Optimal Transmission Scheduling in Small Multimodal Underwater Networks

Campagnaro, Filippo; Casari, Paolo; Zorzi, Michele; Diamant, Roee

doi:10.1109/lwc.2018.2873329

Cited by 11 publications

(9 citation statements)

References 7 publications

(11 reference statements)

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“…Finally, we demonstrate the flexibility of ASUNA by testing the optimal multimodal scheduling (OMS) scheme in [194]. OMS is an adaptive TDMA-based algorithm that exploits multimodal links in order to schedule transmissions that obey a number of constraints.…”

Section: A322 Berlin Multimodalmentioning

confidence: 99%

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Dubrovinskaya

Casari

2019

OCEANS 2019 - Marseille

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Casari knows no boundaries. He believed in me to allow me to work independently while providing all the possible support and was by my side when needed. His high standards both in research and communication have become my constant beacon in my personal and professional growth. His assistance in every aspect of research work was absolutely invaluable.Another thank you should definitely go to my tutor Prof. Albert Banchs Roca for all his help with the paperwork from the very first days of my Ph.D. I would also like to say thanks to Dr. Ivor Nissen for his introduction to the world of underwater acoustic localization research, and for always keeping an eye on my progress. I am grateful to Dr. Diamant for welcoming and hosting me at Haifa University and enduring me during numerous sea trials. All the field experience I got during my trips to Israel is still one of the most unforgettable go through during my Ph.D.Furthermore, I would like to say many thanks to Dr. Konstantin Kebkal and Evologics GmbH colleagues for hosting me at their premises in Berlin and for all the invaluable help in organizing lab and field experiments. Special thanks to Veronika Kebkal who pushed everyone to make it possible (and fun!) Also, I would like to thank Dr. Fraser Dalgleish who hosted me at Florida Atlantic University and for sharing experimental data even after I left.A huge bunch of thanks goes to all my colleagues at IMDEA Networks for all the coffee break talks, dinner drinks, board games battles, and barbeque parties. Special thanks go to the "ground-floor" team for all the evening gossip times and fun we had.Last but not least thank you goes to my wonderful family. Thanks to my parents for teaching me to value knowledge and for giving me everything I need. And the most important thanks -to my husband Sergey Samodov, who was solving all my life problems, listened to my nagging during the hardest days saying, "this too shall pass", waiting for me to come back. I couldn't have done this journey without you.

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Section: A322 Berlin Multimodalmentioning

confidence: 99%

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Dubrovinskaya

Casari

2019

OCEANS 2019 - Marseille

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“…We For a multimodal communications dataset, we also test the optimal multimodal scheduling approach in [64]. We freely share ASUNA as well as the emulation code with the underwater communications community, with the hope that ASUNA will constitute a benchmark to test underwater acoustic networking solutions including, but not limited to, scheduling, routing, and automatic repeat query schemes.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, we demonstrate the flexibility of ASUNA by testing the optimal multimodal scheduling (OMS) scheme in [64]. OMS is an adaptive TDMA-based algorithm that exploits multimodal links in order to schedule transmissions that obey a number of constraints.…”

Section: A Structure Of a Network Emulatormentioning

confidence: 99%

“…These include network topology structure, bounds to interference, and measures to favor multihop routing. OMS was already tested at sea via a dedicated experiment [64] (also part of ASUNA, see the second-to-last line of Table I), hence here we rather test OMS using the "Berlin Multimodal" dataset. This also enables a direct comparison against the baseline TDMA protocol considered above.…”

Section: A Structure Of a Network Emulatormentioning

confidence: 99%

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ASUNA: A Topology Data Set for Underwater Network Emulation

Casari

Campagnaro

Dubrovinskaya

et al. 2021

IEEE J. Oceanic Eng.

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We report the details of ASUNA, a freely shared dataset for underwater network emulation (ASUNA). ASUNA tackles the time-consuming and costly logistics of multiple underwater networking sea trials by providing a benchmark database of time-varying network topologies recorded across multiple sea experiments, thus facilitating experiment replay and network emulation. The ASUNA database currently includes 20 diverse, time-varying topology structures, multimodal communication technologies, and different link quality measurements. With the aim of becoming a standard benchmark, ASUNA is open to extensions as new data becomes available from the underwater communications community. We provide the details of ASUNA structure, the list of recorded topologies, as well as examples of how to use the database as part of an emulation system to test the performance of two scheduling protocols. We freely share the database and the emulation code both through a web server and via the Code Ocean repository.

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“…For maritime communications, most of common resource management schemes are designed for underwater networks. For example, in [22], time resources are determined optimally to maximize the overall channel utilization while preserving flow limitation and maintaining fairness for underwater networks. In [23], a spatial reuse resource allocation scheme is presented for underwater acoustic networks.…”

Section: Introductionmentioning

confidence: 99%

Resource Management of Maritime Edge Nodes for Collected Data Feedback

2020

IEEE Access

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With the development of marine economy, more marine applications emerge leading to more deployed sensors and more generated data. However, current marine Internet only provides low transmission rate constrained by limited communication resources and bad transmission environment. How to efficiently use these resources and guarantee quality-of-service (QoS) of applications need to be addressed. This paper proposes an online optimization resource management algorithm to improve the communication resource efficiency with guaranteed QoSs for different applications. This algorithm needs neither of the resource cost function nor QoS constraint function at the resource scheduling node. Furthermore, the gradient information, which is usually needed in learning strategies, is not required either. Instead, this algorithm performs resource management of both computation and communication resources in each time slot only based on the observation of the last time slot. With slot-by-slot resource allocation, the communication cost can be minimized to be suitable for maritime scenarios. In the meantime, a long-term delay constraint can be satisfied. Results show that the proposed algorithm achieves the goal of reducing communication cost while guaranteeing the delay-constraint of different applications. Although more computation resources will improve its performance, this algorithm still can obtain the minimized cost given a low computation resource. INDEX TERMS Online resource management, data feedback, edge computing, maritime communications.

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Optimal Transmission Scheduling in Small Multimodal Underwater Networks

Cited by 11 publications

References 7 publications

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

Underwater Direction of Arrival Estimation using Wideband Arrays of Opportunity

ASUNA: A Topology Data Set for Underwater Network Emulation

Resource Management of Maritime Edge Nodes for Collected Data Feedback

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