An adaptive hierarchical data dissemination mechanism for mobile data collector enabled dynamic wireless sensor network

Mazumdar, Nabajyoti; Roy, Saugata; Nag, Amitava; Nandi, Sukumar

doi:10.1016/j.jnca.2021.103097

Cited by 19 publications

(7 citation statements)

References 48 publications

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“…[17][18][19] Fazil et al proposed that by efficiently designing the routing algorithm energy efficiency can be achieved effectively. 20 Nabajyoti et al [21][22][23][24] proposed a model that effectively collects the data through UAV and processed using AI algorithm to obtain precise dataset in a wireless sensor network. Adil et al 25 suggested an optimization methodology based on the ant colony algorithm to find the optimized cluster.…”

Section: Literature Reviewmentioning

confidence: 99%

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A novel method of improving energy efficient QoS in FANET using Correlation And Confidence Based Gradient Clustering Metric approach

Ali

Ruby

2023

Int J Communication

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Flying Ad-hoc Networks (FANETs) being the most popular wing of the research in recent time had many evolutions to cope up with the growing demands in defense and other civil applications. Limited number of nodes, limited source of energy and increased mobility of the drones were the major problems to be addressed while building an effective FANET. Drones were aerial-nodes that are driver-less; their actions were prescribed by means of algorithms devoid of some human relations and could be easily deployed in the system. Hence this article aims to propose a novel framework to improvise the energy efficiency of FANET through Correlation and Confidence based Gradient Clustering Metric (CC-GCM) approach in the clustering algorithm.The results obtained through the proposed model are proven to be outstanding by producing an improvised performance efficiency and augmented energy efficiency. This article also involves a comparative study of the performance attributes with the existing models with tabulated values and graphs in terms of energy consumption, average end-to-end delay, cluster building time, average cluster life time, and Packet Delivery Ratio (PDR).

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Section: Literature Reviewmentioning

confidence: 99%

“…Nabajyoti et al 21–24 proposed a model that effectively collects the data through UAV and processed using AI algorithm to obtain precise dataset in a wireless sensor network. Adil et al 25 suggested an optimization methodology based on the ant colony algorithm to find the optimized cluster.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel method of improving energy efficient QoS in FANET using Correlation And Confidence Based Gradient Clustering Metric approach

Ali

Ruby

2023

Int J Communication

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“…Mazumdar et al 3 have proposed an adaptive hierarchical data dissemination (AHDD) system with mobile data collector (MDC) technique helps to minimize the energy consumption in the network and the fault‐tolerance problem in the network. In this proposed approach increases the wireless sensor network's survival life by minimizing the energy consumption among all the sensor nodes in the network there by saving network energy.…”

Section: Literature Surveymentioning

confidence: 99%

“…Yang et al 25 have proposed a hybrid model for effective data dissemination process to reduce the traffic occurs during vehicle to vehicle 26 and vehicle to infrastructure model. For automatic driving services, what data has to be injected to which vehicle is decided and maintained by edge assisted devices to minimize the traffic in the network in order to minimize the delay 3 in the data dissemination process. It has been achieved by offline hybrid algorithm for efficient data dissemination 27 process with the help of online prediction algorithm.…”

Section: Literature Surveymentioning

confidence: 99%

Comprehensive survey on data dissemination protocols for efficient reprogramming in Internet of Things

Shanmugapriya

Kumar

2022

Concurrency and Computation

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SUMMARY The Internet of Things (IoT) is a wide network of interconnected intelligent objects which can recognize the natural phenomenon of the deployed environment with the help of sensors and transmit the sensed information to other devices via internet as a backbone. Data dissemination is one of the important activities in IoT. Data dissemination is the process of updating the design framework of the sensor nodes to make the sensor nodes in IoT device to perform the intended services. Reprogramming is the process of entire change in the configuration parameters of the nodes and reconfiguration is the process of minor modification in the configuration parameter. In data dissemination, the design framework is typically disseminated through the sensor nodes to the base station using multi‐hop communication. In this article, a comprehensive survey on various dissemination approaches such as topology, reliability, scalability, structure, centralized, and de‐centralized are carried out to highlight with their advantages and limitations. Moreover, the proposed survey provides a detailed analysis on both reprogramming–related to data dissemination and reconfiguration‐related to data dissemination in order to improve the efficiency of data dissemination.

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“…Delay tolerant networks (DTNs) are decentralized networks that are characterized by frequent disruptions among mobile nodes [1,2]. A lot of novel wireless and mobile networks belong to DTNs such as wireless sensor networks, underwater sensor networks, and vehicular ad hoc networks [3][4][5][6][7], and so on. Due to the mobility of nodes and the lack of end-to-end connection, there may be no continued or fixed routing path from the source to the destination node.…”

Section: Introductionmentioning

confidence: 99%

A delay tolerant network routing algorithm based on multi‐step double Q‐learning

Jin

Cai

et al. 2023

IET Communications

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Delay tolerant networks (DTNs) refer to a kind of novel wireless mobile network, where there is no constant end‐to‐end connection between network nodes due to frequent movement, sparse distribution and limited communication range of nodes. Instead of the traditional store‐forward routing strategy, in DTNs, the new store‐carry‐forward routing strategy is adopted for data transmission. Therefore, how to select the best next‐hop node among network nodes is the main challenge of the routing in DTNs. To this end, here, a k‐step double Q‐learning routing (K‐DQLR) algorithm is proposed, which integrates the multi‐step and double Q‐learning algorithms to make an unbiased, accurate and efficient routing decision in DTNs. Besides, a new dynamic reward mechanism is proposed, which combines the number of routing hops and the node centrality to adopt the dynamic network environment of DTNs. The simulation results show that K‐DQLR can significantly increase the delivery ratio while reducing the delivery delay and overhead compared with the related state‐of‐the‐art routing protocols of DTNs.

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An adaptive hierarchical data dissemination mechanism for mobile data collector enabled dynamic wireless sensor network

Cited by 19 publications

References 48 publications

A novel method of improving energy efficient QoS in FANET using Correlation And Confidence Based Gradient Clustering Metric approach

A novel method of improving energy efficient QoS in FANET using Correlation And Confidence Based Gradient Clustering Metric approach

Comprehensive survey on data dissemination protocols for efficient reprogramming in Internet of Things

A delay tolerant network routing algorithm based on multi‐step double Q‐learning

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