PTNet

An efficient and green data center network

E. Baccour, Sebti Foufou, R. Hamila, Z. Tari, A. Y. Zomaya

    Research output: Contribution to journalArticle

    Abstract

    In recent years, data centers have witnessed an exponential growth for hosting hundreds of thousands of servers as well as to accommodating a very large demand for resources. To fulfill the required level of demand, some approaches tackled network aspects so to host a huge number of servers while others focused on delivering rapid services to the clients by minimizing the path length between any two servers. In general, network devices are often designed to achieve 1:1 oversubscription. Alternatively, in a realistic data center environment, the average utilization of a network could vary between 5% and 25%, and thus the energy consumed by idle devices is wasted. This paper proposes a new parameterizable data center topology, called PTNet. PTNet offers a gradual scalability that interconnects small to large networks covering different ranges of sizes. This new interconnection network provides also a small path length between any two servers even in large sized data centers. PTNet does not only reduce path length and latency, it also uses a power-aware routing algorithm which saves up to 40% of energy with an acceptable computation time. In comparison to existing solutions (e.g. Flatnet, BCube, DCell and Fat-tree), PTNet shows substantial improvements in terms of capacity, robustness, cost-effectiveness and power efficiency: this improvement reaches up to 50% in some cases.

    Original languageEnglish (US)
    Pages (from-to)3-18
    Number of pages16
    JournalJournal of Parallel and Distributed Computing
    Volume107
    DOIs
    StatePublished - Sep 1 2017

    Fingerprint

    Data Center
    Path Length
    Servers
    Server
    Cost-effectiveness
    Interconnection Networks
    Exponential Growth
    Interconnect
    Routing algorithms
    Routing Algorithm
    Cost effectiveness
    Oils and fats
    Energy
    Latency
    Scalability
    Covering
    Topology
    Vary
    Robustness
    Resources

    Keywords

    • Average path length
    • Data center network
    • Energy saving
    • Network topology
    • Scalability

    ASJC Scopus subject areas

    • Software
    • Theoretical Computer Science
    • Hardware and Architecture
    • Computer Networks and Communications
    • Artificial Intelligence

    Cite this

    PTNet : An efficient and green data center network. / Baccour, E.; Foufou, Sebti; Hamila, R.; Tari, Z.; Zomaya, A. Y.

    In: Journal of Parallel and Distributed Computing, Vol. 107, 01.09.2017, p. 3-18.

    Research output: Contribution to journalArticle

    Baccour, E. ; Foufou, Sebti ; Hamila, R. ; Tari, Z. ; Zomaya, A. Y. / PTNet : An efficient and green data center network. In: Journal of Parallel and Distributed Computing. 2017 ; Vol. 107. pp. 3-18.
    @article{3d7d4f8a99de437a92dcc0a2533b3172,
    title = "PTNet: An efficient and green data center network",
    abstract = "In recent years, data centers have witnessed an exponential growth for hosting hundreds of thousands of servers as well as to accommodating a very large demand for resources. To fulfill the required level of demand, some approaches tackled network aspects so to host a huge number of servers while others focused on delivering rapid services to the clients by minimizing the path length between any two servers. In general, network devices are often designed to achieve 1:1 oversubscription. Alternatively, in a realistic data center environment, the average utilization of a network could vary between 5{\%} and 25{\%}, and thus the energy consumed by idle devices is wasted. This paper proposes a new parameterizable data center topology, called PTNet. PTNet offers a gradual scalability that interconnects small to large networks covering different ranges of sizes. This new interconnection network provides also a small path length between any two servers even in large sized data centers. PTNet does not only reduce path length and latency, it also uses a power-aware routing algorithm which saves up to 40{\%} of energy with an acceptable computation time. In comparison to existing solutions (e.g. Flatnet, BCube, DCell and Fat-tree), PTNet shows substantial improvements in terms of capacity, robustness, cost-effectiveness and power efficiency: this improvement reaches up to 50{\%} in some cases.",
    keywords = "Average path length, Data center network, Energy saving, Network topology, Scalability",
    author = "E. Baccour and Sebti Foufou and R. Hamila and Z. Tari and Zomaya, {A. Y.}",
    year = "2017",
    month = "9",
    day = "1",
    doi = "10.1016/j.jpdc.2017.03.007",
    language = "English (US)",
    volume = "107",
    pages = "3--18",
    journal = "Journal of Parallel and Distributed Computing",
    issn = "0743-7315",
    publisher = "Academic Press Inc.",

    }

    TY - JOUR

    T1 - PTNet

    T2 - An efficient and green data center network

    AU - Baccour, E.

    AU - Foufou, Sebti

    AU - Hamila, R.

    AU - Tari, Z.

    AU - Zomaya, A. Y.

    PY - 2017/9/1

    Y1 - 2017/9/1

    N2 - In recent years, data centers have witnessed an exponential growth for hosting hundreds of thousands of servers as well as to accommodating a very large demand for resources. To fulfill the required level of demand, some approaches tackled network aspects so to host a huge number of servers while others focused on delivering rapid services to the clients by minimizing the path length between any two servers. In general, network devices are often designed to achieve 1:1 oversubscription. Alternatively, in a realistic data center environment, the average utilization of a network could vary between 5% and 25%, and thus the energy consumed by idle devices is wasted. This paper proposes a new parameterizable data center topology, called PTNet. PTNet offers a gradual scalability that interconnects small to large networks covering different ranges of sizes. This new interconnection network provides also a small path length between any two servers even in large sized data centers. PTNet does not only reduce path length and latency, it also uses a power-aware routing algorithm which saves up to 40% of energy with an acceptable computation time. In comparison to existing solutions (e.g. Flatnet, BCube, DCell and Fat-tree), PTNet shows substantial improvements in terms of capacity, robustness, cost-effectiveness and power efficiency: this improvement reaches up to 50% in some cases.

    AB - In recent years, data centers have witnessed an exponential growth for hosting hundreds of thousands of servers as well as to accommodating a very large demand for resources. To fulfill the required level of demand, some approaches tackled network aspects so to host a huge number of servers while others focused on delivering rapid services to the clients by minimizing the path length between any two servers. In general, network devices are often designed to achieve 1:1 oversubscription. Alternatively, in a realistic data center environment, the average utilization of a network could vary between 5% and 25%, and thus the energy consumed by idle devices is wasted. This paper proposes a new parameterizable data center topology, called PTNet. PTNet offers a gradual scalability that interconnects small to large networks covering different ranges of sizes. This new interconnection network provides also a small path length between any two servers even in large sized data centers. PTNet does not only reduce path length and latency, it also uses a power-aware routing algorithm which saves up to 40% of energy with an acceptable computation time. In comparison to existing solutions (e.g. Flatnet, BCube, DCell and Fat-tree), PTNet shows substantial improvements in terms of capacity, robustness, cost-effectiveness and power efficiency: this improvement reaches up to 50% in some cases.

    KW - Average path length

    KW - Data center network

    KW - Energy saving

    KW - Network topology

    KW - Scalability

    UR - http://www.scopus.com/inward/record.url?scp=85018347537&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85018347537&partnerID=8YFLogxK

    U2 - 10.1016/j.jpdc.2017.03.007

    DO - 10.1016/j.jpdc.2017.03.007

    M3 - Article

    VL - 107

    SP - 3

    EP - 18

    JO - Journal of Parallel and Distributed Computing

    JF - Journal of Parallel and Distributed Computing

    SN - 0743-7315

    ER -