Data Reconstructing Algorithm in Unreliable Links Based on Matrix Completion for Heterogeneous Wireless Sensor Networks

2019 ◽  
Vol 33 (13) ◽  
pp. 1951012 ◽  
Author(s):  
Shuang Zhai ◽  
Zhihong Qian ◽  
Bingtao Yang ◽  
Xue Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Compressed Sensing ◽  
Matrix Completion ◽  
Wireless Sensor ◽  
Reconstruction Accuracy ◽  
Heterogeneous Wireless Sensor Networks ◽  
Unreliable Links

In heterogeneous wireless sensor networks, the data collection method based on compressed sensing technology is susceptible to packet loss and noise, which leads to a decrease in data reconstruction accuracy in unreliable links. Combining compressed sensing and matrix completion, we propose a clustering optimization algorithm based on structured noise matrix completion, in which the cluster head transmits the compressed sampling data and compression strategy to the base station. The algorithm we proposed can reduce the energy consumption of the node in the process of data collection, redundant data and transmission delay. The rank-1 matrix completion algorithm constructs an extremely sparse observation matrix, which is adopted by the sink node to complete the reconstruction of the whole network data. Simulation experiments show that the proposed algorithm reduces network transmission data, balances node energy consumption, improves data transmission efficiency and reconstruction accuracy, and extends the network life cycle.

scholarly journals Enhancement of Data Collection Performance in Wireless Sensor Networks Based on Path-Constrained Mobile Sink

2021 ◽  
Vol 14 (1) ◽  
pp. 400-409
Author(s):  
Mohamed Borham ◽  
◽  
Ghada Khoriba ◽  
Mostafa-Sami Mostafa ◽  
◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Routing Protocol ◽  
Maximum Amount ◽  
Wireless Sensor ◽  
Collection Process ◽  
Data Collection Process ◽  
Energy Limitation

Due to the energy limitation in Wireless Sensor Networks (WSNs), most researches related to data collection in WSNs focus on how to collect the maximum amount of data from the network with minimizing the energy consumption as much as possible. Many types of research that are related to data collection are proposed to overcome this issue by using mobility with path constrained as Maximum Amount Shortest Path routing Protocol (MASP) and zone-based algorithms. Recently, Zone-based Energy-Aware Data Collection Protocol (ZEAL) and Enhanced ZEAL have been presented to reduce energy consumption and provide an acceptable data delivery rate. However, the time spent on data collection operations should be taken into account, especially concerning real-time systems, as time is the most critical factor for these systems' performance. In this paper, a routing protocol is proposed to improve the time needed for the data collection process considering less energy consumption. The presented protocol uses a novel path with a communication time-slot assignment algorithm to reduce the count of cycles that are needed for the data collection process with reduction of 50% of the number of cycles needed for other protocols. Therefore, the time and energy needed for data collection are reduced by approximately 25%and 6% respectively, which prolongs the network lifetime. The proposed protocol is called Energy-Time Aware Data Collection Protocol (ETCL).

scholarly journals Low-Energy Data Collection in Wireless Sensor Networks Based on Matrix Completion

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 945 ◽  
Author(s):  
Yi Xu ◽  
Guiling Sun ◽  
Tianyu Geng ◽  
Jingfei He
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Sampling Method ◽  
Matrix Completion ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Real World Data ◽  
Recovery Algorithm ◽  
Sampling Ratio

Sparse sensing schemes based on matrix completion for data collection have been proposed to reduce the power consumption of data-sensing and transmission in wireless sensor networks (WSNs). While extensive efforts have been made to improve the recovery accuracy from the sparse samples, it is usually at the cost of running time. Moreover, most data-collection methods are difficult to implement with low sampling ratio because of the communication limit. In this paper, we design a novel data-collection method including a Rotating Random Sparse Sampling method and a Fast Singular Value Thresholding algorithm. With the proposed method, nodes are in the sleep mode most of the time, and the sampling ratio varies over time slots during the sampling process. From the samples, a corresponding algorithm with Nesterov technique is given to recover the original data accurately and fast. With two real-world data sets in WSNs, simulations verify that our scheme outperforms other schemes in terms of energy consumption, reconstruction accuracy, and rate. Moreover, the proposed sampling method enhances the recovery algorithm and prolongs the lifetime of WSNs.

scholarly journals Designing Constrained Trajectory Based on Maximizing Energy Reduction in Large-Scale Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jia Xu ◽  
Chuan Ping Wang ◽  
Hua Dai ◽  
Da Qiang Zhang ◽  
Jing Jie Yu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Mobile Sink ◽  
Energy Reduction ◽  
Wireless Sensor ◽  
Movement Trajectory ◽  
Computation Efficiency

TheMobile Sinkbased data collection in wireless sensor network can reduce energy consumption efficiently and has been a new data collection paradigm. In this paper, we focus on exploring polynomial algorithm to compute the constrained trajectory of theMobile Sinkfor data collection. We first present a universal system model for designing constrained trajectory in large-scale wireless sensor networks and formulate the problem as theMaximizing Energy Reduction for Constrained Trajectory(MERC) problem. We show that the MERC problem is NP-hard and design an approximation algorithm (CTMER), which follows the greedy approach to design the movement trajectory of theMobile Sinkby maximizing theeffective average energy reduction. Through both rigid theoretical analysis and extensive simulations, we demonstrate that our algorithm achieves high computation efficiency and is superior to otherMobile Sinkbased data collection methods in aspects of energy consumption and network lifetime.

scholarly journals Zonal stable election protocol for heterogeneous wireless sensor networks

2018 ◽  
Vol 7 (2.7) ◽  
pp. 725
Author(s):  
V Appala Raju ◽  
V Sri Harsha ◽  
N Bhanu Deepthi ◽  
N Prasanth
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Stability Period ◽  
Heterogeneous Wireless Sensor Networks ◽  
The Given ◽  
Stable Election Protocol

Wireless sensor networks play a key role in communication. They are comprised of hundreds sensor nodes with limited energy. So energy utilization major issue in WSN for performing the given task. So most of the protocols are concentrate on energy consumption .Zonal mechanism is one popular WSN routing technique.    In this work we are mostly concentrating on optimization of stable election protocol for heterogeneous wireless sensor networks and compare the performance with LEACH and SEP. Most of the work to find stability period, alive nodes and dead nodes, throughput in LEACH, SEP, ZSEP.  We are stimulated in MATLAB tool. Stimulation results prove that improvement in stability period and through put is better in ZSEP when compared to LEACH and SEP.  

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