Geodesic
Game-theoretic model of a volunteer computing grid
Matematičeskaâ teoriâ igr i eë priloženiâ, Tome 10 (2018) no. 3, pp. 76-90.

Voir la notice de l'article provenant de la source Math-Net.Ru

In the paper we propose a simple game-theoretic model of a Desktop Grid for volunteer computing. Task replication reduces the risk of accepting wrong answers due to sabotage. Saboteur's attack by intruding multiple computing nodes brings him some profit in case a wrong answer is accepted, while the server suffers some penalty in this case. Nodes are assigned some reputation as a monotone function of the number of produced correct (or not exposed) answers. We obtain the optimal mixed strategies and show that the average gain of the players depends only on the server's penalty, nodes' reputation, and the size of the subgrid of nodes with the same reputation. Also we estimate the server's cost per an answer. Numerical examples show that the average cost of the server is not more than that in the case when the number of intruders is known.
Keywords: volunteer computing, desktop grid, sabotage-tolerance, reputation. 
@article{MGTA_2018_10_3_a3,
     author = {Ilya A. Chernov},
     title = {Game-theoretic model of a volunteer computing grid},
     journal = {Matemati\v{c}eska\^a teori\^a igr i e\"e prilo\v{z}eni\^a},
     pages = {76--90},
     publisher = {mathdoc},
     volume = {10},
     number = {3},
     year = {2018},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MGTA_2018_10_3_a3/}
}
TY  - JOUR
AU  - Ilya A. Chernov
TI  - Game-theoretic model of a volunteer computing grid
JO  - Matematičeskaâ teoriâ igr i eë priloženiâ
PY  - 2018
SP  - 76
EP  - 90
VL  - 10
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/MGTA_2018_10_3_a3/
LA  - ru
ID  - MGTA_2018_10_3_a3
ER  - 
%0 Journal Article
%A Ilya A. Chernov
%T Game-theoretic model of a volunteer computing grid
%J Matematičeskaâ teoriâ igr i eë priloženiâ
%D 2018
%P 76-90
%V 10
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/MGTA_2018_10_3_a3/
%G ru
%F MGTA_2018_10_3_a3
Ilya A. Chernov. Game-theoretic model of a volunteer computing grid. Matematičeskaâ teoriâ igr i eë priloženiâ, Tome 10 (2018) no. 3, pp. 76-90. http://geodesic.mathdoc.fr/item/MGTA_2018_10_3_a3/

[1] Ivashko E. E., Nikitina N. N., Möller S., “Vysokoproizvoditelnyi virtualnyi skrining v Enterprise Desktop Grid na baze BOINC”, Trudy Mezhdunarodnoi superkompyuternoi konferentsii «Nauchnyi servis v seti Internet», 2015, 58–60

[2] Sarmenta L. F. G., “Sabotage-tolerance mechanisms for volunteer computing systems”, Future Generation Computer Systems, 18 (2002), 561–572 | DOI | Zbl

[3] Khan M. K., Mahmood T., Hyder S. I., “Scheduling in Desktop Grid Systems: Theoretical Evaluation of Policies and Frameworks”, International Journal of Advanced Computer Science and Applications, 8:1 (2017), 119–127

[4] Wang Y., Wei J., Ren Sh., Shen Yu., “Toward integrity assurance of outsourced computing a game theoretic perspective”, Future Generation Computer Systems, 55 (2016), 87–100 | DOI

[5] Anta A. F., Georgiou Ch., Mosteiro M. A., Pareja D., “Multi-round Master-Worker Computing: A Repeated Game Approach”, IEEE 35th Symposium on Reliable Distributed Systems, 2016, 31–40

[6] Anta A. F., Georgiou C., Mosteiro M. A., Pareja D., “Algorithmic Mechanisms for Reliable Crowdsourcing Computation under Collusion”, PLoS ONE, 10:3 (2015), e0116520 | DOI

[7] Christoforou E., Anta A. F., Georgiou Ch., Mosteiro M. A., Sánchez A., “Reputation-based mechanisms for evolutionary master-worker computing”, Principles of Distributed Systems, Lecture Notes in Computer Science, 8304, 2013, 98–113 | DOI | MR

[8] Mazalov V. V., Nikitina N. N., Ivashko E. E., “Hierarchical Two-Level Game Model for Tasks Scheduling in a Desktop Grid”, Applied Problems in Theory of Probabilities and Mathematical Statistics Related to Modeling of Information Systems, 2014, 641–645

[9] Nikitina N. N., Ivashko E. E., Tchernykh A., “Congestion Game Scheduling for Virtual Drug Screening Optimization”, Journal of Computer-Aided Molecular Design, 32:2 (2018), 363–374 | DOI