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Abstract
We consider the optimal opportunistic scheduling problem for downlink data traffic in a wireless cell with time-varying channels. The scheduler itself operates at a very fast time scale of milliseconds, but the objective function is related to minimizing the holding costs at a much longer time scale, at the so-called flow level. The Whittle index approach is a powerful tool in this context, since it renders the flow-level optimization problem with heterogeneous users tractable. Until now, this approach has been applied to the opportunistic scheduling problem to generate non-anticipating index policies that may depend on the amount of attained service but do not utilize the exact size information. In this paper, we produce a size-aware (i.e., anticipating) index policy by applying the Whittle index approach in a novel way. By a numerical study based on simulations, we demonstrate that the resulting size-aware index policy systematically improves performance. As a side result, we show that the opportunistic scheduling problem is indexable when the file sizes follow the Pascal distribution, and we derive the corresponding Whittle index, which generalizes earlier results.
| Original language | English |
|---|---|
| Pages (from-to) | 195–225 |
| Number of pages | 31 |
| Journal | Queueing Systems |
| Volume | 83 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Aug 2016 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- Opportunistic scheduling
- Size-based scheduling
- Stochastic optimization
- Whittle index
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Dive into the research topics of 'Whittle index approach to size-aware scheduling for time-varying channels with multiple states'. Together they form a unique fingerprint.Projects
- 1 Finished
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Towards Optimal Performance-Energy Trade-off in Server Farms
Aalto, S. (Principal investigator), Lassila, P. (Project Member), Gebrehiwot, M. (Project Member), Osti, P. (Project Member) & Hyytiä, E. (Project Member)
01/09/2013 → 31/08/2017
Project: Academy of Finland: Other research funding