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Large-Scale Decentralized
Storage Systems used by
Volunteer Computing
Final Presentation


     G7: Arinto, Diego, Enkhjin, Iuliia
Outline
● Problem Definition
● Volunteer Computing (VC)
● Decentralized Storage Systems
  (DSS)
● Systems Review
● State-of-the-Art DSS used by VC
● Conclusions
Problem Definition

● Decentralized Storage Systems

● Volunteer Computing

● DSS + VC = ?
Problem Definition
Problem Definition
Volunteer Computing
●   Group of computing resources
●   Voluntary share the resource
●   Incentive volunteers!!
●   Trust between peers
●   Example:
    ○   SETI@home
    ○   Storage@home
    ○   Folding@home
●   However, data is centrally stored
Volunteer Computing
BOINC
example
Decentralized Storage
Systems
Decentralized Storage
Systems Review
Focus Criteria:
  AV = availability
  SC = scalability
  ECO = eventual consistency
  P = performance
  SE = security
Decentralized Storage
 Systems Review
System       Description                                     Focus
             Large scale persistent P2P storage system       SE
Farsite
             P2P storage system based on Dhash table         ECO, AV
Ivy
             logs
             P2P DHT-based storage system that used          ECO
OverNet
             XOR-based metrics for routing
             Large scale persistent P2P storage system       SC, SE, AV
PAST
             Highly scalable P2P storage system based on     SC, ECO
Pastis
             trust
             Big, distributed, fault tolerant hashtable      AV
Voldemort
             Globally persistent DSS for any-file-anywhere   SC, SE
OceanStore
Decentralized Storage
  Systems Review
System         Description                                         Focus
                                                                   SC, AV, P
Glacier        Highly durable DSS for archiving, no remote write

               P2P storage system. Automatically manage its        AV, SC
Total Recall
               availability in dynamic changing environment
               DSS with no point of failure to store structured    SC, AV, ECO
Cassandra
               data
                                                                   SC, AV
Riak           Dynamo-inspired NOSQL storage system.
                                                                   P, AV, ECO
Dynamo         Large scale DSS developed by Amazon

               Secure DSS and BitTorrent-like file swarming        SE, AV
Attic
               techniques to serve data and manage load.
                                                                   P, ECO
Squirrel       Decentralized Web Cache
State-of-The-Art DSS-
Characteristics
● Read and Write Access
● Fault Tolerance and Replication Techniques
● Availability and Symmetry
● Video/Images

● Incentives
State-of-The-Art DSS-
Characteristics
State-of-The-Art DSS-
Suggestions for Incentives
Incentives based on amount of storage
dedicated, computing resources volunteered:

● Credit based system
● Printable Certificates
● Government tax break, possible in countries
  with significant amount of nodes
State-of-The-Art DSS-
Challenges
● Providing the right Incentive

● Security

● Integration into current VC environment
Conclusions
● VC data storage/distribution issues.
● Survey on DSS
  ○ Classification

● Integration VC systems - DSS
  ○ Identify characteristics
  ○ Valid and Useful / Define state-art
  ○ Challenges
Work Effort

Arinto Murdopo = 100%
Diego Montero = 100%
Enkhjin Bayarsaikhan = 100%
Iuliia Proskurnia = 100%
Questions
...???

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Group7 presentation

  • 1. Large-Scale Decentralized Storage Systems used by Volunteer Computing Final Presentation G7: Arinto, Diego, Enkhjin, Iuliia
  • 2. Outline ● Problem Definition ● Volunteer Computing (VC) ● Decentralized Storage Systems (DSS) ● Systems Review ● State-of-the-Art DSS used by VC ● Conclusions
  • 3. Problem Definition ● Decentralized Storage Systems ● Volunteer Computing ● DSS + VC = ?
  • 6. Volunteer Computing ● Group of computing resources ● Voluntary share the resource ● Incentive volunteers!! ● Trust between peers ● Example: ○ SETI@home ○ Storage@home ○ Folding@home ● However, data is centrally stored
  • 9. Decentralized Storage Systems Review Focus Criteria: AV = availability SC = scalability ECO = eventual consistency P = performance SE = security
  • 10. Decentralized Storage Systems Review System Description Focus Large scale persistent P2P storage system SE Farsite P2P storage system based on Dhash table ECO, AV Ivy logs P2P DHT-based storage system that used ECO OverNet XOR-based metrics for routing Large scale persistent P2P storage system SC, SE, AV PAST Highly scalable P2P storage system based on SC, ECO Pastis trust Big, distributed, fault tolerant hashtable AV Voldemort Globally persistent DSS for any-file-anywhere SC, SE OceanStore
  • 11. Decentralized Storage Systems Review System Description Focus SC, AV, P Glacier Highly durable DSS for archiving, no remote write P2P storage system. Automatically manage its AV, SC Total Recall availability in dynamic changing environment DSS with no point of failure to store structured SC, AV, ECO Cassandra data SC, AV Riak Dynamo-inspired NOSQL storage system. P, AV, ECO Dynamo Large scale DSS developed by Amazon Secure DSS and BitTorrent-like file swarming SE, AV Attic techniques to serve data and manage load. P, ECO Squirrel Decentralized Web Cache
  • 12. State-of-The-Art DSS- Characteristics ● Read and Write Access ● Fault Tolerance and Replication Techniques ● Availability and Symmetry ● Video/Images ● Incentives
  • 14. State-of-The-Art DSS- Suggestions for Incentives Incentives based on amount of storage dedicated, computing resources volunteered: ● Credit based system ● Printable Certificates ● Government tax break, possible in countries with significant amount of nodes
  • 15. State-of-The-Art DSS- Challenges ● Providing the right Incentive ● Security ● Integration into current VC environment
  • 16. Conclusions ● VC data storage/distribution issues. ● Survey on DSS ○ Classification ● Integration VC systems - DSS ○ Identify characteristics ○ Valid and Useful / Define state-art ○ Challenges
  • 17. Work Effort Arinto Murdopo = 100% Diego Montero = 100% Enkhjin Bayarsaikhan = 100% Iuliia Proskurnia = 100%