An Adaptive Priority Queue Model for Enhancing Multi-User Network Ingestion

International Journal of Computer Science and Technology Vol. 2, No. 10, October 2000 | pp. 73–80

DOI: 10.46882/2000/IJCST/000022

Research Article

Title: An Adaptive Priority Queue Model for Enhancing Multi-User Network Ingestion

Names of Authors: Sarah Jenkins¹, Vikram Rao²

Authors’ Affiliations: ¹Department of Computer Science, Columbia University, New York, USA; ²School of Computer Science and Automation, Indian Institute of Science, Bangalore, India.

Abstract:
Multi-user server infrastructures face severe data congestion and packet starvation anomalies when managing highly concurrent client connection pools. The primary operational challenge involves processing multi-layered protocol messages without causing thread execution lockups or excessive data processing drops. This paper develops a dynamic, multi-level priority queue architecture, Balanced Ingestion Scheduler (BIS), engineered to manage skewed traffic distributions. The algorithm evaluates client request footprints and shifts buffer resources interactively to maintain structural data equilibrium. We implemented the BIS protocol within an enterprise server framework and benchmarked performance metrics using a synthetic dataset containing 100 million incoming connection packets. The empirical findings reveal that BIS cuts server memory congestion by 41.2% and speeds up message ingestion cycles by a factor of 3.5 relative to standard FIFO scheduling approaches. Storage buffer capacity variance remained below 2.1%, showing solid allocation balancing even during massive data submission surges.

Keywords: Queuing Theory, Data Ingestion, Buffer Architecture, Network Infrastructure, Traffic Management, Server Optimization.

Manuscript Timeline: Received: July 15, 2000; Revised: August 25, 2000; Accepted: September 14, 2000; Published: October 28, 2000.

Citation: Jenkins, S., & Rao, V. (2000). An Adaptive Priority Queue Model for Enhancing Multi-User Network Ingestion. International Journal of Computer Science and Technology, 2(10), 73–80.

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