Balancing the trade-off between cost and reliability for wireless sensor networks: a multi-objective optimized deployment method

Chen, Long; Xu, Ying-Ying; Xu, Fangyi; Hu, Qian; Tang, Zhenzhou

doi:10.1007/s10489-022-03875-9

Cited by 16 publications

(9 citation statements)

References 90 publications

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“…Figure 6 shows the total lifetime of the network verses number of sensor nodes deployed. As observed, in our proposed algorithm the total lifetime increases as the number of sensors nodes as compared to PSO-Levy-DFOA, 39 competitive multi-objective marine predator's algorithm (CMOMPA), 40 MOHHO algorithm. 41 When more nodes are considered, the scalability of proposed outperforms when compared with existing approaches.…”

Section: Experimental Results Of Phasementioning

confidence: 79%

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Efficient target monitoring with fault‐tolerant connectivity in wireless sensor networks

Deepa

Revathi

2022

Trans Emerging Tel Tech

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Sensing coverage with fault-tolerant connectivity is considered as a recent research challenge, which measures the Quality of Service (QoS) in wireless sensor networks. QoS is determined based on the set of deployed sensor nodes that monitor all available discrete targets lying at the given point of interest and at the same time have to retain reliable connectivity with the base station. In this article, we focus on two phases namely, monitoring targets in the given sensing area by splitting the sensor network into set covers, which is considered as a nondeterministic polynomial-time complete problem and optimal deployment of intelligent nodes. At first, achieving full coverage with deployed sensors by covering all discrete targets to prolong the network lifetime. On the other hand, a novel S 2 (sensors-spine) node approach was used to place an optimal number of intelligent nodes using a nature-inspired algorithm named moth flame optimization to overcome the fault among the disjoints sets such that the entire network was fully connected and ensure that sensed data from each target points are collected by the sink node. To evaluate our proposed design, extensive simulations were conducted to demonstrate the efficacy of our proposed mechanism that outperforms other existing techniques found in the literature in terms of prolonged network lifetime and there is no failure in the transmission path during data transmission to the sink node at every t s, such that the entire network was fully connected.

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Section: Experimental Results Of Phasementioning

confidence: 79%

“…Chen et al 40 discussed the optimal deployment approach for wireless sensor networks. The optimal deployment of the sensor nodes (SN) was provided for maximizing the connection degree and coverage degree.…”

Section: Related Workmentioning

confidence: 99%

Efficient target monitoring with fault‐tolerant connectivity in wireless sensor networks

Deepa

Revathi

2022

Trans Emerging Tel Tech

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“…In recent years, the research community has witnessed an explosion of literature in the area of heuristic algorithm [18]. Hundreds of novel heuristic optimization algorithms have been reported over the years and applied successfully in many applications, e.g., system reliability optimization [19], DNA sequence compression [20], systems of boundary value problems [21], solving mathematical equations [22,23], object-level video advertising [24], and wireless networks [25]. This paper proposes a novel heuristic algorithm for solving the LPN problem in situations where there are time and memory constraints.…”

Section: Motivation and Contributionmentioning

confidence: 99%

A Heuristic Algorithm for LPN Decoding with Improved Memory and Time Efficiency

Yin

Jin

2023

Preprint

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The LPN problem, which forms the basis of many lightweight and post-quantum cryptographic schemes, has recently received considerable attention. The solution to this problem typically involves two distinct phases, namely the reduce phase and the decode phase. While current research primarily focuses on the reduce phase, the most advanced decoding algorithm, FWHT, suffers from high computational costs in terms of time and space complexity. In this article, we propose a novel LPN decoding algorithm, GNS, which utilizes a heuristic approach to achieve significantly reduced memory and time complexity compared to FWHT. Experimental comparisons between the FWHT and GNS algorithms were conducted, with the computational results demonstrating that the proposed GNS algorithm is both efficient and superior to FWHT.

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“…Recent works such as [10,9,8,6,21] have been proposed to tackle the WSN deployment problem from an optimization perspective. In [10], authors proposed an optimal three-objectives deployment method for practical heterogeneous WSNs which gives a deep insight into the trade-off between the reliability and deployment cost.…”

Section: Related Workmentioning

confidence: 99%

Many-objective optimization of wireless sensor network deployment

Amor

Dagdia²,

Bechikh³

et al. 2022

Evol. Intel.

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Recently, the efficient deployment of Wireless Sensor Networks (WSNs) has become a leading field of research in WSN design optimization. Practical scenarios related to WSN deployment are often considered as optimization models with multiple conflicting objectives that are simultaneously enhanced. In the related literature, it had been shown that moving from monoobjective to multi-objective resolution of WSN deployment is beneficial. However, since the deployment of real-world WSNs encompasses more than three objectives, a multi-objective optimization may harm other deployment criteria that are conflicting with the already considered ones. Thus, our aim is to go further, explore the modeling and the resolution of WSN deployment in a many-objective (i.e., optimization with more than three objectives) fashion and especially, exhibit its added value. In this context, we first propose a manyobjective deployment model involving seven conflicting objectives, and then we solve it using an adaptation of the Decomposition-based Evolutionary Algorithm "θ-DEA". The developed adaptation is named "WSN-θ-DEA" and is validated through a detailed experimental study.

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Balancing the trade-off between cost and reliability for wireless sensor networks: a multi-objective optimized deployment method

Abstract: The deployment of the sensor nodes (SNs)

Cited by 16 publications

References 90 publications

Efficient target monitoring with fault‐tolerant connectivity in wireless sensor networks

Efficient target monitoring with fault‐tolerant connectivity in wireless sensor networks

A Heuristic Algorithm for LPN Decoding with Improved Memory and Time Efficiency

Many-objective optimization of wireless sensor network deployment

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