Towards IQ-Appliances: Quality-awareness in Information Virtualization

Our research addresses two important problems that arise in modern large-scale distributed systems: 1. The necessity to virtualize their data flows by applying actions such as filtering, format translation, coalescing or splitting, etc. 2. The desire to separate such actions from application level logic, to make it easier for future service-oriented codes to inter-operate in diverse and dynamic environments. This research considers the runtimes of the `information appliances used for these purposes, particularly with respect to their ability to provide diverse levels of Quality of Service (QoS) in lieu of dynamic application behaviors and the consequent changes in the resource needs of their data flows. Our specific contribution is the enrichment of these runtimes with methods for QoS-awareness, thereby giving them the ability to deliver desired levels of QoS even under sudden requirement changes IQ-appliances. For experimental evaluation, we enrich a prototype implementation of an IQ-appliance, based on the Intel IXP network processor, with the additional functionality needed to guarantee QoS constraints for diverse data streams. Measurements demonstrate the feasibility and utility of the approach. Further, we enhance the Self-Virtualized Network Interface developed in previous work from our group with QoS awareness and demonstrate the importance of such functionality in end-to-end virtualized infrastructures.M.S.Committee Chair: Schwan, Karsten; Committee Member: Ferri, Bonnie Heck; Committee Member: Gavrilovska, Ada; Committee Member: Yalamanchili, Sudhaka

Automated Scalable Management of Data Center Networks

Data centers today are growing in size and becoming harder to manage. It is more important than ever to concentrate on management of such large networks, and arrive at simple yet efficient designs that involve minimum manual intervention. Reducing network management costs can lead to better service availability, response times and increase return on investment. In this dissertation, we focus on three aspects of data center network management, the network fabric, policy enforcement and fault localization. There are inherent challenges due to scale in each of these areas. Firstly, simple, plug-and-play networks are known not to scale, leading network operators to often stitch complex interior and exterior gateway protocols to connect large data centers. Second, network isolation policies can become too huge for network hardware to handle as the number of applications multiplexed on a single data center increase. Thirdly diagnosis can become extremely hard because of the sheer number of components interacting for a service to be successful. Localizing the fault is often left to knowledgeable operators who work together in war rooms to track down and fight problems. Such an approach can be time consuming, tedious and reduce availability. To address these challenges, we propose to compose the data center management system with these three contributions : (i) PortLand : A scalable layer 2 network fabric that completely eliminates loops and broadcast storms and combines the best elements of traditional layer 2 and layer 3 network fabrics: plug-and-play, support for scale, mobility and path diversity. (ii) FasTrak : A policy enforcement system that moves network isolation rules between server software and network hardware so that performance sensitive traffic is not subject to unnecessary overheads and latency. FasTrak enables performance sensitive applications to move into multi- tenant clouds and supports their requirements. (iii) Gestalt : A fault localization algorithm, developed from first principles, that can operate in large scale networks and beats existing localization algorithms on localization accuracy or time or both. We have prototyped and evaluated each of these systems and believe that these can be easily implemented with minor modifications to data center switches and end host

Towards IQ-Appliances: Quality-awareness in Information Virtualization

Our research addresses two important problems that arise in modern large-scale distributed systems: (1) the necessity to virtualize their data flows by applying actions such as filtering, format translation, coalescing or splitting, etc., and (2) the desire to separate such actions from enterprise applications' business logic, to make it easier for future service-oriented codes to interoperate in diverse and dynamic environments. This paper considers the runtimes of the `information appliances' used for these purposes, particularly with respect to their ability to provide diverse levels of Quality of Service (QoS) in lieu of dynamic application behaviors and the consequent changes in the resource needs of their data flows. Our specific contribution is the enrichment of these runtimes with methods for QoS-awareness, thereby giving them the ability to deliver desired levels of QoS even under sudden requirement changes -- IQ-appliances. For experimental evaluation, we enrich a prototype implementation of an IQ-appliance, based on the Intel IXP network processor with the additional functionality needed to guarantee QoS constraints for diverse data streams. Measurements demonstrate the feasibility and utility of the approach

A Randomized Algorithm for Label Assignment in Dynamic Networks

A basic problem in distributed computing has to do with assigning unique labels --- that is, names or addresses --- to network elements. Some approaches to solving this problem include using static assignment (e.g., MAC addresses), or using a centralized authority (e.g., DHCP). In this paper, we present an approach that is suitable for dynamic environments: where the rules constraining the label choices depend on the network topology, which in turn can change. This problem arose in the context of automatic address assignment in large-scale data center networks, and so we consider issues such as the scalability of message load and convergence time. We give a new algorithm, called the Decider/Chooser Protocol, and show its use in the assignment of labels in data center networks. We evaluate the correctness of the Decider/Chooser Protocol through proofs and model checking, and explore its performance via mathematical analysis and simulation. Through this evaluation, we find that the Decider/Chooser Protocol is well-suited for label assignment in the data center environment.Pre-2018 CSE ID: CS2013-099

PortLand: A Scalable Fault-Tolerant Layer 2 Data Center Network Fabric

This paper considers the requirements for a scalable, easily manageable, fault-tolerant, and efficient data center network fabric. Trends in multi-core processors, end-host virtualization, and commodities of scale are pointing to future single-site data centers with millions of virtual end points. Existing layer 2 and layer 3 network protocols face some combination of limitations in such a setting: lack of scalability, difficult management, inflexible communication, or limited support for virtual machine migration. To some extent, these limitations may be inherent for Ethernet/IP style protocols when trying to support arbitrary topologies. We observe that data center networks are often managed as a single logical network fabric with a known baseline topology and growth model. We leverage this observation in the design and implementation of PortLand, a scalable, fault tolerant layer 2 routing and forwarding protocol for data center environments. Through our implementation and evaluation, we show that PortLand holds promise for supporting a “plug-and-play” large-scale, data center network