scholarly journals Multi-Objective UAV Positioning Mechanism for Sustainable Wireless Connectivity in Environments with Forbidden Flying Zones

Algorithms ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 302
Author(s):  
İbrahim Atli ◽  
Metin Ozturk ◽  
Gianluca C. Valastro ◽  
Muhammad Zeeshan Asghar
Keyword(s):  
Energy Consumption ◽  
Unmanned Aerial Vehicles ◽  
Base Station ◽  
Energy Usage ◽  
Weighting Method ◽  
Q Learning ◽  
Cumulative Distance ◽  
Reducing Energy ◽  
Wireless Connectivity

A communication system based on unmanned aerial vehicles (UAVs) is a viable alternative for meeting the coverage and capacity needs of future wireless networks. However, because of the limitations of UAV-enabled communications in terms of coverage, energy consumption, and flying laws, the number of studies focused on the sustainability element of UAV-assisted networking in the literature was limited thus far. We present a solution to this problem in this study; specifically, we design a Q-learning-based UAV placement strategy for long-term wireless connectivity while taking into account major constraints such as altitude regulations, nonflight zones, and transmit power. The goal is to determine the best location for the UAV base station (BS) while reducing energy consumption and increasing the number of users covered. Furthermore, a weighting method is devised, allowing energy usage and the number of users served to be prioritized based on network/battery circumstances. The suggested Q-learning-based solution is contrasted to the standard k-means clustering method, in which the UAV BS is positioned at the centroid location with the shortest cumulative distance between it and the users. The results demonstrate that the proposed solution outperforms the baseline k-means clustering-based method in terms of the number of users covered while achieving the desired minimization of the energy consumption.

scholarly journals Multi-objective UAV Positioning Mechanism for Sustainable Wireless Connectivity in Environments with Forbidden Flying Zones

2021 ◽  
Author(s):  
İbrahim Atlı ◽  
Metin Ozturk ◽  
Gianluca Camillo Valastro ◽  
Muhammad Zeeshan Asghar
Keyword(s):  
Energy Consumption ◽  
Unmanned Aerial Vehicles ◽  
Base Station ◽  
Clustering Method ◽  
Optimal Position ◽  
Q Learning ◽  
Cumulative Distance ◽  
Promising Solution ◽  
Centroid Location ◽  
Wireless Connectivity

Unmanned aerial vehicles (UAVs)-based communication system is a promising solution to meet coverage and capacity requirements of future wireless networks. However, UAV-enabled communications is constrained with its coverage, energy consumption, and flying regulations, and the number of works focusing on the sustainability aspect of UAV-assisted networking has been limited in the literature so far. In this paper, we propose a solution to this limitation; particularly, we design a $Q$-learning-based UAV positioning scheme for sustainable wireless connectivity considering key constraints, that are, altitude regulations, non-flight zones, and transmit power. The objective is to find the optimal position of the UAV base station (BS) and minimize the energy consumption while maximizing the number of users covered. Moreover, a weighting mechanism is developed, where the energy consumption and number of users covered can be prioritized according to network/battery conditions. The proposed Q-learning-based solution is compared to the baseline k-means clustering method, where the UAV BS is positioned at the centroid location that minimizes the cumulative distance between the UAV BS and the users. The results demonstrate that the proposed solution outperforms the baseline k-means clustering-based method in terms of the number of users covered while achieving the desired minimization of the energy consumption.

Reducing Energy Consumption: The Long-Term Effects of a Single TV Program

1984 ◽  
Vol 34 (3) ◽  
pp. 37-51 ◽  
Author(s):  
Richard A. Winett ◽  
Ingrid N. Leckliter ◽  
Donna E. Chinn ◽  
Brian Stahl
Keyword(s):  
Energy Consumption ◽  
Long Term Effects ◽  
Tv Program ◽  
Reducing Energy

A Clustering Based Data Integration Algorithm in Wireless Sensor Networks

2011 ◽  
Vol 186 ◽  
pp. 552-555
Author(s):  
Jing Huang ◽  
Hai Hua Li ◽  
Rui Yang ◽  
Hai Yan Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Base Station ◽  
Wireless Sensor ◽  
Important Research ◽  
Integration Algorithm ◽  
Clustering Approach ◽  
Static Clustering ◽  
Reducing Energy

Data fusion is an important research issue in wireless sensor networks (WSN). The clustering based approach can reduce the interference among nodes, maintain the balance of energy consumption within WSNs, and therefore prolong the lifetime of WSNs. A clustering-based algorithm called LEACH-EC is presented in the paper. Aiming at solving the problems of the existing algorithms, the LEACH-EC takes the static clustering approach to reduce the energy consumption during clustering stage by first clustering sensors and then selecting the heads of respective clusters. When the heads of clusters send data to the base station, a proposed multi-hop strategy is adopted to further decrease the energy consumption of head sensors. Compared with the existing algorithms, the LEACH-EC has shown a good performance on both extending the lifetime of WSNs as well as reducing energy consumption of sensors.

scholarly journals Energy-Aware Activity Control for Wireless Sensing Infrastructure Using Periodic Communication and Mixed-Integer Programming

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4828
Author(s):  
Piotr Arabas ◽  
Andrzej Sikora ◽  
Wojciech Szynkiewicz
Keyword(s):  
Energy Consumption ◽  
Integer Programming ◽  
Total Energy ◽  
Mixed Integer Programming ◽  
Base Station ◽  
Sensor Data ◽  
Mixed Integer ◽  
Medium Size ◽  
Energy Usage ◽  
Node Energy

This paper addresses the energy conservation problem in wireless sensor networks, in which sensor data are aggregated into packages and then transmitted periodically to the base station according to an established schedule. We formulate two mixed integer programming problems, first for minimum total energy usage and second for min-max per node energy usage. We present two algorithms for slot allocation that exploit the periodic nature of the data collection process by allocating a subset of nodes to subsequent frames. A mixed-integer solver solves the resulting mathematical programming task. The performed numerical experiments show that the proposed approach is appropriate for relatively small networks when minimizing the total energy consumption problem. Hopefully, the problem may be solved for medium size networks when a maximum node energy consumption performance index is used.

scholarly journals A novel methodology for optimum energy consumption in wireless sensor networks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamed Abbas ◽  
Nasser Otayf
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Design Methodology ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Content Type ◽  
Optimum Energy ◽  
The Creation ◽  
Reducing Energy

PurposeThe purpose of this paper is to minimize energy usage by maximizing network life in the creation of applications and protocolsDesign/methodology/approachThis paper presents a novel methodology for optimum energy consumption in wireless sensor networks. The proposed methodology introduces some protocols and logarithms that effectively contributed to reducing energy consumption in these types of networks.FindingsThe results of that comparison showed the ability of those logarithms and protocols to reduce that energy but in varying proportions. It can be concluded that a significant reduction in energy consumption approximately 50% could be obtained by the proposed methodology.Originality/valueHere, a novel methodology for optimum energy consumption in wireless sensor networks has been introduced.

Performance Analysis of RNC Clustering Protocol in Wireless Sensor Network

2019 ◽  
Vol 10 ◽  
Author(s):  
Piyush Rawat ◽  
Siddhartha Chauhan
Keyword(s):  
Energy Consumption ◽  
Network Performance ◽  
Energy Levels ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Threshold Function ◽  
Efficient Manner ◽  
Clustering Protocol

Background and Objective: The functionalities of wireless sensor networks (WSN) are growing in various areas, so to handle the energy consumption of network in an efficient manner is a challenging task. The sensor nodes in the WSN are equipped with limited battery power, so there is a need to utilize the sensor power in an efficient way. The clustering of nodes in the network is one of the ways to handle the limited energy of nodes to enhance the lifetime of the network for its longer working without failure. Methods: The proposed approach is based on forming a cluster of various sensor nodes and then selecting a sensor as cluster head (CH). The heterogeneous sensor nodes are used in the proposed approach in which sensors are provided with different energy levels. The selection of an efficient node as CH can help in enhancing the network lifetime. The threshold function and random function are used for selecting the cluster head among various sensors for selecting the efficient node as CH. Various performance parameters such as network lifespan, packets transferred to the base station (BS) and energy consumption are used to perform the comparison between the proposed technique and previous approaches. Results and Discussion: To validate the working of the proposed technique the simulation is performed in MATLAB simulator. The proposed approach has enhanced the lifetime of the network as compared to the existing approaches. The proposed algorithm is compared with various existing techniques to measure its performance and effectiveness. The sensor nodes are randomly deployed in a 100m*100m area. Conclusion: The simulation results showed that the proposed technique has enhanced the lifespan of the network by utilizing the node’s energy in an efficient manner and reduced the consumption of energy for better network performance.

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%.

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