Scalable high-capacity high-fan-out optical networks for constrained environments

The investigations carried out as part of the dissertation address the architecture and application of optical access networks pertaining to high-capacity and high fan-out applications such as in-flight entertainment (IFE) and video-gaming environment. High-capacity and high-fan-out optical networks have a multitude of applications such as expo-centers, train area networks (TAN), video gaming competitions and other applications that require large number of connected users. For the purpose of keeping the scope of the dissertation within limit however, we have concentrated this work on IFE systems. IFE systems present unique challenges at physical and application layers alike. In-flight entertainment (IFE) systems have been a part of passengers' experience for a while now. Currently available systems can be considered a bare-bone at best due to lack of adequate performance and support infrastructure. According to electronic arts (EA), one of the largest developers of video games in the world, an increase in demand for electronically distributed video games will exceed boxed games in just a matter of few years. This also shows a shifting trend towards the electronic distribution of video game content as opposed to physical distribution. Against the same backdrop, the dissertation project involved defining a novel system architecture and capacity based on the requirements for development of novel physical layer architecture utilizing optical networks for high-speed and high-fan-out distribution of content. At the physical layer of the stacked communication model a novel high-fan-out optical network was proposed and simulated for high data-rates. Having defined the physical layer, protocol stack was identified through rigorous observations and data traffic analysis from a large set of traffic traces obtained from various sources in order to understand the distribution and behavior of video game related traffic compared with regular internet traffic. Data requirements were laid down based on analysis keeping in mind that bandwidth requirements are increasing at a tremendous pace and that the network should be able to support future high-definition and 3D gaming as well. Based on the data analysis, analytical models and latency analysis models were also developed for bandwidth allocation in the high-fan-out network architectures. Analytical modeling gives an insight into the performance of the technique as a function of incoming traffic whereas latency analysis exposes the delay factors involved in running the technique over time. "State-full bandwidth allocation" (SBA) was proposed as part of the network layer design for upstream transmission. The novel technique involves keeping state information from previous states for future allocation. The results show that the proposed high-fan-out high-capacity physical layer architecture can be used to distribute video-gaming related content. Also, latency analysis and design and development of a novel SBA algorithm were carried out. Results were quiet promising, in that; a large number of users can be supported on the same single channel network. SBA criteria can be applied to multi-channel networks such as the physical architecture proposed / simulated and investigated in this project. In summary, the project involved design of a novel physical layer; network layer and protocol stack of the communication model and verification by simulations and mathematical modeling while adhering to application layer requirements

Dynamic bandwidth allocation algorithm for long reach passive optical network

Next generation broadband access networks are gaining more interests from many key players in this field. The demands for longer reach and higher bandwidth are among the driving factors for such network as it can reach wider area up to 100 km, even beyond; has enhanced bandwidth capacity and transmission speed, but with low cost and energy consumption. One promising candidate is long reach passive optical network, a simplified network with reduced number of network elements, equipment interfaces, and even nodes; which leads to a significant reduction in the network’s capital expenditure and operational expenditure. Outcome of an extended reach often results in increased propagation delay of dynamic bandwidth allocation messages exchange between the optical line terminals and optical network units, leading to the degradations of bandwidth allocation and quality of service support. Therefore, an effective bandwidth allocation algorithm with appropriate service interval setup for a long reach network is proposed to ensure the delay is maintained under ITU-T G.987.1 standard requirement. An existing algorithm is improved in terms of service interval so that it can perform well beyond 100 km. Findings show that the improved algorithm can reduce the mean delay of high priority traffic classes for distance up to 140 km

Cloud radio access network fronthaul solution using optimized dynamic bandwidth allocation algorithm

In order to address the challenges that have come with the exploding demand for higher speed, traffic growth and mobile wireless devices, Mobile network operators have decided to move to the notion of small cells based on cloud radio access network. The merits of cloud based RAN includes the ease of infrastructure deployment and network management as well as the fact that its performance are optimized and it is cost effective the merits of cloud based RAN includes the ease of infrastructure deployment and network management as well as the fact that its performance are optimized and it is cost effective. Notwithstanding, cloud radio access network comes with so many strict requirements to be fulfilled for its fronthaul network. In this paper, we have presented these requirements for a 5G fronthaul network. Particular interest on the time division multiplex passive optical network’s challenge of latency was treated by proposing an optimized version of the round robin dynamic bandwidth allocation algorithm. Results obtained show an improvement in the latency of the original algorithm which meets the fronthaul requirement. Other test parameters like jitter and BER were also improved by our proposed optimized algorithm

A Modified Deficit Weighted Round Robin traffic Scheduling Algorithm for GPON Networks

In this paper, we propose the modified deficit weighted round robin (MDWRR) traffic scheduling algorithm for Gigabit Passive Optical Network (GPON), which guarantees the real-time priority traffic. The proposed scheduling algorithm is a variation of the deficit weighted round robin (DWRR) algorithm and it assures the highest priority traffic transmission with minimization of delay. WRR algorithm to be aware of bandwidth and improves the fairness. But for certain traffic types, fairness is not the desired behavior. To achieve predictable service for sensitive, real-time traffic, a priority level for scheduling needs to be introduced. By enabling strict priority, or by offering several priority levels and using DWRR scheduling between queues with the same priority levels, service assurance with regards to delay and loss protection can be achieved for demanding traffic types, such as voice and real-time broadcasting. By offering several priority levels and using DWRR scheduling between queues with the same priority levels, service assurance with regards to delay and loss protection can be achieved for demanding traffic types, such as voice and real-time broadcasting

A Fully Bidirectional Optical Network With Latency Monitoring Capability for the Distribution of Timing-Trigger and Control Signals in High-Energy Physics Experiments

The present paper discusses recent advances on a Passive Optical Network inspired Timing-Trigger and Control scheme for the future upgrade of the TTC system installed in the LHC experiments' and more specifically the currently known as TTCex to TTCrx link. The timing PON is implemented with commercially available FPGAs and 1-Gigabit Ethernet PON transceivers and provides a fixed latency gigabit downlink that can carry level-1 trigger accept decisions and commands as well as an upstream link for feedback from the front-end electronics

Multi-Granular Optical Cross-Connect: Design, Analysis, and Demonstration

A fundamental issue in all-optical switching is to offer efficient and cost-effective transport services for a wide range of bandwidth granularities. This paper presents multi-granular optical cross-connect (MG-OXC) architectures that combine slow (ms regime) and fast (ns regime) switch elements, in order to support optical circuit switching (OCS), optical burst switching (OBS), and even optical packet switching (OPS). The MG-OXC architectures are designed to provide a cost-effective approach, while offering the flexibility and reconfigurability to deal with dynamic requirements of different applications. All proposed MG-OXC designs are analyzed and compared in terms of dimensionality, flexibility/reconfigurability, and scalability. Furthermore, node level simulations are conducted to evaluate the performance of MG-OXCs under different traffic regimes. Finally, the feasibility of the proposed architectures is demonstrated on an application-aware, multi-bit-rate (10 and 40 Gbps), end-to-end OBS testbed

Measurement-Driven Algorithm and System Design for Wireless and Datacenter Networks

The growing number of mobile devices and data-intensive applications pose unique challenges for wireless access networks as well as datacenter networks that enable modern cloud-based services. With the enormous increase in volume and complexity of traffic from applications such as video streaming and cloud computing, the interconnection networks have become a major performance bottleneck. In this thesis, we study algorithms and architectures spanning several layers of the networking protocol stack that enable and accelerate novel applications and that are easily deployable and scalable. The design of these algorithms and architectures is motivated by measurements and observations in real world or experimental testbeds. In the first part of this thesis, we address the challenge of wireless content delivery in crowded areas. We present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast. AMuSe is based on accurate receiver feedback and incurs a small control overhead. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes which periodically send information about the channel quality to the multicast sender. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe's feedback to optimally tune the physical layer multicast rate. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. We implemented the AMuSe system on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi nodes. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions. Further, our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. As an example application, MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality. Next, we specifically focus on ensuring high Quality of Experience (QoE) for video streaming over WiFi multicast. We formulate the problem of joint adaptation of multicast transmission rate and video rate for ensuring high video QoE as a utility maximization problem and propose an online control algorithm called DYVR which is based on Lyapunov optimization techniques. We evaluated the performance of DYVR through analysis, simulations, and experiments using a testbed composed of Android devices and o the shelf APs. Our evaluation shows that DYVR can ensure high video rates while guaranteeing a low but acceptable number of segment losses, buffer underflows, and video rate switches. We leverage the lessons learnt from AMuSe for WiFi to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance. DyMo employs eMBMS for broadcasting instructions which indicate the reporting rates as a function of the observed Quality of Service (QoS) for each UE. This simple feedback mechanism collects very limited QoS reports which can be used for network optimization. We evaluated the performance of DyMo analytically and via simulations. DyMo infers the optimal eMBMS settings with extremely low overhead, while meeting strict QoS requirements under different UE mobility patterns and presence of network component failures. In the second part of the thesis, we study datacenter networks which are key enablers of the end-user applications such as video streaming and storage. Datacenter applications such as distributed file systems, one-to-many virtual machine migrations, and large-scale data processing involve bulk multicast flows. We propose a hardware and software system for enabling physical layer optical multicast in datacenter networks using passive optical splitters. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Our evaluation shows that the optical multicast architecture can achieve higher throughput and lower latency than IP multicast and peer-to-peer multicast schemes with lower switching energy consumption. Finally, we study the problem of congestion control in datacenter networks. Quantized Congestion Control (QCN), a switch-supported standard, utilizes direct multi-bit feedback from the network for hardware rate limiting. Although QCN has been shown to be fast-reacting and effective, being a Layer-2 technology limits its adoption in IP-routed Layer 3 datacenters. We address several design challenges to overcome QCN feedback's Layer- 2 limitation and use it to design window-based congestion control (QCN-CC) and load balancing (QCN-LB) schemes. Our extensive simulations, based on real world workloads, demonstrate the advantages of explicit, multi-bit congestion feedback, especially in a typical environment where intra-datacenter traffic with short Round Trip Times (RTT: tens of s) run in conjunction with web-facing traffic with long RTTs (tens of milliseconds)