP). Our simulation results show that our proposed protocol, ECRSEP outperforms all these protocols in terms of network stability and network lifetime

SEPCS: Prolonging Stability Period of Wireless Sensor Networks using Compressive Sensing

Compressive sensing (CS) is an emerging theory thatis based on the fact that a small number of linear projections of asparse data contains enough information for reconstruction. CScan break through the asymmetry between the data acquisitionand information processing that makes a great challenge to therestriction energy and computation consumption of the sensornodes. In this paper, we propose a routing protocol called SEPCSfor clustered wireless sensor networks (WSNs) using CS. SEPCScombines a new clustering strategy with CS theory for prolongingstability period and network lifetime in WSNs. Our simulationresults show that the proposed protocol can effectively prolongthe stability period and network lifetime compared with existingprotocols

Optimized Clustering Protocol for Balancing Energy in Wireless Sensor Networks

While wireless sensor networks (WSNs) are increasingly equipped to handle more complex functions and in-network processing may require these battery powered sensors to judiciously use their constrained energy to prolong the effective network lifetime. Cluster-based Hierarchical Routing Protocol using compressive sensing (CS) theory (CBHRP-CS) divides the network into several clusters, each managed by a set of CHs called a header. Each member of the header compresses the collected data using CS. This paper proposes an optimized clustering protocol using CS (OCP-CS) to improve the performance of WSNs by exploiting compressibility. In OCP-CS, each cluster is managed by a cluster head (CH). CHs are selected based on node concentration and sensor residual energy, and performs data aggregation using CS to reduce the energy consumed in the process of data sampling and transmission. Simulations show that our proposed protocol is effective in prolonging the network lifetime and supporting scalable data aggregation than existing protocols

Wireless communication, identification and sensing technologies enabling integrated logistics: a study in the harbor environment

In the last decade, integrated logistics has become an important challenge in the development of wireless communication, identification and sensing technology, due to the growing complexity of logistics processes and the increasing demand for adapting systems to new requirements. The advancement of wireless technology provides a wide range of options for the maritime container terminals. Electronic devices employed in container terminals reduce the manual effort, facilitating timely information flow and enhancing control and quality of service and decision made. In this paper, we examine the technology that can be used to support integration in harbor's logistics. In the literature, most systems have been developed to address specific needs of particular harbors, but a systematic study is missing. The purpose is to provide an overview to the reader about which technology of integrated logistics can be implemented and what remains to be addressed in the future

Planeación y despliegue de la red de sensores inalámbricos requerida para la medición inteligente de energía eléctrica usando restricciones de capacidad y cobertura

The electrical energy measurement (EEM), seeks to provide quality services without neglecting the reliability of the system. Therefore, a quality service must be closely linked to the wireless communication technologies, to technify the EEM, not only reading, but also cuts, reconnections, and other additional services that the intelligent measurement infrastructure provides through wireless technologies Such as cell or WiFi, increasingly common because of the reliability they provide in real-time data transmission. Wireless infrastructures allow us to provide coverage to the fixed terminals, determined by the electric meter, and in turn manage and plan the optimal deployment of wireless sensors (SI) in finite areas, whether urban, rural or suburban. This article proposes an optimal model for planning and deploying SI for the EEM in order to guarantee reliable wireless communication links at the lowest implementation cost. Therefore, the proposed algorithm gives global solutions within a finite scenario, making this a scalable model in time able to manage the use of available links. The SIs for the EEM are inserted into the Neighborhood Area Networks (NANs) covered by the mobile communications network.La medición de energía eléctrica (MEE), busca proporcionar servicios de calidad sin descuidar la confiabilidad del sistema. Por lo tanto, un servicio de calidad debe ir estrechamente ligada a las tecnologías de comunicación inalámbrica, para tecnificar la MEE, no solo lectura, sino también cortes, reconexiones, y otros servicios adicionales que la infraestructura de medición inteligente provee a través de tecnologías inalámbricas como celular o WiFi, cada vez más comunes debido a la confiabilidad que estas brindan en la transmisión de datos en tiempo real [1]. Las infraestructuras inalámbricas nos permiten brindar cobertura a los terminales fijos, determinados por el medidor eléctrico, y a su vez gestionar y planificar el óptimo despliegue de sensores inalámbricos (SI) en áreas finitas, ya sean, urbanas, rurales o suburbanas. Este artículo propone un modelo óptimo de planeación y despliegue de SI para la MEE con la finalidad de garantizar enlaces de comunicación inalámbricos confiables al menor costo de implementación. Por lo tanto, el algoritmo propuesto da soluciones globales dentro de un escenario finito, haciendo de este un modelo escalable en el tiempo capaz de gestionar el uso de enlaces disponibles. Los SI para la MEE, son insertados en las Redes de Área Vecindaria (NAN) cubiertas por la red de comunicaciones móviles

Cluster-based Routing Protocols for Energy-Efficiency in Wireless Sensor Networks

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A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. “Large-scale” means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed