scholarly journals Determination of Optimal Number of Relays Using a New Energy Model for WSN

2018 ◽  
Vol 4 (2) ◽  
pp. 572-579
Author(s):  
Partha Pratim Bhattacharya ◽  
Shilpi Gupta ◽  
Nupur Pal
Keyword(s):  
Energy Consumption ◽  
Minimum Energy ◽  
Optimal Number ◽  
Energy Model ◽  
Sensor Nodes ◽  
Direct Transmission ◽  
Direct Path ◽  
Minimum Energy Consumption ◽  
New Energy

Wireless Sensor Networks are proving themselves as a boon to the surroundings and its deployment is a prominent area to be considered for minimum energy consumption. In this paper, we have considered deployment of a sensor grid network for 36 and 100 number of sensor nodes. Diagonally opposite nodes are considered to be source and destination. Using a modified energy model, the energy consumption for direct path and that with different number of relays are calculated. The maximum distance up to which direct transmission is possible and the number of required relays for higher transmission distances are then found out.

scholarly journals Digital Media Art Communication Based on Wireless Cooperative Routing with Minimum Energy Consumption

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Shuli Song
Keyword(s):  
Energy Consumption ◽  
Digital Media ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Target Area ◽  
Media Art ◽  
Cooperative Routing ◽  
Minimum Energy Consumption

Wireless cooperative routing algorithm transmits the data collected in the target area to users, so that users can obtain monitoring information timely and accurately. In the traditional low-power adaptive clustering hierarchical routing protocol, the process of building clusters is random, the resources of nodes are not fully utilized, the node death speed is fast, the network life cycle is short, and the performance is not stable enough. In addition, the route maintenance process is cumbersome and will occupy a lot of bandwidth. In order to solve the problems of real-time transmission of digital media art communication data and network lifetime optimization, a wireless cooperative routing algorithm based on minimum energy consumption is proposed. The facts of transmission strength consumption, node residual strength, and minimal information transmission extension are analyzed, a new weight feature is proposed, and a multipath statistics routing scheme is developed by using the usage of the minimal strength consumption. All digital media art propagation sensor nodes transmit data to sink nodes along multiple transmission paths. Simulation results show that the algorithm can prolong the network lifetime, reduce and balance the node energy consumption, reduce the data transmission delay, reduce the energy consumption of wireless cooperative routing based on the minimum energy consumption by 64.5%, and increase the number of compressed images by 182%.

scholarly journals Energy Conservation In Wsn Using Hyper Sphere Sensor Optimisation

2019 ◽  
Vol 8 (6) ◽  
pp. 3672-3676
Keyword(s):  
Energy Consumption ◽  
Sensor Network ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Network Nodes ◽  
Sensor Optimization ◽  
Minimum Energy Consumption ◽  
Compact Size ◽  
Energy Location ◽  
Almost All

Due to minimum energy consumption and compact size, the Wireless Sensor Network (WSN) is widely used in almost all areas of research. In WSN, optimum coverage and lifetime of nodes are major challenges. In this paper, a Hyper Sphere Sensor Optimization is proposed to estimate the neighbourhood distance for placing the sensor nods in an optimal way over an effective location. Levy fight in flower pollination utilized for optimal energy location with hyper sphere localization. In first phase based on hyper sphere is used to location identification of sensor nodes. Based on neighbour hood distance energy consumption of sensor network nodes are reduced. The results show that the proposed method is effective than other methods in terms of reducing the reduced energy consumption.

Optimal speed control of a multiple-mass train for minimum energy consumption using ant colony and genetic algorithms

2016 ◽  
Vol 231 (3) ◽  
pp. 280-294 ◽  
Author(s):  
Mohammad Ali Sandidzadeh ◽  
Mohammad Reza Alai
Keyword(s):  
Energy Consumption ◽  
Minimum Energy ◽  
Real Data ◽  
Ant Colony ◽  
Transport Systems ◽  
Rail Transportation ◽  
Speed Profile ◽  
Optimal Speed ◽  
Minimum Energy Consumption

Today, rail transport systems are widely used in the world. Because of the high consumption of energy in these systems, finding ways to optimize their energy consumption is important. One of the best ways to save more energy and prevent the losses of rail transportation is using the optimal speed profile. In this article, intelligent algorithms, involving ant colony optimization for continuous domain [Formula: see text] and genetic algorithm, are applied to the energy efficiency problem of electrical trains for various track gradients and curvatures. With proper determination of switching points in the moving strategies such as acceleration, cruising, and coasting, the optimal speed profile for the safe journey of trains will be obtained. For the simulation, real data from rail tracks of Tehran metro have been incorporated.

Evaluation of Energy Consumption of LPWAN Technologies

2021 ◽  
Author(s):  
Husam Rajab ◽  
Tibor Cinkler ◽  
Taoufik Bouguera
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Sensor Node ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Sleep Mode ◽  
Area Network ◽  
Wide Area Network ◽  
Battery Lifetime ◽  
Minimum Energy Consumption

Abstract The modern technological innovations provide small radios with ability to broadcast over vast areas with minimum energy consumption that will significantly influence the future of the Internet of Things (IoT) communications. The majority of IoT implementations demand sensor nodes run reliably for an extended time. Furthermore, the radio settings can endure a high data rate transmission while optimizing the energy-efficiency. The LoRa/LoRaWAN is one of the primary Low-Power Wide Area Network (LPWAN) technology that has highly enticed much concentration recently from the community. The energy limits is a significant issue in wireless sensor networks since battery lifetime that supplies sensor nodes have a restricted amount of energy and neither expendable nor rechargeable in most cases. A common hypothesis in previous work is that the energy consumed by sensors in sleep mode is negligible. With this hypothesis, the usual approach is to consider subsets of nodes that reach all the iterative targets. These subsets also called coverage sets, are then put in the active mode, considering the others are in the low-power or sleep mode. In this paper, we address this question by proposing an energy consumption model based on LoRa and LoRaWAN, that model optimizes the energy consumption of the sensor node for different tasks for a period of time. The proposed analytical approach permits considering the consumed power of every sensor node element; furthermore, it can be used to analyse different LoRaWAN modes to determine the most desirable sensor node design to reach its energy autonomy.

Efficient Data Reporting in a Multi-Object Tracking Using WSNs

2020 ◽  
pp. 638-658
Author(s):  
Fatma H. Elfouly ◽  
Rabie A. Ramadan ◽  
Mohamed I. Mahmoud ◽  
Moawad I. Dessouky
Keyword(s):  
Energy Consumption ◽  
Object Tracking ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Data Reporting ◽  
Minimum Energy Consumption ◽  
Wsn Lifetime ◽  
Efficient Data ◽  
Work First ◽  
Reporting Method

Object tracking is one of the most important applications in wireless sensor networks (WSNs). Many recent articles have been dedicated to localization of objects; however, few of these articles were concentrated on the reliability of network data reporting along with objects localization. In this work, the authors propose an efficient data reporting method for object tracking in WSNs. This paper aims to achieve both minimum energy consumption in reporting operation and balanced energy consumption among sensor nodes for WSN lifetime extension. Furthermore, data reliability is considered in the authors' model where the sensed data can reach the sink node in a more reliable way. This work first formulates the problem as 0/1 Integer Linear Programming (ILP) problem, and then proposes a SWARM intelligence for solving the optimization problem. Through simulation, the performance of proposed method to report information about the detected objects to the sink is compared with the previous works related to the authors' topic, such as LR-based object tracking algorithm, SEB, EPWSN, and ACO.

scholarly journals Swarm intelligence based reliable and energy balance routing algorithm for wireless sensor network

2016 ◽  
Vol 29 (3) ◽  
pp. 339-355
Author(s):  
Fatma Elfouly ◽  
Rabie Ramadan ◽  
Mohamed Mahmoud ◽  
Moawad Dessouky
Keyword(s):  
Energy Consumption ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Algorithm ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Minimum Energy Consumption ◽  
Energy Balanced Routing ◽  
Memory Resources

Energy is an extremely crucial resource for Wireless Sensor Networks (WSNs). Many routing techniques have been proposed for finding the minimum energy routing paths with a view to extend the network lifetime. However, this might lead to unbalanced distribution of energy among sensor nodes resulting in, energy hole problem. Therefore, designing energy-balanced routing technique is a challenge area of research in WSN. Moreover, dynamic and harsh environments pose great challenges in the reliability of WSN. To achieve reliable wireless communication within WSN, it is essential to have reliable routing protocol. Furthermore, due to the limited memory resources of sensor nodes, full utilization of such resources with less buffer overflow remains as a one of main consideration when designing a routing protocol for WSN. Consequently, this paper proposes a routing scheme that uses SWARM intelligence to achieve both minimum energy consumption and balanced energy consumption among sensor nodes for WSN lifetime extension. In addition, data reliability is considered in our model where, the sensed data can reach the sink node in a more reliable way. Finally, buffer space is considered to reduce the packet loss and energy consumption due to the retransmission of the same packets. Through simulation, the performance of proposed algorithm is compared with the previous work such as EBRP, ACO, TADR, SEB, and CLR-Routing.

Efficient Data Reporting in a Multi-Object Tracking Using WSNs

2017 ◽  
Vol 6 (1) ◽  
pp. 38-57
Author(s):  
Fatma H. Elfouly ◽  
Rabie A. Ramadan ◽  
Mohamed I. Mahmoud ◽  
Moawad I. Dessouky
Keyword(s):  
Energy Consumption ◽  
Object Tracking ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Data Reporting ◽  
Minimum Energy Consumption ◽  
Wsn Lifetime ◽  
Efficient Data ◽  
Work First ◽  
Reporting Method

Object tracking is one of the most important applications in wireless sensor networks (WSNs). Many recent articles have been dedicated to localization of objects; however, few of these articles were concentrated on the reliability of network data reporting along with objects localization. In this work, the authors propose an efficient data reporting method for object tracking in WSNs. This paper aims to achieve both minimum energy consumption in reporting operation and balanced energy consumption among sensor nodes for WSN lifetime extension. Furthermore, data reliability is considered in the authors' model where the sensed data can reach the sink node in a more reliable way. This work first formulates the problem as 0/1 Integer Linear Programming (ILP) problem, and then proposes a SWARM intelligence for solving the optimization problem. Through simulation, the performance of proposed method to report information about the detected objects to the sink is compared with the previous works related to the authors' topic, such as LR-based object tracking algorithm, SEB, EPWSN, and ACO.

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.

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