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Relevant bibliographies by topics / Low-Latency applications

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Journal articles

Academic literature on the topic 'Low-Latency applications'

Author: Grafiati

Published: 24 May 2025

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Journal articles on the topic "Low-Latency applications"

1

Gürel, O., and M. U. Çakır. "XMPP Based Applications under Low Bandwidth and High Latency Conditions." Lecture Notes on Software Engineering 3, no. 4 (2015): 314–17. http://dx.doi.org/10.7763/lnse.2015.v3.211.

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2

Brook, Andrew. "Low-latency distributed applications in finance." Communications of the ACM 58, no. 7 (2015): 42–50. http://dx.doi.org/10.1145/2747303.

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3

Fiati, Patrick, and K. Adu Boahen Opare. "Network Architecture for Ultra Low Latency Applications." Communications on Applied Electronics 7, no. 37 (2021): 1–4. http://dx.doi.org/10.5120/cae2021652887.

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4

Sowmiyaa P, Saranya P, Sabena M, Saranya R, and Subhisha K. "LOW-LATENCY APPROXIMATE ADDERIN FPGA." international journal of engineering technology and management sciences 9, no. 2 (2025): 23–25. https://doi.org/10.46647/ijetms.2025.v09i02.005.

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Approximate computing has gained significant attention for applications where absolute precision isnot critical, such as image processing, machine learning, and signal processing. The proposeddesign divides the addition process into two stages: a main sub-adder for high-speed approximatecomputation and an error sub-adder for refining accuracy. By limiting carry propagation in the mainsub-adder, the critical path delay is significantly reduced, achieving low latency. Simultaneously,the error sub-adder operates in parallel to correct errors, ensuring a balance between performanceand precision. E

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5

Gomes Lobato, Thiago Henrique, Roland Sottek, and Michael Vorlaender. "Implementing neural networks in low-latency audio applications." Journal of the Acoustical Society of America 153, no. 3_supplement (2023): A105. http://dx.doi.org/10.1121/10.0018318.

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The use of neural networks is becoming increasingly prevalent due to their ability to represent complex relationships and solve complex problems. However, implementing these models in systems that require low-latency output can be challenging, especially for practitioners who are used to developing their models in controlled environments like Python notebooks. Another issue is the high computational cost of complex models, which limits the minimum possible latency. This paper presents approaches for deploying models in audio applications, discusses the advantages and disadvantages of each appr

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6

Kavamahanga, Lambert, Theodette Uwimbabazi, and Damascene Uwizeyemungu. "Low-Latency and Ultra-Reliable Communication for Industrial 5G." Journal of Current Trends in Computer Science Research 3, no. 4 (2024): 01–05. http://dx.doi.org/10.33140/jctcsr.03.04.02.

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The Internet of Things(IoT) is a planned Internet extension in which everyday objects are outfitted with circuitry, software, sensors, and internet connectivity is required so that data can be received and sent over the Internet. Emerging applications like factory automation and au- tonomous driving necessitate affordable, dependable, and low- latency communication making wireless architecture It’s more convoluted than before. The study’s goal is to understand existing study issues and solutions in connection with 5G-enabled Industrial IoT based on both sectors’ original goals and commitments.

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7

Litz, Heiner, Javier Gonzalez, Ana Klimovic, and Christos Kozyrakis. "RAIL: Predictable, Low Tail Latency for NVMe Flash." ACM Transactions on Storage 18, no. 1 (2022): 1–21. http://dx.doi.org/10.1145/3465406.

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Flash-based storage is replacing disk for an increasing number of data center applications, providing orders of magnitude higher throughput and lower average latency. However, applications also require predictable storage latency. Existing Flash devices fail to provide low tail read latency in the presence of write operations. We propose two novel techniques to address SSD read tail latency, including Redundant Array of Independent LUNs (RAIL) which avoids serialization of reads behind user writes as well as latency-aware hot-cold separation (HC) which improves write throughput while maintaini

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8

Shih, Yuan-Yao, Wei-Ho Chung, Ai-Chun Pang, Te-Chuan Chiu, and Hung-Yu Wei. "Enabling Low-Latency Applications in Fog-Radio Access Networks." IEEE Network 31, no. 1 (2017): 52–58. http://dx.doi.org/10.1109/mnet.2016.1500279nm.

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9

Brook, Andrew. "Evolution and Practice: Low-latency Distributed Applications in Finance." Queue 13, no. 4 (2015): 40–53. http://dx.doi.org/10.1145/2756506.2770868.

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10

Berisa, Tomaz, Kerim Fouli, and Martin Maier. "Real-time PON signaling for emerging low-latency applications." Computer Communications 52 (October 2014): 102–9. http://dx.doi.org/10.1016/j.comcom.2014.06.008.

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