A Theoretical Review of Topological Organization for Wireless Sensor Network

The recent decades have seen the growth in the fields of wireless communication technologies, which has made it possible to produce components with a rational cost of a few cubic millimeters of volume, called sensors. The collaboration of many of these wireless sensors with a basic base station gives birth to a network of wireless sensors. The latter faces numerous problems related to application requirements and the inadequate abilities of sensor nodes, particularly in terms of energy. In order to integrate the different models describing the characteristics of the nodes of a WSN, this paper presents the topological organization strategies to structure its communication. For large networks, partitioning into sub-networks (clusters) is a technique used to reduce consumption, improve network stability and facilitate scalability

A Theoretical Review of Topological Organization for Wireless Sensor Network

The recent decades have seen the growth in the fields of wireless communication technologies, which has made it possible to produce components with a rational cost of a few cubic millimeters of volume, called sensors. The collaboration of many of these wireless sensors with a basic base station gives birth to a network of wireless sensors. The latter faces numerous problems related to application requirements and the inadequate abilities of sensor nodes, particularly in terms of energy. In order to integrate the different models describing the characteristics of the nodes of a WSN, this paper presents the topological organization strategies to structure its communication. For large networks, partitioning into sub-networks (clusters) is a technique used to reduce consumption, improve network stability and facilitate scalability

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

This research article published by Cogent Engineering, 2020Network lifetime remains as a significant requirement in Wireless Sensor Network (WSN) exploited to prolong network processing. Deployment of low power sensor nodes in WSN is essential to utilize the energy efficiently. Clustering and sleep scheduling are the two major processes involved in improving network lifetime. However, abrupt and energy unaware selection of cluster head (CH) is nonoptimal in WSN which reflects in the drop of energy among sensor nodes. This paper addresses the twofold as utilization of sensor nodes to prolong the node’s energy and network lifetime by LEACH-based cluster formation and Time Division Multiple Access scheduling (TDMA). Clusters are constructed by the design of an EnhancedLow-Energy adaptive Clustering Hierarchy protocol (E-LEACH) that uses parallel operating optimization (Grey Wolf Optimization (GWO) and Discrete Particle Swarm Optimization (D-PSO)) for selecting an optimal CH and helper CH. The fitness values estimation from GWO and D-PSO is concatenated to prefer the best optimal CH. E-LEACH also manages the cluster size which is one of the conventional disadvantages in LEACH. CHs are responsible to perform energy-aware TDMA scheduling which segregates the coverage area into 24 sectors. Alternate sectors are assigne

An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches

Wireless sensor network (WSN) is widely acceptable communication network where human-intervention is less. Another prominent factors are cheap in cost and covers huge area of field for communication. WSN as name suggests sensor nodes are present which communicate to the neighboring node to form a network. These nodes are communicate via radio signals and equipped with battery which is one of most challenge in these networks. The battery consumption is depend on weather where sensors are deployed, routing protocols etc. To reduce the battery at routing level various quality of services (QoS) parameters are available to measure the performance of the network. To overcome this problem, many routing protocol has been proposed. In this paper, we considered two energy efficient protocols i.e. LEACH and Sub-cluster LEACH protocols. For provision of better performance of network Levenberg-Marquardt neural network (LMNN) and Moth-Flame optimisation both are implemented one by one. QoS parameters considered to measure the performance are energy efficiency, end-to-end delay, Throughput and Packet delivery ratio (PDR). After implementation, simulation results show that Sub-cluster LEACH with MFO is outperforms among other algorithms.Along with this, second part of paper considered to anomaly detection based on machine learning algorithms such as SVM, KNN and LR. NSLKDD dataset is considered and than proposed the anomaly detection method.Simulation results shows that proposed method with SVM provide better results among others

Self-Organizing and Scalable Routing Protocol (SOSRP) for Underwater Acoustic Sensor Networks

Las redes de sensores acústicas submarinas (UASN) han ganado mucha importancia en los últimos años: el 71% de la superficie de la Tierra está cubierta por océanos. La mayoría de ellos, aún no han sido explorados. Aplicaciones como prospección de yacimientos, prevención de desastres o recopilación de datos para estudios de biología marina se han convertido en el campo de interés para muchos investigadores. Sin embargo, las redes UASN tienen dos limitaciones: un medio muy agresivo (marino) y el uso de señales acústicas. Ello hace que las técnicas para redes de sensores inalámbricas (WSN) terrestres no sean aplicables. Tras realizar un recorrido por el estado del arte en protocolos para redes UASN, se propone en este TFM un protocolo de enrutamiento denominado "SOSRP", descentralizado y basado en tablas en cada nodo. Se usa como criterio para crear rutas una combinación del valor de saltos hasta el nodo recolector y la distancia. Las funciones previstas del protocolo abarcan: autoorganización de las rutas, tolerancia a fallos y detección de nodos aislados. Mediante la implementación en MATLAB de SOSRP así como de un modelo de propagación y energía apropiados para entorno marino, se obtienen resultados de rendimiento en distintos escenarios (variando nºextremo de paquetes, consumo de energía o longitud de rutas creadas (con y sin fallo). Los resultados obtenidos muestran una operación estable, fiable y adecuada para el despliegue y operación de los nodos en redes UASN

A Novel Connectivity-Based LEACH-MEEC Routing Protocol for Mobile Wireless Sensor Network

In mobile wireless sensor network (MWSN), the lifetime of the network largely depends on energy efficient routing protocol. In the literature, cluster leader (CL) is selected based on remaining energy of mobile sensor nodes to enhance sensor network lifetime. In this study, a novel connectivity-based Low-Energy Adaptive Clustering Hierarchy-Mobile Energy Efficient and Connected (LEACH-MEEC) routing protocol was proposed, where CL is selected based on connectivity among neighboring nodes and the remaining energy of mobile sensor nodes. Consequently, it improves data delivery, network lifetime and balances the energy consumption. We studied various performance metrics including the number of alive nodes (NAN), remaining energy (RE) and packet delivery ratio (PDR). Our proposed LEACH-MEEC outperforms all other algorithms due to the connectivity metric. Moreover, the performance of mobility models was investigated through graphical and statistically tabulated results. The results show that Reference Point Group Mobility model (RPGM) is better than other mobility models