Cited By
View all- Tadrous JEryilmaz ASabharwal A(2019)Action-Based SchedulingIEEE/ACM Transactions on Networking10.1109/TNET.2018.288255727:1(112-125)Online publication date: 1-Feb-2019
Application-level scheduling with probabilistic deadline constraints
Pages 1504 - 1517
Abstract
Opportunistic scheduling of delay-tolerant traffic has been shown to substantially improve spectrum efficiency. To encourage users to adopt delay-tolerant scheduling for capacity-improvement, it is critical to provide guarantees in terms of completion time. In this paper, we study application-level scheduling with deadline constraints, where the deadline is pre-specified by users/applications and is associated with a deadline violation probability. To address the exponentially-high complexity due to temporally-varying channel conditions and deadline constraints, we develop a novel asymptotic approach that exploits the largeness of the network to our advantage. Specifically, we identify a lower bound on the deadline violation probability, and propose simple policies that achieve the lower bound in the large-system regime. The results in this paper thus provide a rigorous analytical framework to develop and analyze policies for application-level scheduling under very general settings of channel models and deadline requirements. Further, based on the asymptotic approach, we propose the notion of Application-Level Effective Capacity region, i.e., the throughput region that can be supported subject to deadline constraints, which allows us to quantify the potential gain of application-level scheduling. Simulation results show that application-level scheduling can improve the system capacity significantly while guaranteeing the deadline constraints.
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Index Terms
- Application-level scheduling with probabilistic deadline constraints
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Published: 01 June 2016
Published in TON Volume 24, Issue 3
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View all- Tadrous JEryilmaz ASabharwal A(2019)Action-Based SchedulingIEEE/ACM Transactions on Networking10.1109/TNET.2018.288255727:1(112-125)Online publication date: 1-Feb-2019
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