A fuzzy logic-based secure hierarchical routing scheme using firefly algorithm in Internet of Things for healthcare

Hosseinzadeh, Mehdi; Yoo, Joon; Ali, Saqib; Lánský, Jan; Mildeová, Stanislava; Yousefpoor, Mohammad Sadegh; Ahmed, Omed Hassan; Rahmani, Amir Masoud; Tightiz, Lilia

doi:10.1038/s41598-023-38203-9

Cited by 7 publications

(2 citation statements)

References 39 publications

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“…Moreover, Hosseinzadeh et al 55 provided a secure hierarchical routing scheme for the IoT in healthcare, employing fuzzy logic and the Firefly Algorithm. Their scheme aimed to enhance the security of data transmission in IoT‐based healthcare systems.…”

Section: Nature‐inspired Algorithmsmentioning

confidence: 99%

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

Amiri,

Heidari,

Zavvar

et al. 2024

Trans Emerging Tel Tech

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Nature‐inspired algorithms revolve around the intersection of nature‐inspired algorithms and the IoT within the healthcare domain. This domain addresses the emerging trends and potential synergies between nature‐inspired computational approaches and IoT technologies for advancing healthcare services. Our research aims to fill gaps in addressing algorithmic integration challenges, real‐world implementation issues, and the efficacy of nature‐inspired algorithms in IoT‐based healthcare. We provide insights into the practical aspects and limitations of such applications through a systematic literature review. Specifically, we address the need for a comprehensive understanding of the applications of nature‐inspired algorithms in IoT‐based healthcare, identifying gaps such as the lack of standardized evaluation metrics and studies on integration challenges and security considerations. By bridging these gaps, our paper offers insights and directions for future research in this domain, exploring the diverse landscape of nature‐inspired algorithms in healthcare. Our chosen methodology is a Systematic Literature Review (SLR) to investigate related papers rigorously. Categorizing these algorithms into groups such as genetic algorithms, particle swarm optimization, cuckoo algorithms, ant colony optimization, other approaches, and hybrid methods, we employ meticulous classification based on critical criteria. MATLAB emerges as the predominant programming language, constituting 37.9% of cases, showcasing a prevalent choice among researchers. Our evaluation emphasizes adaptability as the paramount parameter, accounting for 18.4% of considerations. By shedding light on attributes, limitations, and potential directions for future research and development, this review aims to contribute to a comprehensive understanding of nature‐inspired algorithms in the dynamic landscape of IoT‐based healthcare services.

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Section: Nature‐inspired Algorithmsmentioning

confidence: 99%

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

Amiri,

Heidari,

Zavvar

et al. 2024

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…This means that AODV only finds suitable paths in the network when requesting a node to build a route and broadcasting a route request (RREQ) packet in the network. This feature is valuable because it reduces routing overhead and energy consumption and lowers the need for memory 25,26 . Thus, AODV is a popular routing protocol in ad hoc networks, especially FANETs.…”

mentioning

confidence: 99%

A local filtering-based energy-aware routing scheme in flying ad hoc networks

Hosseinzadeh,

Husari,

Yousefpoor

et al. 2024

Preprint

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Flying ad hoc network (FANET) is a new technology, which creates a self-organized wireless network containing unmanned aerial vehicles (UAVs). In FANET, routing protocols deal with important challenges due to limited energy, frequent failures in communication links, high mobility of UAVs, and limited communication range of UAVs. Thus, a suitable path is always essential to transmit data between UAVs reliably. In this paper, a local filtering-based energy-aware routing scheme (LFEAR) is proposed for FANETs. LFEAR improves the template of the route request (RREQ) packet by adding three other fields, namely the energy, reliable distance, and movement similarity of the relevant route to create stable and energy-efficient paths between UAVs. In the routing process, LFEAR presents a local filtering construction technique to avoid the broadcasting storm issue. This filter limits the broadcasting range of RREQs in the network. Accordingly, only UAVs inside this local filtered area can rebroadcast RREQ and other UAVs must eliminate this packet. Upon the end of the route discovery process, the destination begins the route selection phase and extracts information about each discovered route, including the number of hops, route energy, reliable distance, and movement similarity from the relevant RREQ. Then, the destination node calculates a score for each path based on the extracted information, selects the route with the highest score, and sends a route reply (RREP) packet to the source node through this route. Finally, the simulation process of LFEAR is performed using the NS2 simulator, and two simulation scenarios, namely change in network density and change in the speed of UAVs, are defined to evaluate network performance. In the first scenario, LFEAR improves energy consumption, packet delivery rate, network lifespan, and delay by 1.33%, 1.77%, 6.74%, and 1.71%, while its routing overhead is about 16.51% more than EARVRT. In the second scenario, LFEAR optimizes energy consumption and network lifetime by 5.55% and 5.67%, respectively. However, its performance in terms of routing overhead, packet delivery rate, and delay is 23%, 2.29%, and 6.67% weaker than EARVRT, respectively.

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DCFH: A dynamic clustering approach based on fire hawk optimizer in flying ad hoc networks

Hosseinzadeh,

Ali,

Ahmad

et al. 2024

Vehicular Communications

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A fuzzy logic-based secure hierarchical routing scheme using firefly algorithm in Internet of Things for healthcare

Cited by 7 publications

References 39 publications

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

A local filtering-based energy-aware routing scheme in flying ad hoc networks

DCFH: A dynamic clustering approach based on fire hawk optimizer in flying ad hoc networks

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