Abstract We study a single class of traf?c acting on a symmetric set of processorsharing queues with ?nite buffers, and we consider the case where the load scales with the number of servers. We address the problem of giving robust performance bounds based on the study of the asymptotic behaviour of the insensitive load balancing schemes, which have the desirable property that the stationary distribution of the resulting stochastic network depends on the distribution of job-sizes only through its mean.Itwasshownforsmallsystemswithlossesthattheygivegoodestimatesofperformanceindicators,generalizinghenceforthErlangformula,whereasoptimalpolicies are already theoretically and computationally out of reach for networks of moderate size. We characte...
In this paper, we present a bounding methodology that allows to com-pute a tight lower bound on the ...
Abstract: In large-scale distributed systems, balancing the load in an efficient way is crucial in o...
112 pagesThis thesis explores the BAR approach applied on various of stochastic processing networks....
We study a single class of traffic acting on a symmetric set of processor-sharing queues with finite...
International audienceLoad balancing with various types of load information has become a key compone...
International audienceLoad balancing with various types of load information has become a key compone...
It is well known that simple randomized load balancing schemes can balance load effectively while in...
A simple local randomized protocol was presented and its performance on a general n-node network was...
In this paper, we present a bounding methodology that allows to compute a tight lower bound on the c...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
We study the long term (steady state) performance of a simple, randomized, local load balancing tech...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
We study the long-term (steady state) performance of a simple, randomized, local load balancing tech...
In this paper, we present a bounding methodology that allows to com-pute a tight lower bound on the ...
Abstract: In large-scale distributed systems, balancing the load in an efficient way is crucial in o...
112 pagesThis thesis explores the BAR approach applied on various of stochastic processing networks....
We study a single class of traffic acting on a symmetric set of processor-sharing queues with finite...
International audienceLoad balancing with various types of load information has become a key compone...
International audienceLoad balancing with various types of load information has become a key compone...
It is well known that simple randomized load balancing schemes can balance load effectively while in...
A simple local randomized protocol was presented and its performance on a general n-node network was...
In this paper, we present a bounding methodology that allows to compute a tight lower bound on the c...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
We study the long term (steady state) performance of a simple, randomized, local load balancing tech...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
We study the long-term (steady state) performance of a simple, randomized, local load balancing tech...
In this paper, we present a bounding methodology that allows to com-pute a tight lower bound on the ...
Abstract: In large-scale distributed systems, balancing the load in an efficient way is crucial in o...
112 pagesThis thesis explores the BAR approach applied on various of stochastic processing networks....