True Event-Driven and Fault-Tolerant Routing in Wireless Sensor Network

Biswas, Priyajit; Samanta, Tuhina

doi:10.1007/s11277-020-07037-3

Cited by 11 publications

(27 citation statements)

References 23 publications

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“…An event-driven routing between event and fault disambiguation is a very big challenge. Biswas et al [82] present a true event-driven and fault-tolerant routing (TEDFTR) algorithm for event-driven routing. When an event occurs, any node sends events occurrence information report to the base station through multi hopping with the help of the TEDFTR algorithm.…”

Section: Event-driven Modelmentioning

confidence: 99%

Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

et al. 2021

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Wireless sensor networks (WSNs) are considered producers of large amounts of rich data. Four types of data-driven models that correspond with various applications are identified as WSNs: query-driven, event-driven, time-driven, and hybrid-driven. The aim of the classification of data-driven models is to get real-time applications of specific data. Many challenges occur during data collection. Therefore, the main objective of these data-driven models is to save the WSN’s energy for processing and functioning during the data collection of any application. In this survey article, the recent advancement of data-driven models and application types for WSNs is presented in detail. Each type of WSN is elaborated with the help of its routing protocols, related applications, and issues. Furthermore, each data model is described in detail according to current studies. The open issues of each data model are highlighted with their challenges in order to encourage and give directions for further recommendation.

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Section: Event-driven Modelmentioning

confidence: 99%

Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

et al. 2021

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“…For low-energy and fault-prone sensor nodes that are vulnerable, Biswas et al [12] presented a true event-driven and fault-tolerant routing (TED-FTR) algorithm that sends a report to the BS through multiple hops. The ambiguity of the fault measurements is eliminated using the majority voting algorithm among neighbors to identify an actual event.…”

Section: Majority Rule and Hamming Weightmentioning

confidence: 99%

“…If most neighbors experience identical but unusual results, the node considers it an event and sends a report to the BS. In [12], majority voting is performed to disambiguate the reporting event of neighbor nodes. The majority voting algorithm uses Equation (2), which is given below.…”

Section: Majority Rule and Hamming Weightmentioning

confidence: 99%

“…As a result, the total number of messages per round is M total = k × n. The binary value is transmitted to the CH through the sensor nodes in the majority decision part, and the CH stores binarized aggregation data in the one-dimensional matrix to perform Hamming weight operations. Therefore, the time complexity is O(n), and no additional space is consumed; hence, the space complexity is O(1) [12,39].…”

Section: Overhead Cost Analysismentioning

confidence: 99%

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Majority Decision Aggregation with Binarized Data in Wireless Sensor Networks

Liu

2021

Symmetry

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Wireless sensor networks (WSNs) are the cornerstone of the current Internet of Things era. They have limited resources and features, a smaller packet size than other types of networks, and dynamic multi-hop transmission. WSNs can monitor a particular area of interest and are used in many different applications. For example, during the COVID-19 pandemic, WSNs have been used to measure social distancing/contact tracing among people. However, the major challenge faced by WSN protocols is limited battery energy. Therefore, the whole WSN area is divided into odd clusters using k-means++ clustering to make a majority rule decision to reduce the amount of additional data sent to the base station (or sink) and achieve node energy-saving efficiency. This study proposes an energy-efficient binarized data aggregation (EEBDA) scheme, by which, through a threshold value, the collected sensing data are asserted with binary values. Subsequently, the corresponding cluster head (CH), according to the Hamming weight and the final majority decision, is calculated and sent to the base station (BS). The EEBDA is based on each cluster and divides the entire WSN area into four quadrants. All CHs construct a data-relay transmission link in the same quadrant; the binary value is transferred from the CHs to the sink. The EEBDA adopts a CH rotation scheme to aggregate the data based on the majority results in the cluster. The simulation results demonstrate that the EEBDA can reduce redundant data transmissions, average the energy consumption of nodes in the cluster, and obtain a better network lifetime when compared to the LEACH, LEACH-C, and DEEC algorithms.

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“…Event-driven and priority message congestion detection techniques start a congestion detection algorithm whenever event-driven messages about traffic jams, road accidents are detected or generated. Fadilah et al and Biswas et al [44,45] proposed the use of adaptive periodic beaconing to convey time gap data. The adaptive rate control algorithm varies the rate of Periodic Safety Message (PSM) generation based on vehicular safety.…”

Section: Event-driven and Priority-based Congestion Detection Techniquementioning

confidence: 99%

A survey on congestion detection and control in connected vehicles

2020

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The dynamic nature of vehicular ad hoc network (VANET) induced by frequent topology changes and node mobility, imposes critical challenges for vehicular communications. Aggravated by the high volume of information dissemination among vehicles over limited bandwidth, the topological dynamics of VANET causes congestion in the communication channel, which is the primary cause of problems such as message drop, delay, and degraded quality of service. To mitigate these problems, congestion detection, and control techniques are needed to be incorporated in a vehicular network. Congestion control approaches can be either open-loop or closed loop based on pre-congestion or post congestion strategies. We present a general architecture of vehicular communication in urban and highway environment as well as a state-of-the-art survey of recent congestion detection and control techniques. We also identify the drawbacks of existing approaches and classify them according to different hierarchical schemes. Through an extensive literature review, we recommend solution approaches and future directions for handling congestion in vehicular communications.

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True Event-Driven and Fault-Tolerant Routing in Wireless Sensor Network

Cited by 11 publications

References 23 publications

Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

Majority Decision Aggregation with Binarized Data in Wireless Sensor Networks

A survey on congestion detection and control in connected vehicles

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