Smart cities: Energy consumption in wireless sensor networks for road trafile modeling using simulator SUMO

2017 ◽  
Author(s):  
M. Kabrane ◽  
S. Krit ◽  
L. Elmaimouni ◽  
K. Bendaoud ◽  
H. Oudani ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Cities ◽  
Wireless Sensor

scholarly journals Game Theoretic Solution for Power Management in IoT-Based Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3835 ◽  
Author(s):  
Muhammad Sohail ◽  
Shafiullah Khan ◽  
Rashid Ahmad ◽  
Dhananjay Singh ◽  
Jaime Lloret
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Smart Cities ◽  
Level Density ◽  
Evolutionary Game ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Ch Selection

Internet of things (IoT) is a very important research area, having many applications such as smart cities, intelligent transportation system, tracing, and smart homes. The underlying technology for IoT are wireless sensor networks (WSN). The selection of cluster head (CH) is significant as a part of the WSN’s optimization in the context of energy consumption. In WSNs, the nodes operate on a very limited energy source, therefore, the routing protocols designed must meet the optimal utilization of energy consumption in such networks. Evolutionary games can be designed to meet this aspect by providing an adequately efficient CH selection mechanism. In such types of mechanisms, the network nodes are considered intelligent and independent to select their own strategies. However, the existing mechanisms do not consider a combination of many possible parameters associated with the smart nodes in WSNs, such as remaining energy, selfishness, hop-level, density, and degree of connectivity. In our work, we designed an evolutionary game-based approach for CH selection, combined with some vital parameters associated with sensor nodes and the entire networks. The nodes are assumed to be smart, therefore, the aspect of being selfish is also addressed in this work. The simulation results indicate that our work performs much better than typical evolutionary game-based approaches.

Design of Optimal Localization Model for Wireless Sensor Network Nodes Using Improved Krill Herd Algorithm

2021 ◽  
Author(s):  
Jafarsadegh Kamfar ◽  
Hessam Zandhessami ◽  
Mahmood Alborzi
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Heuristic Algorithms ◽  
Smart Cities ◽  
Wireless Sensor ◽  
Localization Error ◽  
Research Issues ◽  
Krill Herd Algorithm ◽  
Krill Herd

Abstract Nowadays, Wireless Sensor Networks (WSNs) are significantly applied in engineering and scientific research. WSNs consist of a group of distributed space sensors that track the environment's physical conditions and control the collected data at one central location. Examples of these sensors' applications are smart cities, transport, volcano surveillance and environmental activity, earthquake monitoring, medicine, post-disaster response, and military control. Wireless sensor networks have a lot of research issues like access to the media, implementation, time synchronization, network security and localization of the nodes. One of the most critical problems in this network research is the optimum position of the sensors to have access to maximum coverage and increase network life span to decrease maintenance costs, develop and manage the network. One of the main causes of the failure in these networks is running out of sensor battery and replacing them which impose high costs to maintenance and managing of the network. In order to solve the issues related to optimization and localization, researchers have focused on the algorithms like Swarm Intelligence (SI), because they enable us to solve complicated issues of optimization and NP-Hard issues to solve optimization. However, most of these algorithms are specialized for a purpose or a special program, and the majority of the solutions are not compatible with most of the wireless network sensors. The DV-Hop is one of the most popular node algorithms. But the main problem of the DV-Hop is the possibility of error in calculating the assessed distance between the unknown node and the nodes of anchor. Therefore, minimizing this error is the key to improve this algorithm. To reduce the problem of high localization error, two meta-heuristic algorithms have been proposed based on a combination. In this paper, a new optimization method based on a combination of Krill Herd Algorithm (KHA) and Particle Swarm Optimization (PSO) called KHAPSO is suggested to improve DV-Hop. Simulation results in MATLAB 2016 show that the KHAPSO model has a lower mean error compared to the DV-Hop, DV-Hop-KHA and DV-Hop-PSO models. Also, energy consumption in the KHAPSO model is less in comparison to the other models. The KHAPSO model with 400 unknown nodes and 30 anchor nodes was able to reduce energy consumption by about 35% and at the same time 27% reduction in Average Localization Error (ALE) compared to DV-Hop.

QoS Aware Multi-hop Multi-path Routing Approach in Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 43-52
Author(s):  
Omkar Singh ◽  
Vinay Rishiwal
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Life Time ◽  
Base Station ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
End To End

Background & Objective: Wireless Sensor Network (WSN) consist of huge number of tiny senor nodes. WSN collects environmental data and sends to the base station through multi-hop wireless communication. QoS is the salient aspect in wireless sensor networks that satisfies end-to-end QoS requirement on different parameters such as energy, network lifetime, packets delivery ratio and delay. Among them Energy consumption is the most important and challenging factor in WSN, since the senor nodes are made by battery reserved that tends towards life time of sensor networks. Methods: In this work an Improve-Energy Aware Multi-hop Multi-path Hierarchy (I-EAMMH) QoS based routing approach has been proposed and evaluated that reduces energy consumption and delivers data packets within time by selecting optimum cost path among discovered routes which extends network life time. Results and Conclusion: Simulation has been done in MATLAB on varying number of rounds 400- 2000 to checked the performance of proposed approach. I-EAMMH is compared with existing routing protocols namely EAMMH and LEACH and performs better in terms of end-to-end-delay, packet delivery ratio, as well as reduces the energy consumption 13%-19% and prolongs network lifetime 9%- 14%.

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

Improved DV-Hop Localization Scheme for Randomly Deployed WSNs

2020 ◽  
Vol 10 (1) ◽  
pp. 94-109 ◽  
Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Research Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Anchor Nodes ◽  
Least Energy ◽  
Range Free

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.

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.

scholarly journals Wireless Sensor Networks for Smart Cities: Network Design, Implementation and Performance Evaluation

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 218
Author(s):  
Ala’ Khalifeh ◽  
Khalid A. Darabkh ◽  
Ahmad M. Khasawneh ◽  
Issa Alqaisieh ◽  
Mohammad Salameh ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Experimental Evaluation ◽  
Large Scale ◽  
Performance Metrics ◽  
Smart Cities ◽  
Field Tests ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Real Field

The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.

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