Improving Software Middleboxes and Datacenter Task Schedulers
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
Ghodsi, A., Zaharia, M., Hindman, B., Konwinski, A., Shenker, S., and Stoica, I. (2011). Dominant resource fairness: Fair allocation of multiple resource types. In USENIX NSDI.
Reiss, C., Tumanov, A., Ganger, G. R., Katz, R. H., and Kozuch, M. A. (2012). Hetero- geneity and dynamicity of clouds at scale: Google trace analysis. In ACM SoCC.
Sadok, H., Campista, M. E. M., and Costa, L. H. M. K. (2018a). A case for spraying packets in software middleboxes. In ACM HotNets.
Sadok, H., Campista, M. E. M., and Costa, L. H. M. K. (2018b). O passado também importa: Um mecanismo de alocação justa de múltiplos tipos de recursos ao longo do tempo. In SBRC.
Sekar, V., Egi, N., Ratnasamy, S., Reiter, M. K., and Shi, G. (2012). Design and imple- mentation of a consolidated middlebox architecture. In USENIX NSDI.