Decentralized Consensus for Edge-Centric Internet of Things: A Review, Taxonomy, and Research Issues

With the exponential rise in the number of devices, the Internet of Things (IoT) is geared toward edge-centric computing to offer high bandwidth, low latency, and improved connectivity. In contrast, legacy cloud-centric platforms offer deteriorated bandwidth and connectivity that affect the quality of service. Edge-centric Internet of Things-based technologies, such as fog and mist computing, offer distributed and decentralized solutions to resolve the drawbacks of cloud-centric models. However, to foster distributed edge-centric models, a decentralized consensus system is necessary to incentivize all participants to share their edge resources. This paper is motivated by the shortage of comprehensive reviews on decentralized consensus systems for edge-centric Internet of Things that elucidates myriad of consensus facets, such as data structure, scalable consensus ledgers, and transaction models. Decentralized consensus systems adopt either blockchain or blockchainless directed acyclic graph technologies, which serve as immutable public ledgers for transactions. This paper scrutinizes the pros and cons of state-of-the-art decentralized consensus systems. With an extensive literature review and categorization based on existing decentralized consensus systems, we propose a thematic taxonomy. The pivotal features and characteristics associated with existing decentralized consensus systems are analyzed via a comprehensive qualitative investigation. The commonalities and variances among these systems are analyzed using key criteria derived from the presented literature. Finally, several open research issues on decentralized consensus for edge-centric IoT are presented, which should be highlighted regarding centralization risk and deficiencies in blockchain/blockchainless solutions.

[1]  Yoad Lewenberg,et al.  SPECTRE: A Fast and Scalable Cryptocurrency Protocol , 2016, IACR Cryptol. ePrint Arch..

[2]  Satoshi Nakamoto Bitcoin : A Peer-to-Peer Electronic Cash System , 2009 .

[3]  Ivan Stojmenovic,et al.  Fog computing: A cloud to the ground support for smart things and machine-to-machine networks , 2014, 2014 Australasian Telecommunication Networks and Applications Conference (ATNAC).

[4]  Leslie Lamport,et al.  The Byzantine Generals Problem , 1982, TOPL.

[5]  Sunny King,et al.  PPCoin: Peer-to-Peer Crypto-Currency with Proof-of-Stake , 2012 .

[6]  John R. Douceur,et al.  The Sybil Attack , 2002, IPTPS.

[7]  Yoad Lewenberg,et al.  Inclusive Block Chain Protocols , 2015, Financial Cryptography.

[8]  Ethan Heilman,et al.  TumbleBit: An Untrusted Bitcoin-Compatible Anonymous Payment Hub , 2017, NDSS.

[9]  Vitalik Buterin A NEXT GENERATION SMART CONTRACT & DECENTRALIZED APPLICATION PLATFORM , 2015 .

[10]  Peter G. Neumann,et al.  The future of the internet of things , 2017, Commun. ACM.

[11]  Aviv Zohar,et al.  Secure High-Rate Transaction Processing in Bitcoin , 2015, Financial Cryptography.

[12]  Thomas Heinz Meitinger,et al.  Smart Contracts , 2017, Informatik-Spektrum.

[13]  Emin Gün Sirer,et al.  Majority Is Not Enough: Bitcoin Mining Is Vulnerable , 2013, Financial Cryptography.

[14]  Min Chen,et al.  A Survey on Internet of Things From Industrial Market Perspective , 2015, IEEE Access.

[15]  Michael Devetsikiotis,et al.  Blockchains and Smart Contracts for the Internet of Things , 2016, IEEE Access.

[16]  Victor C. M. Leung,et al.  Green Internet of Things for Smart World , 2015, IEEE Access.

[17]  Christian Decker,et al.  Bitcoin meets strong consistency , 2014, ICDCN.

[18]  Nancy A. Lynch,et al.  Consensus in the presence of partial synchrony , 1988, JACM.

[19]  Jared Saia,et al.  Load Balanced Scalable Byzantine Agreement through Quorum Building, with Full Information , 2011, ICDCN.

[20]  Fred B. Schneider,et al.  Implementing fault-tolerant services using the state machine approach: a tutorial , 1990, CSUR.

[21]  Aviv Zohar,et al.  Accelerating Bitcoin's Transaction Processing. Fast Money Grows on Trees, Not Chains , 2013, IACR Cryptol. ePrint Arch..

[22]  H. Madsen,et al.  Reliability in the utility computing era: Towards reliable Fog computing , 2013, 2013 20th International Conference on Systems, Signals and Image Processing (IWSSIP).

[23]  Raja Lavanya,et al.  Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.

[24]  Eric A. Brewer,et al.  Towards robust distributed systems (abstract) , 2000, PODC '00.

[25]  Pieter Wuille,et al.  Enabling Blockchain Innovations with Pegged Sidechains , 2014 .

[26]  Teruo Higashino,et al.  Edge-centric Computing: Vision and Challenges , 2015, CCRV.

[27]  Christian Decker,et al.  A Fast and Scalable Payment Network with Bitcoin Duplex Micropayment Channels , 2015, SSS.

[28]  Florian Glaser,et al.  Beyond Cryptocurrencies - A Taxonomy of Decentralized Consensus Systems , 2015, ECIS.

[29]  Marko Vukolic,et al.  The Quest for Scalable Blockchain Fabric: Proof-of-Work vs. BFT Replication , 2015, iNetSeC.

[30]  Emin Gün Sirer,et al.  Bitcoin-NG: A Scalable Blockchain Protocol , 2015, NSDI.

[31]  Daniel Davis Wood,et al.  ETHEREUM: A SECURE DECENTRALISED GENERALISED TRANSACTION LEDGER , 2014 .

[32]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[33]  Björn Scheuermann,et al.  Bitcoin and Beyond: A Technical Survey on Decentralized Digital Currencies , 2016, IEEE Communications Surveys & Tutorials.

[34]  Xavier Boyen,et al.  Blockchain-Free Cryptocurrencies. A Rational Framework for Truly Decentralised Fast Transactions , 2016, IACR Cryptol. ePrint Arch..

[35]  David Schwartz,et al.  The Ripple Protocol Consensus Algorithm , 2014 .

[36]  Ari Juels,et al.  $evwu Dfw , 1998 .

[37]  DECOR + LAMI : A Scalable Blockchain Protocol , 2016 .

[38]  Miguel Oom Temudo de Castro,et al.  Practical Byzantine fault tolerance , 1999, OSDI '99.

[39]  Christian Decker,et al.  Information propagation in the Bitcoin network , 2013, IEEE P2P 2013 Proceedings.

[40]  Angelo Corsaro Cloudy, Foggy and Misty Internet of Things , 2016, ICPE.