CS-FCDA: A Compressed Sensing-Based on Fault-Tolerant Data Aggregation in Sensor Networks

Sun, Zeyu; Liu, Baoluo; Li, Chuan‐Feng; Nie, Yiming

doi:10.3390/s18113749

Cited by 15 publications

(15 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An isolated area is randomly selected, and the location, where the local density of the monitoring target is relatively large, is deployed to deploy the first sensor node. The greedy method based on the local density of the monitoring target is used for tackling the coverage problem of other locations in this area [48], [49]. Specifically, within the maximum communication range R max of the currently deployed sensor node locations x i , the location x i+1 with the highest local density of the monitoring target is selected as the deployment location of the next sensor node, that is,…”

Section: Implementation Of Im-csr Algorithm a Level Determinatiomentioning

confidence: 99%

CSR-IM: Compressed Sensing Routing-Control- Method With Intelligent Migration-Mechanism Based on Sensing Cloud-Computing

Sun

Liu

et al. 2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

Considering the event-based WSNs routing, the frequent changes of topology may result to the large energy costs in the whole network. Therefore, this paper proposes a Compressed Sensing Routingcontrol-method with Intelligent Migration-mechanism based on Sensing Cloud-computing (CSR-IM). First, the method gives a determining the moving speed and position of the target node through compressed sensing theory, and at the same time, it gives the lower bound calculation process of the target node state estimation value at k + 1 time by the probability knowledge. Second, with the purpose of reducing the network load, the routing tree with the center of fog nodes is established to obtain the data in the route effectively and optimize the data aggregation routing process, and then energy cost of the whole network is balanced. Finally, the simulation experiments show that method of this paper (CSR-IM) and other algorithms have improved the average data aggregation rate by 8.19%, and the average network coverage has increased by 12.65%, which proves that the proposed algorithm is effective and practical. INDEX TERMS Intelligent migration-mechanism, sensing cloud-computing, routing-control-method, compressed sensing.

show abstract

Section: Implementation Of Im-csr Algorithm a Level Determinatiomentioning

confidence: 99%

CSR-IM: Compressed Sensing Routing-Control- Method With Intelligent Migration-Mechanism Based on Sensing Cloud-Computing

Sun

Liu

et al. 2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…This algorithm uses clusters for the first time to determine the sensing direction of directional sensor nodes to achieve maximum target coverage. Paper [32] proposed a network coverage enhancement strategy based on an improved genetic algorithm and binary ant colony algorithm. This strategy introduced a genetic operator into the binary ant colony algorithm, and used crossover and mutation to expand the search space and achieve global optimization.…”

Section: A Coverage Problemmentioning

confidence: 99%

CoC-SCS: Cooperative-Optimization Coverage Algorithm Based on Sensor Cloud Systems in Intelligent Computing

Sun

2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

the coverage of traditional Wireless Sensor Networks (WSNs) is limited by node energy and data redundancy, which forces WSNs to be interrupted abnormally. Therefore, Cooperative-optimization Coverage Algorithm based on Sensor Cloud Systems in Intelligent Computing (CoC-SCS) is proposed. First, the algorithm determines the location information of the Focus Target Nodes (FTNs), and uses the Genetic Algorithm (GA) to give the node path planning. Second, the mutation parameters and the controllable threshold parameters are used in order to control the event domain nodes. Optimizing clustering makes the clustering of the nodes to be more uniform, so that it can improve the search ability of the global target nodes and even reduce the nodes energy consumption. Third, the adaptation function covers the continuity of the covered target positions and the monitoring range of the nodes. Optimization is also performed to achieve the goals of increasing network coverage and extending the network lifetime. Finally, simulation results show that the proposed CoC-SCS algorithm compared with other three algorithms in this paper has improved 11.27% and 16.35% on average in terms of network coverage, network lifetime, etc., and 13.95% in terms of network energy overhead, thereby we can further verify that CoC-SCS algorithm has strong stability and effectiveness.

show abstract

“…Lara-Nion et al investigated efficient scalar multiplication for resource-constrained devices in the paper “Energy/Area-Efficient Scalar Multiplication with Binary Edwards Curves for the IoT” [12]. In this work, the proposed energy-reducing techniques can provide efficient area/energy trade-offs.…”

Section: The Papersmentioning

confidence: 99%

Privacy and Security for Resource-Constrained IoT Devices and Networks: Research Challenges and Opportunities

Song

Iqbal

2019

Sensors

View full text Add to dashboard Cite

With the exponential growth of the Internet of Things (IoT) and cyber-physical systems (CPS), a wide range of IoT applications have been developed and deployed in recent years. To match the heterogeneous application requirements in IoT and CPS systems, many resource-constrained IoT devices are deployed, in which privacy and security have emerged as difficult challenges because the devices have not been designed to have effective security features.

show abstract

CS-FCDA: A Compressed Sensing-Based on Fault-Tolerant Data Aggregation in Sensor Networks

Cited by 15 publications

References 23 publications

CSR-IM: Compressed Sensing Routing-Control- Method With Intelligent Migration-Mechanism Based on Sensing Cloud-Computing

CSR-IM: Compressed Sensing Routing-Control- Method With Intelligent Migration-Mechanism Based on Sensing Cloud-Computing

CoC-SCS: Cooperative-Optimization Coverage Algorithm Based on Sensor Cloud Systems in Intelligent Computing

Privacy and Security for Resource-Constrained IoT Devices and Networks: Research Challenges and Opportunities

Contact Info

Product

Resources

About