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Application Layer

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Yuval Shavitt – One of the best experts on this subject based on the ideXlab platform.

  • Approximation and heuristic algorithms for minimum delay ApplicationLayer multicast trees
    Proceedings – IEEE INFOCOM, 2004
    Co-Authors: Eli Brosh, Yuval Shavitt

    Abstract:

    ApplicationLayer Multicast algorithm, applied networking

Suman Banerjee – One of the best experts on this subject based on the ideXlab platform.

  • scalable Application Layer multicast
    ACM Special Interest Group on Data Communication, 2002
    Co-Authors: Suman Banerjee, Bobby Bhattacharjee, Christopher Kommareddy

    Abstract:

    We describe a new scalable ApplicationLayer multicast protocol, specifically designed for low-bandwidth, data streaming Applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the ApplicationLayer multicast peers and can support a number of different data delivery trees with desirable properties.We present extensive simulations of both our protocol and the Narada ApplicationLayer multicast protocol over Internet-like topologies. Our results show that for groups of size 32 or more, our protocol has lower link stress (by about 25%), improved or similar end-to-end latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic.Finally, we present results from our wide-area testbed in which we experimented with 32-100 member groups distributed over 8 different sites. In our experiments, average group members established and maintained low-latency paths and incurred a maximum packet loss rate of less than 1% as members randomly joined and left the multicast group. The average control overhead during our experiments was less than 1 Kbps for groups of size 100.

  • SIGCOMM – Scalable Application Layer multicast
    ACM SIGCOMM Computer Communication Review, 2002
    Co-Authors: Suman Banerjee, Bobby Bhattacharjee, Christopher Kommareddy

    Abstract:

    We describe a new scalable ApplicationLayer multicast protocol, specifically designed for low-bandwidth, data streaming Applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the ApplicationLayer multicast peers and can support a number of different data delivery trees with desirable properties.We present extensive simulations of both our protocol and the Narada ApplicationLayer multicast protocol over Internet-like topologies. Our results show that for groups of size 32 or more, our protocol has lower link stress (by about 25%), improved or similar end-to-end latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic.Finally, we present results from our wide-area testbed in which we experimented with 32-100 member groups distributed over 8 different sites. In our experiments, average group members established and maintained low-latency paths and incurred a maximum packet loss rate of less than 1% as members randomly joined and left the multicast group. The average control overhead during our experiments was less than 1 Kbps for groups of size 100.

  • Analysis of the NICE Application Layer Multicast Protocol
    , 2002
    Co-Authors: Suman Banerjee, Bobby Bhattacharjee

    Abstract:

    Application Layer multicast protocols organize a set of hosts into an overlay tree for data delivery. Each host on the overlay peers with a subset of other hosts. Since ap- plication Layer multicast relies only on an underlying unicast architecture, multiple copies of the same packet can be car- ried by a single physical link or node on the overlay. The stress at a link or node is definedas the number of identical copies of a packet carried by that link or node. Stretch is an- other important metric in Application Layer multicast, which measures the relative increase in delay incurred by the over- lay path between pairs of members with respect to the direct unicast path. In this paper we study the NICE Application Layer multicast protocol to quantify and study the tradeoff between these two important metrics — stress and stretch in scalably building Application Layer multicast paths.

Christopher Kommareddy – One of the best experts on this subject based on the ideXlab platform.

  • scalable Application Layer multicast
    ACM Special Interest Group on Data Communication, 2002
    Co-Authors: Suman Banerjee, Bobby Bhattacharjee, Christopher Kommareddy

    Abstract:

    We describe a new scalable ApplicationLayer multicast protocol, specifically designed for low-bandwidth, data streaming Applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the ApplicationLayer multicast peers and can support a number of different data delivery trees with desirable properties.We present extensive simulations of both our protocol and the Narada ApplicationLayer multicast protocol over Internet-like topologies. Our results show that for groups of size 32 or more, our protocol has lower link stress (by about 25%), improved or similar end-to-end latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic.Finally, we present results from our wide-area testbed in which we experimented with 32-100 member groups distributed over 8 different sites. In our experiments, average group members established and maintained low-latency paths and incurred a maximum packet loss rate of less than 1% as members randomly joined and left the multicast group. The average control overhead during our experiments was less than 1 Kbps for groups of size 100.

  • SIGCOMM – Scalable Application Layer multicast
    ACM SIGCOMM Computer Communication Review, 2002
    Co-Authors: Suman Banerjee, Bobby Bhattacharjee, Christopher Kommareddy

    Abstract:

    We describe a new scalable ApplicationLayer multicast protocol, specifically designed for low-bandwidth, data streaming Applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the ApplicationLayer multicast peers and can support a number of different data delivery trees with desirable properties.We present extensive simulations of both our protocol and the Narada ApplicationLayer multicast protocol over Internet-like topologies. Our results show that for groups of size 32 or more, our protocol has lower link stress (by about 25%), improved or similar end-to-end latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic.Finally, we present results from our wide-area testbed in which we experimented with 32-100 member groups distributed over 8 different sites. In our experiments, average group members established and maintained low-latency paths and incurred a maximum packet loss rate of less than 1% as members randomly joined and left the multicast group. The average control overhead during our experiments was less than 1 Kbps for groups of size 100.