4,839 research outputs found
An Overview on Application of Machine Learning Techniques in Optical Networks
Today's telecommunication networks have become sources of enormous amounts of
widely heterogeneous data. This information can be retrieved from network
traffic traces, network alarms, signal quality indicators, users' behavioral
data, etc. Advanced mathematical tools are required to extract meaningful
information from these data and take decisions pertaining to the proper
functioning of the networks from the network-generated data. Among these
mathematical tools, Machine Learning (ML) is regarded as one of the most
promising methodological approaches to perform network-data analysis and enable
automated network self-configuration and fault management. The adoption of ML
techniques in the field of optical communication networks is motivated by the
unprecedented growth of network complexity faced by optical networks in the
last few years. Such complexity increase is due to the introduction of a huge
number of adjustable and interdependent system parameters (e.g., routing
configurations, modulation format, symbol rate, coding schemes, etc.) that are
enabled by the usage of coherent transmission/reception technologies, advanced
digital signal processing and compensation of nonlinear effects in optical
fiber propagation. In this paper we provide an overview of the application of
ML to optical communications and networking. We classify and survey relevant
literature dealing with the topic, and we also provide an introductory tutorial
on ML for researchers and practitioners interested in this field. Although a
good number of research papers have recently appeared, the application of ML to
optical networks is still in its infancy: to stimulate further work in this
area, we conclude the paper proposing new possible research directions
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Reconfigurable Optically Interconnected Systems
With the immense growth of data consumption in today's data centers and high-performance computing systems driven by the constant influx of new applications, the network infrastructure supporting this demand is under increasing pressure to enable higher bandwidth, latency, and flexibility requirements. Optical interconnects, able to support high bandwidth wavelength division multiplexed signals with extreme energy efficiency, have become the basis for long-haul and metro-scale networks around the world, while photonic components are being rapidly integrated within rack and chip-scale systems. However, optical and photonic interconnects are not a direct replacement for electronic-based components. Rather, the integration of optical interconnects with electronic peripherals allows for unique functionalities that can improve the capacity, compute performance and flexibility of current state-of-the-art computing systems. This requires physical layer methodologies for their integration with electronic components, as well as system level control planes that incorporates the optical layer characteristics. This thesis explores various network architectures and the associated control plane, hardware infrastructure, and other supporting software modules needed to integrate silicon photonics and MEMS based optical switching into conventional datacom network systems ranging from intra-data center and high-performance computing systems to the metro-scale layer networks between data centers. In each of these systems, we demonstrate dynamic bandwidth steering and compute resource allocation capabilities to enable significant performance improvements. The key accomplishments of this thesis are as follows.
In Part 1, we present high-performance computing network architectures that integrate silicon photonic switches for optical bandwidth steering, enabling multiple reconfigurable topologies that results in significant system performance improvements. As high-performance systems rely on increased parallelism by scaling up to greater numbers of processor nodes, communication between these nodes grows rapidly and the interconnection network becomes a bottleneck to the overall performance of the system. It has been observed that many scientific applications operating on high-performance computing systems cause highly skewed traffic over the network, congesting only a small percentage of the total available links while other links are underutilized. This mismatch of the traffic and the bandwidth allocation of the physical layer network presents the opportunity to optimize the bandwidth resource utilization of the system by using silicon photonic switches to perform bandwidth steering. This allows the individual processors to perform at their maximum compute potential and thereby improving the overall system performance. We show various testbeds that integrates both microring resonator and Mach-Zehnder based silicon photonic switches within Dragonfly and Fat-Tree topology networks built with conventional
equipment, and demonstrate 30-60% reduction in execution time of real high-performance benchmark applications.
Part 2 presents a flexible network architecture and control plane that enables autonomous bandwidth steering and IT resource provisioning capabilities between metro-scale geographically distributed data centers. It uses a software-defined control plane to autonomously provision both network and IT resources to support different quality of service requirements and optimizes resource utilization under dynamically changing load variations. By actively monitoring both the bandwidth utilization of the network and CPU or memory resources of the end hosts, the control plane autonomously provisions background or dynamic connections with different levels of quality of service using optical MEMS switching, as well as initializing live migrations of virtual machines to consolidate or distribute workload. Together these functionalities provide flexibility and maximize efficiency in processing and transferring data, and enables energy and cost savings by scaling down the system when resources are not needed. An experimental testbed of three data center nodes was built to demonstrate the feasibility of these capabilities.
Part 3 presents Lightbridge, a communications platform specifically designed to provide a more seamless integration between processor nodes and an optically switched network. It addresses some of the crucial issues faced by the works presented in the previous chapters related to optical switching. When optical switches perform switching operations, they change the physical topology of the network, and they lack the capability to buffer packets, resulting in certain optical circuits being unavailable. This prompts the question of whether it is safe to transmit packets by end hosts at any given time. Lightbridge was developed to coordinate switching and routing of optical circuits across the network, by having the processors gain information about the current state of the optical network before transmitting packets, and being able to buffer packets when the optical circuit is not available. This part describes details of Lightbridge which is constituted by a loadable Linux kernel module along with other supporting modifications to the Linux kernel in order to achieve the necessary functionalities
Wavelength tunable transmitters for future reconfigurable agile optical networks
Wavelength tuneable transmission is a requirement for future reconfigurable agile optical networks as it enables cost efficient bandwidth distribution and a greater degree of transparency. This thesis focuses on the development and characterisation of wavelength tuneable transmitters for the core, metro and access based WDM networks.
The wavelength tuneable RZ transmitter is a fundamental component for the core network as the RZ coding scheme is favoured over the conventional NRZ format as the line rate increases. The combination of a widely tuneable SG DBR laser and an EAM is a propitious technique employed to generate wavelength tuneable pulses at high repetition
rates (40 GHz). As the EAM is inherently wavelength dependant an accurate characterisation of the generated pulses is carried out using the linear spectrogram
measurement technique. Performance issues associated with the transmitter are investigated by employing the generated pulses in a 1500 km 42.7 Gb/s circulating loop
system. It is demonstrated that non-optimisation of the EAM drive conditions at each operating wavelength can lead to a 33 % degradation in system performance. To achieve
consistent operation over a wide waveband the drive conditions of the EAM must be altered at each operating wavelength.
The metro network spans relatively small distances in comparison to the core and therefore must utilise more cost efficient solutions to transmit data, while also
maintaining high reconfigurable functionality. Due to the shorter transmission distances, directly modulated sources can be utilised, as less precise wavelength and chirp control can be tolerated. Therefore a gain-switched FP laser provides an ideal source for wavelength tuneable pulse generation at high data rates (10 Gb/s). A self-seeding scheme that generates single mode pulses with high SMSR (> 30 dB) and small pulse duration is demonstrated. A FBG with a very large group delay disperses the generated pulses and subsequently uses this CW like signal to re-inject the laser diode negating the need to tune the repetition rate for optimum gain-switching operation.
The access network provides the last communication link between the customer’s premises and the first switching node in the network. FTTH systems should take advantage of directly modulated sources; therefore the direct modulation of a SG DBR tuneable laser is investigated. Although a directly modulated TL is ideal for reconfigurable access based networks, the modulation itself leads to a drift in operating frequency which may result in cross channel interference in a WDM network. This effect is investigated and also a possible solution to compensate the frequency drift through simultaneous modulation of the lasers phase section is examined
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