Content Distribution March 2, 2011 2: Application Layer 1 Contents P2P architecture and benefits P2P content distribution Content distribution network (CDN) 2: Application Layer 2 Pure P2P architecture no always-on server arbitrary end systems directly communicate peer-peer peers are intermittently connected and change IP addresses Three topics: File distribution Searching for information Case Study: Skype 2: Application Layer 3 File Distribution: Server-Client vs P2P Question : How much time to distribute file from one server to N peers? us: server upload bandwidth Server us File, size F dN uN u1 d1 u2 ui: peer i upload bandwidth d2 di: peer i download bandwidth Network (with abundant bandwidth) 2: Application Layer 4 File distribution time: server-client server sequentially sends N copies: NF/us time client i takes F/di time to download Server F us dN u1 d1 u2 d2 Network (with abundant bandwidth) uN Time to distribute F to N clients using = dcs = max { NF/us, F/min(di) } i client/server approach increases linearly in N (for large N) 2: Application Layer 5 File distribution time: P2P server must send one Server F u1 d1 u2 d2 copy: F/us time us client i takes F/di time Network (with dN to download abundant bandwidth) uN NF bits must be downloaded (aggregate) fastest possible upload rate: us + Sui dP2P = max { F/us, F/min(di) , NF/(us + Sui) } i 2: Application Layer 6 Server-client vs. P2P: example Client upload rate = u, F/u = 1 hour, us = 10u, dmin ≥ us Minimum Distribution Time 3.5 P2P 3 Client-Server 2.5 2 1.5 1 0.5 0 0 5 10 15 20 25 30 35 N 2: Application Layer 7 Contents P2P architecture and benefits P2P content distribution Content distribution network (CDN) 2: Application Layer 8 P2P content distribution issues Issues Peer discovery and group management Data placement and searching Reliable and efficient file exchange Security/privacy/anonymity/trust Approaches for group management and data search (i.e., who has what?) Centralized (e.g., BitTorrent tracker) Unstructured (e.g., Gnutella) Structured (Distributed Hash Tables [DHT]) 2: Application Layer 9 Centralized index (Napster) original “Napster” design 1) when peer connects, it informs central server: Bob centralized directory server 1 peers IP address content 2) Alice queries for “Hey Jude” 3) Alice requests file from Bob 1 3 1 2 1 Alice 2: Application Layer 10 Centralized model Bob Alice file transfer is decentralized, but locating content is highly centralized Judy Jane 2: Application Layer 11 Centralized Benefits: Low per-node state Limited bandwidth usage Short location time High success rate Fault tolerant Drawbacks: Single point of failure Limited scale Possibly unbalanced load Bob Judy Alice Jane copyright infringement 2: Application Layer 12 File distribution: BitTorrent P2P file distribution tracker: tracks peers participating in torrent torrent: group of peers exchanging chunks of a file obtain list of peers trading chunks peer 2: Application Layer 13 BitTorrent (1) file divided into 256KB chunks. peer joining torrent: has no chunks, but will accumulate them over time registers with tracker to get list of peers, connects to subset of peers (“neighbors”) while downloading, peer uploads chunks to other peers. peers may come and go once peer has entire file, it may (selfishly) leave or (altruistically) remain 2: Application Layer 14 BitTorrent (2) Pulling Chunks at any given time, different peers have different subsets of file chunks periodically, a peer (Alice) asks each neighbor for list of chunks that they have. Alice sends requests for her missing chunks rarest first Sending Chunks: tit-for-tat Alice sends chunks to four neighbors currently sending her chunks at the highest rate re-evaluate top 4 every 10 secs every 30 secs: randomly select another peer, starts sending chunks newly chosen peer may join top 4 “optimistically unchoke” 2: Application Layer 15 BitTorrent: Tit-for-tat (1) Alice “optimistically unchokes” Bob (2) Alice becomes one of Bob’s top-four providers; Bob reciprocates (3) Bob becomes one of Alice’s top-four providers With higher upload rate, can find better trading partners & get file faster! 2: Application Layer 16 P2P Case study: Skype Skype clients (SC) inherently P2P: pairs of users communicate. proprietary Skype login server application-layer protocol (inferred via reverse engineering) hierarchical overlay with SNs Index maps usernames to IP addresses; distributed over SNs Supernode (SN) 2: Application Layer 17 Peers as relays Problem when both Alice and Bob are behind “NATs”. NAT prevents an outside peer from initiating a call to insider peer Solution: Using Alice’s and Bob’s SNs, Relay is chosen Each peer initiates session with relay. Peers can now communicate through NATs via relay 2: Application Layer 18 Distributed Hash Table (DHT) DHT = distributed P2P database Database has (key, value) pairs; key: ss number; value: human name key: content type; value: IP address Peers query DB with key DB returns values that match the key Peers can also insert (key, value) peers 2: Application Layer 19 DHT Identifiers Assign integer identifier to each peer in range [0,2n-1]. Each identifier can be represented by n bits. Require each key to be an integer in same range. To get integer keys, hash original key. eg, key = h(“Led Zeppelin IV”) This is why they call it a distributed “hash” table 2: Application Layer 20 How to assign keys to peers? Central issue: Assigning (key, value) pairs to peers. Rule: assign key to the peer that has the closest ID. Convention in lecture: closest is the immediate successor of the key. Ex: n=4; peers: 1,3,4,5,8,10,12,14; key = 13, then successor peer = 14 key = 15, then successor peer = 1 2: Application Layer 21 Chord (a circular DHT) (1) 1 3 15 4 12 5 10 8 Each peer only aware of immediate successor and predecessor. “Overlay network” 2: Application Layer 22 Chord (a circular DHT) (2) O(N) messages on avg to resolve query, when there are N peers 0001 I am Who’s resp 0011 for key 1110 ? 1111 1110 0100 1110 1110 1100 1110 1110 Define closest as closest successor 1010 0101 1110 1000 2: Application Layer 23 Chord (a circular DHT) with Shortcuts 1 3 15 Who’s resp for key 1110? 4 12 5 10 8 Each peer keeps track of IP addresses of predecessor, successor, short cuts. Reduced from 6 to 2 messages. Possible to design shortcuts so O(log N) neighbors, O(log N) messages in query 2: Application Layer 24 Peer Churn 1 •To handle peer churn, require 3 15 4 12 5 10 each peer to know the IP address of its two successors. • Each peer periodically pings its two successors to see if they are still alive. 8 Peer 5 abruptly leaves Peer 4 detects; makes 8 its immediate successor; asks 8 who its immediate successor is; makes 8’s immediate successor its second successor. What if peer 13 wants to join? 2: Application Layer 25 Contents P2P architecture and benefits P2P content distribution Content distribution network (CDN) 2: Application Layer 26 Why Content Networks? More hops between client and Web server more congestion! Same data flowing repeatedly over links between clients and Web server C1 C3 C4 S C2 Slides from http://www.cis.udel.edu/~iyengar/courses/Overlays.ppt - IP router 2: Application Layer 27 Why Content Networks? Origin server is bottleneck as number of users grows Flash Crowds (for instance, Sept. 11) The Content Distribution Problem: Arrange a rendezvous between a content source at the origin server (www.cnn.com) and a content sink (us, as users) Slides from http://www.cis.udel.edu/~iyengar/courses/Overlays.ppt 2: Application Layer 28 Example: Web Server Farm Simple solution to the content distribution problem: deploy a large group of servers www.cnn.com (Copy 1) www.cnn.com (Copy 2) Request from grad.umd.edu www.cnn.com (Copy 3) Request from ren.cis.udel.edu L4-L7 Switch Request from ren.cis.udel.edu Request from grad.umd.edu Arbitrate client requests to servers using an “intelligent” L4-L7 switch Pretty widely used today 2: Application Layer 29 Example: Caching Proxy Majorly motivated by ISP business interests – reduction in bandwidth consumption of ISP from the Internet Reduced network traffic Reduced user perceived latency ISP Client ren.cis.udel.edu Client merlot.cis.ud el.edu Intercepters TCP port 80 traffic Other traffic Internet www.cnn.com Proxy 2: Application Layer 30 But on Sept. 11, 2001 Web Server www.cnn.com New Content WTC News! 1000,000 other hosts request 1000,000 other hosts ISP old content request User mslab.kaist.ac.kr - Congestion / Bottleneck - Caching Proxy 2: Application Layer 31 Problems with discussed approaches: Server farms and Caching proxies Server farms do nothing about problems due to network congestion, or to improve latency issues due to the network Caching proxies serve only their clients, not all users on the Internet Content providers (say, Web servers) cannot rely on existence and correct implementation of caching proxies Accounting issues with caching proxies. For instance, www.cnn.com needs to know the number of hits to the webpage for advertisements displayed on the webpage 2: Application Layer 32 Again on Sept. 11, 2001 with CDN Web Server www.cnn.com New Content WTC News! WA CA MI 1000,000 other users IL MA 1000,000 other users FL NY DE request new content User mslab.kaist.ac.kr - Distribution Infrastructure - Surrogate 2: Application Layer 33 Web replication - CDNs Overlay network to distribute content from origin servers to users Avoids large amounts of same data repeatedly traversing potentially congested links on the Internet Reduces Web server load Reduces user perceived latency Tries to route around congested networks 2: Application Layer 34 CDN vs. Caching Proxies Caches are used by ISPs to reduce bandwidth consumption, CDNs are used by content providers to improve quality of service to end users Caches are reactive, CDNs are proactive Caching proxies cater to their users (web clients) and not to content providers (web servers), CDNs cater to the content providers (web servers) and clients CDNs give control over the content to the content providers, caching proxies do not 2: Application Layer 35 CDN Architecture Origin Server CDN Request Routing Infrastructure Distribution & Accounting Infrastructure Surrogate Surrogate Client Client 2: Application Layer 36 CDN Components Content Delivery Infrastructure: Delivering content to clients from surrogates Request Routing Infrastructure: Steering or directing content request from a client to a suitable surrogate Distribution Infrastructure: Moving or replicating content from content source (origin server, content provider) to surrogates Accounting Infrastructure: Logging and reporting of distribution and delivery activities 2: Application Layer 37 Server Interaction with CDN www.cnn.com 1. Origin server pushes new content to CDN OR CDN pulls content from origin server Origin Server 1 2 2. Origin server requests logs and other accounting info from CDN OR CDN provides logs and other accounting info to origin server CDN Distribution Infrastructure Accounting Infrastructure 2: Application Layer 38 Client Interaction with CDN 1. Hi! I need www.cnn.com/sept11 2. Go to surrogate newyork.cnn.akamai.com CDN california.cnn.akamai.com Surrogate (CA) Request Routing Infrastructure 3. Hi! I need content /sept11 newyorkcnn.akamai.com Q: How did the CDN choose the New York surrogate over the California surrogate ? Surrogate (NY) 1 2 3 Client 2: Application Layer 39 Request Routing Techniques Request routing techniques use a set of metrics to direct users to “best” surrogate Proprietary, but underlying techniques known: DNS based request routing Content Modification (URL rewriting) Anycast based (how common is anycast?) URL based request routing Transport layer request routing Combination of multiple mechanisms 2: Application Layer 40 DNS based Request-Routing Common due to the ubiquity of DNS as a directory service Specialized DNS server inserted in DNS resolution process DNS server is capable of returning a different set of A, NS or CNAME records based on policies/metrics 2: Application Layer 41 DNS based Request-Routing Q: How does the Akamai DNS know which surrogate is closest ? Akamai CDN newyork.cnn.akamai.com Surrogate 145.155.10.15 www.cnn.com Akamai DNS california.cnn.akamai.com Surrogate 58.15.100.152 1) DNS query: www.cnn.com test.nyu.edu 128.4.30.15 DNS response: A 145.155.10.15 newyork.cnn.akamai.com local DNS server (dns.nyu.edu) 128.4.4.12 2: Application Layer 42 DNS based Request-Routing www.cnn.com Akamai CDN Akamai DNS Surrogate Surrogate DNS query test.nyu.edu 128.4.30.15 DNS response local DNS server (dns.nyu.edu) 128.4.4.12 2: Application Layer 43 DNS based Request Routing: Caching www.cnn.com Akamai DNS Akamai CDN Requesting DNS - 76.43.32.4 Surrogate - 145.155.10.15 Surrogate 58.15.100.152 Surrogate 145.155.10.15 Requesting DNS - 76.43.32.4 Requesting DNS - 76.43.32.4 Available Bandwidth = 10 kbps RTT = 10 ms Client Client DNS 76.43.35.53 76.43.32.4 Available Bandwidth = 5 kbps RTT = 100 ms www.cnn.com A 145.155.10.15 TTL = 10s 2: Application Layer 44 DNS based Request Routing: Discussion Originator Problem: Client may be far removed from client DNS Client DNS Masking Problem: Virtually all DNS servers, except for root DNS servers honor requests for recursion Q: Which DNS server resolves a request for test.nyu.edu? Q: Which DNS server performs the last recursion of the DNS request? Hidden Load Factor: A DNS resolution may result in drastically different load on the selected surrogate – issue in load balancing requests, and predicting load on surrogates 2: Application Layer 45 Server Selection Metrics Network Proximity (Surrogate to Client): Network hops (traceroute) Internet mapping services (NetGeo, IDMaps) … Surrogate Load: Number of active TCP connections HTTP request arrival rate Other OS metrics … Bandwidth Availability 2: Application Layer 46 P4P : Provider Portal for (P2P) Applications Laboratory of Networked Systems Yale University P2P: Benefits and Challenges P2P is a key to content delivery – Low costs to content owners/distributors – Scalability Challenge – Network-obliviousness usually leads to network inefficiency • Intradomain: for Verizon network, P2P traffic traverses 1000 miles and 5.5 metro-hops on average • Interdomain: 50%-90% of existing local pieces in active users are downloaded externally* *Karagiannis et al. Should Internet service providers fear peer-assisted content distribution? In Proceeding of IMC 2005 ISP Attempts to Address P2P Issues Upgrade infrastructure Customer pricing Rate limiting, or termination of services P2P caching ISPs cannot effectively address network efficiency alone Locality-aware P2P: P2P’s Attempt to Improve Network Efficiency P2P has flexibility in shaping communication patterns Locality-aware P2P tries to use this flexibility to improve network efficiency E.g., Karagiannis et al. 2005, Bindal et al. 2006, Choffnes et al. 2008 (Ono) Problems of Locality-aware P2P Locality-aware P2P needs to reverse engineer network topology, traffic load and network policy Locality-aware P2P may not achieve network efficiency Choose congested links Traverse costly interdomain links ISP 1 ISP 0 ISP 2 ISP K A Fundamental Problem Feedback from networks is limited E.g., end-to-end flow measurements or limited ICMP feedback Our Goal Design a framework to enable better cooperation between networks and P2P P4P: Provider Portal for (P2P) Applications P4P Architecture ISP A Providers iTracker publish information via iTracker Applications query providers’ information adjust traffic patterns accordingly iTracker P2P ISP B Example:Tracker-based P2P Information flow 1. peer queries appTracker appTracker 2 iTracker 3 2/3. appTracker queries 1 iTracker 4 4. appTracker selects a set of active peers peer ISP A