Evaluation of data centre networks and future directions

Traffic forecasts predict a more than threefold increase in the global datacentre workload in coming years, caused by the increasing adoption of cloud and data-intensive applications. Consequently, there has been an unprecedented need for ultra-high throughput and minimal latency. Currently deployed hierarchical architectures using electronic packet switching technologies are costly and energy-inefficient. Very high capacity switches are required to satisfy the enormous bandwidth requirements of cloud datacentres and this limits the overall network scalability. With the maturity of photonic components, turning to optical switching in data centres is a viable option to accommodate greater bandwidth and network flexibility while potentially minimising the latency, cost and power consumption. Various DCN architectures have been proposed to date and this thesis includes a comparative analysis of such electronic and optical topologies to judge their suitability based on network performance parameters and cost/energy effectiveness, while identifying the challenges faced by recent DCN infrastructures. An analytical Layer 2 switching model is introduced that can alleviate the simulation scalability problem and evaluate the performance of the underlying DCN architecture. This model is also used to judge the variation in traffic arrival/offloading at the intermediate queueing stages and the findings are used to derive closed form expressions for traffic arrival rates and delay. The results from the simulated network demonstrate the impact of buffering and versubscription and reveal the potential bottlenecks and network design tradeoffs. TCP traffic forms the bulk of current DCN workload and so the designed network is further modified to include TCP flows generated from a realistic traffic generator for assessing the impact of Layer 4 congestion control on the DCN performance with standard TCP and datacentre specific TCP protocols (DCTCP). Optical DCN architectures mostly concentrate on core-tier switching. However, substantial energy saving is possible by introducing optics in the edge tiers. Hence, a new approach to optical switching is introduced using Optical ToR switches which can offer better delay performance than commodity switches of similiar size, while having far less power dissipation. An all-optical topology has been further outlined for the efficient implementation of the optical switch meeting the future scalability demands

Future PON Data Centre Networks

Significant research efforts have been devoted over the last decade to design efficient data centre networks. However, major concerns are still raised about the power consumption of data centres and its impact on global warming in the first place and on the electricity bill of data centres in the second place. Passive Optical Network (PON) technology with its proven performance in residential access networks can provide energy efficient, high capacity, low cost, scalable, and highly elastic solutions to support connectivity inside modern data centres. Here, we focus on introducing PONs in the architecture of data centres to resolve many issues in current data centre designs such as high cost and high power consumption resulting from the large number of access and aggregation switches needed to interconnect hundreds of thousands of servers. PONs can also overcome the problems of switch oversubscription and unbalanced traffic in data centres where PON architectures and protocols have historically been optimised to deal with these problems and handle bursty traffic efficiently. In this thesis, five novel PON data centre designs are proposed and compared to facilitate intra and inter rack communications. In addition to maximising the use of only passive optical devices, other challenges have to be addressed by these designs including off-loading the inter-rack traffic from the Optical Line Terminal (OLT) switch to avoid undesired power consumption and delays, facilitating multi-path routing, and reducing or eliminating the need for expensive tuneable lasers. The Scalability of the proposed architectures in terms of efficiently accommodating hundreds of thousands of servers is discussed. CAPEX and energy consumption of the proposed architectures are also investigated and savings compared to conventional architectures, such as the Fat-Tree and BCube, are demonstrated. The Routing and Wavelength Assignment (RWA) in intra and inter rack communication and the resource provisioning needed to cater for different applications that can be hosted in data centre are optimised using Mixed Integer Linear Programming (MILP) models to minimise the PON designs power consumption. Furthermore, real-time energy-efficient routing and resource provisioning algorithms are developed. In addition to optimising the power consumption, delay is also considered for the delay sensitive applications that can be hosted in the proposed data centre architectures. To further reduce power consumption and overcome issues related to link oversubscription and multi-path routing, Software Defined Network (SDN) based design is proposed

Multistage Packet-Switching Fabrics for Data Center Networks

Recent applications have imposed stringent requirements within the Data Center Network (DCN) switches in terms of scalability, throughput and latency. In this thesis, the architectural design of the packet-switches is tackled in different ways to enable the expansion in both the number of connected endpoints and traffic volume. A cost-effective Clos-network switch with partially buffered units is proposed and two packet scheduling algorithms are described. The first algorithm adopts many simple and distributed arbiters, while the second approach relies on a central arbiter to guarantee an ordered packet delivery. For an improved scalability, the Clos switch is build using a Network-on-Chip (NoC) fabric instead of the common crossbar units. The Clos-UDN architecture made with Input-Queued (IQ) Uni-Directional NoC modules (UDNs) simplifies the input line cards and obviates the need for the costly Virtual Output Queues (VOQs). It also avoids the need for complex, and synchronized scheduling processes, and offers speedup, load balancing, and good path diversity. Under skewed traffic, a reliable micro load-balancing contributes to boosting the overall network performance. Taking advantage of the NoC paradigm, a wrapped-around multistage switch with fully interconnected Central Modules (CMs) is proposed. The architecture operates with a congestion-aware routing algorithm that proactively distributes the traffic load across the switching modules, and enhances the switch performance under critical packet arrivals. The implementation of small on-chip buffers has been made perfectly feasible using the current technology. This motivated the implementation of a large switching architecture with an Output-Queued (OQ) NoC fabric. The design merges assets of the output queuing, and NoCs to provide high throughput, and smooth latency variations. An approximate analytical model of the switch performance is also proposed. To further exploit the potential of the NoC fabrics and their modularity features, a high capacity Clos switch with Multi-Directional NoC (MDN) modules is presented. The Clos-MDN switching architecture exhibits a more compact layout than the Clos-UDN switch. It scales better and faster in port count and traffic load. Results achieved in this thesis demonstrate the high performance, expandability and programmability features of the proposed packet-switches which makes them promising candidates for the next-generation data center networking infrastructure

Multistage Packet-Switching Fabrics for Data Center Networks

Recent applications have imposed stringent requirements within the Data Center Network (DCN) switches in terms of scalability, throughput and latency. In this thesis, the architectural design of the packet-switches is tackled in different ways to enable the expansion in both the number of connected endpoints and traffic volume. A cost-effective Clos-network switch with partially buffered units is proposed and two packet scheduling algorithms are described. The first algorithm adopts many simple and distributed arbiters, while the second approach relies on a central arbiter to guarantee an ordered packet delivery. For an improved scalability, the Clos switch is build using a Network-on-Chip (NoC) fabric instead of the common crossbar units. The Clos-UDN architecture made with Input-Queued (IQ) Uni-Directional NoC modules (UDNs) simplifies the input line cards and obviates the need for the costly Virtual Output Queues (VOQs). It also avoids the need for complex, and synchronized scheduling processes, and offers speedup, load balancing, and good path diversity. Under skewed traffic, a reliable micro load-balancing contributes to boosting the overall network performance. Taking advantage of the NoC paradigm, a wrapped-around multistage switch with fully interconnected Central Modules (CMs) is proposed. The architecture operates with a congestion-aware routing algorithm that proactively distributes the traffic load across the switching modules, and enhances the switch performance under critical packet arrivals. The implementation of small on-chip buffers has been made perfectly feasible using the current technology. This motivated the implementation of a large switching architecture with an Output-Queued (OQ) NoC fabric. The design merges assets of the output queuing, and NoCs to provide high throughput, and smooth latency variations. An approximate analytical model of the switch performance is also proposed. To further exploit the potential of the NoC fabrics and their modularity features, a high capacity Clos switch with Multi-Directional NoC (MDN) modules is presented. The Clos-MDN switching architecture exhibits a more compact layout than the Clos-UDN switch. It scales better and faster in port count and traffic load. Results achieved in this thesis demonstrate the high performance, expandability and programmability features of the proposed packet-switches which makes them promising candidates for the next-generation data center networking infrastructure

Optical Burst Switching (OBS), Current and Future Perspectives

This paper intends to take a tour of the evolution of optical networking with emphasis on the Optical Burst Switching (OBS) technology, which is currently in a state of development and research, and its current and future perspectives, that aim to visualize this paradigm as a promising solution for the new generation Optical Internet, which could be adopted for the transport of information at the core level and within the data centers, in order to minimize electronic processing to overcome the bottleneck of current routers compared to the high transmission speeds achieved at the optical level, and in turn routed and switched large volumes of information assembled in bursts in the fully optical domain

Climbing Up Cloud Nine: Performance Enhancement Techniques for Cloud Computing Environments

With the transformation of cloud computing technologies from an attractive trend to a business reality, the need is more pressing than ever for efficient cloud service management tools and techniques. As cloud technologies continue to mature, the service model, resource allocation methodologies, energy efficiency models and general service management schemes are not yet saturated. The burden of making this all tick perfectly falls on cloud providers. Surely, economy of scale revenues and leveraging existing infrastructure and giant workforce are there as positives, but it is far from straightforward operation from that point. Performance and service delivery will still depend on the providers’ algorithms and policies which affect all operational areas. With that in mind, this thesis tackles a set of the more critical challenges faced by cloud providers with the purpose of enhancing cloud service performance and saving on providers’ cost. This is done by exploring innovative resource allocation techniques and developing novel tools and methodologies in the context of cloud resource management, power efficiency, high availability and solution evaluation. Optimal and suboptimal solutions to the resource allocation problem in cloud data centers from both the computational and the network sides are proposed. Next, a deep dive into the energy efficiency challenge in cloud data centers is presented. Consolidation-based and non-consolidation-based solutions containing a novel dynamic virtual machine idleness prediction technique are proposed and evaluated. An investigation of the problem of simulating cloud environments follows. Available simulation solutions are comprehensively evaluated and a novel design framework for cloud simulators covering multiple variations of the problem is presented. Moreover, the challenge of evaluating cloud resource management solutions performance in terms of high availability is addressed. An extensive framework is introduced to design high availability-aware cloud simulators and a prominent cloud simulator (GreenCloud) is extended to implement it. Finally, real cloud application scenarios evaluation is demonstrated using the new tool. The primary argument made in this thesis is that the proposed resource allocation and simulation techniques can serve as basis for effective solutions that mitigate performance and cost challenges faced by cloud providers pertaining to resource utilization, energy efficiency, and client satisfaction

Optimisation for Optical Data Centre Switching and Networking with Artificial Intelligence

Cloud and cluster computing platforms have become standard across almost every domain of business, and their scale quickly approaches $\mathbf{O}(10^6)$ servers in a single warehouse. However, the tier-based opto-electronically packet switched network infrastructure that is standard across these systems gives way to several scalability bottlenecks including resource fragmentation and high energy requirements. Experimental results show that optical circuit switched networks pose a promising alternative that could avoid these. However, optimality challenges are encountered at realistic commercial scales. Where exhaustive optimisation techniques are not applicable for problems at the scale of Cloud-scale computer networks, and expert-designed heuristics are performance-limited and typically biased in their design, artificial intelligence can discover more scalable and better performing optimisation strategies. This thesis demonstrates these benefits through experimental and theoretical work spanning all of component, system and commercial optimisation problems which stand in the way of practical Cloud-scale computer network systems. Firstly, optical components are optimised to gate in $\approx 500 ps$ and are demonstrated in a proof-of-concept switching architecture for optical data centres with better wavelength and component scalability than previous demonstrations. Secondly, network-aware resource allocation schemes for optically composable data centres are learnt end-to-end with deep reinforcement learning and graph neural networks, where $3\times$ less networking resources are required to achieve the same resource efficiency compared to conventional methods. Finally, a deep reinforcement learning based method for optimising PID-control parameters is presented which generates tailored parameters for unseen devices in $\mathbf{O}(10^{-3}) s$. This method is demonstrated on a market leading optical switching product based on piezoelectric actuation, where switching speed is improved $>20\%$ with no compromise to optical loss and the manufacturing yield of actuators is improved. This method was licensed to and integrated within the manufacturing pipeline of this company. As such, crucial public and private infrastructure utilising these products will benefit from this work