Open Access
Subscription Access
Open Access
Subscription Access
Improving Byzantine Fault Tolerance in Swarm Robotics Collective Decision-making Scenario via a New Blockchain Consensus Algorithm
Subscribe/Renew Journal
Swarm robotics applies concepts of swarm intelligence to robotics. Discrete consensus achievement is one of the major behaviors found in swarm robotics. Various algorithms have been developed for discrete consensus achievement. However, existing discrete consensus achievement algorithms are vulnerable to Byzantine robots. Blockchain has been successfully used to mitigate the negative effect of Byzantine robots. Nevertheless, since the blockchain solution uses the Proof-of-Work blockchain consensus algorithm, it is vulnerable to the 51% attack. Besides, the swarm also takes longer to achieve consensus. This research proposes a novel blockchain consensus algorithm called Proof-of-Identity—which uses a private-public key pair and a swarm controller—to create a dynamically permissioned blockchain that would negate the 51%-attack problem associated with the Proof-of-Work algorithm while also reducing the consensus time. This proposed solution was tested against the classical solution and the existing blockchain solution using the collective perception scenario. Test results show that the Proof-of-Identity algorithm prevents the 51%-attack problem while improving the consensus time in comparison to the existing blockchain solution without affecting the exit probability.
Keywords
Blockchain, Swarm Robotics, Proof Of Identity, Proof Of Work, Blockchain Consensus Algorithm, Collective Perception.
Subscription
Login to verify subscription
User
Font Size
Information
- G. Beni, “From Swarm Intelligence to Swarm Robotics”, Lecture Notes in Computer Science, Vol. 3342, pp. 1-9, 2005.
- E. Şahin, “Swarm Robotics: From Sources of Inspiration to Domains of Application”, Lecture Notes in Computer Science, Vol. 3342, pp. 10-20, 2005.
- M. Brambilla, E. Ferrante, M. Birattari and M. Dorigo, “Swarm Robotics: A Review from the Swarm Engineering Perspective”, Swarm Intelligence, Vol. 7, No. 1, pp. 1-41, 2013.
- M. Crosby, “BlockChain Technology: Beyond Bitcoin”, Available at: http://scet.berkeley.edu/wp-content/uploads/AIR-2016-Blockchain.pdf, Accessed at 2016.
- T. Krishnamohan and K. Janarthanan, “BlockFlow: A Decentralized SDN Controller using Blockchain”, International Journal of Scientific and Research Publications, Vol. 10, No. 3, pp. 1-14, 2020.
- S. Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System”, Available at: www.bitcoin.org, Accessed at 2009.
- G. Valentini, D. Brambilla, H. Hamann and M. Dorigo, “Collective Perception of Environmental Features in a Robot Swarm”, Proceedings of International Conference on Swarm Intelligence, pp. 65-76, 2016.
- K. Von Frisch, “The Dance Language and Orientation of Bees”, Harvard University Press, 1993.
- G. Valentini, H. Hamann and M. Dorigo, “Efficient Decision-Making in a Self-Organizing Robot Swarm: On the Speed Versus Accuracy Trade-Off”, Proceedings of International Conference on Swarm Robotics, pp. 1-8, 2021.
- G. Valentini, E. Ferrante, H. Hamann and M. Dorigo, “Collective Decision with 100 Kilobots: Speed versus Accuracy in Binary Discrimination Problems”, Autonomous Agents and Multi-Agent Systems, Vol. 30, No. 3, pp. 553-580, 2016.
- G. Valentini, H. Hamann and M. Dorigo, “Self-Organized Collective Decision Making: The Weighted Voter Model”, Proceedings of International Conference on Autonomous Agents and Multiagent Systems, pp. 45-52, 2014.
- V. Strobel, E.C. Ferrer and M. Dorigo, “Managing Byzantine Robots via Blockchain Technology in a Swarm Robotics Collective Decision Making Scenario”, Proceedings of International Conference on Autonomous Agents and Multiagent Systems, pp. 1-13, 2021.
- A.L. Christensen, R. O’Grady and M. Dorigo, “From Fireflies to Fault-Tolerant Swarms of Robots”, IEEE Transactions on Evolutionary Computation, Vol. 13, No. 4, pp. 754-766, 2009.
- N. Anita and M. Vijayalakshmi, “Blockchain Security Attack: A Brief Survey”, Proceedings of International Conference on Computing, Communication and Networking Technologies, pp. 1-6, 2019.
- M.S. Ferdous, M.J.M. Chowdhury, M.A. Hoque and A. Colman, “Blockchain Consensus Algorithms: A Survey”, Available: http://arxiv.org/abs/2001.07091, Accessed at 2021.
Abstract Views: 81
PDF Views: 2