Fast computation by population protocols with a leader
Fast algorithms are presented for performing computations in a probabilistic population model. This is a variant of the standard population protocol model, in which finite-state agents interact in pairs under the control of an adversary scheduler, where all pairs are equally likely to be chosen for...
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| Vydané v: | Distributed computing Ročník 21; číslo 3; s. 183 - 199 |
|---|---|
| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Berlin/Heidelberg
Springer-Verlag
01.09.2008
Springer Nature B.V |
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| ISSN: | 0178-2770, 1432-0452 |
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| Abstract | Fast algorithms are presented for performing computations in a probabilistic population model. This is a variant of the standard population protocol model, in which finite-state agents interact in pairs under the control of an adversary scheduler, where all pairs are equally likely to be chosen for each interaction. It is shown that when a unique leader agent is provided in the initial population, the population can simulate a virtual register machine with high probability in which standard arithmetic operations like comparison, addition, subtraction, and multiplication and division by constants can be simulated in
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(
n
log
5
n
) interactions using a simple register representation or in
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(
n
log
2
n
) interactions using a more sophisticated representation that requires an extra
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(
n
log
O
(1)
n
)-interaction initialization step. The central method is the extensive use of epidemics to propagate information from and to the leader, combined with an epidemic-based phase clock used to detect when these epidemics are likely to be complete. Applications include a reduction of the cost of computing a semilinear predicate to
O
(
n
log
5
n
) interactions from the previously best-known bound of
O
(
n
2
log
n
) interactions and simulation of a LOGSPACE Turing machine using
O
(
n
log
2
n
) interactions per step after an initial
O
(
n
log
O
(1)
n
)-interaction startup phase. These bounds on interactions translate into polylogarithmic time per step in a natural parallel model in which each agent participates in an expected
Θ
(1) interactions per time unit. Open problems are discussed, together with simulation results that suggest the possibility of removing the initial-leader assumption. |
|---|---|
| AbstractList | Fast algorithms are presented for performing computations in a probabilistic population model. This is a variant of the standard population protocol model, in which finite-state agents interact in pairs under the control of an adversary scheduler, where all pairs are equally likely to be chosen for each interaction. It is shown that when a unique leader agent is provided in the initial population, the population can simulate a virtual register machine with high probability in which standard arithmetic operations like comparison, addition, subtraction, and multiplication and division by constants can be simulated in O(n log5 n) interactions using a simple register representation or in O(n log2 n) interactions using a more sophisticated representation that requires an extra O(n log O(1) n)-interaction initialization step. The central method is the extensive use of epidemics to propagate information from and to the leader, combined with an epidemic-based phase clock used to detect when these epidemics are likely to be complete. Applications include a reduction of the cost of computing a semilinear predicate to O(n log5 n) interactions from the previously best-known bound of O(n 2 log n) interactions and simulation of a LOGSPACE Turing machine using O(n log2 n) interactions per step after an initial O(n log O(1) n)-interaction startup phase. These bounds on interactions translate into polylogarithmic time per step in a natural parallel model in which each agent participates in an expected Θ(1) interactions per time unit. Open problems are discussed, together with simulation results that suggest the possibility of removing the initial-leader assumption. [PUBLICATION ABSTRACT] Fast algorithms are presented for performing computations in a probabilistic population model. This is a variant of the standard population protocol model, in which finite-state agents interact in pairs under the control of an adversary scheduler, where all pairs are equally likely to be chosen for each interaction. It is shown that when a unique leader agent is provided in the initial population, the population can simulate a virtual register machine with high probability in which standard arithmetic operations like comparison, addition, subtraction, and multiplication and division by constants can be simulated in O ( n log 5 n ) interactions using a simple register representation or in O ( n log 2 n ) interactions using a more sophisticated representation that requires an extra O ( n log O (1) n )-interaction initialization step. The central method is the extensive use of epidemics to propagate information from and to the leader, combined with an epidemic-based phase clock used to detect when these epidemics are likely to be complete. Applications include a reduction of the cost of computing a semilinear predicate to O ( n log 5 n ) interactions from the previously best-known bound of O ( n 2 log n ) interactions and simulation of a LOGSPACE Turing machine using O ( n log 2 n ) interactions per step after an initial O ( n log O (1) n )-interaction startup phase. These bounds on interactions translate into polylogarithmic time per step in a natural parallel model in which each agent participates in an expected Θ (1) interactions per time unit. Open problems are discussed, together with simulation results that suggest the possibility of removing the initial-leader assumption. Fast algorithms are presented for performing computations in a probabilistic population model. This is a variant of the standard population protocol model, in which finite-state agents interact in pairs under the control of an adversary scheduler, where all pairs are equally likely to be chosen for each interaction. It is shown that when a unique leader agent is provided in the initial population, the population can simulate a virtual register machine with high probability in which standard arithmetic operations like comparison, addition, subtraction, and multiplication and division by constants can be simulated in O(n log5 n) interactions using a simple register representation or in O(n log2 n) interactions using a more sophisticated representation that requires an extra O(n log O(1) n)-interaction initialization step. The central method is the extensive use of epidemics to propagate information from and to the leader, combined with an epidemic-based phase clock used to detect when these epidemics are likely to be complete. Applications include a reduction of the cost of computing a semilinear predicate to O(n log5 n) interactions from the previously best-known bound of O(n 2 log n) interactions and simulation of a LOGSPACE Turing machine using O(n log2 n) interactions per step after an initial O(n log O(1) n)-interaction startup phase. These bounds on interactions translate into polylogarithmic time per step in a natural parallel model in which each agent participates in an expected (1) interactions per time unit. Open problems are discussed, together with simulation results that suggest the possibility of removing the initial-leader assumption. [PUBLICATION ABSTRACT] |
| Author | Aspnes, James Angluin, Dana Eisenstat, David |
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| Keywords | Parallel Time Infected Node Turing Machine Leader Election Phase Clock |
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A199218840442510.1016/0378-4371(92)90283-V Daliot, A., Dolev, D., Parnas, H.: Self-stabilizing pulse synchronization inspired by biological pacemaker networks. In: Huang, S.-T., Herman, T. (eds.) Self-Stabilizing Systems, vol. 2704 of Lecture Notes in Computer Science, pp. 32–48. Springer (2003) Guerraoui, R., Ruppert, E.: Even small birds are unique: Population protocols with identifiers. Technical Report CSE-2007-04, Department of Computer Science and Engineering, York University, (2007) Angluin, D., Aspnes, J., Eisenstat, D., Ruppert, E.: On the power of anonymous one-way communication. In: Ninth International Conference on Principles of Distributed Systems, pp. 307–318, December 2005 Angluin, D., Fischer, M.J., Jiang, H.: Stabilizing consensus in mobile networks. In: Proceedings of the Second IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS ’06), pp. 37–50 (2006) Angluin, D., Aspnes, J., Fischer, M.J., Jiang, H.: Self-stabilizing population protocols. In: Ninth International Conference on Principles of Distributed Systems, pp. 79–90, December 2005 BirmanK.P.HaydenM.OzkasapO.XiaoZ.BudiuM.MinskyY.Bimodal multicastACM Trans. Comput. Syst.1999172418810.1145/312203.312207 DolevS.WelchJ.L.Self-stabilizing clock synchronization in the presence of Byzantine faultsJ. ACM200451578079910.1145/1017460.10174632147706 Angluin, D., Aspnes, J., Chan, M., Fischer, M.J., Jiang, H., Peralta, R.: Stably computable properties of network graphs. In: Prasanna, V.K., Iyengar, S., Spirakis, P., Welsh, M. (eds.) Distributed Computing in Sensor Systems: First IEEE International Conference, DCOSS 2005, Marina del Rey, CA, USA, June/July, 2005, Proceedings, vol. 3560 of Lecture Notes in Computer Science, pp. 63–74. 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