WIP bittorrent
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_bibliography/bittorrent.bib
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_bibliography/bittorrent.bib
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@article{DBLP:journals/sigops/DemersGHILSSST88,
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author = {Alan J. Demers and
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Daniel H. Greene and
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Carl Hauser and
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Wes Irish and
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John Larson and
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Scott Shenker and
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Howard E. Sturgis and
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Daniel C. Swinehart and
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Douglas B. Terry},
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title = {Epidemic Algorithms for Replicated Database Maintenance},
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journal = {{ACM} {SIGOPS} Oper. Syst. Rev.},
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volume = {22},
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number = {1},
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pages = {8--32},
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year = {1988},
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url = {https://doi.org/10.1145/43921.43922},
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doi = {10.1145/43921.43922},
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timestamp = {Tue, 14 Jul 2020 14:25:20 +0200},
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biburl = {https://dblp.org/rec/journals/sigops/DemersGHILSSST88.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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@inproceedings{DBLP:conf/infocom/BharambeHP06,
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author = {Ashwin R. Bharambe and
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Cormac Herley and
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Venkata N. Padmanabhan},
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title = {Analyzing and Improving a BitTorrent Networks Performance Mechanisms},
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booktitle = {{INFOCOM} 2006. 25th {IEEE} International Conference on Computer Communications,
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Joint Conference of the {IEEE} Computer and Communications Societies,
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23-29 April 2006, Barcelona, Catalunya, Spain},
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year = {2006},
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crossref = {DBLP:conf/infocom/2006},
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url = {https://doi.org/10.1109/INFOCOM.2006.328},
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doi = {10.1109/INFOCOM.2006.328},
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timestamp = {Wed, 16 Oct 2019 14:14:51 +0200},
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biburl = {https://dblp.org/rec/conf/infocom/BharambeHP06.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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@proceedings{DBLP:conf/infocom/2006,
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title = {{INFOCOM} 2006. 25th {IEEE} International Conference on Computer Communications,
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Joint Conference of the {IEEE} Computer and Communications Societies,
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23-29 April 2006, Barcelona, Catalunya, Spain},
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publisher = {{IEEE}},
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year = {2006},
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url = {https://ieeexplore.ieee.org/xpl/conhome/4146652/proceeding},
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isbn = {1-4244-0221-2},
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timestamp = {Wed, 16 Oct 2019 14:14:51 +0200},
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biburl = {https://dblp.org/rec/conf/infocom/2006.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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---
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layout: post
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slug: enseigner-le-cloud
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status: draft
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sitemap: true
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title: Enseigner le "cloud"
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description: Connection timed out
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categories:
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- systeme
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- enseignement
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tags:
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---
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Apple, Adobe, Orange, SFR, Google, le _futur de la tech'_ ne serait se concevoir sans le cloud.
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Certaines mêmes vont plus loins, elles _sont_ le cloud comme OVH, autrefois hébergeur de site web, qui s'appelle maintenant OVHCloud.
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Le cloud fait également l'actualité, entre questions de souverainetés, de données ou encore de parts de marchés, il y a toujours un bon article à écrire.
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Le cloud est partout et maintenant jusque dans les universités et les écoles d'ingénieur... où je me suis retrouvé à l'enseigner.
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![](/assets/images/posts/cloud-evol.png)
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<div style="text-align:center">_Évolution de l'intérêt pour le sujet "cloud" sur Google_</div>
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Du TP qui nécessite une carte bancaire, au TP qui n'aura pas lieu car les infrastructures informatiques sont indiponibles en passant par le relai du discours des Amazon et consors sans prise de recul, cet article résume deux années de cours houleuses.
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## Un concept dur à cerner
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aa
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#### L'histoire du mot et des offres commerciales
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A développé de nombreux outils pour
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Amazon a des ressources inutilisées
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sous traitance, externalisation
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<!-- https://www.lesechos.fr/partenaires/econocom/comment-le-cloud-booste-les-entreprises-1034026 -->
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<!-- https://www.cairn.info/revue-communication-et-langages1-2014-4-page-77.htm -->
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<!-- http://www.slate.fr/story/91703/internet-mot-cloud -->
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#### Un mot qui cache une réalité
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On commence par la base : le cloud ce sont des ordinateurs. Beaucoup d'ordinateurs, allumés 24h/24. On les appelle des serveurs et on les place dans des datacenters.
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D'ailleurs, les serveurs et les datacenters existaient bien avant l'invention du mot cloud.
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#### Pourquoi une telle addiction ?
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L'objectif de notre cours, c'est de comprendre comment, avec ces serveurs on peut créer des Netflix, Google, Facebook, Twitter, Amazon, etc.
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C'est à dire des services qui ne tombent pas en panne, qui supportent des milliers (puis des millions et enfin des milliards) d'utilisateurs et qui ne coutent pas trop cher à maintenir.
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C'est plus compliqué que ça, il y a un
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#### Quels axes pour un cours
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réseau
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systèmes
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systèmes distribués
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architecture logiciel distribuée
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## Place à la pratique
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#### La sous-traitance comme modèle
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#### La nécessité d'avoir une infrastructure
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Épuisement des ressources
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Effets de bord en pagaille
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Redémarrage des VMs
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Coupures réseaux
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Machines de TP
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Migration qui échoue
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SSE4.2 n'est plus disponible
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_posts/2020-10-22-understand-bittorrent.md
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_posts/2020-10-22-understand-bittorrent.md
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---
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layout: post
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slug: understanding-bittorrent
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status: draft
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sitemap: false
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title: Understanding BitTorrent
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description: From the network perspective
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categories:
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tags:
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- p2p
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- distributed system
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---
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In this blog post, we will only review the core of BitTorrent.
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We are not interested in its extensions, its optimizations, how it manages spam, etc.
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Compared to the specifications, we will focus our analysis on the importance of parameters and the emerging behaviours that arise when many BitTorrent clients communicate together.
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Moreover, as this (hopefully series of) article will be written in a goal to evaluate Peertube planned implementation of "webstream" (live-streaming over webtorrent), we will use the webtorrent implementation as reference for everything outside specifications.
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We will also try to connect BitTorrent design to some academic papers to put things in perspective.
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## A problem well stated is a problem half solved
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**Discover content**
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**Discover peers**
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**Discover peers' content**
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**Induce a desirable emerging behavior**
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## The .torrent file
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Describes the content of the file to download.
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Multiplexing.
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## The role of the tracker
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Discovering peers.
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What property it must enforce.
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Random sample of the network
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You will have some neighbors.
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## Discovering the chunks known by your neighbors
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introduce some Xerox Taxonomy {% cite DBLP:journals/sigops/DemersGHILSSST88 %}.
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"bitfield" puis "have" -> le push sur l'anti entropy
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If it's done symmetrically, we are in a push+pull model.
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## Downloading the data
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The importance of Local Rarest First {% cite DBLP:conf/infocom/BharambeHP06 %}
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## Conclusion
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BitTorrent is efficient as it multiplexes chunks.
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## References
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{% bibliography --cited %}
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