Improving Software Middleboxes and Datacenter Task Schedulers

  • Hugo Sadok UFRJ
  • Miguel Elias M. Campista UFRJ
  • Luis Henrique M. K. Costa UFRJ


Shared systems have contributed to the popularity ofmany technolo- gies. However, these systems often confront a common challenge: to ensure that resources are fairly divided without compromising utilization efficiency. In this master’s thesis we look at this problem in two distinct systems—software mid- dleboxes and datacenter task schedulers. We first present Sprayer, a system that uses packet spraying to load balance packets to cores in software middleboxes. Our design eliminates the imbalance problems of per-flow solutions and ad- dresses the new challenges ofhandling shared flow states that come with packet spraying. Then, we present Stateful Dominant Resource Fairness (SDRF), a task scheduling policy for datacenters that looks at past allocations and en- forces fairness in the long run. SDRF reduces users’ waiting time on average and improves fairness by increasing the number of completed tasks for users with lower demands, with small impact on high-demand users

Palavras-chave: Middleboxes, escalonadores de tarefa, justiça


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SADOK, Hugo; CAMPISTA, Miguel Elias M.; COSTA, Luis Henrique M. K.. Improving Software Middleboxes and Datacenter Task Schedulers. In: CONCURSO DE TESES E DISSERTAÇÕES (CTD), 32. , 2019, Belém. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . ISSN 2763-8820. DOI: