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

Investigation into yield and reliability enhancement of TSV-based three-dimensional integration circuits

Three dimensional integrated circuits (3D ICs) have been acknowledged as a promising technology to overcome the interconnect delay bottleneck brought by continuous CMOS scaling. Recent research shows that through-silicon-vias (TSVs), which act as vertical links between layers, pose yield and reliability challenges for 3D design. This thesis presents three original contributions.The first contribution presents a grouping-based technique to improve the yield of 3D ICs under manufacturing TSV defects, where regular and redundant TSVs are partitioned into groups. In each group, signals can select good TSVs using rerouting multiplexers avoiding defective TSVs. Grouping ratio (regular to redundant TSVs in one group) has an impact on yield and hardware overhead. Mathematical probabilistic models are presented for yield analysis under the influence of independent and clustering defect distributions. Simulation results using MATLAB show that for a given number of TSVs and TSV failure rate, careful selection of grouping ratio results in achieving 100% yield at minimal hardware cost (number of multiplexers and redundant TSVs) in comparison to a design that does not exploit TSV grouping ratios. The second contribution presents an efficient online fault tolerance technique based on redundant TSVs, to detect TSV manufacturing defects and address thermal-induced reliability issue. The proposed technique accounts for both fault detection and recovery in the presence of three TSV defects: voids, delamination between TSV and landing pad, and TSV short-to-substrate. Simulations using HSPICE and ModelSim are carried out to validate fault detection and recovery. Results show that regular and redundant TSVs can be divided into groups to minimise area overhead without affecting the fault tolerance capability of the technique. Synthesis results using 130-nm design library show that 100% repair capability can be achieved with low area overhead (4% for the best case). The last contribution proposes a technique with joint consideration of temperature mitigation and fault tolerance without introducing additional redundant TSVs. This is achieved by reusing spare TSVs that are frequently deployed for improving yield and reliability in 3D ICs. The proposed technique consists of two steps: TSV determination step, which is for achieving optimal partition between regular and spare TSVs into groups; The second step is TSV placement, where temperature mitigation is targeted while optimizing total wirelength and routing difference. Simulation results show that using the proposed technique, 100% repair capability is achieved across all (five) benchmarks with an average temperature reduction of 75.2? (34.1%) (best case is 99.8? (58.5%)), while increasing wirelength by a small amount

Radiation Hardened by Design Methodologies for Soft-Error Mitigated Digital Architectures

abstract: Digital architectures for data encryption, processing, clock synthesis, data transfer, etc. are susceptible to radiation induced soft errors due to charge collection in complementary metal oxide semiconductor (CMOS) integrated circuits (ICs). Radiation hardening by design (RHBD) techniques such as double modular redundancy (DMR) and triple modular redundancy (TMR) are used for error detection and correction respectively in such architectures. Multiple node charge collection (MNCC) causes domain crossing errors (DCE) which can render the redundancy ineffectual. This dissertation describes techniques to ensure DCE mitigation with statistical confidence for various designs. Both sequential and combinatorial logic are separated using these custom and computer aided design (CAD) methodologies. Radiation vulnerability and design overhead are studied on VLSI sub-systems including an advanced encryption standard (AES) which is DCE mitigated using module level coarse separation on a 90-nm process with 99.999% DCE mitigation. A radiation hardened microprocessor (HERMES2) is implemented in both 90-nm and 55-nm technologies with an interleaved separation methodology with 99.99% DCE mitigation while achieving 4.9% increased cell density, 28.5 % reduced routing and 5.6% reduced power dissipation over the module fences implementation. A DMR register-file (RF) is implemented in 55 nm process and used in the HERMES2 microprocessor. The RF array custom design and the decoders APR designed are explored with a focus on design cycle time. Quality of results (QOR) is studied from power, performance, area and reliability (PPAR) perspective to ascertain the improvement over other design techniques. A radiation hardened all-digital multiplying pulsed digital delay line (DDL) is designed for double data rate (DDR2/3) applications for data eye centering during high speed off-chip data transfer. The effect of noise, radiation particle strikes and statistical variation on the designed DDL are studied in detail. The design achieves the best in class 22.4 ps peak-to-peak jitter, 100-850 MHz range at 14 pJ/cycle energy consumption. Vulnerability of the non-hardened design is characterized and portions of the redundant DDL are separated in custom and auto-place and route (APR). Thus, a range of designs for mission critical applications are implemented using methodologies proposed in this work and their potential PPAR benefits explored in detail.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Improved Physical Design for Manufacturing Awareness and Advanced VLSI

Increasing challenges arise with each new semiconductor technology node, especially in advanced nodes, where the industry tries to extract every ounce of benefit as it approaches the limits of physics, through manufacturing-aware design technology co-optimization and design-based equivalent scaling. The increasing complexity of design and process technologies, and ever-more complex design rules, also become hurdles for academic researchers, separating academic researchers from the most up-to-date technical issues.This thesis presents innovative methodologies and optimizations to address the above challenges. There are three directions in this thesis: (i) manufacturing-aware design technology co-optimization; (ii) advanced node design-based equivalent scaling; and (iii) an open source academic detailed routing flow.To realize manufacturing-aware design technology co-optimization, this thesis presents two works: (i) a multi-row detailed placement optimization for neighbor diffusion effect mitigation between neighboring standard cells; and (ii) a post-routing optimization to generate 2D block mask layout for dummy segment removal in self-aligned multiple patterning.To achieve advanced node design-based equivalent scaling, this thesis presents two improved physical design methodologies: (i) a post-placement flop tray generation approach for clock power reduction; and (ii) a detailed placement approach to exploit inter-row M1 routing for congestion and wirelength reduction.To address the increasing gap between academia and industry, this thesis presents two works toward an open source academic detailed routing flow: (i) a complete, robust, scalable and design ruleaware dynamic programming-based pin access analysis framework; and (ii) TritonRoute – the open source detailed router that is capable of delivering DRC-clean detailed routing solutions in advanced nodes.This thesis concludes with a summary of its contributions and open directions for future research

Fault Tolerant Electronic System Design

Due to technology scaling, which means reduced transistor size, higher density, lower voltage and more aggressive clock frequency, VLSI devices may become more sensitive against soft errors. Especially for those devices used in safety- and mission-critical applications, dependability and reliability are becoming increasingly important constraints during the development of system on/around them. Other phenomena (e.g., aging and wear-out effects) also have negative impacts on reliability of modern circuits. Recent researches show that even at sea level, radiation particles can still induce soft errors in electronic systems. On one hand, processor-based system are commonly used in a wide variety of applications, including safety-critical and high availability missions, e.g., in the automotive, biomedical and aerospace domains. In these fields, an error may produce catastrophic consequences. Thus, dependability is a primary target that must be achieved taking into account tight constraints in terms of cost, performance, power and time to market. With standards and regulations (e.g., ISO-26262, DO-254, IEC-61508) clearly specify the targets to be achieved and the methods to prove their achievement, techniques working at system level are particularly attracting. On the other hand, Field Programmable Gate Array (FPGA) devices are becoming more and more attractive, also in safety- and mission-critical applications due to the high performance, low power consumption and the flexibility for reconfiguration they provide. Two types of FPGAs are commonly used, based on their configuration memory cell technology, i.e., SRAM-based and Flash-based FPGA. For SRAM-based FPGAs, the SRAM cells of the configuration memory highly susceptible to radiation induced effects which can leads to system failure; and for Flash-based FPGAs, even though their non-volatile configuration memory cells are almost immune to Single Event Upsets induced by energetic particles, the floating gate switches and the logic cells in the configuration tiles can still suffer from Single Event Effects when hit by an highly charged particle. So analysis and mitigation techniques for Single Event Effects on FPGAs are becoming increasingly important in the design flow especially when reliability is one of the main requirements

Investigation of domestic level EV chargers in the Distribution Network: An Assessment and mitigation solution

This research focuses on the electrification of the transport sector. Such electrification could potentially pose challenges to the distribution system operator (DSO) in terms of reliability, power quality and cost-effective implementation. This thesis contributes to both, an Electrical Vehicle (EV) load demand profiling and advanced use of reactive power compensation (D-STATCOM) to facilitate flexible and secure network operation. The main aim of this research is to investigate the planning and operation of low voltage distribution networks (LVDN) with increasing electrical vehicles (EVs) proliferation and the effects of higher demand charging systems. This work is based on two different independent strands of research. Firstly, the thesis illustrates how the flexibility and composition of aggregated EVs demand can be obtained with very limited information available. Once the composition of demand is available, future energy scenarios are analysed in respect to the impact of higher EVs charging rates on single phase connections at LV distribution network level. A novel planning model based on energy scenario simulations suitable for the utilization of existing assets is developed. The proposed framework can provide probabilistic risk assessment of power quality (PQ) variations that may arise due to the proliferation of significant numbers of EVs chargers. Monte Carlo (MC) based simulation is applied in this regard. This probabilistic approach is used to estimate the likely impact of EVs chargers against the extreme-case scenarios. Secondly, in relation to increased EVs penetration, dynamic reactive power reserve management through network voltage control is considered. In this regard, a generic distribution static synchronous compensator (D-STATCOM) model is adapted to achieve network voltage stability. The main emphasis is on a generic D-STATCOM modelling technique, where each individual EV charging is considered through a probability density function that is inclusive of dynamic D-STATCOM support. It demonstrates how optimal techniques can consider the demand flexibility at each bus to meet the requirement of network operator while maintaining the relevant steady state and/or dynamic performance indicators (voltage level) of the network. The results show that reactive power compensation through D-STATCOM, in the context of EVs integration, can provide continuous voltage support and thereby facilitate 90% penetration of network customers with EV connections at a normal EV charging rate (3.68 kW). The results are improved by using optimal power flow. The results suggest, if fast charging (up to 11 kW) is employed, up to 50% of network EV customers can be accommodated by utilising the optimal planning approach. During the case study, it is observed that the transformer loading is increased significantly in the presence of D-STATCOM. The transformer loading reaches approximately up to 300%, in one of the contingencies at 11 kW EV charging, so transformer upgrading is still required. Three-phase connected DSTATCOM is normally used by the DSO to control power quality issues in the network. Although, to maintain voltage level at each individual phase with three-phase connected device is not possible. So, single-phase connected D-STATCOM is used to control the voltage at each individual phase. Single-phase connected D-STATCOM is able maintain the voltage level at each individual phase at 1 p.u. This research will be of interest to the DSO, as it will provide an insight to the issues associated with higher penetration of EV chargers, present in the realization of a sustainable transport electrification agenda