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Decentralized, Trust-less Marketplace for Brokered IoT Data Trading using Blockchain

a talk given at the 2nd IEEE Blockchain conference, Atlanta, US ?july 2019.
here is the paper: http://homepages.cs.ncl.ac.uk/paolo.missier/doc/Decentralised_Marketplace_USA_Conference___Accepted_Version_.pdf

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Decentralized, Trust-less Marketplace for Brokered IoT Data Trading using Blockchain

  1. 1. Shaimaa Bajoudah, Changyu Dong, and Paolo Missier Newcastle University, UK School of Computing 2nd IEEE Blockchain Conference Atlanta, USA July 15th, 2019 Toward a Decentralized, Trust-less Marketplace for Brokered IoT Data Trading using Blockchain
  2. 2. 2 Motivation <eventname> Setting: Trading data streams from ioT devices Primary IoT data flows Strava Secondary markets Primary VAS Garmin server Edge network IoT data marketplace Health Insurance Follow-your-runner portal Technology enabler: message brokering based eg on MQTT  single data stream delivered to multiple parties
  3. 3. 3 What are we aiming for? <eventname> • Open to new participants with No trust assumptions: • No trusted authority in the marketplace management platform • Participants must earn their reputation • Computed from history of past behaviour • Managing adversarial behavior: • Ensure upper bound on revenue loss • Fair resolution of disputes
  4. 4. 4 Contract framework <eventname> Offer validity time interval Topic Message unit price Expected streaming message rate TATI: time interval during which the contract is in forceData offering
  5. 5. 5 Baseline model <eventname> Data producer Data consumer Public Data Offeringsadvertise 1️⃣ Settlement 5️⃣ discover 2️⃣ Negotiation 3️⃣ MQTT broker Data streaming Data streaming4️⃣
  6. 6. 6 The problem <eventname> No trust between any pair <Consumer C, Producer P> No trusted authority in data transport network or message brokers P may deliver data to C without receiving payment But: assumption of QoS guarantees for message delivery - MQTT
  7. 7. 7 Data receipts <eventname> Approach: Data receipt protocol - Data stream broken down into batches b1… bn Data producer Data consumer MQTT broker Batch 1 Batch 1 Receipt 1 … Data producer Data consumer MQTT broker Batch n Batch n Receipt n - Consumer C must acknowledge receipt of each batch bi - Producer P only sends batch bi+1 when it sees receipt for bi
  8. 8. 8 Transaction scenarios <eventname> 1- Normal termination - Data transfer takes place as expected - Both parties comply with the contract 2- Bad termination – no fault - Data loss along the network - C claims no data received, stops sending receipts 3- Bad termination – C fraud - C claims no data batch received, stops sending receipts Note: producer P has no incentive to commit fraud in this model
  9. 9. 9 Role of Smart Contracts <eventname> Data receipt protocol supported by a Smart Contract SC: Data producer Data consumer MQTT broker Batch Batch ACK Receipt SCSC SC Eth blockchain Data producer Data consumer MQTT broker Batch 1 Batch 1 Receipt 1
  10. 10. 10 Transaction scenarios involving SC <eventname> 1- Normal termination - Data transfer takes place as expected - Both parties comply with the contract - SC settles payment 2- Bad termination – no fault - Data loss along the network - C claims no data received, stops sending receipts to SC - SC terminates trade early 3- Bad termination – C dishonest - C claims no data batch received, stops sending receipts to SC - SC terminates trade early However: SC cannot distinguish between cases (2) and (3)
  11. 11. 11 Loss control: Batch size <eventname> Batch Size BS controls data loss Number of messages that P will have sent to C, that C will not acknowledge and therefore will not pay for SC invoked after each batch Max data loss = 1 batch
  12. 12. 12 Cost <eventname> ATM: actual number of messages delivered at the end of TATI: This decreases as BS and RTmax increase, as expected Assumptions: - transaction fees for data receipts are charged to C - latency RT due to each data receipt transaction is detracted from TATI Ethereum cost model, including:
  13. 13. 13 Cost / trust trade-off <eventname> BS ↑ Cost ↓ Lack of trust generates a tension: P  low risk C  low transaction cost and minimal overhead C fully trusted Crep =1   Min cost
  14. 14. 14 Evaluation: reputation and batch size <eventname> Define a family of reference BS functions: k controls min number of receipts / trade
  15. 15. 15 Evaluation: number of receipts vs reputation <eventname> Assume k = 2.77
  16. 16. 17 Evaluation: cost breakdown <eventname> Goal: assess cost / trust trade-offs
  17. 17. 18 Evaluation: cost / messages vs reputation <eventname>
  18. 18. 19 Summary <eventname> A marketplace for streaming data Trust enforced through blockchain / Smart Contracts SC roles: - manages users registration - uses signed contracts to verify data receipts during trading - SC settles payments at the end of each trade Prototyped on Ethereum (private network) Coming next: reputation model and empirical analysis Reputation + Blockchain + Rational risk decisions  Sustainable Marketplace

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