Nowadays, cloud platforms usually offer several types of Virtual Machines (VMs) which have different guarantees in terms of availability and volatility, provisioning the same resource through multiple pricing models. For instance, in the Amazon EC2 cloud, the user pays per hour for on-demand VMs while spot VMs are unused instances available for a lower price. Despite the monetary advantages, a spot VM can be terminated or hibernated by EC2 at any moment. In this talk, we present the Hibernation-Aware Dynamic Scheduler (HADS), to schedule applications composed of independent tasks (bag-of-tasks) with deadline constraints in both hibernation-prone spot VMs (for cost sake) and on-demand VMs. We also consider the problem of temporal failures, that occurs when a spot VM hibernates, and does not resume within a time that guarantees the application's deadline. Our dynamic scheduling approach aims at minimizing the monetary costs of bag-of-tasks applications execution, respecting its deadline even in the presence of hibernation. It is also able to avoid temporal failures, by using task migration and work-stealing techniques. Experimental results with real executions using Amazon EC2 VMs confirm the effectiveness of our scheduling when compared with on-demand VM only based approaches, in terms of monetary costs and execution times. It is also shown that our strategy can tolerate temporal failures.
Short bioLucia Drummond obtained her D.Sc. in Systems Engineering and Computer Science from the Federal University of Rio deJaneiro, Brazil, in 1994, where she took part of the group which developed the first Brazilian parallel computer. She is in the Department of Computer Science of the Fluminense Federal University (UFF) since 1989, where she is now Full Professor. She currently acts in undergraduate and graduate program, advising a number of master and doctoral students. She is a Level 1 Researcher at CNPq (a Brazilian Research Agency), possessing more than 100 publications in journals and proceedings of national and international conferences. Her research interests are parallel and distributed computing, including theory and applications. She has been invited to give talks in Université Paris-Sud, École de Mines, Université d’Avignon et des Pays du Vaucluse, where she has also co-advised Ph.D. students.
A causal broadcast ensures that messages are delivered to all nodes (processes) preserving causal relation of the messages. We have proposed [ICPP 2018] a causal broadcast protocol for distributed systems whose nodes are logically organized in a virtual hypercube-like topology called Vcube. Messages are broadcast by dynamically building spanning trees rooted in the message's source node. By using multiple trees, the contention bottleneck problem of a single root spanning tree approach is avoided. Furthermore, different trees can intersect at some node. Hence, by taking advantage of both the out-of-order reception of causally related messages at a node and these paths intersections, a node can delay to one or more of its children in the tree, the forwarding of the messages whose some causal dependencies it knows that the children in question cannot satisfy yet. Such a delay does not induce any overhead. Experimental evaluation conducted on top of PeerSim simulator confirms the communication effectiveness of our causal broadcast protocol in terms of latency and message traffic reduction.
Short bioLuciana Arantes é graduada em ciência da computação pela Unicamp, fez seu mestrado na Escola da Politécnica da Universidade de São Paulo e doutorado na Universidade Pierre et Marie Curie (UPMC), Paris, França. Desde 2011 é professora/pesquisadora da Faculdade de Ciências da Universidade Sorbonne (ex-UPMC) e membro do grupo Delys, uma cooperação entre o LIP6 (Laboratoire d’Informatique de Paris 6) e o INRIA. O foco da sua pesquisa é propor e adaptar algoritmos distribuídos, para ambientes, heterogêneos, dinâmicos e sujeitos a falhas como, por exemplo, redes móveis, Cloud, P2P e Grids.
Luan Teylo is a Ph.D. student at the Institute of Computing at Fluminense Federal University (UFF). He graduated in Computer Science from Mato Grosso Federal University (UFMT) in 2015 and obtained the M.S. degree in Computer Science from UFF in 2017. His research interests includes distributed algorithms, cloud computing and optimization problems. By now, his main activities are related to scheduling problems in cloud computing environments.