The Experts below are selected from a list of 74904 Experts worldwide ranked by ideXlab platform

Albert Greenberg - One of the best experts on this subject based on the ideXlab platform.

  • eyeq practical network Performance Isolation at the edge
    Networked Systems Design and Implementation, 2013
    Co-Authors: Vimalkumar Jeyakumar, Mohammad Alizadeh, David Mazieres, Balaji Prabhakar, Albert Greenberg
    Abstract:

    The datacenter network is shared among untrusted tenants in a public cloud, and hundreds of services in a private cloud. Today we lack fine-grained control over network bandwidth partitioning across tenants. In this paper we present EyeQ, a simple and practical system that provides tenants with bandwidth guarantees as if their endpoints were connected to a dedicated switch. To realize this goal, EyeQ leverages the high bisection bandwidth in a datacenter fabric and enforces admission control on traffic, regardless of the tenant transport protocol. We show that this pushes bandwidth contention to the network's edge, enabling EyeQ to support end-to-end minimum bandwidth guarantees to tenant end-points in a simple and scalable manner at the servers. EyeQ requires no changes to applications and is deployable with support from the network available today. We evaluate EyeQ with an efficient software implementation at 10Gb/s speeds using unmodified applications and adversarial traffic patterns. Our evaluation demonstrates EyeQ's promise of predictable network Performance Isolation. For instance, even with an adversarial tenant with bursty UDP traffic, EyeQ is able to maintain the 99.9th percentile latency for a collocated memcached application close to that of a dedicated deployment.

  • vl2 a scalable and flexible data center network
    Communications of The ACM, 2011
    Co-Authors: Albert Greenberg, James R Hamilton, Navendu Jain, Srikanth Kandula, Parantap Lahiri, David A Maltz, Parveen Patel, Sudipta Sengupta
    Abstract:

    To be agile and cost effective, data centers must allow dynamic resource allocation across large server pools. In particular, the data center network should provide a simple flat abstraction: it should be able to take any set of servers anywhere in the data center and give them the illusion that they are plugged into a physically separate, noninterfering Ethernet switch with as many ports as the service needs. To meet this goal, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, Performance Isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end system--based address resolution to scale to large server pools without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 s---sustaining a rate that is 94% of the maximum possible.

  • Sharing the data center network
    Nsdi, 2011
    Co-Authors: Alan Shieh, Albert Greenberg, Srikanth Kandula, Changhoon Kim, Bikas Saha
    Abstract:

    While today's data centers are multiplexed across many non-cooperating applications, they lack effective means to share their network. Relying on TCP's congestion control, as we show from experiments in production data centers, opens up the network to denial of service attacks and Performance interference. We present Seawall, a network bandwidth allocation scheme that divides network capacity based on an administrator-specified policy. Seawall computes and enforces allocations by tunneling traffic through congestion controlled, point to multipoint, edge to edge tunnels. The resulting allocations remain stable regardless of the number of flows, protocols, or destinations in the application's traffic mix. Unlike alternate proposals, Seawall easily supports dynamic policy changes and scales to the number of applications and churn of today's data centers. Through evaluation of a prototype, we show that Seawall adds little overhead and achieves strong Performance Isolation.

  • seawall Performance Isolation for cloud datacenter networks
    IEEE International Conference on Cloud Computing Technology and Science, 2010
    Co-Authors: Alan Shieh, Albert Greenberg, Srikanth Kandula, Changhoon Kim
    Abstract:

    While today's virtual datacenters have hypervisor based mechanisms to partition compute resources between the tenants co-located on an end host, they provide little control over how tenants shore the network. This opens cloud applications to interference from other tenants, resulting in unpredictable Performance and exposure to denial of service attacks. This paper explores the design space for achieving Performance Isolation between tenants. We find that existing schemes for enterprise datacenters suffer from at least one of these problems: they cannot keep up with the numbers of tenants and the VM churn observed in cloud datacenters; they impose static bandwidth limits to obtain Isolation at the cost of network utilization; they require switch and/or NIC modifications; they cannot tolerate malicious tenants and compromised hypervisors. We propose Seawall, an edge-based solution, that achieves max-min fairness across tenant VMs by sending traffic through congestion-controlled, hypervisor-to-hypervisor tunnels.

  • vl2 a scalable and flexible data center network
    ACM Special Interest Group on Data Communication, 2009
    Co-Authors: Albert Greenberg, James R Hamilton, Navendu Jain, Srikanth Kandula, Parantap Lahiri, David A Maltz, Parveen Patel, Sudipta Sengupta
    Abstract:

    To be agile and cost effective, data centers should allow dynamic resource allocation across large server pools. In particular, the data center network should enable any server to be assigned to any service. To meet these goals, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, Performance Isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end-system based address resolution to scale to large server pools, without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 seconds - sustaining a rate that is 94% of the maximum possible.

Sudipta Sengupta - One of the best experts on this subject based on the ideXlab platform.

  • flashblox achieving both Performance Isolation and uniform lifetime for virtualized ssds
    File and Storage Technologies, 2017
    Co-Authors: Jian Huang, Sudipta Sengupta, Anirudh Badam, Laura Marie Caulfield, Suman Nath, Bikash Sharma, Moinuddin K Qureshi
    Abstract:

    A longstanding goal of SSD virtualization has been to provide Performance Isolation between multiple tenants sharing the device. Virtualizing SSDs, however, has traditionally been a challenge because of the fundamental tussle between resource Isolation and the lifetime of the device - existing SSDs aim to uniformly age all the regions of flash and this hurts Isolation. We propose utilizing flash parallelism to improve Isolation between virtual SSDs by running them on dedicated channels and dies. Furthermore, we offer a complete solution by also managing the wear. We propose allowing the wear of different channels and dies to diverge at fine time granularities in favor of Isolation and adjusting that imbalance at a coarse time granularity in a principled manner. Our experiments show that the new SSD wears uniformly while the 99th percentile latencies of storage operations in a variety of multi-tenant settings are reduced by up to 3.1x compared to software isolated virtual SSDs.

  • vl2 a scalable and flexible data center network
    Communications of The ACM, 2011
    Co-Authors: Albert Greenberg, James R Hamilton, Navendu Jain, Srikanth Kandula, Parantap Lahiri, David A Maltz, Parveen Patel, Sudipta Sengupta
    Abstract:

    To be agile and cost effective, data centers must allow dynamic resource allocation across large server pools. In particular, the data center network should provide a simple flat abstraction: it should be able to take any set of servers anywhere in the data center and give them the illusion that they are plugged into a physically separate, noninterfering Ethernet switch with as many ports as the service needs. To meet this goal, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, Performance Isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end system--based address resolution to scale to large server pools without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 s---sustaining a rate that is 94% of the maximum possible.

  • vl2 a scalable and flexible data center network
    ACM Special Interest Group on Data Communication, 2009
    Co-Authors: Albert Greenberg, James R Hamilton, Navendu Jain, Srikanth Kandula, Parantap Lahiri, David A Maltz, Parveen Patel, Sudipta Sengupta
    Abstract:

    To be agile and cost effective, data centers should allow dynamic resource allocation across large server pools. In particular, the data center network should enable any server to be assigned to any service. To meet these goals, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, Performance Isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end-system based address resolution to scale to large server pools, without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 seconds - sustaining a rate that is 94% of the maximum possible.

Marco Caccamo - One of the best experts on this subject based on the ideXlab platform.

  • Memory Bandwidth Management for Efficient Performance Isolation in Multi-Core Platforms
    IEEE Transactions on Computers, 2016
    Co-Authors: Rodolfo Pellizzoni, Marco Caccamo
    Abstract:

    Memory bandwidth in modern multi-core platforms is highly variable for many reasons and it is a big challenge in designing real-time systems as applications are increasingly becoming more memory intensive. In this work, we proposed, designed, and implemented an efficient memory bandwidth reservation system, that we call MemGuard. MemGuard separates memory bandwidth in two parts: guaranteed and best effort. It provides bandwidth reservation for the guaranteed bandwidth for temporal Isolation, with efficient reclaiming to maximally utilize the reserved bandwidth. It further improves Performance by exploiting the best effort bandwidth after satisfying each core's reserved bandwidth. MemGuard is evaluated with SPEC2006 benchmarks on a real hardware platform, and the results demonstrate that it is able to provide memory Performance Isolation with minimal impact on overall throughput.

  • MemGuard: Memory bandwidth reservation system for efficient Performance Isolation in multi-core platforms
    2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium (RTAS), 2013
    Co-Authors: Rodolfo Pellizzoni, Marco Caccamo
    Abstract:

    Memory bandwidth in modern multi-core platforms is highly variable for many reasons and is a big challenge in designing real-time systems as applications are increasingly becoming more memory intensive. In this work, we proposed, designed, and implemented an efficient memory bandwidth reservation system, that we call MemGuard. MemGuard distinguishes memory bandwidth as two parts: guaranteed and best effort. It provides bandwidth reservation for the guaranteed bandwidth for temporal Isolation, with efficient reclaiming to maximally utilize the reserved bandwidth. It further improves Performance by exploiting the best effort bandwidth after satisfying each core's reserved bandwidth. MemGuard is evaluated with SPEC2006 benchmarks on a real hardware platform, and the results demonstrate that it is able to provide memory Performance Isolation with minimal impact on overall throughput.

Vimalkumar Jeyakumar - One of the best experts on this subject based on the ideXlab platform.

  • eyeq practical network Performance Isolation at the edge
    Networked Systems Design and Implementation, 2013
    Co-Authors: Vimalkumar Jeyakumar, Mohammad Alizadeh, David Mazieres, Balaji Prabhakar, Albert Greenberg
    Abstract:

    The datacenter network is shared among untrusted tenants in a public cloud, and hundreds of services in a private cloud. Today we lack fine-grained control over network bandwidth partitioning across tenants. In this paper we present EyeQ, a simple and practical system that provides tenants with bandwidth guarantees as if their endpoints were connected to a dedicated switch. To realize this goal, EyeQ leverages the high bisection bandwidth in a datacenter fabric and enforces admission control on traffic, regardless of the tenant transport protocol. We show that this pushes bandwidth contention to the network's edge, enabling EyeQ to support end-to-end minimum bandwidth guarantees to tenant end-points in a simple and scalable manner at the servers. EyeQ requires no changes to applications and is deployable with support from the network available today. We evaluate EyeQ with an efficient software implementation at 10Gb/s speeds using unmodified applications and adversarial traffic patterns. Our evaluation demonstrates EyeQ's promise of predictable network Performance Isolation. For instance, even with an adversarial tenant with bursty UDP traffic, EyeQ is able to maintain the 99.9th percentile latency for a collocated memcached application close to that of a dedicated deployment.

  • eyeq practical network Performance Isolation for the multi tenant cloud
    USENIX conference on Hot Topics in Cloud Ccomputing, 2012
    Co-Authors: Vimalkumar Jeyakumar, Mohammad Alizadeh, David Mazieres, Balaji Prabhakar
    Abstract:

    The shared multi-tenant nature of the cloud has raised serious concerns about its security and Performance for high valued services. Of many shared resources like CPU, memory, etc., the network is pivotal for distributed applications. Benign, or perhaps malicious traffic interference between tenants can cause significant Performance degradation that hurts Performance of applications, and hence, impacts their revenue. Network Performance Isolation is particularly hard because of the distributed nature of the problem, and the short (few RTT) timescales at which they manifest themselves. This problem is further exacerbated by the large number of competing entities in the cloud, and their volatile traffic patterns. In this paper, we motivate the design of our system called EyeQ, with the goal of providing predictable network Performance to tenants. The enabler for EyeQ is the availability of high bisection bandwidth in data centers. The key insight is that by leaving a headroom of (say) 10% of access link bandwidth, EyeQ simplifies dealing with potentially a global contention problem into one that is mostly local, at the sender and receiver. This allows EyeQ to enforce predictable network sharing completely at the end hosts, with minimum support from the physical network.

Srikanth Kandula - One of the best experts on this subject based on the ideXlab platform.

  • vl2 a scalable and flexible data center network
    Communications of The ACM, 2011
    Co-Authors: Albert Greenberg, James R Hamilton, Navendu Jain, Srikanth Kandula, Parantap Lahiri, David A Maltz, Parveen Patel, Sudipta Sengupta
    Abstract:

    To be agile and cost effective, data centers must allow dynamic resource allocation across large server pools. In particular, the data center network should provide a simple flat abstraction: it should be able to take any set of servers anywhere in the data center and give them the illusion that they are plugged into a physically separate, noninterfering Ethernet switch with as many ports as the service needs. To meet this goal, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, Performance Isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end system--based address resolution to scale to large server pools without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 s---sustaining a rate that is 94% of the maximum possible.

  • Sharing the data center network
    Nsdi, 2011
    Co-Authors: Alan Shieh, Albert Greenberg, Srikanth Kandula, Changhoon Kim, Bikas Saha
    Abstract:

    While today's data centers are multiplexed across many non-cooperating applications, they lack effective means to share their network. Relying on TCP's congestion control, as we show from experiments in production data centers, opens up the network to denial of service attacks and Performance interference. We present Seawall, a network bandwidth allocation scheme that divides network capacity based on an administrator-specified policy. Seawall computes and enforces allocations by tunneling traffic through congestion controlled, point to multipoint, edge to edge tunnels. The resulting allocations remain stable regardless of the number of flows, protocols, or destinations in the application's traffic mix. Unlike alternate proposals, Seawall easily supports dynamic policy changes and scales to the number of applications and churn of today's data centers. Through evaluation of a prototype, we show that Seawall adds little overhead and achieves strong Performance Isolation.

  • seawall Performance Isolation for cloud datacenter networks
    IEEE International Conference on Cloud Computing Technology and Science, 2010
    Co-Authors: Alan Shieh, Albert Greenberg, Srikanth Kandula, Changhoon Kim
    Abstract:

    While today's virtual datacenters have hypervisor based mechanisms to partition compute resources between the tenants co-located on an end host, they provide little control over how tenants shore the network. This opens cloud applications to interference from other tenants, resulting in unpredictable Performance and exposure to denial of service attacks. This paper explores the design space for achieving Performance Isolation between tenants. We find that existing schemes for enterprise datacenters suffer from at least one of these problems: they cannot keep up with the numbers of tenants and the VM churn observed in cloud datacenters; they impose static bandwidth limits to obtain Isolation at the cost of network utilization; they require switch and/or NIC modifications; they cannot tolerate malicious tenants and compromised hypervisors. We propose Seawall, an edge-based solution, that achieves max-min fairness across tenant VMs by sending traffic through congestion-controlled, hypervisor-to-hypervisor tunnels.

  • vl2 a scalable and flexible data center network
    ACM Special Interest Group on Data Communication, 2009
    Co-Authors: Albert Greenberg, James R Hamilton, Navendu Jain, Srikanth Kandula, Parantap Lahiri, David A Maltz, Parveen Patel, Sudipta Sengupta
    Abstract:

    To be agile and cost effective, data centers should allow dynamic resource allocation across large server pools. In particular, the data center network should enable any server to be assigned to any service. To meet these goals, we present VL2, a practical network architecture that scales to support huge data centers with uniform high capacity between servers, Performance Isolation between services, and Ethernet layer-2 semantics. VL2 uses (1) flat addressing to allow service instances to be placed anywhere in the network, (2) Valiant Load Balancing to spread traffic uniformly across network paths, and (3) end-system based address resolution to scale to large server pools, without introducing complexity to the network control plane. VL2's design is driven by detailed measurements of traffic and fault data from a large operational cloud service provider. VL2's implementation leverages proven network technologies, already available at low cost in high-speed hardware implementations, to build a scalable and reliable network architecture. As a result, VL2 networks can be deployed today, and we have built a working prototype. We evaluate the merits of the VL2 design using measurement, analysis, and experiments. Our VL2 prototype shuffles 2.7 TB of data among 75 servers in 395 seconds - sustaining a rate that is 94% of the maximum possible.