Abstract
In this paper a new application of the distributed ledger technology is proposed. The swarm robotics is a rapidly developing area due to the numerous advantages of the swarm. Yet there can be situations when some additional functional tasks should be relocated from one robot to another, for example, if there is a need to offload one of the robots. For such resource allocation tasks the robot reliability must be taken into account. This causes the importance of the robot workload logging in the swarm, because it is not sufficient to take into account the current workload to estimate the reliability level. In the paper the technique of the distributed-ledger-based workload logging is presented as well as information propagation methods are considered and the peculiarities of the robot swarm has been taken into account.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Şahin, E.: Swarm robotics: from sources of inspiration to domains of application. In: Şahin, E., Spears, William M. (eds.) SR 2004. LNCS, vol. 3342, pp. 10–20. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-30552-1_2
Mohan, Y., Ponnambalam, S.G.: An extensive review of research in swarm robotics. In: 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 – Proceedings, pp. 140–145. IEEE Xplore (2009)
Sharkey, A.J.C.: Robots, insects and swarm intelligence. Artif. Intell. Rev. 26(4), 255–268 (2006)
Brambilla, M., Ferrante, E., Birattari, M., Dorigo, M.: Swarm robotics: a review from the swarm engineering perspective. Swarm Intell. 7(1), 1–41 (2013)
Prorok, A., Hsieh, M.A., Kumar, V.: Formalizing the impact of diversity on performance in a heterogeneous swarm of robots. In: Proceedings - IEEE International Conference on Robotics and Automation, Stockholm, Sweden, pp. 5364–5371. IEEE (2016)
Stranieri, A., et al.: Self-organized flocking with a heterogeneous mobile robot swarm). In: Lenaerts, T., et al. (eds.) Proceedings of ECAL 2011, pp 789–796, MIT Press, Cambridge (2011)
Verbelen, T., Simoens, P., De Turck, F.: AIOLOS: middleware for improving mobile application performance through cyber foraging. J. Syst. Softw. 85(11), 2629–2639 (2012)
De Coninck, E., Bohez, S., Leroux, S.: Middleware platform for distributed applications incorporating robots, sensors and the cloud. In: 5th IEEE International Conference on Cloud Networking (CloudNet), Pisa, Italy, pp. 218–223. IEEE (2016)
Bacciu, D., Chessa, S., Gallicchio, C.: A general purpose distributed learning model for robotic ecologies. In: 10th International IFAC Symposium on Robot Control (SYROCO), Proceedings, Dubrovnik, Croatia, vol. 45, no. 22, pp. 435–440. IEEE (2012)
Verstraeten, D., Schrauwen, B., D’Haene, M.: An experimental unification of reservoir computing methods. Neural Netw. 20(3), 391–403 (2007)
Zhang, K., Collins, E.G., Shi, D.: Centralized and distributed task allocation in multi-robot teams via a stochastic clustering auction. ACM Trans. Autonom. Adapt. Syst. 7(2), 21 (2012)
Crestani, D., Godary-Dejean, K.: Fault tolerance in control architectures for mobile robots: fantasy or reality? In: 7th National Conference on Control Architectures of Robots, Nancy, France (2012)
Wüst, K., Ritzdorf, H., Karame, G.O., Glykantzis, V., Capkun, S., Gervais, A.: On the security and performance of proof of work blockchains. In: Proceedings of the 2016 ACM SIGSAC Conference, Vienna, Austria, pp. 3–16 (2016)
Crosby, M., Nachiappan, Pattanayak, P., Verma, S., Kalyanaraman, V.: Blockchain technology - beyond bitcoin. Berkley Engineering, p. 35 (2016)
Nguyen, G.T., Kim, K.: A survey about consensus algorithms used in blockchain. J. Inf. Process. Syst. 14(1), 101–128 (2018)
Castello, E.: The blockchain: a new framework for robotic swarm systems. https://www.researchgate.net/publication/305807446_The_blockchain_a_new_framework_for_robotic_swarm_systems. Accessed 05 Apr 2019
Melnik, E.V., Klimenko, A.B.: Informational and control system configuration generation problem with load-balancing optimization. In: 10th International Conference on Application of Information and Communication Technologies, Azerbaijan, Baku, pp. 492–496. IEEE (2016)
Melnik, E., Klimenko, A., Ivanov, D.: The model of device community forming problem for the geographically-distributed information and control systems using fog-computing concept. In: Proceedings of the 4th International Research Conference “Information Technologies in Science, Management, Social Sphere and Medicine”, Tomsk, Russia, vol. 72, pp. 132–136. Atlantis-Press (2017)
Decker, C., Wattenhofer, R.: Information propagation in the Bitcoin network. In: 13th IEEE International Conference on Peer-to-Peer Computing Proceedings, Trento, Italy, pp. 1–10. IEEE (2013)
Acknowledgements
The current study is granted by the RFBR project 18-29-03229 and the GZ SSC RAS N GR project AAAA-A19-119011190173-6.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Kalyaev, I., Melnik, E., Klimenko, A. (2019). Distributed Ledger Based Workload Logging in the Robot Swarm. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds) Interactive Collaborative Robotics. ICR 2019. Lecture Notes in Computer Science(), vol 11659. Springer, Cham. https://doi.org/10.1007/978-3-030-26118-4_12
Download citation
DOI: https://doi.org/10.1007/978-3-030-26118-4_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-26117-7
Online ISBN: 978-3-030-26118-4
eBook Packages: Computer ScienceComputer Science (R0)