ReNEW: A Practical Module for Reliable Routing in Networks of Energy-Harvesting Wireless Sensors

Prasad, R. Venkatesha; Rao, Vijay S.; Sarkar, Chayan; Niemegeers, Ignas

doi:10.1109/tgcn.2021.3094771

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…Transmission scheduling can, instead, reduce collisions caused by multiple information flows, which is a typical IoT characteristic. An example of a paper belonging to this category is [69], where the design of a routing protocol with low latency and high reliability is proposed for IoT devices purely powered by ambient harvested energy.…”

Section: ) Low-latency Communicationsmentioning

confidence: 99%

A Cross-Layer Survey on Secure and Low-Latency Communications in Next-Generation IoT

Martalò,

Pettorru,

Atzori

2024

IEEE Trans. Netw. Serv. Manage.

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The last years have been characterized by strong market exploitation of the Internet of Things (IoT) technologies in different application domains, such as Industry 4.0, smart cities, and eHealth. All the relevant solutions should properly address the security issues to ensure that sensor data and actuators are not under the control of malicious entities. Additionally, many applications should at the same time provide low-latency communications, as in the case for instance of remote control of industrial robots. Low latency and security are two of the most important challenges to be addressed for the successful deployment of IoT applications.These issues have been analyzed by several scientific papers and surveys that appeared in the last decade. However, few of them consider the two challenges jointly. Moreover, the security aspects are primarily investigated only in specific application domains or protocol levels and the latency issues are typically investigated only at low layers (e.g., physical, access). This paper addresses this shortcoming and provides a systematic review of state-of-the-art solutions for providing fast and secure IoT communications. Although the two requirements may appear to be in contrast to each other, we investigate possible integrated solutions that minimize device connection and service provisioning. We follow an approach where the proposals are reviewed by grouping them based on the reference architectural layer, i.e., access, network, and application layers. We also review the works that propose promising solutions that rely on the exploitation of the QUIC protocol at the higher levels of the protocol stack.

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Section: ) Low-latency Communicationsmentioning

confidence: 99%

A Cross-Layer Survey on Secure and Low-Latency Communications in Next-Generation IoT

Martalò,

Pettorru,

Atzori

2024

IEEE Trans. Netw. Serv. Manage.

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“…An important technology for ensuring transmission reliability lies in the deployment of highly reliable routing algorithms [ 4 , 5 , 6 ], with multipath routing standing out as a widely adopted strategy to improve the reliability of data transmission in WSNs. In contrast to single-path routing, multipath routing augments data transmission reliability by establishing multiple paths between source and destination nodes.…”

Section: Introductionmentioning

confidence: 99%

An Accuracy-Aware Energy-Efficient Multipath Routing Algorithm for WSNs

Dan,

Ma,

Yin

et al. 2024

Sensors

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In the fields of industrial production or safety monitoring, wireless sensor networks are often content with unreliable and time-varying channels that are susceptible to interference. Consequently, ensuring both transmission reliability and data accuracy has garnered substantial attention in recent years. Although multipath routing-based schemes can provide transmission reliability for wireless sensor networks, achieving high data accuracy simultaneously remains challenging. To address this issue, an Energy-efficient Multipath Routing algorithm balancing data Accuracy and transmission Reliability (EMRAR) is proposed to balance the reliability and accuracy of data transmission. The multipath routing problem is formulated into a multi-objective programming problem aimed at optimizing both reliability and power consumption while adhering to data accuracy constraints. To obtain the solution of the multi-objective programming, an adaptive artificial immune algorithm is employed, in which the antibody initialization method, antibody incentive calculation method, and immune operation are improved, especially for the multipath routing scheme. Simulation results show that the EMRAR algorithm effectively balances data accuracy and transmission reliability while also saving energy when compared to existing algorithms.

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“…The ability to send data between nodes in a wireless network that is both accurate and dependable is made possible by time synchronization, which is an essential component of an efficient wireless network [14,15,16]. This chaining together of individual components is typical in interference-aware routing schemes [17,18,19,20]. Any situation in which there is a deterioration or interruption of the signals that are being transferred between devices in wireless networks is referred to as communication interference.…”

mentioning

confidence: 99%

IARMTS: Design of an Interference-Aware Routing Model with Time Synchronization Capabilities for Dense Wireless Sensor Network Deployments

Shrivastav¹,

Karmore

2023

IJEER

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Performance of dense wireless sensor networks is often degraded due to communication interference and time synchronization issues. Existing machine learning & deep learning models that propose bioinspired & pre-emptive packet-analysis solutions for these tasks either have high complexity, or high deployment costs. Moreover, these models cannot be scaled for heterogeneous node & traffic types, which limits their applicability when applied to real-time scenarios. To overcome these issues, this text proposes design of an interference-aware routing model with time synchronization capabilities for dense wireless sensor network deployments. The network initially collects temporal clock states & packet delivery performance of different nodes on heterogeneous traffic scenarios. These traffic patterns are converted into frequency, entropy, Gabor, and Wavelet components. The converted components are used to train an ensemble set of Naïve Bayes (NB), k Nearest Neighbour (kNN), Multilayer Perceptron (MLP), and Support Vector Machine (SVM) classifiers. These classifiers assist in identification of optimal clock deviations and set of routing paths. These routing paths are further fine-tuned via use of a Bacterial Foraging Optimization (BFO) Model, which assists in identification of interference-aware paths. The BFO Model uses a temporal fitness function that fuses throughput, communication delay, energy levels, and packet delivery performance for different set of contextual communications. Due to which, the model is able to showcase lower end-to-end delay, higher throughput, lower energy consumption, and higher packet delivery performance when compared with existing routing methods under high density nodes & heterogeneous network scenarios. The model showcases 99% PDR, 18.3% lower delay, 19.5% higher energy efficiency and 10.4% lower delay levels when compared with existing methods.

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ReNEW: A Practical Module for Reliable Routing in Networks of Energy-Harvesting Wireless Sensors

Cited by 5 publications

References 28 publications

A Cross-Layer Survey on Secure and Low-Latency Communications in Next-Generation IoT

A Cross-Layer Survey on Secure and Low-Latency Communications in Next-Generation IoT

An Accuracy-Aware Energy-Efficient Multipath Routing Algorithm for WSNs

IARMTS: Design of an Interference-Aware Routing Model with Time Synchronization Capabilities for Dense Wireless Sensor Network Deployments

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