Hybrid and Multi-Hop Advanced Zonal-Stable Election Protocol for Wireless Sensor Networks

Internet of things grew swiftly and many services, software, sensors-embedded electronic devices and related protocols were developed and still in progress with full swing. Internet of things enabling physically existing things to see, hear, think and perform a notable task by allowing them to talk to each other and share useful information while making decision and caring-on/out their important tasks. Internet of things is greatly promoted by wireless sensor network as it becomes a perpetual layer for it. Wireless sensor network works as a base-stone for most of the Internet of things applications. There are severe general and specific threats and technical challenges to Internet of things–based sensor networks which must overcome to ensure adaptation and diffusion of it. Most of the limitations of wireless sensor networks are due to its resource constraint objects nature. The specified open research challenges in Internet of things–based sensor network are power consumption, network lifespan, network throughput, routing and network security. To overcome aforementioned problems, this work aimed to prolong network lifetime, improve throughput, decrease packet latency/packet loss and further improvise in encountering malicious nodes. To further tune the network lifetime in terms of energy, wireless harvesting energy is suggested in proposed three-layer cluster-based wireless sensor network routing protocol. The proposed mechanism is a three-tier clustering technique with implanted security mechanism to encounter malicious activities of sensor nodes and to slant them into blacklist. It is a centred-based clustering protocol, where selection of cluster head and grid head is carried out by sink node based on the value of its cost function. Moreover, hardware-based link quality estimators are used to check link effectiveness and to further improve routing efficiency. At the end, excessive experiments have been carried out to check efficacy of the proposed protocol. It outperforms most of its counterpart protocols such as fuzzy logic–based unequal clustering and ant colony optimization–based routing hybrid, Artificial Bee Colony-SD, enhanced three-layer hybrid clustering mechanism and energy aware multi-hop routing in terms of network lifetime, network throughput, average energy consumption and packet latency.

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“…These LQEs are built-in hardware chip (CC1101 and CC2420) and can be directly obtained from radio transceiver. 63,67 In this research to predict…”

Section: Hardware-based Triangle Metricsmentioning

confidence: 99%

Trust-based energy-efficient routing protocol for Internet of things–based sensor networks

Ilyas

Ullah

Khan

et al. 2020

International Journal of Distributed Sensor Networks

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“…WSNs usually operate in crucial applications such as dealing with sensitive information in real time; therefore, they should communicate BS with lesser delay, high efficiency, and minimum utilization of energy. To achieve these goals, many clustering techniques have been proposed in the literature, [5][6][7]15,[21][22][23][24][25][26] including solutions for traditional as well as energy harvesting enabled WSNs. Some state of the art and recent studies are discussed below.…”

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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“…For example, when the EEUC protocol constructs the routing path, the sending CH selects the relay node by judging the distance between the candidate CH and itself on the premise of ensuring the data transmission to the SN direction. Advanced zonal stable election protocol (AZ-SEP) [6] protocol uses CHs far away from the SN to communicate with the SN through flooding.…”

Section: Relative Workmentioning

confidence: 99%

“…We adopted a general energy consumption model as adopted in the literature [6], [7], [10]. Node energy consumption includes two parts: data receiving energy consumption and data sending energy consumption.…”

Section: B Node Energy Consumption Modelmentioning

confidence: 99%

Routing Clustering Protocol for 3D Wireless Sensor Networks Based on Fragile Collection Ant Colony Algorithm

et al. 2020

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Compared with two-dimensional wireless sensor networks (2DWSNs), three-dimensional wireless sensor networks (3DWSNs) have higher node energy consumption and weaker load balancing. To alleviate these problems, we propose a new multi-hop routing clustering protocol for a wide range of 3DWSNs. In terms of clustering, nodes will run for cluster head (CH) by timing broadcast based on their remaining energy and their average distance from surrounding nodes. Two new identity nodes are added between the CH and the member nodes, the load transfer node responsible for transferring the energy consumption of the CH, and the secondary cluster head node (SCH) acting as the CH for the next round. In order to reduce energy consumption in key node areas, we also enable key nodes to communicate directly with the sink node. In the aspect of routing construction, SN generates the routing table corresponding to each CH through our proposed fragile ant colony algorithm. Because CH and SCH exist at the same time and have a certain replacement order, the SN only needs to obtain the location of each CH when the network is first clustered, and can continuously generate a new routing table corresponding to the CH, which reduces the energy consumption of the network in the routing path construction. We simulate this protocol, LEACH protocol, AZ-SEP protocol, and UCNPD protocol in a three-dimensional environment. The results show that this protocol is better than the other three protocols in terms of network lifetime and network load balance, respectively. INDEX TERMS 3DWSNs, clustering algorithm, routing algorithm, network lifetime, network load balancing.

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Hybrid and Multi-Hop Advanced Zonal-Stable Election Protocol for Wireless Sensor Networks

Cited by 55 publications

References 8 publications

Trust-based energy-efficient routing protocol for Internet of things–based sensor networks

Trust-based energy-efficient routing protocol for Internet of things–based sensor networks

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

Routing Clustering Protocol for 3D Wireless Sensor Networks Based on Fragile Collection Ant Colony Algorithm

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Hybrid and Multi-Hop Advanced Zonal-Stable Election Protocol for Wireless Sensor Networks

Cited by 55 publications

References 8 publications

Trust-based energy-efficient routing protocol for Internet of things–based sensor networks

Trust-based energy-efficient routing protocol for Internet of things–based sensor networks

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

Routing Clustering Protocol for 3D Wireless Sensor Networks Based on Fragile Collection Ant Colony Algorithm

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