We study a single class of traffic acting on a symmetric set of processor-sharing queues with finite 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. It was shown for small systems with losses that they give good estimates of performance indicators, generalizing henceforth Erlang formula, whereas optimal policies are already theoretically and computationally out of reach for networks of moderate ...
This paper studies the heavy-traffic joint distribution of queue lengths in two stochastic processin...
We consider the model of a token-based joint auto-scaling and load balancing strategy, proposed in a...
Abstract: In large-scale distributed systems, balancing the load in an efficient way is crucial in o...
International audienceLoad balancing with various types of load information has become a key compone...
Abstract We study a single class of traf?c acting on a symmetric set of processorsharing queues with...
In this paper, we present a bounding methodology that allows to compute a tight lower bound on the c...
112 pagesThis thesis explores the BAR approach applied on various of stochastic processing networks....
Randomized load balancing is a cost efficient policy for job scheduling in parallel server queueing ...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
Randomized load balancing is a cost efficient policy for job scheduling in parallel server queueing ...
We present an overview of scalable load balancing algorithms which provide favorable delay performan...
It is well known that simple randomized load balancing schemes can balance load effectively while in...
this paper, we propose a new technique for estimating the performance of queueing networks with buff...
In this paper, we present a bounding methodology that allows to com-pute a tight lower bound on the ...
We consider a system of N identical server pools and a single dispatcher in which tasks with unit-ex...
This paper studies the heavy-traffic joint distribution of queue lengths in two stochastic processin...
We consider the model of a token-based joint auto-scaling and load balancing strategy, proposed in a...
Abstract: In large-scale distributed systems, balancing the load in an efficient way is crucial in o...
International audienceLoad balancing with various types of load information has become a key compone...
Abstract We study a single class of traf?c acting on a symmetric set of processorsharing queues with...
In this paper, we present a bounding methodology that allows to compute a tight lower bound on the c...
112 pagesThis thesis explores the BAR approach applied on various of stochastic processing networks....
Randomized load balancing is a cost efficient policy for job scheduling in parallel server queueing ...
In this thesis, we tackle the problem of insensitivity in queueing networks and consider some applic...
Randomized load balancing is a cost efficient policy for job scheduling in parallel server queueing ...
We present an overview of scalable load balancing algorithms which provide favorable delay performan...
It is well known that simple randomized load balancing schemes can balance load effectively while in...
this paper, we propose a new technique for estimating the performance of queueing networks with buff...
In this paper, we present a bounding methodology that allows to com-pute a tight lower bound on the ...
We consider a system of N identical server pools and a single dispatcher in which tasks with unit-ex...
This paper studies the heavy-traffic joint distribution of queue lengths in two stochastic processin...
We consider the model of a token-based joint auto-scaling and load balancing strategy, proposed in a...
Abstract: In large-scale distributed systems, balancing the load in an efficient way is crucial in o...