Scheduling to Minimize Age of Information With Multiple Sources
Finding an optimal/near-optimal scheduling algorithm to minimize the age of information (AoI) in a multi-source G/G/1 system is well-known to be a hard problem, more so if there is a transmission (energy) cost. In this paper, we consider a multi-source G/G/1 system and the goal is to minimize a weig...
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| Published in: | IEEE journal on selected areas in information theory Vol. 4; pp. 539 - 550 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Piscataway
IEEE
2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 2641-8770, 2641-8770 |
| Online Access: | Get full text |
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| Summary: | Finding an optimal/near-optimal scheduling algorithm to minimize the age of information (AoI) in a multi-source G/G/1 system is well-known to be a hard problem, more so if there is a transmission (energy) cost. In this paper, we consider a multi-source G/G/1 system and the goal is to minimize a weighted sum of the AoI of all sources, subject to an energy cost constraint. We propose a novel doubly randomized non-preemptive scheduling algorithm and show that in the non-preemptive setting, where an update under transmission cannot be preempted, the competitive ratio of the proposed algorithm is at most 3 plus the maximum of the ratio of the variance and the mean of the update inter-generation time distribution of sources. Notably, the competitive ratio is independent of the number of sources, or their service time distributions, and is at most 4 for several common update inter-generation time distributions such as exponential, uniform and Rayleigh. For preemptive setting, where an update under transmission can be preempted, we consider a multi-source G/M/1 system and show that the proposed non-preemptive algorithm has competitive ratio at most 5 plus the maximum of the ratio of the variance and the mean of the update inter-generation time distribution of sources. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2641-8770 2641-8770 |
| DOI: | 10.1109/JSAIT.2023.3322077 |