scholarly journals Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2385 ◽  
Author(s):  
Meihua Wang ◽  
Wei-Chang Yeh ◽  
Ta-Chung Chu ◽  
Xianyong Zhang ◽  
Chia-Ling Huang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Grids ◽  
Signal Transmission ◽  
Fuzzy Optimization ◽  
Battery Life ◽  
Smart Sensor ◽  
Multi Objective ◽  
Wide Range ◽  
Consumption Cost

Wireless (smart) sensor networks (WSNs), networks made up of embedded wireless smart sensors, are an important paradigm with a wide range of applications, including the internet of things (IoT), smart grids, smart production systems, smart buildings and many others. WSNs achieve better execution efficiency if their energy consumption can be better controlled, because their component sensors are either difficult or impossible to recharge, and have a finite battery life. In addition, transmission cost must be minimized, and signal transmission quantity must be maximized to improve WSN performance. Thus, a multi-objective involving energy consumption, cost and signal transmission quantity in WSNs needs to be studied. Energy consumption, cost and signal transmission quantity usually have uncertain characteristics, and can often be represented by fuzzy numbers. Therefore, this work suggests a fuzzy simplified swarm optimization algorithm (fSSO) to resolve the multi-objective optimization problem consisting of energy consumption, cost and signal transmission quantity of the transmission process in WSNs under uncertainty. Finally, an experiment of ten benchmarks from smaller to larger scale WSNs is conducted to demonstrate the effectiveness and efficiency of the proposed fSSO algorithm.

PERFORMANCE EVALUATION ANALYSIS OF WIRELESS SENSOR NETWORKS ROUTING PROTOCOLS IN SMART GRIDS

2016 ◽  
Vol 26 (1) ◽  
pp. 17
Author(s):  
Carlos Deyvinson Reges Bessa
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Smart Grids ◽  
Network Routing ◽  
Base Station ◽  
Wireless Sensor ◽  
Delay Jitter ◽  
La Red

ABSTRACTThis work aims to study which wireless sensor network routing protocol is more suitable for Smart Grids applications, through simulation of AODV protocols, AOMDV, DSDV and HTR in the NS2 simulation environment. Was simulated a network based on a residential area with 47 residences, with one node for each residence and one base station, located about 25m from the other nodes. Many parameters, such as packet loss, throughput, delay, jitter and energy consumption were tested.  The network was increased to 78 and 93 nodes in order to evaluate the behavior of the protocols in larger networks. The tests proved that the HTR is the routing protocol that has the best results in performance and second best in energy consumption. The DSDV had the worst performance according to the tests.Key words.- Smart grid, QoS analysis, Wireless sensor networks, Routing protocols.RESUMENEste trabajo tiene como objetivo estudiar el protocolo de enrutamiento de la red de sensores inalámbricos es más adecuado para aplicaciones de redes inteligentes, a través de la simulación de protocolos AODV, AOMDV, DSDV y HTR en el entorno de simulación NS2. Se simuló una red basada en una zona residencial con 47 residencias, con un nodo para cada residencia y una estación base, situada a unos 25 metros de los otros nodos. Muchos parámetros, tales como la pérdida de paquetes, rendimiento, retardo, jitter y el consumo de energía se probaron. La red se incrementó a 78 y 93 nodos con el fin de evaluar el comportamiento de los protocolos de redes más grandes. Las pruebas demostraron que el HTR es el protocolo de enrutamiento que tiene los mejores resultados en el rendimiento y el segundo mejor en el consumo de energía. El DSDV tuvo el peor desempeño de acuerdo a las pruebas.Palabras clave.- redes inteligentes, análisis de calidad de servicio, redes de sensores inalámbricas, protocolos de enrutamiento.

Energy Efficient Image Compression and Transmission in WSN

2016 ◽  
pp. 67-78
Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Sensor Network ◽  
Image Data ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.

scholarly journals Distributed fuzzy logic based cluster head election scheme (DFLCHES) for prolonging the lifetime of the wireless sensor network

2017 ◽  
Vol 7 (1.5) ◽  
pp. 111
Author(s):  
S. Ramakrishnan ◽  
S. Prayla Shyry
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Significant Feature ◽  
Cluster Head Election ◽  
Wide Range

Wireless sensor networks (WSNs) is considered as the predominant technology due to their high suitability and adaptability that makes it possible to be deployed in wide range of applications like civil and military domain. But energy-constraint is the significant feature that needs to be addressed for sensor networks since energy drain of sensor nodes affects network lifetime, stability and co-operation of sensor nodes in the event of enforce reliable data dissemination. Cluster head election has to been performed periodically in order to handle energy balance for facilitating reliable packet delivery. Most of the cluster head election schemes of the literature elect a node as cluster head either randomly or by elucidating their stochastic probabilities. Hence a Distributed Fuzzy Logic based Cluster Head Election Scheme (DFLCHES) that discriminates and discards packets from the sensor nodes that has the least probability of being elected as cluster head is proposed. DFLCHES utilizes five significant parameters such as trust, energy, node density, hop count and centrality measure for quantifying the probability of cluster head election. This DFLCHES is run on each neighbor nodes of the cluster members to facilitate the action of discrimination. DFLCHES also balances the energy consumption of the cluster members during transmission as it discards packets from ineligible nodes. Further the action of cluster head election has to be optimized periodically for reducing and balancing energy consumption for prolonging the network lifetime. In DFLCHES, the process of optimizing cluster head depends on the incorporation of the concept of Genetic algorithms for enabling and ensuring reliable routing.

scholarly journals Optimizing Hybrid Metaheuristic Algorithm with Cluster Head to Improve Performance Metrics on the IoT

2021 ◽  
Author(s):  
Malik bader alazzam ◽  
Fawaz Alassery
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Smart Grids ◽  
Weather Prediction ◽  
Cluster Head ◽  
Optimization Techniques ◽  
The Internet ◽  
Wide Range ◽  
Whale Optimization ◽  
The Internet Of Things

Abstract The Internet of Things (IoT) has subsequently been applied to a variety of sectors, including smart grids, farming, weather prediction, power generation, wastewater treatment, and so on. So if the Internet of Things has enormous promise in a wide range of applications, there still are certain areas where it may be improved. Designers had focused our present research on reducing the energy consumption of devices in IoT networks, which will result in a longer network lifetime. The far more suitable Cluster Head (CH) throughout the IoT system is determined in this study to optimize energy consumption. Whale Optimization Algorithm (WOA) with Evolutionary Algorithm (EA) is indeed a mixed meta-heuristic algorithm used during the suggested study. Various quantifiable metrics, including the variety of adult nodes, workload, temperatures, remaining energy, and a target value, were utilized IoT network groups. The suggested method then is contrasted to several cutting-edge optimization techniques, including the Artificial Bee Colony method, Neural Network, Adapted Gravity Simulated annealing. The findings show that the suggested hybrid method outperforms conventional methods.

scholarly journals Energy-Efficient Multi-Disjoint Path Opportunistic Node Connection Routing Protocol in Wireless Sensor Networks for Smart Grids

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3789 ◽  
Author(s):  
Anees ◽  
Zhang ◽  
Baig ◽  
Lougou
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Real Time ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Smart Grids ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Disjoint Path

The gradual increase in the maturity of sensor electronics has resulted in the increasing demand for wireless sensor networks for many industrial applications. One of the industrial platforms for efficient usage and deployment of sensor networks is smart grids. The critical network traffic in smart grids includes both delay-sensitive and delay-tolerant data for real-time and non-real-time usage. To facilitate these traffic requirements, the asynchronous working–sleeping cycle of sensor nodes can be used as an opportunity to create a node connection. Efficient use of wireless sensor network in smart grids depends on various parameters like working–sleeping cycle, energy consumption, network lifetime, routing protocol, and delay constraints. In this paper, we propose an energy-efficient multi-disjoint path opportunistic node connection routing protocol (abbreviated as EMOR) for sensor nodes deployed in neighborhood area network. EMOR utilizes residual energy, availability of sensor node’s buffer size, working–sleeping cycle of the sensor node and link quality factor to calculate optimum path connectivity after opportunistic connection random graph and spanning tree formation. The multi-disjoint path selection in EMOR based on service differentiation of real-time and non-real-time traffic leads to an improvement in packet delivery rate, network lifetime, end-end delay and total energy consumption.

scholarly journals Adaptive Chaotic Ant Colony Optimization for Energy Optimization in Smart Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wenxian Jia ◽  
Menghan Liu ◽  
Jie Zhou
Keyword(s):  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Transition Probability ◽  
Ant Colony ◽  
Network Clustering ◽  
Smart Sensor ◽  
Chaotic Mapping ◽  
Wide Range

Smart sensor network has the characteristics of low cost, low power consumption, real time, strong adaptability, etc., and it has a wide range of application prospects in the agricultural field. However, the smart sensor node is limited by its own energy; it also faces many bottlenecks in agricultural applications. Therefore, balancing the energy consumption of nodes and extending the life of the network are important considerations in the design of efficient routing for smart sensor networks. Aiming at the problem of energy constraints, this paper proposes an intelligent sensor network clustering algorithm based on adaptive chaotic ant colony optimization (ACACO). ACACO introduces logical chaotic mapping to interfere with the pheromone on the initial path and uses the adaptive strategy to improve the transition probability formula. After selecting the best next hop node, the advancing ants are released to update the local pheromone, and the current pheromone content is adjusted by the chaos factor. When the ants determine the path, they release subsequent ants to update the global pheromone. The simulation results show that ACACO has obvious advantages over genetic algorithm (GA) and particle swarm optimization (PSO).

scholarly journals ERP-DDA: Event Reporting Protocol Based on Distributed Data Aggregation for Wireless Sensor Networks

2021 ◽  
Vol 50 (3) ◽  
pp. 470-484
Author(s):  
Raed T AL-Zubi ◽  
Mohammad Q Alawad ◽  
Abdulraheem A Kreishan ◽  
Khalid A Darabkh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Human Life ◽  
Base Station ◽  
Wireless Sensor ◽  
Distributed Data ◽  
Event Reporting ◽  
Wide Range

Wireless Sensor Networks (WSNs) have a wide range of applications in human life. Accordingly, WSNs have beenthoroughly considered in research community to improve their performance and address their challenges. Eventreporting in WSNs has always been a major challenge in terms of energy consumption. Event reporting requiressensing the event and sending a reporting packet from the sensor to the centralized base station (BS). However,sensor’s energy is limited and stored in a non-rechargeable battery. Therefore, several event-reporting (or datacollection) protocols have been proposed to improve energy consumption in WSNs, and consequently, to extendtheir lifetime. In this paper, we propose an efficient event reporting protocol for WSNs called Event ReportingProtocol Based on Distributed Data Aggregation (ERP-DDA). This protocol mainly aims at reporting any event byno more than one sensor node such that energy saving is satisfied in the whole network. To achieve this goal, ERPDDAis mainly based on the following features: it is a cluster-based protocol, it is a multi-hop routing protocol, itapplies distributed data aggregation, and it employs variable clustering and cluster head selection. Simulationsshow that ERP-DDA significantly extends the lifetime of WSNs compared with other related protocols.

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