Abstract

Optical Burst Switching (OBS) paradigm coupled with Dense Wavelength Division Multiplexing (DWDM) has become a practical candidate solution for the next-generation optical backbone networks. In its practical deployment only the edge nodes are provisioned with buffering capabilities, whereas all interior (core) nodes remain buffer-less. In that way the implementation becomes quite simple as well as cost effective as there will be no need for optical buffers in the interior. However, the buffer-less nature of the interior nodes makes such networks prone to data burst contention occurrences that lead to a degradation in overall network performance as a result of sporadic heavy burst losses. Such drawbacks can be partly countered by appropriately dimensioning available network resources and reactively by way of deflecting excess as well as contending data bursts to available least-cost alternate paths. However, the deflected data bursts (traffic) must not cause network performance degradations in the deflection routes. Because minimizing contention occurrences is key to provisioning a consistent Quality of Service (QoS), we therefore in this paper propose and analyze a framework (scheme) that seeks to intelligently deflect traffic in the core network such that QoS degradations caused by contention occurrences are minimized. This is by way of regulated deflection routing (rDr) in which neural network agents are utilized in reinforcing the deflection route choices at core nodes. The framework primarily relies on both reactive and proactive regulated deflection routing approaches in order to prevent or resolve data burst contentions. Simulation results show that the scheme does effectively improve overall network performance when compared with existing contention resolution approaches. Notably, the scheme minimizes burst losses, end-to-end delays, frequency of contention occurrences, and burst deflections.

Highlights

  • Dense Wavelength Division Multiplexing (DWDM) does support speeds in the terabit ranges in a single fiber; it can adequately handle the massive amounts of heterogeneous data in present and future service networks. e terabit range speeds are primarily achieved by way of individually modulating several wavelengths before multiplexing them into a single fiber

  • Fairness and data burst loss owing to cascading constraint when bursts have longer hop count value in Optical Burst Switching (OBS) networks is explored in [13]. e authors propose a preemptive scheduling technique for nextgeneration OBS networks in which newly arriving bursts with higher priority may preempt already scheduled ones when contention occurs. It is on the strength of the earlier cited weakness that in this paper we propose a controllable deflection routing scheme which couples with a simple wavelength and routing assignment (WRA) algorithm to enhance overall network performance, by way of minimizing contention, wavelength congestion, and bursts blocking probabilities

  • The paper’s contributions are as follows: We propose a three-step approach to reducing contention occurrences in the core OBS network: (1) offset time regulation at burstification, (2) regulated deflection routing, and (3) neural network-based robust network state updating. erefore, in this regard, the following steps are carried out: (1) We describe a novel adjustable offset time coupled with a segmented burst assembly algorithm that regulates the offset timing such that extra delays are not incurred by traffic in the network. e algorithm suits both delay and non-delay-sensitive applications data

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Summary

A Node-Regulated Deflection Routing Framework for Contention Minimization

Received 30 April 2019; Revised 9 December 2019; Accepted 28 December 2019; Published 8 June 2020. The buffer-less nature of the interior nodes makes such networks prone to data burst contention occurrences that lead to a degradation in overall network performance as a result of sporadic heavy burst losses. Such drawbacks can be partly countered by appropriately dimensioning available network resources and reactively by way of deflecting excess as well as contending data bursts to available least-cost alternate paths. The deflected data bursts (traffic) must not cause network performance degradations in the deflection routes. The scheme minimizes burst losses, end-to-end delays, frequency of contention occurrences, and burst deflections

Introduction
Related Work on Contention Resolution
Adjustable Offset Timing
ANN Agents and Reinforcement Learning
Node-Regulated Deflection Routing Framework
Simulation Results and Analysis
II III
Conclusions
Full Text
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