Quality of Service-Based Node Relocation Technique for Mobile Sensor Networks

Awan, Ahmed Bilal; Khan, Muhammad Amir; Malik, Arshad Nawaz; Shah, Syed Ayaz Ali; Shahzad, Aamir; Nazir, Babar; Khan, Iftikhar Ahmed; Jadoon, Waqas; Sattar, Naveed; Jadoon, Rab Nawaz

doi:10.1155/2019/5043187

Cited by 8 publications

(4 citation statements)

References 27 publications

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“…Underwater sensor networks are one of the hot ocean observation technologies that have emerged in the recent years [4,5]. Underwater sensor networks have broad applications in many military and civilian fields, for example, for ocean exploration and development [6], for disaster warning and forecast [7], for environmental monitoring [8], and submarine detection [9]. erefore, the underwater sensor network has attracted widespread attention from domestic and foreign researchers.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Hierarchical Clustering Data Gathering Algorithm Based on Multiple Criteria Decision Making for 3D Underwater Sensor Networks

2020

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Data gathering is the basis of monitoring applications in an underwater sensor network, and excellent network coverage and data transmission reliability are the guarantees for the quality of monitoring tasks. However, the energy consumption of the nodes is too fast due to the heavy load of the cluster heads closer to the sink when data is transmitted between cluster heads (CHs) and the sink by multihop, which leads to an energy hole problem in an underwater sensor network of clustering technology. Aiming to address this problem, we propose a dynamic hierarchical clustering data gathering algorithm based on multiple criteria decision making (DHCDGA) in a 3D underwater sensor network. Firstly, the entire monitoring network is divided into many layers. For selecting a cluster head in each layer, multiple criteria decision making of an intuitionistic fuzzy Analytic Hierarchy Process (AHP) and hierarchical fuzzy integration is adopted. Furthermore, a sorting algorithm is used to form a clustering topology algorithm to solve the problem that there is the only node in one cluster. Then, an energy-balanced routing algorithm between clusters is proposed according to the residual energy of the node, the depth, and the number of neighbor nodes. Finally, the simulation results show that DHCDGA can not only effectively balance the energy consumption of the network and prolong the network lifetime but also improve network coverage and data gathering reliability.

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Section: Introductionmentioning

confidence: 99%

A Dynamic Hierarchical Clustering Data Gathering Algorithm Based on Multiple Criteria Decision Making for 3D Underwater Sensor Networks

2020

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“…This information is updated periodically to recover from network partitioning. A partition detection and recovery approach is presented in Awan et al 44 Collaborative node movement is used to cover the void region. A reconnectivity approach is proposed in Shriwastav and Ghose 45 using mobile restoration nodes.…”

Section: Related Workmentioning

confidence: 99%

Toward connectivity of a disconnected cluster in partitioned wireless sensor network for time-critical data collection

Nasr

Khan

2020

International Journal of Distributed Sensor Networks

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Reliable network connectivity is one of the major design issues in the context of wireless sensor networks. These networks have diverse communication patterns due to non-uniform sensing activities at various locations in the environment being monitored. In such scenarios, some nodes lying in high-traffic zones may consume more energy and eventually die out resulting in network partitioning. This gives rise to a situation in which alive nodes are trapped in a disconnected cluster, and they do not have enough radio range to communicate their data to the destination (i.e. a sink or a relay node connected to the main part of the network). This phenomenon may deprive a large number of alive nodes of sending their important time-critical data to the sink. In this article, we propose a virtual antenna–based cooperative beamforming approach for retrieving valuable data from these disconnected nodes. In the proposed approach, the sensor nodes in an isolated partition work together to form a directional beam. This directional beam significantly increases their overall communication range to reach out to a distant relay node which is connected to the main part of the network. The proposed approach of cooperative beamforming–based partition connectivity is more effective when a cluster with a favorably large number of nodes gets partitioned. Furthermore, a beamforming-based mechanism is proposed for a disconnected cluster to locate the nearest relay node which is still connected to the sink and to reconnect itself to the main part of the network via the most adjacent relay node for time-critical data transmission. The proposed mechanism is then evaluated through simulation results.

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“…Increasingly inexpensive UAVs, thanks to their mobility and flexibility, may efficiently help maintain the network connectivity and relay data [1,2]. While WSN is an appropriate solution to continuously gather data, its network nodes are not easily relocated and their wireless communication links are essentially unreliable [1][2][3]. This hinders capturing a full view over a large area.…”

Section: Introductionmentioning

confidence: 99%

Self-Navigating UAVs for Supervising Moving Objects over Large-Scale Wireless Sensor Networks

Van

Trung

2020

International Journal of Aerospace Engineering

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Increasingly inexpensive unmanned aerial vehicles (UAVs) are helpful for searching and tracking moving objects in ground events. Previous works either have assumed that data about the targets are sufficiently available, or they solely rely on on-board electronics (e.g., camera and radar) to chase them. In a searching mission, path planning is essentially preprogrammed before taking off. Meanwhile, a large-scale wireless sensor network (WSN) is a promising means for monitoring events continuously over immense areas. Due to disadvantageous networking conditions, it is nevertheless hard to maintain a centralized database with sufficient data to instantly estimate target positions. In this paper, we therefore propose an online self-navigation strategy for a UAV-WSN integrated system to supervise moving objects. A UAV on duty exploits data collected on the move from ground sensors together with its own sensing information. The UAV autonomously executes edge processing on the available data to find the best direction toward a target. The designed system eliminates the need of any centralized database (fed continuously by ground sensors) in making navigation decisions. We employ a local bivariate regression to formulate acquired sensor data, which lets the UAV optimally adjust its flying direction, synchronously to reported data and object motion. In addition, we also construct a comprehensive searching and tracking framework in which the UAV flexibly sets its operation mode. As a result, least communication and computation overhead is actually induced. Numerical results obtained from NS-3 and Matlab cosimulations have shown that the designed framework is clearly promising in terms of accuracy and overhead costs.

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Quality of Service-Based Node Relocation Technique for Mobile Sensor Networks

Cited by 8 publications

References 27 publications

A Dynamic Hierarchical Clustering Data Gathering Algorithm Based on Multiple Criteria Decision Making for 3D Underwater Sensor Networks

A Dynamic Hierarchical Clustering Data Gathering Algorithm Based on Multiple Criteria Decision Making for 3D Underwater Sensor Networks

Toward connectivity of a disconnected cluster in partitioned wireless sensor network for time-critical data collection

Self-Navigating UAVs for Supervising Moving Objects over Large-Scale Wireless Sensor Networks

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