Computer networks lack a general control paradigm, as traditional networks do not provide any network-wide management abstractions. As a result, each new function (such as routing) must provide its own state distribution, element discovery, and failure recovery mechanisms. We believe this lack of a common control platform has significantly hindered the development of flexible, reliable and feature-rich network control planes.To address this, we present Onix, a platform on top of which a network control plane can be implemented as a distributed system. Control planes written within Onix operate on a global view of the network, and use basic state distribution primitives provided by the platform. Thus Onix provides a general API for control plane implementations, while allowing them to make their own trade-offs among consistency, durability, and scalability.

/pdf/onix-a-distributed-control-platform-for-large-scale-2nyb613mj2.pdf

Onix: a distributed control platform for large-scale production networks

We study the virtual machine live migration (LM) and disaster recovery (DR) from a networking perspective, considering long-distance networks, for example, between data centers. These networks are usually constrained by limited available bandwidth, increased latency and congestion, or high cost of use when dedicated network resources are used, while their exact characteristics cannot be controlled. LM and DR present several challenges due to the large amounts of data that need to be transferred over long-distance networks, which increase with the number of migrated or protected resources. In this context, our work presents the way LM and DR are currently being performed and their operation in long-distance networking environments, discussing related issues and bottlenecks and surveying other works. We also present the way networks are evolving today and the new technologies and protocols (e.g., software-defined networking, or SDN, and flexible optical networks) that can be used to boost the efficiency of LM and DR over long distances. Traffic redirection in a long-distance environment is also an important part of the whole equation, since it directly affects the transparency of LM and DR. Related works and solutions both from academia and the industry are presented.

Survey: Live Migration and Disaster Recovery over Long-Distance Networks

A novel method for logically routing a packet between a source machine that is in a first logical domain and a destination machine that is in a second logical domain is described. The method configures a managed switching element as a second-level managed switching element. The method configures a router in a host that includes the second-level managed switching element. The method communicatively couples the second-level managed switching element with the router. The method causes the router to route a packet when the router receives a packet from the first logical domain that is addressed to the second logical domain.

Distributed logical l3 routing

A survey on virtual machine migration and server consolidation frameworks for cloud data centers

Virtual machine technology and the ease with which VMs can be migrated within the LAN, has changed the scope of resource management from allocating resources on a single server to manipulating pools of resources within a data center. We expect WAN migration of virtual machines to likewise transform the scope of provisioning compute resources from a single data center to multiple data centers spread across the country or around the world. In this paper we present the CloudNet architecure as a cloud framework consisting of cloud computing platforms linked with a VPN based network infrastructure to provide seamless and secure connectivity between enterprise and cloud data center sites. To realize our vision of efficiently pooling geographically distributed data center resources, CloudNet provides optimized support for live WAN migration of virtual machines. Specifically, we present a set of optimizations that minimize the cost of transferring storage and virtual machine memory during migrations over low bandwidth and high latency Internet links. We evaluate our system on an operational cloud platform distributed across the continental US. During simultaneous migrations of four VMs between data centers in Texas and Illinois, CloudNet's optimizations reduce memory migration time by 65% and lower bandwidth consumption for the storage and memory transfer by 19GB, a 50% reduction.

/pdf/cloudnet-dynamic-pooling-of-cloud-resources-by-live-wan-33mwt6z5am.pdf

CloudNet: dynamic pooling of cloud resources by live WAN migration of virtual machines

Network operation is inherently complex because it consists of many functions such as routing, firewalling, VPN provisioning, traffic load-balancing, network maintenance, etc. To cope with this, network designers have created modular components to handle each function. Unfortunately, in reality, unavoidable dependencies exist between some of the components and they may interact accidentally. At the same time, some policies are realized by compositions of different components, but the methods of composition are ad hoc and fragile. In other words, there is no single mechanism for systematically governing the interactions between the various components. To address these problems, we propose a clean-late system called Maestro. Maestro is an “operating system” that orchestrates the network control applications that govern the behavior of a network, and directly controls the underlying network devices. Maestro provides abstractions for the modular implementation of network control applications, and is the first system to address the fundamental problems originating from the concurrent operations of network control applications, namely communication between applications, scheduling of application executions, feedback management, concurrency management, and network state transition management. As the This research was sponsored by the NSF under grant numbers CNS0520280, CNS-0721990, CNS-033162, CNS-0448546 and by Microsoft Corporation. Views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of NSF, Microsoft Corporation, or the U.S. government. networking industry moves towards building directly controllable devices like the OpenFlow Switch, we believe Maestro can become a common platform.

http://www.cs.rice.edu/~eugeneng/papers/Maestro-TR.pdf

The Preliminary Design and Implementation of the Maestro Network Control Platform

The emerging open cloud computing model will provide users with great freedom to dynamically migrate virtualized computing services to, from, and between clouds over the wide-area. While this freedom leads to many potential benefits, the running services must be minimally disrupted by the migration. Unfortunately, current solutions for wide-area migration incur too much disruption as they will significantly slow down storage I/O operations during migration. The resulting increase in service latency could be very costly to a business. This paper presents a novel storage migration scheduling algorithm that can greatly improve storage I/O performance during wide-area migration. Our algorithm is unique in that it considers individual virtual machine's storage I/O workload such as temporal locality, spatial locality and popularity characteristics to compute an efficient data transfer schedule. Using a fully implemented system on KVM and a trace-driven framework, we show that our algorithm provides large performance benefits across a wide range of popular virtual machine workloads.

/pdf/workload-aware-live-storage-migration-for-clouds-4armutwkmi.pdf

Workload-aware live storage migration for clouds

A virtual machine is migrated between a source cloud and a destination cloud A temporary storage is mounted to a partition management firmware of the source cloud and to a partition management firmware of the destination cloud A first storage location migration migrates the virtual machine from the source cloud to the at least one temporary storage A second storage location migration migrates the virtual machine from the at least one temporary storage to final destination storage of the destination cloud The temporary storage is then unmounted from the partition management firmware of the source cloud and from the partition management firmware of the destination cloud

Enablement and acceleration of live and near-live migration of virtual machines and their associated storage across networks

Live migration of virtual machines is a key management function in cloud computing. Unfortunately, no live migration progress management system exists in the state-of-theart, leading to (1) guesswork over how long a migration might take and the inability to schedule dependent tasks accordingly; (2) unacceptable application degradation when application components become split over distant cloud datacenters for an arbitrary period during migration; (3) inability to tradeoff application performance and migration time e.g. to finish migration later for less impact on application performance. Pacer is the first migration progress management system that solves these problems. Pacer's techniques are based on robust and lightweight run-time measurements of system and workload characteristics, efficient and accurate analytic models for progress predictions, and online adaptation to maintain user-defined migration objectives for coordinated and timely migrations. Our experiments on a local testbed and on Amazon EC2 show that Pacer is highly effective under a range of application workloads and network conditions.

Pacer: A Progress Management System for Live Virtual Machine Migration in Cloud Computing

Multi-tier applications are widely deployed in today's virtualized cloud computing environments. At the same time, management operations in these virtualized environments, such as load balancing, hardware maintenance, workload consolidation, etc., often make use of live virtual machine (VM) migration to control the placement of VMs. Although existing solutions are able to migrate a single VM efficiently, little attention has been devoted to migrating related VMs in multi-tier applications. Ignoring the relatedness of VMs during migration can lead to serious application performance degradation. This paper formulates the multi-tier application migration problem, and presents a new communication-impact-driven coordinated approach, as well as a system called COMMA that realizes this approach. Through extensive testbed experiments, numerical analyses, and a demonstration of COMMA on Amazon EC2, we show that this approach is highly effective in minimizing migration's impact on multi-tier applications' performance.

http://www.cs.rice.edu/~eugeneng/papers/comma-tr13-08.pdf

Jie Zheng

Papers

The Preliminary Design and Implementation of the Maestro Network Control Platform

Workload-aware live storage migration for clouds

Enablement and acceleration of live and near-live migration of virtual machines and their associated storage across networks

Pacer: A Progress Management System for Live Virtual Machine Migration in Cloud Computing

COMMA: coordinating the migration of multi-tier applications