A new hybrid routing protocol for wireless sensor networks

Chelbi, Slaheddine; Dhahri, Habib; Abdouli, Majed; Duvallet, Claude; Bouaziz, Rafik

doi:10.1504/ijahuc.2018.093330

Cited by 11 publications

(15 citation statements)

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“…By reviewing the related work, it is clear that existing clustering techniques uses one or more parameters such as current energy, distance from BS, and location of the node, for CH selection criteria [27][28][29][30][31][32][33][34][35][36][37][38][39][40] to ensure energy efficiency and prolong network lifetime. However, none of them considers quality of the link and energy gain rate by a node in CH selection process, which potentially contributes to the enhancement of energy utilization, network lifetime, and reliability of packets delivery.…”

Section: Related Workmentioning

confidence: 99%

E²-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

Haq

Javaid

Ullah

et al. 2020

International Journal of Distributed Sensor Networks

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Internet of things have emerged enough due to its applications in a wide range of fields such as governance, industry, healthcare, and smart environments (home, smart, cities, and so on). Internet of things–based networks connect smart devices ubiquitously. In such scenario, the role of wireless sensor networks becomes vital in order to enhance the ubiquity of the Internet of things devices with lower cost and easy deployment. The sensor nodes are limited in terms of energy storage, processing, and data storage capabilities, while their radio frequencies are very sensitive to noise and interference. These factors consequently threaten the energy consumption, lifetime, and throughput of network. One way to cope with energy consumption issue is energy harvesting techniques used in wireless sensor network–based Internet of things. However, some recent studies addressed the problems of clustering and routing in energy harvesting wireless sensor networks which either concentrate on energy efficiency or quality of service. There is a need of an adequate approach that can perform efficiently in terms of energy utilization as well as to ensure the quality of service. In this article, a novel protocol named energy-efficient multi-attribute-based clustering scheme (E2-MACH) is proposed which addresses the energy efficiency and communication reliability. It uses selection criteria of reliable cluster head based on a weighted function defined by multiple attributes such as link statistics, neighborhood density, current residual energy, and the rate of energy harvesting of nodes. The consideration of such parameters in cluster head selection helps to preserve the node’s energy and reduce its consumption by sending data over links possessing better signal-to-noise ratio and hence ensure minimum packet loss. The minimized packet loss ratio contributes toward enhanced network throughput, energy consumption, and lifetime with better service availability for Internet of things applications. A set of experiments using network simulator 2 revealed that our proposed approach outperforms the state-of-the-art low-energy adaptive clustering hierarchy and other recent protocols in terms of first-node death, overall energy consumption, and network throughput.

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Section: Related Workmentioning

confidence: 99%

E²-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

Haq

Javaid

Ullah

et al. 2020

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…Meanwhile, the benefit brought by the data aggregation was evaluated so that the data aggregation behavior of the nodes could be adjusted adaptively. Paper [32] designed a centralized algorithm with polynomial time complexity and a distributed algorithm based on local information to customize the optimal transmission strategy for a tree and assign related slots for each node to perform transmission, which could optimize the data aggregation. For duty-cycled wireless sensor network, papers [33] were based on the connected support set to construct the routing tree and proposed the centralized greedy aggregation scheduling (GAS) and partitioned-based distributed aggregation scheduling (PAS).…”

Section: Related Workmentioning

confidence: 99%

An Optimized Clustering Communication Protocol Based on Intelligent Computing in Information-Centric Internet of Things

et al. 2019

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A narrow bandwidth may lead to a large amount of redundant data, which further causes the interruptions of the communication network. In order to address this problem, an optimized clustering communication protocol based on intelligent computing (CCP-IC) is proposed in this paper. First, we adopt the intelligent algorithm to perform the optimization of the clustering in the sensor network. The adaptation function and the heuristic function are introduced to make a targeted choice on the cluster head for the next hop of the nodes in the network. Second, the controllable threshold parameter and variation coefficient are employed to optimize the shortest path chosen by the network routing. Therefore, the node energy consumption is lowered when the minimum network delay is guaranteed and the transmission efficiency is improved. Finally, it is verified via the simulation results and compared with other algorithms; the proposed protocol reduces the network energy consumption by 15.3% and prolongs the network lifetime by 18.72%, which proves the validity and effectiveness of the proposed protocol. INDEX TERMS Internet of Things, clustering communication protocol, intelligent computing, network lifetime.

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“…The researchers in the security of the WSNs have suggested many security systems that have been improved for these networks with resource limitations. A number of safe and effective routing protocols [3,4][5] [6] and encryption techniques [7,8] [9] and secure data aggregation [10,11] [12], and the key management [13,14] [15] were suggested by many WSNs security researchers. The paper is structured as follows.…”

Section: Introductionmentioning

confidence: 99%

Study of environmentally sustainable security in wireless sensor networks

Hamza¹,

Al-Alak²

2019

PEN

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The popular technology Wireless sensor networks (WSNs) are used in many fields of the application such as the medical, the military, the industry, the agricultural, etc. In this paper, explains the security issues in the WSNs. Firstly explain the challenges of wireless sensor networks, the security requirements such as confidentiality, integrity, authenticity, data freshness, and availability and the attacks in the WSNs, the security issues are accomplished via these classes: [the encryption algorithms (symmetric, asymmetric, hybrid) , the security protocols such as (Tinysec, SPINS, LEDS, Minisec, LEAP, MASA, Lightweight LCG, MiniSec, VEBEK of WSN), the secure data aggregation, and the key management, etc.]. Also, this paper concentrates on the study researches that fulfill the high level of the security in the WSNs.

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A new hybrid routing protocol for wireless sensor networks

Cited by 11 publications

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E²-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

E²-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

An Optimized Clustering Communication Protocol Based on Intelligent Computing in Information-Centric Internet of Things

Study of environmentally sustainable security in wireless sensor networks

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A new hybrid routing protocol for wireless sensor networks

Cited by 11 publications

References 0 publications

E2-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

E2-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

An Optimized Clustering Communication Protocol Based on Intelligent Computing in Information-Centric Internet of Things

Study of environmentally sustainable security in wireless sensor networks

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E²-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks

E²-MACH: Energy efficient multi-attribute based clustering scheme for energy harvesting wireless sensor networks