Stability Under Adversarial Injection of Dependent Tasks (Extended Abstract)

Abstract

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 and properties of jobs are 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.

This submission is a short paper. This work was partially funded by the Spanish grant PID2019-109805RB-I00 (ECID), the Region of Madrid EdgeData-CM program (P2018/TCS-4499), and the NSF of China grant 61520106005.