Maria Serna’s contributions to adversarial queuing theory

Blesa, Miguel A.; Anta, Antonio Fernández

doi:10.1016/j.cosrev.2020.100348

Cited by 2 publications

(1 citation statement)

References 48 publications

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“…As has been pointed out previously, in real networks the assumption that input traffic is characterized by a stochastic process may not be realistic, in general [10]. Therefore, to capture the bursty phenomenon in job arrivals, new models have been proposed [11], [12]. These models consider the time evolution of a job-routing network as a game between a malicious adversary that has the power to perform a number of actions (such as injecting jobs at particular nodes, choosing their destination, routing them, etc.)…”

Section: A Related Workmentioning

confidence: 99%

System Stability Under Adversarial Injection of Dependent Tasks

et al. 2021

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Technological changes (NFV, Osmotic Computing, Cyber-physical Systems) are making very important devising techniques to efficiently run a flow of jobs formed by dependent tasks in a set of servers. These problem can be seen as generalizations of the dynamic job-shop scheduling problem, with very rich dependency patterns and arrival assumptions. In this work, we consider a computational model of a distributed system formed by a set of servers in which jobs, that are continuously arriving, have to be executed. Every job is formed by a set of dependent tasks (i. e., each task may have to wait for others to be completed before it can be started), each of which has to be executed in one of the servers. The arrival of jobs and their properties is assumed to be controlled by a bounded adversary, whose only restriction is that it cannot overload any server. This model is a non-trivial generalization of the Adversarial Queuing Theory model of Borodin et al., and, like that model, focuses on the stability of the system: whether the number of jobs pending to be completed is bounded at all times. We show multiple results of stability and instability for this adversarial model under different combinations of the scheduling policy used at the servers, the arrival rate, and the dependence between tasks in the jobs.INDEX TERMS Tasks scheduling, task queuing, dependent tasks, adversarial queuing models, stability.

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Section: A Related Workmentioning

confidence: 99%