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This paper studies the “age of information” (AoI) in a multi-source status update system where N active sources each send updates of their time-varying process to a monitor through a server with packet delivery errors. We analyze the average AoI for stationary randomized and round-robin scheduling policies. For both of these scheduling policies, we further analyze the effect of packet retransmission policies, i.e., retransmission without re- sampling, retransmission with resampling, or no retransmission, when errors occur. Expressions for the average AoI are derived for each case. It is shown that the round-robin schedule policy in conjunction with retransmission with resampling when errors occur achieves the lowest average AoI among the considered cases. For stationary randomized schedules with equiprobable source selection, it is further shown that the average AoI gap to round-robin schedules with the same packet management policy scales as O(N). Finally, for stationary randomized policies, the optimal source selection probabilities that minimize a weighted sum average AoI metric are derived.
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This content will become publicly available on May 27, 2026
Design and Modeling of a New File Transfer Architecture to Reduce Undetected Errors Evaluated in the FABRIC Testbed
Ensuring the integrity of petabyte-scale file transfers is essential for the data gathered from scientific instruments. As packet sizes increase, so does the likelihood of errors, resulting in a higher probability of undetected errors in the packet. This paper presents a Multi-Level Error Detection (MLED) framework that leverages in-network resources to reduce undetected error probability (UEP) in file transmission. MLED is based on a configurable recursive architecture that organizes communication in layers at different levels, decoupling network functions such as error detection, routing, addressing, and security. Each layer Lij at level i implements a policy Pij that governs its operation, including the error detection mechanism used, specific to the scope of that layer. MLED can be configured to mimic the error detection mechanisms of existing large-scale file transfer protocols. The recursive structure of MLED is analyzed and it shows that adding additional levels of error detection reduces the overall UEP. An adversarial error model is designed to introduce errors into files that evade detection by multiple error detection policies. Through experimentation using the FABRIC testbed the traditional approach, with transport- and data link- layer error detection, results in a corrupt file transfer requiring retransmission of the entire file. Using its recursive structure, an implementation of MLED detects and corrects these adversarial errors at intermediate levels inside the network, avoiding file retransmission under non-zero error rates. MLED therefore achieves a 100% gain in goodput over the traditional approach, reaching a goodput of over 800 Mbps on a single connection with no appreciable increase in delay.
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- PAR ID:
- 10630774
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- Proceedings of the ACM on Measurement and Analysis of Computing Systems
- Volume:
- 9
- Issue:
- 2
- ISSN:
- 2476-1249
- Page Range / eLocation ID:
- 1 to 42
- Subject(s) / Keyword(s):
- Large-scale Data Transfer High-speed Wide Area Network Multi-Level Error Detection Recursive Architecture Error Detection Adversarial Error Model CRC Internet checksum
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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