Key Laboratory for IOT and Information Fusion Technology of Zhejiang

Hangzhou, China

Key Laboratory for IOT and Information Fusion Technology of Zhejiang

Hangzhou, China
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Jiang P.,Hangzhou Dianzi University | Jiang P.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | Feng Y.,Hangzhou Dianzi University | Feng Y.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | And 2 more authors.
Tien Tzu Hsueh Pao/Acta Electronica Sinica | Year: 2017

In three-dimensional(3D) underwater wireless sensor network, the bad environment is easy to cause node invalidation and topology instability. Considering that obstacles and boundary exist in practical water environment, we put forward the fruit fly inspired underwater sensor network deployment algorithm. Firstly, the method regarded connectivity as the constraint condition, and it used foraging behavior of fruit fly to obtain the nodes location. Meanwhile, it added European starling flying features to keep the stability of network topology. Finally, it used obstacle local perceive model to avoid obstacles. The results show that the algorithm can avoid obstacles, further improve coverage and connectivity, and reduce energy consumption. © 2017, Chinese Institute of Electronics. All right reserved.


Jiang P.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | Jiang P.,Hangzhou Dianzi University | Liu J.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | Liu J.,Hangzhou Dianzi University | And 5 more authors.
Sensors (Switzerland) | Year: 2016

Considering that deployment strategies for underwater sensor networks should contribute to fully connecting the networks, a Guaranteed Full Connectivity Node Deployment (GFCND) algorithm is proposed in this study. The GFCND algorithm attempts to deploy the coverage nodes according to the greedy iterative strategy, after which the connectivity nodes are used to improve network connectivity and fully connect the whole network. Furthermore, a Location Dispatch Based on Command Nodes (LDBCN) algorithm is proposed, which accomplishes the location adjustment of the common nodes with the help of the SINK node and the command nodes. The command nodes then dispatch the common nodes. Simulation results show that the GFCND algorithm achieves a comparatively large coverage percentage and a fully connected network; furthermore, the LDBCN algorithm helps the common nodes preserve more total energy when they reach their destination locations. © 2016 by the authors, licensee MDPI, Basel, Switzerland.


Jiang P.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | Jiang P.,Hangzhou Dianzi University | Liu J.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | Liu J.,Hangzhou Dianzi University | And 2 more authors.
Sensors (Switzerland) | Year: 2015

A node non-uniform deployment based on clustering algorithm for underwater sensor networks (UWSNs) is proposed in this study. This algorithm is proposed because optimizing network connectivity rate and network lifetime is difficult for the existing node non-uniform deployment algorithms under the premise of improving the network coverage rate for UWSNs. A high network connectivity rate is achieved by determining the heterogeneous communication ranges of nodes during node clustering. Moreover, the concept of aggregate contribution degree is defined, and the nodes with lower aggregate contribution degrees are used to substitute the dying nodes to decrease the total movement distance of nodes and prolong the network lifetime. Simulation results show that the proposed algorithm can achieve a better network coverage rate and network connectivity rate, as well as decrease the total movement distance of nodes and prolong the network lifetime. © 2015 by the authors; licensee MDPI, Basel, Switzerland.


Jiang P.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | Jiang P.,Hangzhou Dianzi University | Liu J.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | Liu J.,Hangzhou Dianzi University | And 6 more authors.
Sensors (Switzerland) | Year: 2016

Existing node deployment algorithms for underwater sensor networks are nearly unable to improve the network coverage rate under the premise of ensuring the full network connectivity and do not optimize the communication and move energy consumption during the deployment. Hence, a node deployment algorithm based on connected dominating set (CDS) is proposed. After randomly sowing the nodes in 3D monitoring underwater space, disconnected nodes move to the sink node until the network achieves full connectivity. The sink node then performs centralized optimization to determine the CDS and adjusts the locations of dominated nodes. Simulation results show that the proposed algorithm can achieve a high coverage rate while ensuring full connectivity and decreases the communication and movement energy consumption during deployment. © 2016 by the authors; licensee MDPI, Basel, Switzerland.


Jiang P.,Hangzhou Dianzi University | Jiang P.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | Xu Y.,Hangzhou Dianzi University | Xu Y.,Key Laboratory for IOT and Information Fusion Technology of Zhejiang | And 2 more authors.
Sensors (Switzerland) | Year: 2016

Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption. © 2016 by the authors; licensee MDPI, Basel, Switzerland.


PubMed | Key Laboratory for IOT and Information Fusion Technology of Zhejiang
Type: Journal Article | Journal: Sensors (Basel, Switzerland) | Year: 2015

A node non-uniform deployment based on clustering algorithm for underwater sensor networks (UWSNs) is proposed in this study. This algorithm is proposed because optimizing network connectivity rate and network lifetime is difficult for the existing node non-uniform deployment algorithms under the premise of improving the network coverage rate for UWSNs. A high network connectivity rate is achieved by determining the heterogeneous communication ranges of nodes during node clustering. Moreover, the concept of aggregate contribution degree is defined, and the nodes with lower aggregate contribution degrees are used to substitute the dying nodes to decrease the total movement distance of nodes and prolong the network lifetime. Simulation results show that the proposed algorithm can achieve a better network coverage rate and network connectivity rate, as well as decrease the total movement distance of nodes and prolong the network lifetime.


PubMed | Key Laboratory for IOT and Information Fusion Technology of Zhejiang
Type: Journal Article | Journal: Sensors (Basel, Switzerland) | Year: 2016

Existing node deployment algorithms for underwater sensor networks are nearly unable to improve the network coverage rate under the premise of ensuring the full network connectivity and do not optimize the communication and move energy consumption during the deployment. Hence, a node deployment algorithm based on connected dominating set (CDS) is proposed. After randomly sowing the nodes in 3D monitoring underwater space, disconnected nodes move to the sink node until the network achieves full connectivity. The sink node then performs centralized optimization to determine the CDS and adjusts the locations of dominated nodes. Simulation results show that the proposed algorithm can achieve a high coverage rate while ensuring full connectivity and decreases the communication and movement energy consumption during deployment.

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