Enhanced Event Reliability in Wireless Sensor Networks

Mahmood, Muhammad Adeel; Welch, Ian; Andreae, Peter

doi:10.1109/aina.2018.00026

Cited by 3 publications

(7 citation statements)

References 15 publications

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“…Attempting to solve the congestion problem of different regions (event priority, node density) through similar methods reduces the throughput. Further, the ESRT protocol does not factor in the interferences [39].…”

Section: B Popular Congestion Control Methods 1) Congestion Control mentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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The classical Internet of things routing and wireless sensor networks can provide more precise monitoring of the covered area due to the higher number of utilized nodes. Because of the limitations in shared transfer media, many nodes in the network are prone to the collision in simultaneous transmissions. Medium access control protocols are usually more practical in networks with low traffic, which are not subjected to external noise from adjacent frequencies. There are preventive, detection and control solutions to congestion management in the network which are all the focus of this study. In the congestion prevention phase, the proposed method chooses the next step of the path using the Fuzzy decision-making system to distribute network traffic via optimal paths. In the congestion detection phase, a dynamic approach to queue management was designed to detect congestion in the least amount of time and prevent the collision. In the congestion control phase, the back-pressure method was used based on the quality of the queue to decrease the probability of linking in the pathway from the pre-congested node. The main goals of this study are to balance energy consumption in network nodes, reducing the rate of lost packets and increasing quality of service in routing. Simulation results proved the proposed Congestion Control Fuzzy Decision Making (CCFDM) method was more capable in improving routing parameters as compared to recent algorithms. INDEX TERMS Internet of Things, wireless sensor network, congestion control, fuzzy decision making, and back-pressure.

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Section: B Popular Congestion Control Methods 1) Congestion Control mentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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“…Event identification is one of the major challenges for event reliability protocols in WSNs. Among the existing event reliability protocols, only ERP [71] and EERP [78] raised this challenge of performing event identification before reliably transmitting it towards the sink.…”

Section: Discussionmentioning

confidence: 99%

“…Section 4.5 presents the limitations of the system design and Section 4.6 concludes the chapter with a summary. Parts of Sections 4.2, 4.3 and 4.4 have been published in [71], [78] and [93] 68 CHAPTER 4. SYSTEM DESIGN respectively.…”

Section: Chapter 4 System Designmentioning

confidence: 99%

“…PROTOTYPICAL IMPLEMENTATION OF ERP and Section 5.5 concludes the chapter with a summary. Parts of Section 5.2 and 5.3 are previously published in [78] and [93].…”

Section: Chapter 5 Prototypical Implementation Of Erpmentioning

confidence: 99%

“…114 CHAPTER 6. PERFORMANCE EVALUATION Parts of this chapter are previously published in [71], [78] and [93].…”

Section: Chapter 6 Performance Evaluationmentioning

confidence: 99%

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Event Reliability in Wireless Sensor Networks

Mahmood¹

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<p>Ensuring reliable transport of data in resource-constrained Wireless Sensor Networks (WSNs) is one of the primary concerns to achieve a high degree of efficiency in monitoring and control systems. The two reliability mechanisms typically used in WSNs are packet reliability and event reliability. Packet reliability, which requires all packets from all the sensor nodes to reach the sink, can result in wastage of the sensors' limited energy resources. Event reliability, which only requires that one packet related to each event reaches the sink, exploits the overlap of the sensing regions of densely deployed sensor nodes to eliminate redundant packets from nodes in close proximity that contain duplicate information about an event. The majority of previous research in this area focuses on packet reliability rather than event reliability. Moreover, the research that does focus on event reliability relies on the sink to impose some form of control over the flow of data in the network. The sinks' centralized control and decision-making increases the transmission of unnecessary packets, which degrades overall network performance in terms of energy, congestion and data flow. This thesis proposes a distributed approach to the control of the flow of data in which each node makes in-node decisions using data readily available to it. This reduces the transmission of unnecessary packets, which reduces the network cost in terms of energy, congestion, and data flow. The major challenges involved in this research are to: (i) accurately identify that multiple packets are carrying information about the same event, (ii) reliably deliver the packets carrying information about the unique event, (iii) ensure that enough information about the area of interest is reliably delivered to the sink, and (iv) maintain the event coverage throughout the network. This thesis presents the Event Reliability Protocol (ERP) and its extension, the Enhanced Event Reliability Protocol (EERP). The protocols aim for the reliable transmission of a packet containing information about each unique event to the sink while identifying and minimizing the unnecessary transmission of similar redundant packets from nodes in the region of the event. In this way, the sensor nodes consume less energy and increase the overall network lifetime. EERP uses a multilateration technique to identify multiple packets containing similar event information and thus is able to filter redundant packets of the same event. It also makes use of implicit acknowledgment (iACKs) for reliable delivery of the packets to the sink node. The process is based on the hop-by-hop mechanism where the decisions are made locally by the intermediate nodes. The thesis reports on simulations in QualNet 5.2 for verifying the accuracy of our event identification and event reliability mechanisms employed in the ERP and EERP. The results show that EERP performs better in terms of minimizing overall packet transmission and hence the energy consumption at the sensor nodes in a WSN. Also, the results for event identification mechanism and reliable event delivery show that EERP considerably improves upon other protocols in terms of unique events delivery.</p>

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Collaborative Reliable Event Transport Based on Mobile-Assisted Sensing in Urban Digital Twin

Park

Kim

2022

Electronics

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For urban digital twin, this paper comes up with a novel urban data acquisition scheme, denoted by collaborative reliable event transport (cRET), that conducts micro-scale sensing resolution in urban environments. cRET relies on battery-powered sensors with Bluetooth low-energy (BLE) modules and the smart mobile devices that people carry around urban places. However, the traditional data acquisition schemes with mobile assistance suffer from the poor communication channel quality of BLE. So, it is tough to achieve enough reliability of event observation. Hence, cRET utilizes overhearing-based collaboration among sensors to improve the data delivery ratio. It also could support reliable transmission over mobile devices despite high-speed moving. A proof-of-concept demonstrates that the reliability is improved by the overhearing and collaboration among sensors against low-channel conditions and a high moving speed of mobile devices, i.e., 30 km/h and more.

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Enhanced Event Reliability in Wireless Sensor Networks

Cited by 3 publications

References 15 publications

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

Event Reliability in Wireless Sensor Networks

Collaborative Reliable Event Transport Based on Mobile-Assisted Sensing in Urban Digital Twin

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