A Predictive Resource Reservation Protocol for High-Speed Asynchronous Transfer Networks

International Journal of Computer Science and Technology Vol. 3, No. 2, February 2001 | pp. 9–16

DOI: 10.46882/2001/IJCST/000026

Research Article

Title: A Predictive Resource Reservation Protocol for High-Speed Asynchronous Transfer Networks

Names of Authors: Carlos Mendez¹, Elena Rostova²

Authors’ Affiliations: ¹Department of Telecommunications, Polytechnic University of Madrid, Spain; ²Department of Computer Science, Saint Petersburg State University, Russia.

Abstract:
Asynchronous Transfer Mode (ATM) networks experience significant cell drop rates and buffer overflows during variable bit-rate multimedia streaming phases. Static resource reservation policies either fail to absorb sudden traffic spikes or lead to poor channel efficiency. This paper presents an optimized, dynamic bandwidth reservation protocol, Predictive Cell Allocator (PCA), that integrates short-term traffic forecasting with adaptive threshold constraints. By evaluating cell arrival derivatives over sliding time windows, the protocol adjusts queue capacities before congestion states occur. We executed simulation runs across a wide-area network topology under heavy load factors. The results indicate that PCA improves the cell delivery ratio by 28.6% and drops cell delay variance by 34.1% relative to conventional static reservation mechanisms. Total end-to-end latency dropped by 45 milliseconds, complying with standard quality of service bounds for live voice applications, confirming network stability under heavy traffic loads.

Keywords: ATM Networks, Resource Reservation, Congestion Control, Predictive Allocation, Buffer Architecture, Communication Protocols.

Manuscript Timeline: Received: November 01, 2000; Revised: December 12, 2000; Accepted: January 05, 2001; Published: February 22, 2001.

Citation: Mendez, C., & Rostova, E. (2001). A Predictive Resource Reservation Protocol for High-Speed Asynchronous Transfer Networks. International Journal of Computer Science and Technology, 3(2), 9–16.

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