1 / 46

A P2P-based Storage Platform for Storing Session Data in Internet Access Networks

Peter Danielis , M. Gotzmann , D. Timmermann University of Rostock, Germany Institute of Applied Microelectronics and Computer Engineering. A P2P-based Storage Platform for Storing Session Data in Internet Access Networks.

eryk
Download Presentation

A P2P-based Storage Platform for Storing Session Data in Internet Access Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Peter Danielis, M. Gotzmann, D. Timmermann University of Rostock, Germany Institute of Applied Microelectronics and Computer Engineering A P2P-based Storage Platform for Storing Session Data in Internet Access Networks World TelecommunicationCongress 2010 Network & Service Management ReliabilitySeptember 13-14 T. Bahls, D. Duchow Nokia Siemens Networks Broadband Access Division Greifswald, Germany

  2. Outline • Introduction & Motivation • Utilizationof P2P Technology • Erasure Resilient Codes for High Data Availability • Realizationofthe P2P-based Storage Platform • Summary

  3. Introduction & Motivation • Internet Service Providers (ISPs) provide Internet access  Access nodes (ANs) = essential networkelements • E.g., DSLAMs (Digital Subscriber Line Access Multiplexers)

  4. Introduction & Motivation  Access nodes (ANs) = essential networkelements • ANs havetobe powerful but well-priced ANs ≠servers! • Budget withavailableresources! $ $ $ $

  5. Introduction & Motivation  Access nodes (ANs) = essential networkelements • ANs needresets (ormayfail)  data must not be lost! • AN configurationdataneedstobesavedpersistently! • But there‘smore…

  6. Introduction & Motivation • Data - calledsessiondata - … • … comprises MAC/IP addresses, IP lease timesofcustomers • … isrequiredfordataforwarding/trafficfiltering DHCP Request: I have MAC address 00-50-04-E1-15-A0! DHCP Response: Your IP addressis 139.30.201.254 for60 min! MAC address: 00-50-04-E1-15-A0 IP address: 139.30.201.254 Lease Time: 60 min Active: No

  7. Introduction & Motivation • Data - calledsessiondata - … • … comprises MAC/IP addresses, IP lease timesofcustomers • … isrequiredfordataforwarding/trafficfiltering • … hastobealwaysavailable  persistent storageneeded • … ishighly volatile due tocontinouschanges DHCP Request: I have MAC address 00-50-04-E1-15-A0! DHCP Response: Your IP addressis 139.30.201.254 for 60 min! MAC address: 00-50-04-E1-15-A0 IP address: 139.30.201.254 Lease Time: 60 min Active: Yes

  8. Introduction & Motivation • Today: ANs storesessiondata in persistentflashmemory • Problem: Flash memory limited availability/rewritability • ISPs „sacrifice“ flashmemoryforsessiondatareluctantly

  9. Introduction & Motivation • Today: ANs storesessiondata in persistentflashmemory • Problem: Flash memory limited availability/rewritability • Solution: Useavailablevolatile RAM resourcesof ANs!

  10. Introduction & Motivation • Average AN, e.g., PowerQuicc III (Freescale Semiconductor) • RAM capacity = 1 Gbyte + unlimitedrewritability

  11. Introduction & Motivation • Average AN, e.g., PowerQuicc III (Freescale Semiconductor) • Calculatingcapacity = 1234 Dhrystone MIPS

  12. Introduction & Motivation • Average AN, e.g., PowerQuicc III (Freescale Semiconductor) • Calculatingcapacity = 1234 Dhrystone MIPS

  13. Introduction & Motivation • Average AN, e.g., PowerQuicc III (Freescale Semiconductor) • Problem: Howtoefficientlyutilizeavailableresources?

  14. Outline • Introduction & Motivation • Utilizationof P2P Technology • Erasure Resilient Codes for High Data Availability • Realizationofthe P2P-based Storage Platform • Summary

  15. Whatoptionsdoes P2P offer? • ...beyond the incriminated applications, of course. • New networking paradigm • No clients and servers anymore

  16. Whatoptionsdoes P2P offer? • ...beyond the incriminated applications, of course. • New networking paradigm • No clients and servers anymore • All peers form a self-organizing network • Network = storage resource • Network = computing resource • Scalability and resilience = intrinsic features • Proven concept (BitTorrent, Zattoo, Joost)

  17. Utilizationof P2P technology • Networking paradigm • Each AN ispartof a logical P2P overlay on itsuplink • Network = Storage Resource • Each AN stores just a pieceofsessiondata • Network = Computing Resource • Each AN implements P2P protocol • But ANs maybecomeunavailable… • Problem: Howtoensurehighdataavailability? Storage Capacity ofANs

  18. Outline • Introduction & Motivation • Utilizationof P2P Technology • ErasureResilientCodes (ERCs) forHigh Data Availability • Realizationofthe P2P-based Storage Platform • Summary

  19. ERCs for High Data Availability • Objective: High sessiondataavailability = 99.999 % • Simple replicationwastesmemoryressources  Reed-Solomon Codes • Split sessiondataofeach AN into m datachunks

  20. ERCs for High Data Availability • Objective: High sessiondataavailability = 99.999 % • Simple replicationwastesmemoryressources  Reed-Solomon Codes • Split sessiondataofeach AN into m datachunks • Encoding: Add k interleavedcodingchunks n=m+kchunks

  21. ERCs for High Data Availability • Objective: High sessiondataavailability = 99.999 % • Simple replicationwastesmemoryressources  Reed-Solomon Codes • Split sessiondataofeach AN into m datachunks • Encoding: Add k interleavedcodingchunks n=m+kchunks • Decoding: Restoresessiondatafromany m of n chunks

  22. Outline • Introduction & Motivation • Utilizationof P2P Technology • ErasureResilient Codes for High Data Availability • Realizationofthe P2P-based Storage Platform • Summary

  23. Kad-based Realization

  24. Kad-based Realization • Connection ofaccessnodes (ANs) with P2P-based overlay

  25. Kad-based Realization • Connection ofaccessnodes (ANs) with P2P-based overlay • P2P protocol: Kad-based Distributed Hash Table (DHT) ring

  26. Kad-based Realization • Connection ofaccessnodes (ANs) with P2P-based overlay • P2P protocol: Kad-based Distributed Hash Table (DHT) ring • Structured chunkstorage via DHT ring • Assignmentofhashvaluesto ANs andsessiondatachunks • ANs save sessiondatachunkswithsimilarhashvalues

  27. Kad-based Realization • Connection ofaccessnodes (ANs) with P2P-based overlay • P2P protocol: Kad-based Distributed Hash Table (DHT) ring • Structured chunkstorage via DHT ring • Assignmentofhashvaluesto ANs andsessiondatachunks • ANs save sessiondatachunkswithsimilarhashvalues Admin

  28. Block Diagram • The maincomponentsare… DHCP Server

  29. Block Diagram • (1) module with controlling functionality Save Session Data! DHCP Server 1 Time to Save Session Data!

  30. Block Diagram • (2) memory with own session data DHCP Server 2

  31. Block Diagram • (3) Kad block with ERC functionality DHCP Server 3

  32. Block Diagram • (4) routing table DHCP Server 4

  33. Block Diagram • (5) memory with session data chunks of other nodes DHCP Server 5

  34. Outline • Introduction & Motivation • Utilizationof P2P Technology • ErasureResilient Codes for High Data Availability • Realizationofthe P2P-based Storage Platform • Summary

  35. Summary • Successfuldevelopmentof P2P-based storageplatform • Utilizationoffree RAM insteadofrarelyavailableflashmemory • Connection ofaccessnodesby P2P overlay • High scalabilityandresiliencetowardsnetworkerrors • Efficientsharingof RAM andcomputingresources • ERCs forhighdataavailability & lowredundandy • Completionoffullyfunctional prototype

  36. Thankyou! Anyquestions? peter.danielis@uni-rostock.dehttp://www.imd.uni-rostock.de/networking

  37. Backup: Related Work J. Kubiatowicz et. al., “Oceanstore: An architecture for global-scale persistent storage”, 2000 Schwarz, Xin, Miller, “Availability in Global Peer-To-Peer Storage Systems”, 2004 Sattler, Hauswirth, Schmidt, „UniStore: Querying a DHT-based Universal Storage“, 2007 Morariu, „DIPStorage: Distributed Storage of IP Flow Records“, 2008

  38. Backup: Kad-based DHT Kad (eMule): 128 bitaddressspace Distancesbetweenhashvaluesarecalculatedbythe XOR metric

  39. Backup: Kad Routing Table • Binary tree with XOR distances of other peers to itself • Organized into k-buckets • Each peer knows many close peers • Each peer knows only few distant peers • Each peer has a life time

  40. Backup: Kad Bootstrapping & Maintenance • Bootstrapping • New peer contacts a known peer and inserts itself on ring • Maintenance • Contact peers from routing table with expired life time • Contact other peers periodically to learn new contacts

  41. Backup: Kad Lookup Process • Searching peer selects peers close to target These peersarecontacted via a request Somerespondwithnewpeers 41

  42. Backup: Kad Lookup Process • Some of the new peers are contacted • Some of them respond 42

  43. Backup: Kad Lookup Process • Respondingpeerswithin a definedsearchtolerance • Action request: Execute theaction! • Ifthey send an actionresponse, a counterisincreased • Ifcounter==definedvalue, thelookupterminates • Otherwise, itisterminated via a timeout

  44. Backup: Prototype

  45. Backup: RelatedIssues • Benefitfromusing ERCs insteadofdatareplication • Moderate quantitativememorysavings • But significantlyhigherdataavailability • Kadnetwork: open sourceishighquality! • Minimal trafficoverheadintroducedbyKadmaintenance

  46. Backup: Memory requirements & performance • Currently, prototype is ported to a Xilinx FPGA board • Long-time test/simuof prototype at our institute intended • Functional verification • Determination of performance • Determination of memory requirements • Determination of CPU utilization

More Related