scholarly journals Two-Tier PSO Based Data Routing Employing Bayesian Compressive Sensing in Underwater Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5961
Author(s):  
Xuechen Chen ◽  
Wenjun Xiong ◽  
Sheng Chu
Keyword(s):  
Sensor Networks ◽  
Compressive Sensing ◽  
Fitness Function ◽  
Cluster Head ◽  
Three Dimensional ◽  
Life Time ◽  
Reconstruction Error ◽  
Underwater Sensor Networks ◽  
Data Routing ◽  
Reconstructed Signal

Underwater acoustic sensor networks play an important role in assisting humans to explore information under the sea. In this work, we consider the combination of sensor selection and data routing in three dimensional underwater wireless sensor networks based on Bayesian compressive sensing and particle swarm optimization. The algorithm we proposed is a two-tier PSO approach. In the first tier, a PSO-based clustering protocol is proposed to synthetically consider the energy consumption and uniformity of cluster head distribution. Then in the second tier, a PSO-based routing protocol is proposed to implement inner-cluster one-hop routing and outer-cluster multi-hop routing. The nodes selected to constitute i-th effective routing path decide which positions in the i-th row of the measurement matrix are nonzero. As a result, in this tier the protocol comprehensively considers energy efficiency, network balance and data recovery quality. The Bayesian Cramér-Rao Bound (BCRB) in such a case is analyzed and added in the fitness function to monitor the mean square error of the reconstructed signal. The experimental results validate that our algorithm maintains a longer life time and postpones the appearance of the first dead node while keeps the reconstruction error lower compared with the cutting-edge algorithms which are also based on distributed multi-hop compressive sensing approaches.

scholarly journals LEVEL PARTITIONING OF NODES TO ENHANCE THE NETWORK LIFETIME DURING INTRUSION DETECTION IN WIRELESS SENSOR NETWORKS

2013 ◽  
pp. 21-26
Author(s):  
A. BABU KARUPPIAH ◽  
KEERTHINATH KEERTHINATH ◽  
M. KUNDRU MALAI RAJAN ◽  
K.ASHIF ISMAIL SHERIFF ◽  
S. RAJARAM
Keyword(s):  
Sensor Networks ◽  
Intrusion Detection ◽  
Cluster Head ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Efficient Operation ◽  
Network Life Time ◽  
Power Capability

A Wireless Sensor Network (WSN) consists of many sensor nodes with low cost and power capability Based on the deployment, in the sensing coverage of a sensor node, typically more nodes are covered. A major challenge in constructing a WSN is to enhance the network life time. Nodes in a WSN are usually highly energy-constrained and expected to operate for long periods from limited on-board energy reserves. To permit this, nodes and the embedded software that they execute – must have energy-aware operation. Because of this, continued developments in energy-efficient operation are paramount, requiring major advances to be made in energy hardware, power management circuitry and energy aware algorithms znd protocols. During Intrusion Detection in sensor networks, some genuine nodes need to communicate with the Cluster Head to inform about the details of malicious nodes. For such applications in sensor networks, a large number of sensor nodes that are deployed densely in specific sensing environment share the same sensing tasks. Due to this, the individual nodes might waste their energy in sensing data that are not destined to it and as a result the drain in the energy of the node is more resulting in much reduced network life time. In this paper, a novel algorithm is developed to avoid redundancy in sensing the data thereby enhancing the life time of the network. The concept of Power Factor bit is proposed while a node communicates with the Cluster Head. The simulation results show that the network life time is greatly enhanced by the proposed method.

scholarly journals Energy-Efficient QoS-Aware Intelligent Hybrid Clustered Routing Protocol for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Parvinder Singh ◽  
Rajeshwar Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Large Scale ◽  
Fitness Function ◽  
Geographical Area ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor

A wireless sensor network consists of numerous low-power microsensor devices that can be deployed in a geographical area for remote sensing, surveillance, control, and monitoring applications. The advancements of wireless devices in terms of user-friendly interface, size, and deployment cost have given rise to many smart applications of wireless sensor networks (WSNs). However, certain issues like energy efficiency, long lifetime, and communication reliability restrict their large scale utilization. In WSNs, the cluster-based routing protocols assist nodes to collect, aggregate, and forward sensed data from event regions towards the sink node through minimum cost links. A clustering method helps to improve data transmission efficiency by dividing the sensor nodes into small groups. However, improper cluster head (CH) selection may affect the network lifetime, average network energy, and other quality of service (QoS) parameters. In this paper, a multiobjective clustering strategy is proposed to optimize the energy consumption, network lifetime, network throughput, and network delay. A fitness function has been formulated for heterogenous and homogenous wireless sensor networks. This fitness function is utilized to select an optimum CH for energy minimization and load balancing of cluster heads. A new hybrid clustered routing protocol is proposed based on fitness function. The simulation results conclude that the proposed protocol achieves better efficiency in increasing the network lifetime by 63%, 26%, and 10% compared with three well-known heterogeneous protocols: DEEC, EDDEEC, and ATEER, respectively. The proposed strategy also attains better network stability than a homogenous LEACH protocol.

scholarly journals ProLo: Localization via Projection for Three-Dimensional Mobile Underwater Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1414 ◽  
Author(s):  
Feng Zhou ◽  
Yushi Li ◽  
Hejun Wu ◽  
Zhimin Ding ◽  
Xiying Li
Keyword(s):  
Sensor Networks ◽  
Sensor Node ◽  
Three Dimensional ◽  
Mobile Sensor Networks ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Water Currents ◽  
Localization Scheme ◽  
Moving Direction ◽  
Gps Devices

We study the problem of three-dimensional localization of the underwater mobile sensor networks using only range measurements without GPS devices. This problem is challenging because sensor nodes often drift with unknown water currents. Consequently, the moving direction and speed of a sensor node cannot be predicted. Moreover, the motion devices of the sensor nodes are not accurate in underwater environments. Therefore, we propose an adaptive localization scheme, ProLo, taking these uncertainties into consideration. This scheme applies the rigidity theory and maintains a virtual rigid structure through projection. We have proved the correctness of this three-dimensional localization scheme and also validated it using simulation. The results demonstrate that ProLo is promising for real mobile underwater sensor networks with various noises and errors.

Improving the performance of hierarchical wireless sensor networks using the metaheuristic algorithms: efficient cluster head selection

Sensor Review ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Farzad Kiani ◽  
Amir Seyyedabbasi ◽  
Sajjad Nematzadeh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Fitness Function ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Second Phase ◽  
Content Type

Purpose Efficient resource utilization in wireless sensor networks is an important issue. Clustering structure has an important effect on the efficient use of energy, which is one of the most critical resources. However, it is extremely vital to choose efficient and suitable cluster head (CH) elements in these structures to harness their benefits. Selecting appropriate CHs and finding optimal coefficients for each parameter of a relevant fitness function in CHs election is a non-deterministic polynomial-time (NP-hard) problem that requires additional processing. Therefore, the purpose of this paper is to propose efficient solutions to achieve the main goal by addressing the related issues. Design/methodology/approach This paper draws inspiration from three metaheuristic-based algorithms; gray wolf optimizer (GWO), incremental GWO and expanded GWO. These methods perform various complex processes very efficiently and much faster. They consist of cluster setup and data transmission phases. The first phase focuses on clusters formation and CHs election, and the second phase tries to find routes for data transmission. The CH selection is obtained using a new fitness function. This function focuses on four parameters, i.e. energy of each node, energy of its neighbors, number of neighbors and its distance from the base station. Findings The results obtained from the proposed methods have been compared with HEEL, EESTDC, iABC and NR-LEACH algorithms and are found to be successful using various analysis parameters. Particularly, I-HEELEx-GWO method has provided the best results. Originality/value This paper proposes three new methods to elect optimal CH that prolong the networks lifetime, save energy, improve overhead along with packet delivery ratio.

A LOW-COST RANGE-FREE LOCALIZATION SCHEME FOR THREE-DIMENSIONAL UNDERWATER SENSOR NETWORKS

2013 ◽  
Vol 05 (01) ◽  
pp. 1350005
Author(s):  
XIANLING LU ◽  
DEYING LI ◽  
YI HONG ◽  
WENPING CHEN
Keyword(s):  
Sensor Networks ◽  
Low Cost ◽  
Three Dimensional ◽  
Underwater Sensor Networks ◽  
Transmission Power ◽  
Localization Accuracy ◽  
Localization Scheme ◽  
Variable Transmission ◽  
Anchor Nodes ◽  
Range Free

Localization is one of the fundamental tasks for underwater sensors networks (USNs). It is required for data tagging, target detection, route protocols, and so on. In this paper, we propose an efficient low-cost range-free localization scheme for 3D underwater sensor networks (3D-LRLS) without any additional hardware infrastructure. In our scheme, each anchor node has variable transmission power levels. At first, the power levels of each anchor are decided by the Delaunay triangulation for the network space. Then, ordinary sensors listen to the beacons sent from the anchor nodes. Based on the beacon messages, each node calculates its location individually by a low computational complexity method. The extensive simulation results demonstrate that 3D-LRLS is efficient in terms of both localization ratio and localization accuracy.

Clustering Algorithm to Reduce Power Consumptions for Wireless Sensor Networks

2012 ◽  
Vol 433-440 ◽  
pp. 5228-5232
Author(s):  
Mohammad Ahmadi ◽  
Hamid Faraji ◽  
Hossien Zohrevand
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Cluster Heads

A sensor network has many sensor nodes with limited energy. One of the important issues in these networks is the increase of the life time of the network. In this article, a clustering algorithm is introduced for wireless sensor networks that considering the parameters of distance and remaining energy of each node in the process of cluster head selection. The introduced algorithm is able to reduce the amount of consumed energy in the network. In this algorithm, the nodes that have more energy and less distance from the base station more probably will become cluster heads. Also, we use algorithm for finding the shortest path between cluster heads and base station. The results of simulation with the help of Matlab software show that the proposed algorithm increase the life time of the network compared with LEACH algorithm.

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