TY - JOUR

T1 - Computing the Fault Tolerant Capability of Multiagent Deployment⋆

AU - Zhang, Yingqian

AU - Manisterski, Efrat

AU - Kraus, Sarit

AU - Subrahmanian, V.S.

AU - Peleg, D.

PY - 2008

Y1 - 2008

N2 - A deployment of a multiagent system on a network refers to the placement of one
or more copies of each agent on network hosts, in such a manner that the memory
constraints of each node are satisfied. Finding the deployment that is most likely to
tolerate faults (i.e. have at least one copy of each agent functioning and in communication
with other agents) is a challenge. In this paper, we address the problem of
finding the probability of survival of a deployment (i.e. the probability that a deployment
will tolerate faults), under the assumption that node failures are independent.
We show that the problem of computing the survival probability of a deployment is
at least NP-hard. Moreover, it is hard to approximate. We produce two algorithms
to accurately compute the probability of survival of a deployment—these algorithms
are expectedly exponential. We also produce five heuristic algorithms to estimate
survival probabilities—these algorithms work in acceptable time frames. We report
on a detailed set of experiments to determine the conditions under which some of
these algorithms perform better than the others.

AB - A deployment of a multiagent system on a network refers to the placement of one
or more copies of each agent on network hosts, in such a manner that the memory
constraints of each node are satisfied. Finding the deployment that is most likely to
tolerate faults (i.e. have at least one copy of each agent functioning and in communication
with other agents) is a challenge. In this paper, we address the problem of
finding the probability of survival of a deployment (i.e. the probability that a deployment
will tolerate faults), under the assumption that node failures are independent.
We show that the problem of computing the survival probability of a deployment is
at least NP-hard. Moreover, it is hard to approximate. We produce two algorithms
to accurately compute the probability of survival of a deployment—these algorithms
are expectedly exponential. We also produce five heuristic algorithms to estimate
survival probabilities—these algorithms work in acceptable time frames. We report
on a detailed set of experiments to determine the conditions under which some of
these algorithms perform better than the others.

UR - https://scholar.google.co.il/scholar?q=%09%09Computing+the+Fault+Tolerant+Capability+of+Multiagent+Deployment&btnG=&hl=en&as_sdt=0%2C5

M3 - Article

SP - 1

EP - 53

JO - Preprint submitted to Elsevier

JF - Preprint submitted to Elsevier

ER -