Efficient coding techniques algorithm for cluster-heads communication in wireless sensor networks

Ar-Reyouchi, El Miloud; Chatei, Youssra; Ghoumid, Kamal; Hammouti, Maria; Hajji, Bekkay

doi:10.1016/j.aeue.2017.08.047

Cited by 19 publications

(10 citation statements)

References 34 publications

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“…In each category of the classification, criteria and parameters are presented according to the type of methodology. The authors [15] gave a efficient coding techniques algorithm for cluster-heads communication in wireless sensor networks to improve the Bit-error rate. The paper [16] proposed a new cluster-based algorithm to minimize energy consumption in WSNs.…”

Section: Related Workmentioning

confidence: 99%

A Node Deployment Model with Variable Transmission Distance for Wireless Sensor Networks

Fan¹,

Chen²

2020

IJWMN

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The deployment of network nodes is essential to ensure the wireless sensor network's regular operation and affects the multiple network performance metrics, such as connectivity, coverage, lifetime, and cost. This paper focuses on the problem of minimizing network costs while meeting network requirements, and proposes a corona-based deployment method by using the variable transmission distance sensor. Based on the analysis of node energy consumption and network cost, an optimization model to minimize Cost Per Unit Area is given. The transmission distances and initial energy of the sensors are obtained by solving the model. The optimization model is improved to ensure the energy consumption balance of nodes in the same corona. Based on these parameters, the process of network node deployment is given. Deploying the network through this method will greatly reduce network costs.

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Section: Related Workmentioning

confidence: 99%

A Node Deployment Model with Variable Transmission Distance for Wireless Sensor Networks

Fan¹,

Chen²

2020

IJWMN

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“…Compared to other error-correction codes, like Bose-Chaudhuri-Hocquenghem (BCH) codes, Reed Solomon (RS) codes, and turbo codes, LDPC codes have many advantages, e.g., very low error floor, high-speed encoder and decoder, and more varieties in code construction [20][21][22][23]. Therefore, LDPC codes have become the focal choice for many communication standards, such as 10-Gigabit Ethernet (802.3an) [24] and Wi-Fi (802.11n/ac/ad) [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Reduced‐Complexity LDPC Decoding for Next‐Generation IoT Networks

Asif

Khan

Afzal

et al. 2021

Wireless Communications and Mobile Computing

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Low-density parity-check (LDPC) codes have become the focal choice for next-generation Internet of things (IoT) networks. This correspondence proposes an efficient decoding algorithm, dual min-sum (DMS), to estimate the first two minima from a set of variable nodes for check-node update (CNU) operation of min-sum (MS) LDPC decoder. The proposed architecture entirely eliminates the large-sized multiplexing system of sorting-based architecture which results in a prominent decrement in hardware complexity and critical delay. Specifically, the DMS architecture eliminates a large number of comparators and multiplexors while keeping the critical delay equal to the most delay-efficient tree-based architecture. Based on experimental results, if the number of inputs is equal to 64, the proposed architecture saves 69%, 68%, and 52% area over the sorting-based, the tree-based, and the low-complexity tree-based architectures, respectively. Furthermore, the simulation results show that the proposed approach provides an excellent error-correction performance in terms of bit error rate (BER) and block error rate (BLER) over an additive white Gaussian noise (AWGN) channel.

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“…Routing and clustering are two important approaches to maximize the lifetime of WSN [4][5][6][7][8]. The SNs are grouped into cluster-based on certain features or attributes.…”

Section: Introductionmentioning

confidence: 99%

FEECS: Fuzzy-Based Energy-Efficient Cluster Head Selection Algorithm for Lifetime Enhancement of Wireless Sensor Networks

Jayaraman

Dhulipala

2021

Arab J Sci Eng

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The wireless sensor network (WSN) infrastructure is deployed with sensor nodes that are used to collect the sensed information and transmit to the central station, namely base station. The power limitations of sensors are commonly known in WSN. Due to limitation in power supply, energy utilization becomes a challenge in the networks. Various categories of protocols have been developed and addressed the energy issues, but the longevity of network lifetime is a crucial factor. In this paper, fuzzy-based energy-efficient cluster head selection algorithm is introduced to prolong the network lifetime. While the formation of the cluster, k-means algorithm is used to form a cluster in an efficient way and cluster head is selected based on fuzzy logic system. Simulation results show the proposed algorithm outperforms the existing algorithms.

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Efficient coding techniques algorithm for cluster-heads communication in wireless sensor networks

Cited by 19 publications

References 34 publications

A Node Deployment Model with Variable Transmission Distance for Wireless Sensor Networks

A Node Deployment Model with Variable Transmission Distance for Wireless Sensor Networks

Reduced‐Complexity LDPC Decoding for Next‐Generation IoT Networks

FEECS: Fuzzy-Based Energy-Efficient Cluster Head Selection Algorithm for Lifetime Enhancement of Wireless Sensor Networks

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