LaGOON : a simple energy‐aware routing protocol for wireless nano‐sensor networks

Al‐Turjman, Fadi; Kilic, Kemal Ihsan

doi:10.1049/iet-wss.2018.5079

Cited by 11 publications

(8 citation statements)

References 29 publications

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“…Additionally, to be best of the authors' knowledge, the present work also constitutes the first application of distributed consensus algorithms [24], [25] as the enabler for the autonomic and collective operation of nano-networks. In this aspect, we note that related works have studied controlled flooding [26], [27], peerto-peer [26], [28]- [31] and nature-inspired alternatives [32].…”

Section: Related Studiesmentioning

confidence: 99%

ABSense: Sensing Electromagnetic Waves on Metasurfaces via Ambient Compilation of Full Absorption

Liaskos,

Pirialakos,

Pitilakis

et al. 2019

Preprint

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Metasurfaces constitute effective media for manipulating and transforming impinging EM waves. Related studies have explored a series of impactful MS capabilities and applications in sectors such as wireless communications, medical imaging and energy harvesting. A key-gap in the existing body of work is that the attributes of the EM waves to-be-controlled (e.g., direction, polarity, phase) are known in advance. The present work proposes a practical solution to the EM wave sensing problem using the intelligent and networked MS counterparts-the HyperSurfaces (HSFs), without requiring dedicated field sensors. An nano-network embedded within the HSF iterates over the possible MS configurations, finding the one that fully absorbs the impinging EM wave, hence maximizing the energy distribution within the HSF. Using a distributed consensus approach, the nano-network then matches the found configuration to the most probable EM wave traits, via a static lookup table that can be created during the HSF manufacturing. Realistic simulations demonstrate the potential of the proposed scheme. Moreover, we show that the proposed workflow is the first-of-its-kind embedded EM compiler, i.e., an autonomic HSF that can translate highlevel EM behavior objectives to the corresponding, low-level EM actuation commands.

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Section: Related Studiesmentioning

confidence: 99%

ABSense: Sensing Electromagnetic Waves on Metasurfaces via Ambient Compilation of Full Absorption

Liaskos,

Pirialakos,

Pitilakis

et al. 2019

Preprint

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“…LaGOON [5] is one of the rare routing approaches for nanonetworks that take into account the nodes' volatility. LaGOON uses the destination MAC address of the received packet to identify the targeted relay and uses the network address to identify the final destination of the packet.…”

Section: Nanonetwork Routing Protocolsmentioning

confidence: 99%

“…In this context, traditional routing protocols such as AODV [3], DSR [4] based on a chain of retransmissions (one node every time) are a risky strategy in terms of communication reliability. Major recent protocols dedicated to the nanonetworks such as [5,6,7,8] also adopt the point to point relay mode.…”

Section: Introductionmentioning

confidence: 99%

Efficient routing protocol for concave unstable terahertz nanonetworks

2020

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The recent progress in nanotechnologies is giving birth to a novel topology of wireless networks characterized by a high local density and an intensive node instability such as in WBAN and swarm micro-robots systems. In this paper, we show that classical and dedicated ad hoc nanonetwork routing solutions are inefficient in this case and present a low reliability level and add a supplementary delay and control traffic. Majority of these solutions are based on point to point relaying mode, which is not adapted to the instability context. The multirelay to multirelay approaches allow countering the problem of nanonodes uncertainty by using the high number of inter-node connections. However, these approaches perform badly when the nanonetwork deployment presents distortions and concave sides. We propose a new routing protocol called Multirelay to Multirelay Routing Protocol (M2MRPv2), which provides a natural way to manage the residual energy levels on the nanonodes. M2MRPv2 is, to the best of our knowledge, the only approach that proposes a proactive multirelay to multirelay routing mode where the residual energy level of the nanonodes and reliability of the routing paths are taken into account. We study the performances of multirelay to multirelay protocols according to different multi-source to multi-sink communication scenarios. The obtained results show that M2MRPv2 protocol outperforms by far the Sustainable Longevity Routing (SLR) protocol (the reference protocol for Terahertz nanonetworks) in terms of transmission reliability and energy management. This outperformance is accentuated when the Terahertz nanonetwork deployment presents many concavities.

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“…It is a technique employed to fool the models through malicious inputs. It is used to cause a malfunction in the model 12 . The idea behind the adversarial attacks is adding a calculated perturbation or noise to the input of the model.…”

Section: Challenges and Issuesmentioning

confidence: 99%

Machine learning for wearable IoT‐based applications: A survey

Al‐Turjman

Baali

2019

Trans Emerging Tel Tech

Self Cite

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This paper gives an overview about applying machine learning (ML) in wearable Wireless Body Area Network (WBAN). It highlights the main challenges and open issues for deploying ML models in such sensitive networks. The WBAN is an emerging technology in the last few years, which attracts lots of interest from the academic and industrial communities. It enables a wide range of IoT‐based applications in medical, lifestyle, sport, and entertainment. WBAN are constrained in many aspects such as those related to power resources, communication capabilities, and computation power. Moreover, these networks generate ample amount of sensory data. To overcome the limitations of these networks and make use of the big data generated, artificial intelligence is the best way to deal with gigantic data and help in automating several aspects of the network and its applications. This survey paper aims at reporting numerous ways ML is used to benefit these networks, the design factors that are considered when implementing the ML algorithms, and the communication technologies used in connecting wearable WBAN in the IoT era. The reported studies are based on real overviewed experiment and extensive simulation results.

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LaGOON : a simple energy‐aware routing protocol for wireless nano‐sensor networks

Cited by 11 publications

References 29 publications

ABSense: Sensing Electromagnetic Waves on Metasurfaces via Ambient Compilation of Full Absorption

ABSense: Sensing Electromagnetic Waves on Metasurfaces via Ambient Compilation of Full Absorption

Efficient routing protocol for concave unstable terahertz nanonetworks

Machine learning for wearable IoT‐based applications: A survey

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