The data communications field recently marked the 50th anniversary of the start of the ARPANET, which was one of the first and certainly the most influential of the early data communications networks. The anniversary provoked discussions about which concepts or ideas in data communications have proven to be enduring in the evolution of data communications. This paper presents one perspective
{"title":"Important concepts in data communications","authors":"Chris Partridge","doi":"10.1145/3523230.3523237","DOIUrl":"https://doi.org/10.1145/3523230.3523237","url":null,"abstract":"The data communications field recently marked the 50th anniversary of the start of the ARPANET, which was one of the first and certainly the most influential of the early data communications networks. The anniversary provoked discussions about which concepts or ideas in data communications have proven to be enduring in the evolution of data communications. This paper presents one perspective","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"48 1","pages":"38 - 41"},"PeriodicalIF":2.8,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74188399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matthieu Gouel, Kevin Vermeulen, Maxime Mouchet, Justin P. Rohrer, Olivier Fourmaux, T. Friedman
We describe a new system for distributed tracing at the IP level of the routes that packets take through the IPv4 internet. Our Zeph algorithm coordinates route tracing efforts across agents at multiple vantage points, assigning to each agent a number of /24 destination prefixes in proportion to its probing budget and chosen according to a reinforcement learning heuristic that aims to maximize the number of multipath links discovered. Zeph runs on top of Iris, our fault tolerant system for orchestrating internet measurements across distributed agents of heterogeneous probing capacities. Iris is built around third party free open source software and modern containerization technology, thereby presenting a new model for assembling a resilient and maintainable internet measurement architecture. We show that carefully choosing the destinations to probe from which vantage point matters to optimize topology discovery and that a system can learn which assignment will maximize the overall discovery based on previous measurements. After 10 cycles of probing, Zeph is capable of discovering 2.4M nodes and 10M links in a cycle of 6 hours, when deployed on 5 Iris agents. This is at least 2 times more nodes and 5 times more links than other production systems for the same number of prefixes probed.
{"title":"Zeph & Iris map the internet","authors":"Matthieu Gouel, Kevin Vermeulen, Maxime Mouchet, Justin P. Rohrer, Olivier Fourmaux, T. Friedman","doi":"10.1145/3523230.3523232","DOIUrl":"https://doi.org/10.1145/3523230.3523232","url":null,"abstract":"We describe a new system for distributed tracing at the IP level of the routes that packets take through the IPv4 internet. Our Zeph algorithm coordinates route tracing efforts across agents at multiple vantage points, assigning to each agent a number of /24 destination prefixes in proportion to its probing budget and chosen according to a reinforcement learning heuristic that aims to maximize the number of multipath links discovered. Zeph runs on top of Iris, our fault tolerant system for orchestrating internet measurements across distributed agents of heterogeneous probing capacities. Iris is built around third party free open source software and modern containerization technology, thereby presenting a new model for assembling a resilient and maintainable internet measurement architecture. We show that carefully choosing the destinations to probe from which vantage point matters to optimize topology discovery and that a system can learn which assignment will maximize the overall discovery based on previous measurements. After 10 cycles of probing, Zeph is capable of discovering 2.4M nodes and 10M links in a cycle of 6 hours, when deployed on 5 Iris agents. This is at least 2 times more nodes and 5 times more links than other production systems for the same number of prefixes probed.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"12 1","pages":"2 - 9"},"PeriodicalIF":2.8,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81882601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This January 2022 issue contains three technical papers and four editorial notes.
2022年1月的这一期包含三篇技术论文和四篇社论。
{"title":"The January 2022 issue","authors":"Steve Uhlig","doi":"10.1145/3523230.3523231","DOIUrl":"https://doi.org/10.1145/3523230.3523231","url":null,"abstract":"This January 2022 issue contains three technical papers and four editorial notes.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"51 1","pages":"1 - 1"},"PeriodicalIF":2.8,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82375558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over the years, web content has evolved from simple text and static images hosted on a single server to a complex, interactive and multimedia-rich content hosted on different servers. As a result, a modern website during its loading time fetches content not only from its owner's domain but also from a range of third-party domains providing additional functionalities and services. Here, we infer the network of the third-party domains by observing the domains' interactions within users' browsers from all over the globe. We find that this network possesses structural properties commonly found in complex networks, such as power-law degree distribution, strong clustering, and small-world property. These properties imply that a hyperbolic geometry underlies the ecosystem's topology. We use statistical inference methods to find the domains' coordinates in this geometry, which abstract how popular and similar the domains are. The hyperbolic map we obtain is meaningful, revealing the large-scale organization of the ecosystem. Furthermore, we show that it possesses predictive power, providing us the likelihood that third-party domains are co-hosted; belong to the same legal entity; or merge under the same entity in the future in terms of company acquisition. We also find that complementarity instead of similarity is the dominant force driving future domains' merging. These results provide a new perspective on understanding the ecosystem's organization and performing related inferences and predictions.
{"title":"Topology and Geometry of the Third-Party Domains Ecosystem","authors":"Costas Iordanou, Fragkiskos Papadopoulos","doi":"10.1145/3577929.3577932","DOIUrl":"https://doi.org/10.1145/3577929.3577932","url":null,"abstract":"Over the years, web content has evolved from simple text and static images hosted on a single server to a complex, interactive and multimedia-rich content hosted on different servers. As a result, a modern website during its loading time fetches content not only from its owner's domain but also from a range of third-party domains providing additional functionalities and services. Here, we infer the network of the third-party domains by observing the domains' interactions within users' browsers from all over the globe. We find that this network possesses structural properties commonly found in complex networks, such as power-law degree distribution, strong clustering, and small-world property. These properties imply that a hyperbolic geometry underlies the ecosystem's topology. We use statistical inference methods to find the domains' coordinates in this geometry, which abstract how popular and similar the domains are. The hyperbolic map we obtain is meaningful, revealing the large-scale organization of the ecosystem. Furthermore, we show that it possesses predictive power, providing us the likelihood that third-party domains are co-hosted; belong to the same legal entity; or merge under the same entity in the future in terms of company acquisition. We also find that complementarity instead of similarity is the dominant force driving future domains' merging. These results provide a new perspective on understanding the ecosystem's organization and performing related inferences and predictions.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"19 1","pages":"12 - 25"},"PeriodicalIF":2.8,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86747510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Ding, Ella Peltonen, Tobias Meuser, Atakan Aral, Christian Becker, S. Dustdar, Thomas Hiessl, D. Kranzlmuller, Madhusanka Liyanage, Setareh Magshudi, Nitinder Mohan, J. Ott, Jan S. Rellermeyer, Stefan Schulte, H. Schulzrinne, Gürkan Solmaz, S. Tarkoma, B. Varghese, L. Wolf
Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimisation, and deployment of distributed AI/ML pipelines with given quality of experience, trust, security and privacy targets. The Edge AI community investigates novel ML methods for the edge computing environment, spanning multiple sub-fields of computer science, engineering and ICT. The goal is to share an envisioned roadmap that can bring together key actors and enablers to further advance the domain of Edge AI.
{"title":"Roadmap for edge AI","authors":"A. Ding, Ella Peltonen, Tobias Meuser, Atakan Aral, Christian Becker, S. Dustdar, Thomas Hiessl, D. Kranzlmuller, Madhusanka Liyanage, Setareh Magshudi, Nitinder Mohan, J. Ott, Jan S. Rellermeyer, Stefan Schulte, H. Schulzrinne, Gürkan Solmaz, S. Tarkoma, B. Varghese, L. Wolf","doi":"10.1145/3523230.3523235","DOIUrl":"https://doi.org/10.1145/3523230.3523235","url":null,"abstract":"Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimisation, and deployment of distributed AI/ML pipelines with given quality of experience, trust, security and privacy targets. The Edge AI community investigates novel ML methods for the edge computing environment, spanning multiple sub-fields of computer science, engineering and ICT. The goal is to share an envisioned roadmap that can bring together key actors and enablers to further advance the domain of Edge AI.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"60 1","pages":"28 - 33"},"PeriodicalIF":2.8,"publicationDate":"2021-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90437513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
High-speed programmable switches have emerged as a promising building block for developing performant data-plane applications. In this paper, we argue that the resource constraints and programming model of hardware switches have led to developers adopting problematic design patterns, whose security implications are not widely understood. We bridge the gap by identifying the major challenges and common design pitfalls in switch-based applications in adversarial settings. Examining five recently-proposed switch-based security applications, we find that adversaries can exploit these design pitfalls to completely bypass the protection these applications were designed to provide, or disrupt system operations by introducing collateral damage.
{"title":"Data-plane security applications in adversarial settings","authors":"Liang Wang, Prateek Mittal, J. Rexford","doi":"10.1145/3544912.3544914","DOIUrl":"https://doi.org/10.1145/3544912.3544914","url":null,"abstract":"High-speed programmable switches have emerged as a promising building block for developing performant data-plane applications. In this paper, we argue that the resource constraints and programming model of hardware switches have led to developers adopting problematic design patterns, whose security implications are not widely understood. We bridge the gap by identifying the major challenges and common design pitfalls in switch-based applications in adversarial settings. Examining five recently-proposed switch-based security applications, we find that adversaries can exploit these design pitfalls to completely bypass the protection these applications were designed to provide, or disrupt system operations by introducing collateral damage.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"17 1","pages":"2 - 9"},"PeriodicalIF":2.8,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81698433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Several emerging classes of interactive applications are demanding for extremely low-latency to be fully unleashed, with edge computing generally regarded as a key enabler thanks to reduced delays. This paper presents the outcome of a large-scale end-to-end measurement campaign focusing on task-offloading scenarios, showing that moving the computation closer to the end-users, alone, may turn out not to be enough. Indeed, the complexity associated with modern networks, both at the access and in the core, the behavior of the protocols at different levels of the stack, as well as the orchestration platforms used in data-centers hide a set of pitfalls potentially reverting the benefits introduced by low propagation delays. In short, we highlight how ensuring good QoS to latency-sensitive applications is definitely a multi-dimensional problem, requiring to cope with a great deal of customization and cooperation to get the best from the underlying network.
{"title":"When latency matters","authors":"Marco Iorio, Fulvio Risso, C. Casetti","doi":"10.1145/3503954.3503956","DOIUrl":"https://doi.org/10.1145/3503954.3503956","url":null,"abstract":"Several emerging classes of interactive applications are demanding for extremely low-latency to be fully unleashed, with edge computing generally regarded as a key enabler thanks to reduced delays. This paper presents the outcome of a large-scale end-to-end measurement campaign focusing on task-offloading scenarios, showing that moving the computation closer to the end-users, alone, may turn out not to be enough. Indeed, the complexity associated with modern networks, both at the access and in the core, the behavior of the protocols at different levels of the stack, as well as the orchestration platforms used in data-centers hide a set of pitfalls potentially reverting the benefits introduced by low propagation delays. In short, we highlight how ensuring good QoS to latency-sensitive applications is definitely a multi-dimensional problem, requiring to cope with a great deal of customization and cooperation to get the best from the underlying network.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"21 1","pages":"2 - 13"},"PeriodicalIF":2.8,"publicationDate":"2021-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73353694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Mogul, Priya Mahadevan, C. Diot, J. Wilkes, Phillipa Gill, A. Vahdat
We in Google's various networking teams would like to increase our collaborations with academic researchers related to data-driven networking research. There are some significant constraints on our ability to directly share data, which are not always widely-understood in the academic community; this document provides a brief summary. We describe some models which can work - primarily, interns and visiting scientists working temporarily as employees, which simplifies the handling of some confidentiality and privacy issues. We describe some specific areas where we would welcome proposals to work within those models.
{"title":"Data-driven networking research","authors":"J. Mogul, Priya Mahadevan, C. Diot, J. Wilkes, Phillipa Gill, A. Vahdat","doi":"10.1145/3503954.3503960","DOIUrl":"https://doi.org/10.1145/3503954.3503960","url":null,"abstract":"We in Google's various networking teams would like to increase our collaborations with academic researchers related to data-driven networking research. There are some significant constraints on our ability to directly share data, which are not always widely-understood in the academic community; this document provides a brief summary. We describe some models which can work - primarily, interns and visiting scientists working temporarily as employees, which simplifies the handling of some confidentiality and privacy issues. We describe some specific areas where we would welcome proposals to work within those models.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"83 1","pages":"47 - 49"},"PeriodicalIF":2.8,"publicationDate":"2021-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76550046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In an educational context, experimenting with a real cloud computing platform is very important to let students understand the core concepts, methodologies and technologies of cloud computing. However, API heterogeneity of cloud providers complicates the experimentation by forcing students to focus on the use of different APIs, and by hindering the jointly use of different platforms. In this paper, we present EasyCloud, a toolkit enabling the easy and effective use of different cloud platforms. In particular, we describe its features, architecture, scalability, and use in our cloud computing courses, as well as the pedagogical insights we learnt over the years.
{"title":"An educational toolkit for teaching cloud computing","authors":"C. Anglano, M. Canonico, Marco Guazzone","doi":"10.1145/3503954.3503959","DOIUrl":"https://doi.org/10.1145/3503954.3503959","url":null,"abstract":"In an educational context, experimenting with a real cloud computing platform is very important to let students understand the core concepts, methodologies and technologies of cloud computing. However, API heterogeneity of cloud providers complicates the experimentation by forcing students to focus on the use of different APIs, and by hindering the jointly use of different platforms. In this paper, we present EasyCloud, a toolkit enabling the easy and effective use of different cloud platforms. In particular, we describe its features, architecture, scalability, and use in our cloud computing courses, as well as the pedagogical insights we learnt over the years.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"54 1","pages":"36 - 46"},"PeriodicalIF":2.8,"publicationDate":"2021-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84994052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Kiran, Scott Campbell, F. Wala, Nick Buraglio, I. Monga
This study explores how fallout from the changing public health policy around COVID-19 has changed how researchers access and process their science experiments. Using a combination of techniques from statistical analysis and machine learning, we conduct a retrospective analysis of historical network data for a period around the stay-at-home orders that took place in March 2020. Our analysis takes data from the entire ESnet infrastructure to explore DOE high-performance computing (HPC) resources at OLCF, ALCF, and NERSC, as well as User sites such as PNNL and JLAB. We look at detecting and quantifying changes in site activity using a combination of t-Distributed Stochastic Neighbor Embedding (t-SNE) and decision tree analysis. Our findings bring insights into the working patterns and impact on data volume movements, particularly during late-night hours and weekends.
{"title":"Machine learning-based analysis of COVID-19 pandemic impact on US research networks","authors":"M. Kiran, Scott Campbell, F. Wala, Nick Buraglio, I. Monga","doi":"10.1145/3503954.3503958","DOIUrl":"https://doi.org/10.1145/3503954.3503958","url":null,"abstract":"This study explores how fallout from the changing public health policy around COVID-19 has changed how researchers access and process their science experiments. Using a combination of techniques from statistical analysis and machine learning, we conduct a retrospective analysis of historical network data for a period around the stay-at-home orders that took place in March 2020. Our analysis takes data from the entire ESnet infrastructure to explore DOE high-performance computing (HPC) resources at OLCF, ALCF, and NERSC, as well as User sites such as PNNL and JLAB. We look at detecting and quantifying changes in site activity using a combination of t-Distributed Stochastic Neighbor Embedding (t-SNE) and decision tree analysis. Our findings bring insights into the working patterns and impact on data volume movements, particularly during late-night hours and weekends.","PeriodicalId":50646,"journal":{"name":"ACM Sigcomm Computer Communication Review","volume":"4 1","pages":"23 - 35"},"PeriodicalIF":2.8,"publicationDate":"2021-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79633115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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