Abstract

Lately, the importance of swarm robotics has been recognized in a wide range of areas, including logistics, surveillance, disaster management, agriculture, and other industrial applications. The swarm intelligence introduced by the existing paradigm of artificial intelligence and machine learning often ignores the aspect of providing security and reliability guarantees. Consider a futuristic scenario wherein self-driving cars will transport people, self-driving trucks will carry cargo between warehouses, and a combination of legged robots/drones will ship cargo from warehouses to doorsteps. In the case of such a heterogeneous swarm of robots, it is crucial to ensure a trustful and reliable operating platform for smooth coordination, collaborative decision-making via appropriate consensus, and seamless information sharing while ensuring data security. In this direction, blockchain has been proven to be an effective technology that maintains the transactions (records) in a trustful manner after being validated through consensus. This guarantees accountability, transparency, and trust concerning the storage, safeguarding, and sharing of information among the parties. In this paper, we provide a walkthrough demonstrating the feasibility of using blockchain technology to make the robotic swarm trustful systems in their adoption to critical applications at large-scale. We highlight the pros and cons of the use of cloud vis-a-vis blockchain in swarm robotics. Finally, we present various future research opportunities pertaining to the adoption of blockchain technology in swarm robotics applications.

References

1.
Wen
,
J.
,
He
,
L.
, and
Zhu
,
F.
,
2018
, “
Swarm Robotics Control and Communications: Imminent Challenges for Next Generation Smart Logistics
,”
IEEE Commun. Mag.
,
56
(
7
), pp.
102
107
.
2.
Stolfi
,
D. H.
,
Brust
,
M. R.
,
Danoy
,
G.
, and
Bouvry
,
P.
,
2021
, “
UAV-UGV-UMV Multi-swarms for Cooperative Surveillance
,”
Front. Rob. AI
,
8
, p.
616950
.
3.
Roldán-Gómez
,
J. J.
,
González-Gironda
,
E.
, and
Barrientos
,
A.
,
2021
, “
A Survey on Robotic Technologies for Forest Firefighting: Applying Drone Swarms to Improve Firefighters’ Efficiency and Safety
,”
Appl. Sci.
,
11
(
1
), p.
363
.
4.
Trotta
,
A.
,
Montecchiari
,
L.
,
Felice
,
M. D.
, and
Bononi
,
L.
,
2020
, “
A GPS-Free Flocking Model for Aerial Mesh Deployments in Disaster-Recovery Scenarios
,”
IEEE Access
,
8
, pp.
91558
91573
.
5.
Albiero
,
D.
,
Pontin Garcia
,
A.
,
Kiyoshi Umezu
,
C.
, and
Leme de Paulo
,
R.
,
2022
, “
Swarm Robots in Mechanized Agricultural Operations: A Review About Challenges for Research
,”
Comput. Electron. Agric.
,
193
, p.
106608
.
6.
Aloui
,
K.
,
Guizani
,
A.
,
Hammadi
,
M.
,
Soriano
,
T.
, and
Haddar
,
M.
,
2021
, “
Integrated Design Methodology of Automated Guided Vehicles Based on Swarm Robotics
,”
Appl. Sci.
,
11
(
13
), p.
6187
.
7.
Chung
,
S.-J.
,
Paranjape
,
A. A.
,
Dames
,
P.
,
Shen
,
S.
, and
Kumar
,
V.
,
2018
, “
A Survey on Aerial Swarm Robotics
,”
IEEE Trans. Rob.
,
34
(
4
), pp.
837
855
.
8.
Zikratov
,
I. A.
,
Lebedev
,
I. S.
,
Gurtov
,
A. V.
, and
Kuzmich
,
E. V.
,
2014
, “
Securing Swarm Intellect Robots With a Police Office Model
,”
2014 IEEE 8th International Conference on Application of Information and Communication Technologies (AICT)
,
Astana, Kazakhstan
,
Oct. 15–17
, pp.
1
5
.
9.
Khalastchi
,
E.
, and
Kalech
,
M.
,
2019
, “
Fault Detection and Diagnosis in Multi-robot Systems: A Survey
,”
Sensors
,
19
(
18
), p.
4019
.
10.
Nakamoto
,
S.
,
2009
, “
Bitcoin: A Peer-to-Peer Electronic Cash System
,” Available online at http://bitcoin.org/bitcoin.pdf
11.
Courtois
,
N. T.
,
2014
, “
On the Longest Chain Rule and Programmed Self-destruction of Crypto Currencies
,”
preprint arXiv:1405.0534.
12.
Kroll
,
J. A.
,
Davey
,
I. C.
, and
Felten
,
E. W.
,
2013
, “
The Economics of Bitcoin Mining, Or Bitcoin in the Presence of Adversaries
,” Proceedings of WEIS, Vol. 2013, No.11,
Washington, DC
.
13.
Buterin
,
V.
,
2013
, “
Ethereum White Paper
,”
GitHub Repository
,
1
, pp.
22
23
.
14.
Kolling
,
A.
,
Walker
,
P.
,
Chakraborty
,
N.
,
Sycara
,
K.
, and
Lewis
,
M.
,
2015
, “
Human Interaction With Robot Swarms: A Survey
,”
IEEE Trans. Human Mach. Syst.
,
46
(
1
), pp.
9
26
.
15.
Queralta
,
J. P.
,
Qingqing
,
L.
,
Gia
,
T. N.
,
Truong
,
H.-L.
, and
Westerlund
,
T.
,
2020
, “
End-to-End Design for Self-reconfigurable Heterogeneous Robotic Swarms
,”
2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)
,
Online Event, Marina Del Rey, LA, California
,
June 15–17
, pp.
281
287
.
16.
Nguyen
,
T.
,
Katila
,
R.
, and
Gia
,
T. N.
,
2023
, “
An Advanced Internet-of-Drones System With Blockchain for Improving Quality of Service of Search and Rescue: A Feasibility Study
,”
Future Gener. Comput. Syst.
,
140
, pp.
36
52
.
17.
Singh
,
P. K.
,
Singh
,
R.
,
Nandi
,
S. K.
,
Ghafoor
,
K. Z.
,
Rawat
,
D. B.
, and
Nandi
,
S.
,
2020
, “
An Efficient Blockchain-Based Approach for Cooperative Decision Making in Swarm Robotics
,”
Internet Technol. Lett.
,
3
(
1
), p.
e140
.
18.
“Oracle Autonomous Blockchain Cloud Service.” https://www.oracle.com/a/ocom/docs/blockchain-cloud-service-data-sheet.pdf, Accessed March 4, 2023.
19.
“Blockchain Secure Cloud: A New Generation Integrated Cloud and Blockchain Platforms—General Concepts and Challenges.” https://www.awilczynski.me/wp-content/uploads/2018/09/ECJvol4issue2.pdf, Accessed March 4, 2023.
20.
Al-Jaroodi
,
J.
, and
Mohamed
,
N.
,
2019
, “
Blockchain in Industries: A Survey
,”
IEEE Access
,
7
, pp.
36500
36515
.
21.
Hägele
,
M.
,
Nilsson
,
K.
,
Pires
,
J. N.
, and
Bischoff
,
R.
,
2016
, “
Industrial Robotics
,” Springer Handbook of Robotics,
B.
Siciliano
, ed.,
Springer
, pp.
1385
1422
.
22.
Dorigo
,
M.
,
Birattari
,
M.
, and
Brambilla
,
M.
,
2014
, “
Swarm Robotics
,”
Scholarpedia
,
9
(
1
), p.
1463
.
23.
Brambilla
,
M.
,
Ferrante
,
E.
,
Birattari
,
M.
, and
Dorigo
,
M.
,
2013
, “
Swarm Robotics: A Review From the Swarm Engineering Perspective
,”
Swarm Intell.
,
7
(
1
), pp.
1
41
.
24.
Alladi
,
T.
,
Chamola
,
V.
,
Sahu
,
N.
, and
Guizani
,
M.
,
2020
, “
Applications of Blockchain in Unmanned Aerial Vehicles: A Review
,”
Veh. Commun.
,
23
, p.
100249
.
25.
Mehta
,
P.
,
Gupta
,
R.
, and
Tanwar
,
S.
,
2020
, “
Blockchain Envisioned UAV Networks: Challenges, Solutions, and Comparisons
,”
Comput. Commun.
,
151
, pp.
518
538
.
26.
Howe
,
R. D.
, and
Matsuoka
,
Y.
,
1999
, “
Robotics for Surgery
,”
Annu. Rev. Biomed. Eng.
,
1
(
1
), pp.
211
240
.
27.
Davies
,
B.
,
2000
, “
A Review of Robotics in Surgery
,”
Proc. Inst. Mech. Eng. Part H: J. Eng. Med.
,
214
(
1
), pp.
129
140
.
28.
Falcone
,
S.
,
Zhang
,
J.
,
Cameron
,
A.
, and
Abdel-Rahman
,
A.
,
2019
,
Blockchain Design for an Embedded System
,
Ledger
.
29.
Castelló Ferrer
,
E.
,
2019
, “
The Blockchain: A New Framework for Robotic Swarm Systems
,”
Proceedings of the Future Technologies Conference (FTC)
,
Vancouver, Canada
,
Nov. 15–16, 2018
,
K.
Arai
,
R.
Bhatia
, and
S.
Kapoor
, eds., Springer International Publishing, pp.
1037
1058
.
30.
Strobel
,
V.
,
Castelló Ferrer
,
E.
, and
Dorigo
,
M.
,
2020
, “
Blockchain Technology Secures Robot Swarms: A Comparison of Consensus Protocols and Their Resilience to Byzantine Robots
,”
Front. Rob. AI
,
7
, p.
54
.
31.
Strobel
,
V.
,
Ferrer
,
E. C.
, and
Dorigo
,
M.
,
2018
, “
Managing Byzantine Robots Via Blockchain Technology in a Swarm Robotics Collective Decision Making Scenario
,”
Proceedings of 17th International Conference Autonomous Agents and MultiAgent Systems
,
Stockholm, Sweden
,
July 10–15
, pp.
541
549
.
32.
Mokhtar
,
A.
,
Murphy
,
N.
, and
Bruton
,
J.
,
2019
, “
Blockchain-Based Multi-robot Path Planning
,”
2019 IEEE 5th World Forum on Internet of Things (WF-IoT)
,
Limerick, Ireland
,
Apr. 15–18
, IEEE, pp.
584
589
.
33.
Guo
,
S.
,
Cao
,
S.
,
Guo
,
J.
, and
Xu
,
J.
,
2020
, “
Study on Distributed Data Processing System for Decentralized Spherical Multi-robot Based on Edge Computing and Blockchain
,”
2020 IEEE International Conference on Mechatronics and Automation (ICMA), IEEE
,
Beijing, China
,
Oct. 13–16
, IEEE, pp.
1852
1857
.
34.
Queralta
,
J. P.
, and
Westerlund
,
T.
,
2019
, “Blockchain-Powered Collaboration in Heterogeneous Swarms of Robots,” preprint arXiv:1912.01711.
35.
Basegio
,
T. L.
,
Michelin
,
R. A.
,
Zorzo
,
A. F.
, and
Bordini
,
R. H.
,
2017
, “
A Decentralised Approach to Task Allocation Using Blockchain
,”
International Workshop on Engineering Multi-agent Systems, Springer
,
Sao Paulo, Brazil
,
May 8–9
, Springer, pp.
75
91
.
36.
Kapitonov
,
A.
,
Lonshakov
,
S.
,
Krupenkin
,
A.
, and
Berman
,
I.
,
2017
, “
Blockchain-Based Protocol of Autonomous Business Activity for Multi-agent Systems Consisting of UAVS
,”
” 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS)
,
Cranfield, UK
,
Nov. 25–27
, IEEE, pp.
84
89
.
37.
Ge
,
C.
,
Ma
,
X.
, and
Liu
,
Z.
,
2020
, “
A Semi-Autonomous Distributed Blockchain-Based Framework for UAVs System
,”
J. Syst. Arch.
,
107
, p.
101728
.
38.
Lopes
,
V.
,
Pereira
,
N.
, and
Alexandre
,
L. A.
,
2019
, “
Robot Workspace Monitoring Using a Blockchain-Based 3d Vision Approach
,”
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops
,
Long Beach, CA
,
June 16–20
.
39.
Li
,
J.
,
Wu
,
J.
,
Li
,
J.
,
Bashir
,
A. K.
,
Piran
,
M. J.
, and
Anjum
,
A.
,
2021
, “
Blockchain-Based Trust Edge Knowledge Inference of Multi-robot Systems for Collaborative Tasks
,”
IEEE Commun. Mag.
,
59
(
7
), pp.
94
100
.
40.
Nishida
,
Y.
,
Kaneko
,
K.
,
Sharma
,
S.
, and
Sakurai
,
K.
,
2018
, “
Suppressing Chain Size of Blockchain-Based Information Sharing for Swarm Robotic Systems
,”
2018 Sixth International Symposium on Computing and Networking Workshops (CANDARW)
,
Takayama, Japan
,
Nov. 27–30
, IEEE, pp.
524
528
.
41.
Nguyen
,
T. T.
,
Hatua
,
A.
, and
Sung
,
A. H.
,
2019
, “
Blockchain Approach to Solve Collective Decision Making Problems for Swarm Robotics
,”
International Congress on Blockchain and Applications, Springer
,
Ávila, Spain
,
June 26–28
, Springer, pp.
118
125
.
42.
Karthik
,
S.
,
Chandhar
,
N. P.
,
Akil
,
M.
,
Chander
,
S.
,
Amogh
,
J.
, and
Aditya
,
R.
,
2020
, “
Bee-bots: A Blockchain Based Decentralised Swarm Robotic System
,”
2020 6th International Conference on Control, Automation and Robotics (ICCAR)
,
Singapore (Virtual Conference)
,
Apr. 20–23
, pp.
145
150
.
43.
Pacheco
,
A.
,
Strobel
,
V.
, and
Dorigo
,
M.
,
2020
, “A Framework for Swarm Robotics Experimentation With Pi-Puck Robots and an Ethereum-Based Blockchain,” Tech. Rep., TR/IRIDIA/2020-001, IRIDIA, Université Libre de Bruxelles.
44.
Xiao
,
Y.
,
Zhang
,
N.
,
Lou
,
W.
, and
Hou
,
Y. T.
,
2020
, “
A Survey of Distributed Consensus Protocols for Blockchain Networks
,”
IEEE Commun. Surv. Tutorials
,
22
(
2
), pp.
1432
1465
.
45.
Cebe
,
M.
,
Erdin
,
E.
,
Akkaya
,
K.
,
Aksu
,
H.
, and
Uluagac
,
S.
,
2018
, “
Block4forensic: An Integrated Lightweight Blockchain Framework for Forensics Applications of Connected Vehicles
,”
IEEE Commun. Mag.
,
56
(
10
), pp.
50
57
.
46.
Bjørner
,
D.
, and
Havelund
,
K.
,
2014
, “
40 Years of Formal Methods
,” FM 2014: Formal Methods,
C.
Jones
,
P.
Pihlajasaari
, and
J.
Sun
, eds.,
Springer International Publishing
,
Singapore
, pp.
42
61
.
47.
Douceur
,
J. R.
,
2002
, “
The Sybil Attack
,”
International Workshop on Peer-to-Peer Systems
,
Mar. 7–8
, Springer, Berlin/Heidelberg, pp.
251
260
.
48.
Mirkovic
,
J.
, and
Reiher
,
P.
,
2004
, “
A Taxonomy of DDoS Attack and Ddos Defense Mechanisms
,”
ACM SIGCOMM Comput. Commun. Rev.
,
34
(
2
), pp.
39
53
.
49.
Kholidy
,
H. A.
,
Baiardi
,
F.
, and
Hariri
,
S.
,
2014
, “
Ddsga: A Data-Driven Semi-global Alignment Approach for Detecting Masquerade Attacks
,”
IEEE Trans. Dependable Secure Comput.
,
12
(
2
), pp.
164
178
.
50.
Androulaki
,
E.
,
Barger
,
A.
,
Bortnikov
,
V.
,
Cachin
,
C.
,
Christidis
,
K.
,
De Caro
,
A.
,
Enyeart
,
D.
,
Ferris
,
C.
,
Laventman
,
G.
,
Manevich
,
Y.
, and
Muralidharan
,
S.
,
2018
, “
Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains
,”
Proceedings of the Thirteenth EuroSys Conference
,
Porto Portugal
,
Apr. 23–26
, pp.
1
15
.
51.
Al-shareeda
,
M. A.
,
Anbar
,
M.
,
Manickam
,
S.
, and
Hasbullah
,
I. H.
,
2020
, “
Review of Prevention Schemes for Modification Attack in Vehicular Ad Hoc Networks
,”
Int. J. Eng. Manage. Res.
,
10
(
3
), pp.
149
152
.
52.
Holkar
,
A. M.
,
Holkar
,
N. S.
, and
Nitnawwre
,
D.
,
2013
, “
Investigative Analysis of Repudiation Attack on Manet With Different Routing Protocols
,”
Int. J. Emerg. Trends Technol. Comput. Sci.
,
2
(
3
).
53.
Chen
,
Y.
,
Trappe
,
W.
, and
Martin
,
R. P.
,
2007
, “
Detecting and Localizing Wireless Spoofing Attacks
,”
” 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks
,
San Diego, CA
,
June 18–21
, IEEE, pp.
193
202
.
54.
Choi
,
H.
,
Lee
,
W.-C.
,
Aafer
,
Y.
,
Fei
,
F.
,
Tu
,
Z.
,
Zhang
,
X.
,
Xu
,
D.
, and
Deng
,
X.
,
2018
, “
Detecting Attacks Against Robotic Vehicles: A Control Invariant Approach
,”
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security
,
Toronto, Canada
,
Oct. 15–19
, pp.
801
816
.
55.
Hamieh
,
A.
,
Ben-Othman
,
J.
, and
Mokdad
,
L.
,
2009
, “
Detection of Radio Interference Attacks in Vanet
,”
In GLOBECOM 2009-2009 IEEE Global Telecommunications Conference
,
Honolulu, HI
,
Nov. 3–Dec. 4
, IEEE, pp.
1
5
.
56.
Mpitziopoulos
,
A.
,
Gavalas
,
D.
,
Konstantopoulos
,
C.
, and
Pantziou
,
G.
,
2009
, “
A Survey on Jamming Attacks and Countermeasures in WSNs
,”
IEEE Commun. Surv. Tutorials
,
11
(
4
), pp.
42
56
.
57.
Rudd
,
E. M.
,
Rozsa
,
A.
,
Günther
,
M.
, and
Boult
,
T. E.
,
2016
, “
A Survey of Stealth Malware Attacks, Mitigation Measures, and Steps Toward Autonomous Open World Solutions
,”
IEEE Commun. Surv. Tutorials
,
19
(
2
), pp.
1145
1172
.
58.
Kwon
,
C.
,
Liu
,
W.
, and
Hwang
,
I.
,
2013
, “
Security Analysis for Cyber-Physical Systems Against Stealthy Deception Attacks
,”
2013 American Control Conference
,
Washington, DC
,
June 17–19
, IEEE, pp.
3344
3349
.
59.
Shokri
,
R.
,
Theodorakopoulos
,
G.
,
Troncoso
,
C.
,
Hubaux
,
J.-P.
, and
Le Boudec
,
J.-Y.
,
2012
, “
Protecting Location Privacy: Optimal Strategy Against Localization Attacks
,”
Proceedings of the 2012 ACM Conference on Computer and Communications Security
,
Raleigh, NC
,
Oct. 16–18
, pp.
617
627
.
60.
Hei
,
X.
,
Du
,
X.
,
Hei
,
X.
, and
Du
,
X.
,
2013
, “The Resource Depletion Attack and Defense Scheme,”
Security for Wireless Implantable Medical Devices
,
Springer
,
New York
, pp.
9
18
.
61.
Lin
,
I.-C.
, and
Liao
,
T.-C.
,
2017
, “
A Survey of Blockchain Security Issues and Challenges.
,”
Int. J. Netw. Secur.
,
19
(
5
), pp.
653
659
.
62.
Kumar
,
N. M.
, and
Mallick
,
P. K.
,
2018
, “
Blockchain Technology for Security Issues and Challenges in IoT
,”
Procedia Comput. Sci.
,
132
, pp.
1815
1823
.
63.
Sengupta
,
J.
,
Ruj
,
S.
, and
Bit
,
S. D.
,
2020
, “
A Comprehensive Survey on Attacks, Security Issues and Blockchain Solutions for IoT and IIoT
,”
J. Netw. Comput. Appl.
,
149
, p.
102481
.
64.
Ferdous
,
M. S.
,
Chowdhury
,
M. J. M.
,
Hoque
,
M. A.
, and
Colman
,
A.
,
2020
, “Blockchain Consensus Algorithms: A Survey,” preprint arXiv:2001.07091.
65.
Nguyen
,
G.-T.
, and
Kim
,
K.
,
2018
, “
A Survey About Consensus Algorithms Used in Blockchain
,”
J. Inf. Process. Syst.
,
14
(
1
), pp.
101
128
.
66.
Bamakan
,
S. M. H.
,
Motavali
,
A.
, and
Bondarti
,
A. B.
,
2020
, “
A Survey of Blockchain Consensus Algorithms Performance Evaluation Criteria
,”
Exp. Syst. Appl.
,
154
, p.
113385
.
67.
Bentov
,
I.
,
Lee
,
C.
,
Mizrahi
,
A.
, and
Rosenfeld
,
M.
,
2014
, “
Proof of Activity: Extending Bitcoin’s Proof of Work Via Proof of Stake [Extended Abstract] Y
,”
ACM SIGMETRICS Perform. Eval. Rev.
,
42
(
3
), pp.
34
37
.
68.
Mythili
,
R.
, and
Venkataraman
,
R.
,
2021
, “Proof of Policy (PoP): A New Attribute-Based Blockchain Consensus Protocol,”
Computational Methods and Data Engineering
,
V.
Singh
,
V. K.
Asari
,
S.
Kumar
, and
R. B.
Patel
, eds.,
Springer
,
New Delhi, India
, pp.
451
464
.
69.
Castro
,
M.
, and
Liskov
,
B.
,
1999
, “
Practical Byzantine Fault Tolerance
,” OsDI, Vol. 99, pp.
173
186
.
70.
‘sawtooth lake,’ Intel Corporation. https://github.com/hyperledger/sawtooth-core, Accessed March 4, 2023.
71.
Snider
,
M.
,
Samani
,
K.
, and
Jain
,
T.
,
2018
, “Delegated Proof of Stake: Features & Tradeoffs,” Multicoin Cap, 19.
72.
Miller
,
A.
,
Juels
,
A.
,
Shi
,
E.
,
Parno
,
B.
, and
Katz
,
J.
,
2014
, “
Permacoin: Repurposing Bitcoin Work for Data Preservation
,”
2014 IEEE Symposium on Security and Privacy
,
San Jose, CA
,
May 18–21
, IEEE, pp.
475
490
.
73.
De Angelis
,
S.
,
2018
, “Assessing Security and Performances of Consensus Algorithms for Permissioned Blockchains,” preprint arXiv:1805.03490.
74.
Buchman
,
E.
,
2016
, “Tendermint: Byzantine Fault Tolerance in the Age of Blockchains,” PhD thesis,
University of Guelph, Guelph, Canada
.
75.
Schwartz
,
D.
,
Youngs
,
N.
, and
Britto
,
A.
,
2014
, “
The Ripple Protocol Consensus Algorithm
,”
Ripple Labs Inc White Paper
,
5
(
8
), p.
151
.
76.
Klaokliang
,
N.
,
Teawtim
,
P.
,
Aimtongkham
,
P.
,
So-In
,
C.
, and
Niruntasukrat
,
A.
,
2018
, “
A Novel IoT Authorization Architecture on Hyperledger Fabric With Optimal Consensus Using Genetic Algorithm
,”
2018 Seventh ICT International Student Project Conference (ICT-ISPC)
,
Nakhon Pathom, Thailand
,
Nov. 11–13
, IEEE, pp.
1
5
.
77.
Xie
,
J.
,
Yu
,
F. R.
,
Huang
,
T.
,
Xie
,
R.
,
Liu
,
J.
, and
Liu
,
Y.
,
2019
, “
A Survey on the Scalability of Blockchain Systems
,”
IEEE Netw.
,
33
(
5
), pp.
166
173
.
78.
Salimitari
,
M.
,
Chatterjee
,
M.
, and
Fallah
,
Y. P.
,
2020
, “
A Survey on Consensus Methods in Blockchain for Resource-Constrained IoT Networks
,”
Internet Things
,
11
, p.
100212
.
79.
Belchior
,
R.
,
Vasconcelos
,
A.
,
Guerreiro
,
S.
, and
Correia
,
M.
,
2021
, “
A Survey on Blockchain Interoperability: Past, Present, and Future Trends
,”
ACM Comput. Surv.
,
54
(
8
), pp.
1
41
.
80.
Sun
,
Z.
,
Zhang
,
X.
,
Xiang
,
F.
, and
Chen
,
L.
,
2021
, “
Survey of Storage Scalability on Blockchain
,”
J. Softw.
,
32
(
1
), pp.
1
20
.
81.
Zou
,
J.
,
He
,
D.
,
Zeadally
,
S.
,
Kumar
,
N.
,
Wang
,
H.
, and
Choo
,
K. R.
,
2021
, “
Integrated Blockchain and Cloud Computing Systems: A Systematic Survey, Solutions, and Challenges
,”
ACM Comput. Surv.
,
54
(
8
), pp.
1
36
.
82.
Ong
,
H. Y.
,
Chavez
,
K.
, and
Hong
,
A.
,
2015
, “Distributed Deep Q-Learning,” preprint arXiv:1508.04186.
83.
Weng
,
J.
,
Weng
,
J.
,
Zhang
,
J.
,
Li
,
M.
,
Zhang
,
Y.
, and
Luo
,
W.
,
2019
, “
Deepchain: Auditable and Privacy-Preserving Deep Learning With Blockchain-Based Incentive
,”
IEEE Trans. Dependable Secure Comput.
,
18
(
5
), pp.
2438
2455
.
84.
Quigley
,
M.
,
Conley
,
K.
,
Gerkey
,
B.
,
Faust
,
J.
,
Foote
,
T.
,
Leibs
,
J.
,
Wheeler
,
R.
, and
Ng
,
A. Y.
,
2009
, “
Ros: An Open-Source Robot Operating System
,”
ICRA Workshop on Open Source Software, Vol. 3
,
Kobe, Japan
,
May 12
, p.
5
.
85.
Kapitonov
,
A.
,
Berman
,
I.
,
Bulatov
,
V.
,
Lonshakov
,
S.
, and
Krupenkin
,
A.
,
2018
, “
Robonomics Based on Blockchain as a Principle of Creating Smart Factories
,”
2018 Fifth International Conference on Internet of Things: Systems, Management and Security
,
Valencia, Spain
,
Oct. 15–18
, pp.
78
85
.
86.
Avellaneda
,
O.
,
Bachmann
,
A.
,
Barbir
,
A.
,
Brenan
,
J.
,
Dingle
,
P.
,
Duffy
,
K. H.
,
Maler
,
E.
,
Reed
,
D.
, and
Sporny
,
M.
,
2019
, “
Decentralized Identity: Where Did It Come From and Where Is It Going?
,”
IEEE Commun. Standards Mag.
,
3
(
4
), pp.
10
13
.
You do not currently have access to this content.