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A load balancer is an essential part of many network systems. A load balancer is capable of dividing and redistributing incoming network traffic to different back end servers, thus improving reliability and performance. Existing load balancing solutions can be classified

A load balancer is an essential part of many network systems. A load balancer is capable of dividing and redistributing incoming network traffic to different back end servers, thus improving reliability and performance. Existing load balancing solutions can be classified into two categories: hardware-based or software-based. Hardware-based load balancing systems are hard to manage and force network administrators to scale up (replacing with more powerful but expensive hardware) when their system can not handle the growing traffic. Software-based solutions have a limitation when dealing with a single large TCP flow. In recent years, with the fast developments of virtualization technology, a new trend of network function virtualization (NFV) is being adopted. Instead of using proprietary hardware, an NFV network infrastructure uses virtual machines running to implement network functions such as load balancers, firewalls, etc. In this thesis, a new load balancing system is designed and evaluated. This system is high performance and flexible. It can fully utilize the bandwidth between a load balancer and back end servers compared to traditional load balancers such as HAProxy. The experimental results show that using this NFV load balancer could have $n$ ($n$ is the number of back end servers) times better performance than HAProxy. Also, an extract, transform and load (ETL) application was implemented to demonstrate that this load balancer can shorten data load time. The experiment shows that when loading a large data set (18.3GB), our load balancer needs only 28\% less time than traditional load balancer.
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    Title
    • A network function virtualization based load balancer for TCP
    Contributors
    Date Created
    2015
    Resource Type
  • Text
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    Note
    • thesis
      Partial requirement for: M.S., Arizona State University, 2015
    • bibliography
      Includes bibliographical references (pages 35-36)
    • Field of study: Computer science

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    by Jinxuan Wu

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