| 1. |
- Corneo, Lorenzo, et al.
(author)
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Surrounded by the Clouds : A Comprehensive Cloud Reachability Study
- 2021
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In: Proceedings Of The World Wide Web Conference 2021 (WWW 2021). - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450383127 ; , s. 295-304, s. 295-304
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Conference paper (peer-reviewed)abstract
- In the early days of cloud computing, datacenters were sparsely deployed at distant locations far from end-users with high end-toend communication latency. However, today's cloud datacenters have become more geographically spread, the bandwidth of the networks keeps increasing, pushing the end-users latency down. In this paper, we provide a comprehensive cloud reachability study as we perform extensive global client-to-cloud latency measurements towards 189 datacenters from all major cloud providers. We leverage the well-known measurement platform RIPE Atlas, involving up to 8500 probes deployed in heterogeneous environments, e.g., home and offices. Our goal is to evaluate the suitability of modern cloud environments for various current and predicted applications. We achieve this by comparing our latency measurements against known human perception thresholds and are able to draw inferences on the suitability of current clouds for novel applications, such as augmented reality. Our results indicate that the current cloud coverage can easily support several latency-critical applications, like cloud gaming, for the majority of the world's population.
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| 2. |
- Coronado, Estefania, et al.
(author)
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AI-Empowered Software-Defined WLANs
- 2021
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In: IEEE Communications Magazine. - : Institute of Electrical and Electronics Engineers Inc.. - 0163-6804 .- 1558-1896. ; 59:3, s. 54-60
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Journal article (peer-reviewed)abstract
- The complexity of wireless and mobile networks is growing at an unprecedented pace. This trend is proving current network control and management techniques based on analytical models and simulations to be impractical, especially if combined with the data deluge expected from future applications such as augmented reality. This is particularly true for software-defined wireless local area networks (SO-WLANs). It is our belief that to battle this growing complexity, future SO-WLANs must follow an artificial intelligence (AI) -native approach. In this article, we introduce aiOS, which is an AI-based platform that builds toward the autonomous management of SD-WLANs. Our proposal is aligned with the most recent trends in in-network AI promoted by the ITU Telecommunication Standardization Sector (ITU-T) and with the architecture for disaggregated radio access networks promoted by the Open Radio Access Network Alliance. We validate aiOS in a practical use case, namely frame size optimization in SD-WLANs, and we consider the long-term evolution, challenges, and scenarios for AI-assisted network automation in the wireless and mobile networking domain
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| 3. |
- Mohan, Nitinder, et al.
(author)
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Pruning Edge Research with Latency Shears
- 2020
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In: Proceedings of the 19th ACM Workshop on Hot Topics in Networks. - New York, NY, USA : Association for Computing Machinery. ; , s. 182-189
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Conference paper (peer-reviewed)abstract
- Edge computing has gained attention from both academia and industry by pursuing two significant challenges: 1) moving latency critical services closer to the users, 2) saving network bandwidth by aggregating large flows before sending them to the cloud. While the rationale appeared sound at its inception almost a decade ago, several current trends are impacting it. Clouds have spread geographically reducing end-user latency, mobile phones? computing capabilities are improving, and network bandwidth at the core keeps increasing. In this paper, we scrutinize edge computing, examining its outlook and future in the context of these trends. We perform extensive client-to-cloud measurements using RIPE Atlas, and show that latency reduction as motivation for edge is not as persuasive as once believed; for most applications the cloud is already ’close enough’ for majority of the world’s population. This implies that edge computing may only be applicable for certain application niches, as opposed to a general-purpose solution.
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| 4. |
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| 5. |
- Zavodovski, Aleksandr, et al.
(author)
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Decentralizing Computation with Edge Computing : Potential and Challenges
- 2021
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In: IWCI'21. - New York, NY, USA : ACM. - 9781450391382 ; , s. 34-36
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Conference paper (peer-reviewed)abstract
- Edge computing promises to bring computation close to the end-users to support emergent applications such as virtual reality. However, the computational capacity at the edge of the network is currently limited. To become a pervasive paradigm, edge computing needs highly dispersed decentralized deployments, that, contrary to cloud, cannot benefit from economies of scale. In this situation, crowdsourcing appears attractive - there are plenty of computing devices at the disposal of the general public, and these devices are located exactly where computing power is needed the most - at the edge of the network. Crowdsourcing has been a success maker for scientific computing projects, e.g., SETI@home, or distributed ledger systems empowering decentralized finance. However, as of now, there is no crowdsourced system that addresses the needs of edge computing. In this position paper, we aim to identify the causes of this shortcoming, analyze the potential ways to overcome it, and outline future directions.
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