Flexi-grid technology has emerged as the evolution of fixed-grid DWDM core optical networks, enabling more efficient utilization of spectral resources and leading to higher overall network throughput. However, it suffers from an aggravated form of the spectrum fragmentation problem that affects fixed-grid networks. This work presents a novel path-based metric to better evaluate the fragmentation of spectral resources in flexi-grid optical networks, which considers that not all links of a path may contain enough free frequency slots and the likelihood that an end-to-end spectral void is large enough to house a connection. Furthermore, two families of heuristic routing and spectrum allocation (RSA) algorithms that preventively attempt to minimize the value of an input fragmentation metric are presented. These are used to evaluate the effectiveness of multiple metrics, both introduced in this work and from the existing literature, via simulations. We find that both proposed families can perform better, in terms of blocking probability and achievable network throughput, than the well-known K-shortest paths routing with a first fit spectrum allocation policy, with one of them trading performance for lower complexity, and that the proposed fragmentation metric outperforms the existing ones.

Path-based fragmentation metric and RSA algorithms for elastic optical networks

Spectrum defragmentation algorithms in elastic optical networks

The rapid growth of the technologies, high bandwidth applications, and cloud data centers consume heavy internet service. So, the consumer of the internet expects a high capacity medium for communication. The Elastic Optical Network (EON) provides a flexible and reliable transmission service for consumers. The spectrum fragmentation is a key challenge in EON. In simple terms, unaligned Frequency Slots (FSs) in the network are referred to as fragmented spectrum, while in defragmentation, the available FSs need to be rearranged to create room for the new connection requests. The problem in defragmentation occurs due to the lack of a continuous spectrum and it leads to depreciation in spectrum usage and simultaneously increasing the Blocking Probability (BP) which disrupts the majority of the existing connections in the network. Several techniques and approaches were suggested to reduce the possibility of disruption and reconfiguration in the network while defragmenting the frequency slots. This paper proposes a new algorithm to overcome the drawbacks and improvement in the quality of service of the network. The proposed algorithm holds the approach of proactive and reactive along with the meta-heuristic nature-inspired optimization technique called Jellyfish Search Optimization (JSO). The proposed combination, PR-DF-JFSO outperforms well in terms of spectrum utilization, network efficiency, and quality of service offered when compared to the state-of-the-art spectrum defragmentation algorithms according to the results of experiments done using standard quality metrics. The simulation results show the better utilization of spectrum, reduce the spectrum fragmentation complexity, better bandwidth fragmentation ratio, and overall connection blocking reduced.

/pdf/a-spectrum-defragmentation-algorithm-using-jellyfish-2puyvzepx7.pdf

A Spectrum Defragmentation Algorithm Using Jellyfish Optimization Technique in Elastic Optical Network (EON)

When circuits are set up and dismantled dynamically in elastic optical networks, spectrum tends to become fragmented in the fiber links. The fragmentation limits the available path choices and may lead to significant blocking of connection requests. There are two types of fragmentation in the network spectrum in the links due to contiguity constraints and over the paths due to continuity. Study of fragmentation and its management is essential to operate the networks efficiently. This paper proposes a vectored fragmentation metric for characterizing the fragmentation, which covers both types of fragmentation. We discuss the characteristics of this metric in both transient and steady-state of the dynamic network. We also test the proposed metric for connection requests granularity range, arrival rates and holding times, to establish functionality of this metric. We also compare the link-based fragmentation metric with our Vectored Fragmentation Metric to understand the better representation.

A Vectored Fragmentation Metric for Elastic Optical Networks.

When circuits are set up and dismantled dynamically in elastic optical networks, the link spectrum becomes fragmented. The fragmentation limits the available path choices and may lead to significant blocking of connection requests. The fragmentation can be link fragmentation due to non-contiguity of available spectral resources on individual links or path fragmentation due to non-continuity of available spectral resources on the paths of the connection requests. The study of fragmentation and its management is essential to operate the networks efficiently. This paper proposes a vectored fragmentation metric for characterizing the fragmentation, which includes both types of fragmentation. We discuss the characteristics of this metric considering different network scenarios, where connection requests arrive and depart dynamically. To establish the functionality of this metric, we also test the utility of the metric in fragmentation management cases. We compare the different link-based fragmentation metrics and a path-based fragmentation metric with our Adapted vectored fragmentation metric to understand the efficacy of the proposed measure. We find the vectored fragmentation metric to be effective in this study. 

/pdf/a-vectored-fragmentation-metric-for-elastic-optical-networks-1sy63zxy.pdf

A vectored fragmentation metric for elastic optical networks

A wide overview of metrics to evaluate the spectrum fragmentation is presented together with their application for Routing and Spectrum Assignment (RSA) in Elastic Optical Networks (EONs). A basic heuristic spectrum allocation algorithm conceived for keeping the fragmentation index low during the connection allocation process has been defined. Starting from the application of such algorithm on a single link, the analysis has been extended to encompass sample networks and a real size case study. It has been found that, in both contexts of dynamic traffic and semi-static incremental network loading, good heuristics based on simple and low computational demanding allocation policy (e.g., First Fit), perform very close, in terms of average traffic loss, to methods which use more complex algorithms based on fragmentation metrics. However some of the applied metrics result still beneficial as they obtain an equalization of the connection blocking rates between the various types of multi granular traffic and the probability of blocking of high spectrum demanding superchannels results considerably reduced.

Spectrum fragmentation metrics and their use in optical channel allocation algorithms

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Spectrum fragmentation metrics and their use in optical channel allocation algorithms