LAZY MULTI-LEVEL DYNAMIC TRAFFIC LOAD BALANCING PROTOCOL FOR DATA CENTER (LMDTLB)

被引:0
|
作者
Yasari, Abidulkarim K., I [1 ]
Abbas, Abdulkarim D. [2 ]
Atee, Hayfaa A. [3 ]
Latiff, L. A. [4 ]
Dziyauddin, Rudzidatul A. [4 ]
Hammood, Dalal A. [5 ]
机构
[1] Al Muthanna Univ, Engn Coll, Samawah, Al Muthanna, Iraq
[2] Al Maaref Univ Coll, Ramadi, Iraq
[3] Middle Tech Univ MTU, Inst Adm Rusafa, Baghdad, Iraq
[4] UTM Razak Fac Technol & Informat, Kuala Lumpur, Malaysia
[5] Middle Tech Univ MTU, Elect Engn Tech Coll, Baghdad, Iraq
来源
关键词
Datacenter; Data mining; Flow completion time; Tail latency; Traffic load;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The minimization of tail latency is especially crucial in user interfacing services and fast responding apps. The literature on the datacenter load balancing protocols contains of many protocols but works discussing tail latency are scarce. This work proposes a novel variant of the Multi-Level Dynamic Traffic Load Balancing (MDTLB) protocol for a datacenter called the Lazy MDTLB or LMDTLB, which uses the concept of delaying the rerouting decision by a few packets for every flow that require path changes to provide the network with the time to ensure that a terrible path condition is not temporary. An evaluation of the state-of-the-art protocols of load balancing was conducted to determine the best performing one for curtailing tail latency involving flows of data mining, web search, and general flows. The findings confirmed that LMDTLB was the most efficient in minimizing tail latency and flow completion time (FCT).
引用
收藏
页码:2439 / 2453
页数:15
相关论文
共 50 条
  • [11] Traffic load balancing in data center networks: A comprehensive survey
    Liu, Guisheng
    Liu, Yong
    Meng, Qian
    Wang, Ben
    Chen, Kefei
    Shen, Zhonghua
    COMPUTER SCIENCE REVIEW, 2025, 57
  • [12] Network Traffic Load Balancing Protocol
    Amelina, Natalia
    Chernov, Andrey
    Granichin, Oleg
    Ivanskiy, Yury
    Len, Irina
    2020 EUROPEAN CONTROL CONFERENCE (ECC 2020), 2020, : 906 - 910
  • [13] Traffic Load Balancing based on Probabilistic Routing in Data Center Networks
    Wang, Fu
    Yan, Fulong
    Xue, Xuwei
    Liu, Bo
    Zhang, Lijia
    Zhang, Qi
    Xin, Xiangjun
    Calabretta, Nicola
    2020 INTERNATIONAL CONFERENCE ON OPTICAL NETWORK DESIGN AND MODELING (ONDM), 2020,
  • [14] Load balancing multi-zone applications on a heterogeneous cluster with multi-level parallelism
    Wong, P
    Jin, HQ
    Becker, J
    ISPDC 2004: THIRD INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED COMPUTING/HETEROPAR '04: THIRD INTERNATIONAL WORKSHOP ON ALGORITHMS, MODELS AND TOOLS FOR PARALLEL COMPUTING ON HETEROGENEOUS NETWORKS, PROCEEDINGS, 2004, : 388 - 393
  • [15] Dynamic Distributed Multi-Path Aided Load Balancing for Optical Data Center Networks
    Wang, Fu
    Yao, Haipeng
    Zhang, Qi
    Wang, Jingjing
    Gao, Ran
    Guo, Dong
    Guizani, Mohsen
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2022, 19 (02): : 991 - 1005
  • [16] MLBLM: A Multi-Level Load Balancing mechanism in agent-based grid
    Salehi, Mohsen Amini
    Deldari, Hossain
    Dorri, Bahare Mokarram
    DISTRIBUTED COMPUTING AND NETWORKING, PROCEEDINGS, 2006, 4308 : 157 - 162
  • [17] Static Load Balancing for Multi-level Monte Carlo Finite Volume Solvers
    Sukys, Jonas
    Mishra, Siddhartha
    Schwab, Christoph
    PARALLEL PROCESSING AND APPLIED MATHEMATICS, PT I, 2012, 7203 : 245 - 254
  • [18] Adaptive Load Balancing for Massively Parallel Multi-Level Monte Carlo Solvers
    Sukys, Jonas
    PARALLEL PROCESSING AND APPLIED MATHEMATICS (PPAM 2013), PT I, 2014, 8384 : 47 - 56
  • [19] Multipath-aware TCP for Data Center Traffic Load-balancing
    Xia, Yu
    Wu, Jinsong
    Xia, Jingwen
    Wang, Ting
    Mao, Sun
    2021 IEEE/ACM 29TH INTERNATIONAL SYMPOSIUM ON QUALITY OF SERVICE (IWQOS), 2021,
  • [20] Efficient Load Balancing for Multicast Traffic in Data Center Networks Using SDN
    Nithin, V
    Rathod, A.
    Badarla, V.
    Humernbrum, T.
    Gorlatch, S.
    2018 10TH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS & NETWORKS (COMSNETS), 2018, : 113 - 120