Guohui Wang

The Impact of Virtualization on Network Performance of Amazon EC2 Data Center

Cloud computing services allow users to lease computing resources from large scale data centers operated by service providers. Using cloud services, users can deploy a wide variety of applications dynamically and on-demand. Most cloud service providers use machine virtualization to provide flexible and cost-effective resource sharing. However, few studies have investigated the impact of machine virtualization in the cloud on networking performance. In this paper, we present a measurement study to characterize the impact of virtualization on the networking performance of the Amazon Elastic Cloud Computing (EC2) data center. We measure the processor sharing, packet delay, TCP/UDP throughput and packet loss among Amazon EC2 virtual machines. Our results show that even though the data center network is lightly utilized, virtualization can still cause significant throughput instability and abnormal delay variations. We discuss the implications of our findings on several classes of applications.

c-Through: part-time optics in data centers

Data-intensive applications that operate on large volumes of data have motivated a fresh look at the design of data center networks. The first wave of proposals focused on designing pure packet-switched networks that provide full bisection bandwidth. However, these proposals significantly increase network complexity in terms of the number of links and switches required and the restricted rules to wire them up. On the other hand, optical circuit switching technology holds a very large bandwidth advantage over packet switching technology. This fact motivates us to explore how optical circuit switching technology could benefit a data center network. In particular, we propose a hybrid packet and circuit switched data center network architecture (or HyPaC for short) which augments the traditional hierarchy of packet switches with a high speed, low complexity, rack-to-rack optical circuit-switched network to supply high bandwidth to applications. We discuss the fundamental requirements of this hybrid architecture and their design options. To demonstrate the potential benefits of the hybrid architecture, we have built a prototype system called c-Through. c-Through represents a design point where the responsibility for traffic demand estimation and traffic demultiplexing resides in end hosts, making it compatible with existing packet switches. Our emulation experiments show that the hybrid architecture can provide large benefits to unmodified popular data center applications at a modest scale. Furthermore, our experimental experience provides useful insights on the applicability of the hybrid architecture across a range of deployment scenarios.

Meridian: an SDN platform for cloud network services

As the number and variety of applications and workloads moving to the cloud grows, networking capabilities have become increasingly important. Over a brief period, networking support offered by both cloud service providers and cloud controller platforms has developed rapidly. In most of these cloud networking service models, however, users must configure a variety of network-layer constructs such as switches, subnets, and ACLs, which can then be used by their cloud applications. In this article, we argue for a service-level network model that provides higher- level connectivity and policy abstractions that are integral parts of cloud applications. Moreover, the emergence of the software-defined networking (SDN) paradigm provides a new opportunity to closely integrate application provisioning in the cloud with the network through programmable interfaces and automation. We describe the architecture and implementation of Meridian, an SDN controller platform that supports a service-level model for application networking in clouds. We discuss some of the key challenges in the design and implementation, including how to efficiently handle dynamic updates to virtual networks, orchestration of network tasks on a large set of devices, and how Meridian can be integrated with multiple cloud controllers.

Programming your network at run-time for big data applications

Recent advances of software defined networking and optical switching technology make it possible to program the network stack all the way from physical topology to flow level traffic control. In this paper, we leverage the combination of SDN controller with optical switching to explore the tight integration of application and network control. We particularly study the run-time network configuration for big data applications to jointly optimize application performance and network utilization. We use Hadoop as an example to discuss the integrated network control architecture, job scheduling, topology and routing configuration mechanisms for Hadoop jobs. Our analysis suggests that such an integrated control has great potential to improve application performance with relatively small configuration overhead. We believe our study shows early promise of achieving the long-term goal of tight network and application integration using SDN.

Measurement based analysis, modeling, and synthesis of the internet delay space

Understanding the characteristics of the Internet delay space (i.e., the all-pairs set of static round-trip propagation delays among edge networks in the Internet) is important for the design of global-scale distributed systems. For instance, algorithms used in overlay networks are often sensitive to violations of the triangle inequality and to the growth properties within the Internet delay space. Since designers of distributed systems often rely on simulation and emulation to study design alternatives, they need a realistic model of the Internet delay space. In this paper, we analyze measured delay spaces among thousands of Internet edge networks and quantify key properties that are important for distributed system design. Our analysis shows that existing delay space models do not adequately capture these important properties of the Internet delay space. Furthermore, we derive a simple model of the Internet delay space based on our analytical findings. This model preserves the relevant metrics far better than existing models, allows for a compact representation, and can be used to synthesize delay data for simulations and emulations at a scale where direct measurement and storage are impractical. We present the design of a publicly available delay space synthesizer tool called DS 2 and demonstrate its effectiveness.

Towards network triangle inequality violation aware distributed systems

Many distributed systems rely on neighbor selection mechanisms to create overlay structures that have good network performance. These neighbor selection mechanisms often assume the triangle inequality holds for Internet delays. However, the reality is that the triangle inequality is violated by Internet delays. This phenomenon creates astrange environment that confuses neighbor selection mechanisms. This paper investigates the properties of triangle inequality violation (TIV) in Internet delays, the impacts of TIV on representative neighbor selection mechanisms, specifically Vivaldi and Meridian, and avenues to reduce these impacts. We propose a TIV alert mechanism that can inform neighbor selection mechanisms to avoid the pitfalls caused by TIVs and improve their effectiveness.

Switching the optical divide: fundamental challenges for hybrid electrical/optical datacenter networks

Recent proposals to build hybrid electrical (packet-switched) and optical (circuit switched) data center interconnects promise to reduce the cost, complexity, and energy requirements of very large data center networks. Supporting realistic traffic patterns, however, exposes a number of unexpected and difficult challenges to actually deploying these systems in the wild. In this paper, we explore several of these challenges, uncovered during a year of experience using hybrid interconnects. We discuss both the problems that must be addressed to make these interconnects truly useful, and the implications of these challenges on what solutions are likely to be ultimately feasible.

Measurement-based analysis, modeling, and synthesis of the internet delay space

Understanding the characteristics of the Internet delay space (i.e., the all-pairs set of static round-trip propagation delays among edge networks in the Internet) is important for the design of global-scale distributed systems. For instance, algorithms used in overlay networks are often sensitive to violations of the triangle inequality and to the growth properties within the Internet delay space. Since designers of distributed systems often rely on simulation and emulation to study design alternatives, they need a realistic model of the Internet delay space. In this paper, we analyze measured delay spaces among thousands of Internet edge networks and quantify key properties that are important for distributed system design. Our analysis shows that existing delay space models do not adequately capture these important properties of the Internet delay space. Furthermore, we derive a simple model of the Internet delay space based on our analytical findings. This model preserves the relevant metrics far better than existing models, allows for a compact representation, and can be used to synthesize delay data for simulations and emulations at a scale where direct measurement and storage are impractical. We present the design of a publicly available delay space synthesizer tool called DS2 and demonstrate its effectiveness.

Distributed algorithms for stable and secure network coordinates

Since its inception, the concept of network coordinates has been proposed to solve a wide variety of problems such as overlay optimization, network routing, network localization, and network modeling. However, two practical problems significantly limit the applications of network coordinates today. First, how can network coordinates be stabilized without losing accuracy so that they can be cached by applications? Second, how can network coordinates be secured such that legitimate nodes coordinates are not impacted by misbehaving nodes? Although these problems have been discussed extensively, solving them in decentralized network coordinates systems remains an open problem.n This paper presents new distributed algorithms to solve the coordinates stability and security problems. For the stability problem, we propose an error elimination model that can achieve stability without hurting accuracy. A novel algorithm based on this model is presented. For the security problem, we show that recently proposed statistical detection mechanisms cannot achieve an acceptable level of security against even simple attacks. We propose to address the security problem in two parts. First, we show how the computation of coordinates can be protected by a customized Byzantine fault detection algorithm. Second, we adopt a triangle inequality violation detection algorithm to protect delay measurements. These algorithms can be integrated together to provide stable and secure network coordinates.

Virtual network diagnosis as a service

Todays cloud network platforms allow tenants to construct sophisticated virtual network topologies among their VMs on a shared physical network infrastructure. However, these platforms provide little support for tenants to diagnose problems in their virtual networks. Network virtualization hides the underlying infrastructure from tenants as well as prevents deploying existing network diagnosis tools. This paper makes a case for providing virtual network diagnosis as a service in the cloud. We identify a set of technical challenges in providing such a service and propose a Virtual Network Diagnosis (VND) framework. VND exposes abstract configuration and query interfaces for cloud tenants to troubleshoot their virtual networks. It controls software switches to collect flow traces, distributes traces storage, and executes distributed queries for different tenants for network diagnosis. It reduces the data collection and processing overhead by performing local flow capture and on-demand query execution. Our experiments validate VNDs functionality and shows its feasibility in terms of quick service response and acceptable overhead; our simulation proves the VND architecture scales to the size of a real data center network.