Made available in DSpace on 2016-06-02T19:07:10Z (GMT). No. of bitstreams: 1 SANDRI_Marcus_2015.pdf: 2702736 bytes, checksum: 227059d931183af24cbcab4cc7a1eb19 (MD5) Previous issue date: 2015-06-10 / Financiadora de Estudos e Projetos / This Master s thesis shows a solution for splitting MPTCP subflows in an Openflow network. MPTCP is a network protocol designed to branch a single TCP connection into many subflows. The main idea is to forward subflows th- rough disjointed paths. Commonly, ECMP protocol is adopted together to split flows through distinct paths. Nevertheless, there are many issues that shows that ECMP is not pareto-optimal, such as: ECMP can easily set two subflows from the same TCP connection on the same path and/or set a distinct forward and back forward route to the same subflow. To solve these issues, it is designed MultiFlow, a module which uses a controller for guarantee multipath routing by setting subflows from the same MPTCP connection so that such subflows are forwarded through distinct paths. MultiFlow is evaluated in experimentation where is analyzed throughput and resilience comparing it with Spanning-Tree (STP) and ECMP. The experiments were done by using Mininet: An OpenFlow emulator for experimenting with a set of topologies. / Esta dissertação apresenta uma solução para distribuir subfluxos Multipath-TCP (MPTCP) em redes OpenFlow. MPTCP é um protocolo desenvolvido para derivar um fluxo TCP em diversos subfluxos e estes serem roteados por caminhos disjuntos ao longo da rede. Convencionalmente, adota-se em conjunto o protocolo Equal-Cost Multipath (ECMP), do qual distribui fluxos de todos os tipos de protocolos ao longo de uma rede com múltiplos caminhos. Entretanto, existem diversas questões que mostram que o ECMP não é um protocolo altamente eficiente. Dentre elas, o ECMP comumente pode alocar dois subfluxos de uma mesma conexão em um mesmo caminho e/ou distribuir um caminho de ida diferente do caminho de volta. A fim de solucionar estes problemas, é desenvolvido o MultiFlow, um módulo para o controlador POX a fim de garantir que subfluxos pertencentes a uma mesma conexão MPTCP possam ser encaminhados em caminhos disjuntos, em uma rede OpenFlow. MultiFlow é validado em experimentos de desempenho onde são analisados taxa de transferência (throughput) e resiliência em experimentos comparativos com os protocolos Spanning-Tree (STP) e ECMP. Para isso, utilizamos o Mininet: Um emulador de rede OpenFlow que permite a criação de diferentes topologias para experimentação.

The conventional battery for genotoxicity testing is not well-suited to assessing the large number of chemicals needing evaluation. Traditional in vitro tests lack throughput capacity, provide little mechanistic information, and have poor specificity in predicting in vivo genotoxicity. The Health Canada GeneTox21 research program is developing a multi-endpoint platform for modernized in vitro genotoxicity assessment. The GeneTox21 assays include the TGx-DDI transcriptomic biomarker (i.e., 64-gene expression signature to identify DNA damage-inducing (DDI) substances), the MicroFlow® assay (i.e., a flow cytometry-based micronucleus (MN) test), and the MultiFlow® assay (i.e., a multiplexed flow cytometry-based reporter assay that yields mechanism-of-action (MoA) information). As part of GeneTox21 development, the objective of this study was to investigate the utility of the TGx-DDI transcriptomic biomarker, multiplexed with the MicroFlow® and MultiFlow® assays, as an integrated testing strategy for screening data-poor substances prioritized by Health Canada’s New Substances Assessment and Control Bureau. Human lymphoblastoid TK6 cells were exposed to 3 control and 10 data-poor substances, using a 6-point concentration range. Cells were exposed for 4 hours with or without exogenous metabolic activation. Gene expression profiling was conducted using the targeted TempO-SeqTM assay, and the TGx-DDI classifier was applied to the dataset. Classifications were compared with those based on the MicroFlow® and MultiFlow® assays. Benchmark Concentration (BMC) modeling was used for potency ranking. The results of the integrated hazard calls indicate that five data-poor compounds are genotoxic in vitro, causing DNA damage via a clastogenic MoA, and one is positive via a pan-genotoxic MoA. Two compounds are likely irrelevant positives in the MN test; two are considered possibly genotoxic causing DNA damage via an ambiguous MoA. From quantitative analyses of concentration-response data, we observed nearly identical potency rankings for each assay with two main potency groups being observed. This ranking was maintained when all endpoint BMCs were converted into a single score using the Toxicological Prioritization (ToxPi) approach. Overall, this study contributes to the establishment of a modernized approach for effective genotoxicity assessment and chemical prioritization for further regulatory scrutiny. We conclude that integration of the TGx-DDI biomarker with other GeneTox21 assays is an effective NAM-based strategy for genotoxicity assessment of data-poor compounds.