A Modified K-Medoids Algorithm for Deploying a Required Number of Computing Systems in a Three Dimensional Space in Underwater Wireless Sensor Networks

2020 ◽  
Author(s):  
Mohammad Alsulami ◽  
Raafat Elfouly ◽  
Reda Ammar ◽  
Abdullah Alenizi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Computing Systems ◽  
Three Dimensional Space

Sensor Localization in Three-Dimensional Space

2017 ◽  
pp. 120-144
Author(s):  
Habib M. Ammari ◽  
Angela J. Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Wireless Sensor ◽  
Two Dimensional ◽  
Localization Problem ◽  
Sensor Localization ◽  
Battery Power ◽  
Three Dimensional Space

Thanks to key advances in wireless communication and electronics, sensors have emerged as an appealing technology for several interesting applications, such as civilian (health and environment monitoring), natural (disaster detection), military (battlefield surveillance), and agricultural (precision agriculture) applications, to name a few. When grouped together, these sensors form a network to measure and gather data of the surrounding environment with respect to a specific phenomenon. The sensors are battery-powered, tiny devices that possess all the characteristics of a traditional computer, including storage, processing, and communication capabilities. In addition, these sensors are capable of sensing the environment and collecting data regarding several parameters, such as temperature, light, sound, vibration, etc. Unfortunately, all the sensors' capabilities are limited due to their physical size. In particular, the sensors have limited battery power as usually they are equipped with AA/AAA batteries whose lifetime is short. Therefore, the main challenge in the design of this type of network is the sensors' battery power (or energy), which is a critical component for the operation of the whole network. Moreover, these sensors communicate (possibly) wirelessly with each other to collect sensed data and accomplish the goals of their missions. To this end, the sensors are required to know their locations and those of their neighbors. Therefore, sensor localization is a crucial aspect for the design and development of wireless sensor networks. Various algorithms and protocols have been developed for sensor localization in both two-dimensional and three- dimensional wireless sensor networks. However, the problem of sensor localization in a three-dimensional space has not been investigated in the literature as extensively as its counterpart in a two-dimensional space. In this book chapter, we propose to study the sensor localization problem in three-dimensional wireless sensor networks. More precisely, this book chapter's sole focus will be on three-dimensional sensor deployment, and it aims to provide an overview of the existing solutions to the localization problem in a three-dimensional space. Basically, it proposes a classification of localization algorithms, and discusses different three-dimensional sensor localization approaches along with their motivation and evaluation.

Node Deployment of Wireless Sensor Networks in Long Narrow Area

2011 ◽  
Vol 128-129 ◽  
pp. 648-651
Author(s):  
Xu Guang Sun ◽  
Jing Sha He ◽  
Ming Xin Yang ◽  
Xiao Ling Sun
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Wireless Sensor ◽  
Two Dimensional ◽  
Node Deployment ◽  
Significant Difference ◽  
Narrow Area ◽  
Three Dimensional Space

In this paper, we study the node deployment in long narrow area of wireless sensor networks. Currently, studies on node deployment of wireless sensor networks mostly concentrated in two-dimensional flat area and three-dimensional space area which are complicated or inapplicable for long narrow area. The significant difference of node deployment between long narrow area and two-dimensional area is that the nodes in two-dimensional monitored area can be deployed anywhere, while the nodes in long narrow area can only be deployed by side with the environmental constraints. Considering the coverage, connectivity and reliability, we give out the densities and numbers of needed nodes in node deployment scheme for both 1-connected cover and k-connected cover in long narrow area covered completely by sensor networks.

Sensor Localization in Three-Dimensional Space

2020 ◽  
pp. 427-451
Author(s):  
Habib M. Ammari ◽  
Angela J. Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Wireless Sensor ◽  
Two Dimensional ◽  
Localization Problem ◽  
Sensor Localization ◽  
Battery Power ◽  
Three Dimensional Space

Thanks to key advances in wireless communication and electronics, sensors have emerged as an appealing technology for several interesting applications, such as civilian (health and environment monitoring), natural (disaster detection), military (battlefield surveillance), and agricultural (precision agriculture) applications, to name a few. When grouped together, these sensors form a network to measure and gather data of the surrounding environment with respect to a specific phenomenon. The sensors are battery-powered, tiny devices that possess all the characteristics of a traditional computer, including storage, processing, and communication capabilities. In addition, these sensors are capable of sensing the environment and collecting data regarding several parameters, such as temperature, light, sound, vibration, etc. Unfortunately, all the sensors' capabilities are limited due to their physical size. In particular, the sensors have limited battery power as usually they are equipped with AA/AAA batteries whose lifetime is short. Therefore, the main challenge in the design of this type of network is the sensors' battery power (or energy), which is a critical component for the operation of the whole network. Moreover, these sensors communicate (possibly) wirelessly with each other to collect sensed data and accomplish the goals of their missions. To this end, the sensors are required to know their locations and those of their neighbors. Therefore, sensor localization is a crucial aspect for the design and development of wireless sensor networks. Various algorithms and protocols have been developed for sensor localization in both two-dimensional and three- dimensional wireless sensor networks. However, the problem of sensor localization in a three-dimensional space has not been investigated in the literature as extensively as its counterpart in a two-dimensional space. In this book chapter, we propose to study the sensor localization problem in three-dimensional wireless sensor networks. More precisely, this book chapter's sole focus will be on three-dimensional sensor deployment, and it aims to provide an overview of the existing solutions to the localization problem in a three-dimensional space. Basically, it proposes a classification of localization algorithms, and discusses different three-dimensional sensor localization approaches along with their motivation and evaluation.

scholarly journals Research on Algorithm of Three-Dimensional Wireless Sensor Networks Node Localization

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jiang Minlan ◽  
Luo Jingyuan ◽  
Zou Xiaokang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Minimum Problem ◽  
Localization Algorithm ◽  
Node Localization ◽  
Anchor Nodes

This paper proposes a three-dimensional wireless sensor networks node localization algorithm based on multidimensional scaling anchor nodes, which is used to realize the absolute positioning of unknown nodes by using the distance between the anchor nodes and the nodes. The core of the proposed localization algorithm is a kind of repeated optimization method based on anchor nodes which is derived from STRESS formula. The algorithm employs the Tunneling Method to solve the local minimum problem in repeated optimization, which improves the accuracy of the optimization results. The simulation results validate the effectiveness of the algorithm. Random distribution of three-dimensional wireless sensor network nodes can be accurately positioned. The results satisfy the high precision and stability requirements in three-dimensional space node location.

scholarly journals A data forwarding algorithm based on Markov thought in underwater wireless sensor networks

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769198
Author(s):  
Dongwei Li ◽  
Jingli Du ◽  
Linfeng Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Success Rate ◽  
Three Dimensional ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks ◽  
Data Forwarding ◽  
Bottom To Top

The underwater wireless sensor networks composed of sensor nodes are deployed underwater for monitoring and gathering submarine data. Since the underwater environment is usually unpredictable, making the nodes move or be damaged easily, such that there are several vital objectives in the data forwarding issue, such as the delivery success rate, the error rate, and the energy consumption. To this end, we propose a data forwarding algorithm based on Markov thought, which logically transforms the underwater three-dimensional deployment model into a two-dimensional model, and thus the nodes are considered to be hierarchically deployed. The data delivery is then achieved through a “bottom to top” forwarding mode, where the delivery success rate is improved and the energy consumption is reduced because the established paths are more stable, and the proposed algorithm is self-adaptive to the dynamic routing loads.

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