Improving the Network Lifetime and Performance of Wireless Sensor Networks for IoT Applications Based on Fuzzy Logic

Rahimi, Payam; Chrysostomou, Chrysostomos

doi:10.1109/dcoss.2019.00120

Cited by 15 publications

(14 citation statements)

References 18 publications

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“…Performance of the IoT networks is the essential factor to be calculated, as many networking layers must be incorporated, and that too networking must be done considering many heterogeneous devices. Many issues are to be considered when assessing and improving the performance of IoT networks [Rahimi, P. and Chrysostomou, C] [1]. Keeping in view the minimum power dissipation, many alternate paths for communication is one of the most important criteria.…”

Section: Switch Box: a Switch Box Is A Device That Receives And Trans...mentioning

confidence: 99%

“…The input will first arrive at the switch box (3, 1), which will forward it to (3,2), and so on until it reaches the switch box (3,5). This switch box will turn the message into column 5 and forward it to the box (2, 5), which will send it to the box (1,5), which will send it to its destination. If input 3 is to be sent to output 5, the data will be received by switch box (3,1), which will forward it to (3,2) and so on until it reaches (3,5), which will then forward it to (2,5) and then to (1,5) which will then be sent to the connected device.…”

Section: Performance Improvement Through the Availability Of Alternat...mentioning

confidence: 99%

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Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Sowmya,

Sastry

2022

Scientia Iranica

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Multiple networking layers existing in the IoT network involve heterogeneity that must be addressed to facilitate proper communication such that the performance of an IoT network does not suffer. The performance of the IoT networks depends on networking topologies used in different layers, clustering algorithms, protocols used for handling heterogeneity, communication speeds, and data packet sizes. In this Research, the performance of IoT networks is improved by adding device clustering via a multi-Stage network and using an efficient SOJK clustering algorithm in the device layer, which minimizes power depletion and increases the quantity of data and data packets; transmitted at zero power. A mechanism to handle heterogeneity due to Wi-Fi, CDMA, and USB communication protocols is also presented while optimizing the communication speeds and data transmission size. It has also been shown that the use of 170Mbps cellular speed and the data size of 468 bytes give the optimum response time of an IoT network. The time taken to transport information from the device to the storage layer is reduced by 57% compared to the time taken to transport the data using the prototype network.

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Section: Switch Box: a Switch Box Is A Device That Receives And Trans...mentioning

confidence: 99%

Section: Performance Improvement Through the Availability Of Alternat...mentioning

confidence: 99%

Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Sowmya,

Sastry

2022

Scientia Iranica

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“…•System power. Rahimi and Chrysostomou [38] suggested a load-balancing method that can optimize the distribution of energy consumption among nodes. The proposed algorithm used a fuzzy logic controller to form a priority queue depending on optimization parameters to allocate CH among nodes within a cluster.…”

Section: Energy Optimization-based Clustering Algorithmsmentioning

confidence: 99%

Investigation of Energy Efficient Clustering Algorithms in WSNs: A Review

Ahmad¹,

Al-Nayar²,

Mahmood³

2022

MMEP

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In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime issues in these networks are discussed and summarized using comparison tables, including the main features, limitations, and the kind of simulation toolbox. Energy efficiency is compared between some techniques and showed that according to clustering mode “Distributed” and CH distribution “Uniform”, HEED and EECS are best, while in the non-uniform clustering, both DDAR and THC are efficient. According to clustering mode “Centralized” and CH distribution “Uniform”, the LEACH-C protocol is more effective.

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“…In pursuit of reducing battery energy spent by SNs communicating localised messages about whatever they sensing to the GW of an IoT network, the following article has implemented a smart clustering algorithm that balances the connectivity load of the SNs [10]. This will keep the various SNs in the network alive longer as they proved in their testing.…”

Section: Literature Reviewmentioning

confidence: 99%

DXN: Dynamic AI-Based Analysis and Optimisation of IoT Networks’ Connectivity and Sensor Nodes’ Performance

Lami

Abdulkhudhur

2021

Signals

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Most IoT networks implement one-way messages from the sensor nodes to the “application host server” via a gateway. Messages from any sensor node in the network are sent when its sensor is triggered or at regular intervals as dictated by the application, such as a Smart-City deployment of LoRaWAN traps/sensors for rat detection. However, these traps can, due to the nature of this application, be moved out of signal range from their original location, or obstructed by objects, resulting in under 69% of the messages reaching the gateway. Therefore, applications of this type would benefit from control messages from the “application host server” back to the sensor nodes for enhancing their performance/connectivity. This paper has implemented a cloud-based AI engine, as part of the “application host server”, that dynamically analyses all received messages from the sensor nodes and exchanges data/enhancement back and forth with them, when necessary. Hundreds of sensor nodes in various blocked/obstructed IoT network connectivity scenarios are used to test our DXN solution. We achieved 100% reporting success if access to any blocked sensor node was possible via a neighbouring node. DXN is based on DNN and Time Series models.

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Improving the Network Lifetime and Performance of Wireless Sensor Networks for IoT Applications Based on Fuzzy Logic

Cited by 15 publications

References 18 publications

Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Improving the Performance of Heterogeneous IoT Networks through Multi-Stage and Parallel Computing Systems

Investigation of Energy Efficient Clustering Algorithms in WSNs: A Review

DXN: Dynamic AI-Based Analysis and Optimisation of IoT Networks’ Connectivity and Sensor Nodes’ Performance

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