Distributed Data Management in Internet of Things Networking Environments: IOTA Tangle and Bitcoin Blockchain Distributed Ledger Technologies
2018 (engelsk)Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hp
Oppgave
Abstract [en]
Distributed ledger technology (DLT) is one of the latest in a long list of digital technologies, which appear to be heading towards a new industrial revolution. DLT has become very popular with the publication of the Bitcoin Blockchain in 2008. However, when we consider its suitability for dynamic networking environments, such as the Internet of Things, issues like transaction fees, scalability, and offline accessibility have not been resolved. The IOTA Foundation has designed the IOTA protocol, which is the data and value transfer layer for the Machine Economy. IOTA protocol uses an alternative blockless Blockchain which claims to solve the previous problems: the Tangle.
This thesis first inquires into the theoretical concepts of both technologies Tangleand Blockchain, to understand them and identify the reasons to be compatible or not with the Internet of Things networking environments. After the analysis, the thesis focuses on the proposed implementation as a solution to address the connectivity issue suffered by the IOTA network. The answer to the problem is the development of a Neighbor Discovery algorithm, which has been designed to fulfill the requirements demanded by the IOTA application.
Dealing with IOTA network setup can be very interesting for the community that is looking for new improvements at each release. Testing the solution in a peer-to-peer specific protocol (PeerSim), with different networking scenarios, allowed us to get valuable and more realistic information. Thus, after analyzing the results, we were able to determine the appropriate IOTA network configuration to build a more reliable and long-lasting network.
sted, utgiver, år, opplag, sider
2018. , s. 45
Emneord [en]
Distributed Ledger Technology (DLT), Bitcoin, IOTA, peer-to-peer, dynamic networks
HSV kategori
Identifikatorer
URN: urn:nbn:se:lnu:diva-77359OAI: oai:DiVA.org:lnu-77359DiVA, id: diva2:1242322
Fag / kurs
Computer Science
Utdanningsprogram
Computer Engineering Programme, 180 credits
Veileder
Examiner
2018-08-292018-08-272022-03-07bibliografisk kontrollert