Francesc Solsona

A queuing theory model for cloud computing

The ability to deliver guaranteed QoS (Quality of Service) is crucial for the commercial success of cloud platforms. This paper presents a model based on queuing theory to study computer service QoS in cloud computing. Cloud platforms are modeled with an open Jackson network that can be used to determine and measure the QoS guarantees the cloud can offer regarding the response time. The analysis can be performed according to different parameters, such as the arrival rate of customer services and the number and service rate of processing servers, among others. Detailed results for the model are presented. When scaling the system and depending on the types of bottleneck in the system, we show how our model can provide us with the best option to guarantee QoS. The results obtained confirm the usefulness of the model presented for designing real cloud computing systems.

The cloud paradigm applied to e-Health.

BackgroundCloud computing is a new paradigm that is changing how enterprises, institutions and people understand, perceive and use current software systems. With this paradigm, the organizations have no need to maintain their own servers, nor host their own software. Instead, everything is moved to the cloud and provided on demand, saving energy, physical space and technical staff. Cloud-based system architectures provide many advantages in terms of scalability, maintainability and massive data processing.MethodsWe present the design of an e-health cloud system, modelled by an M/M/m queue with QoS capabilities, i.e. maximum waiting time of requests.ResultsDetailed results for the model formed by a Jackson network of two M/M/m queues from the queueing theory perspective are presented. These results show a significant performance improvement when the number of servers increases.ConclusionsPlatform scalability becomes a critical issue since we aim to provide the system with high Quality of Service (QoS). In this paper we define an architecture capable of adapting itself to different diseases and growing numbers of patients. This platform could be applied to the medical field to greatly enhance the results of those therapies that have an important psychological component, such as addictions and chronic diseases.

CheNER: Chemical Named Entity Recognizer

Motivation: Chemical named entity recognition is used to automatically identify mentions to chemical compounds in text and is the basis for more elaborate information extraction. However, only a small number of applications are freely available to identify such mentions. Particularly challenging and useful is the identification of International Union of Pure and Applied Chemistry (IUPAC) chemical compounds, which due to the complex morphology of IUPAC names requires more advanced techniques than that of brand names. Results: We present CheNER, a tool for automated identification of systematic IUPAC chemical mentions. We evaluated different systems using an established literature corpus to show that CheNER has a superior performance in identifying IUPAC names specifically, and that it makes better use of computational resources. Availability and implementation: http://metres.udl.cat/index.php/9-download/4-chener, http://chener.bioinfo.cnio.es/ Contact: miguel.vazquez@cnio.es Supplementary information: Supplementary data are available at Bioinformatics online.

CISNE: a new integral approach for scheduling parallel applications on non-dedicated clusters

Our main interest is oriented towards keeping both local and parallel jobs together in a non-dedicated cluster. In order to obtain some profits from the parallel applications, it is important to consider time and space sharing as a mean to enhance the scheduling decisions. In this work, we introduce an integral scheduling system for non-dedicated clusters, termed CISNE. It includes both a previously developed dynamic coscheduling system and a space-sharing job scheduler to make better scheduling decisions than can be made separately. CISNE allows multiple parallel applications to be executed concurrently in a non dedicated Linux cluster with a good performance, as much from the point of view of the local user as that of the parallel application user. This is possible without disturbing the local user and obtaining profits for the parallel user. The good performance of CISNE has been evaluated in a Linux cluster.

Cooperative scheduling mechanism for large-scale peer-to-peer computing systems

Over recent years, peer-to-peer (P2P) systems have become an important part of Internet. Millions of users have been attracted to their structures and services. P2P computing is a distributed computing paradigm that uses Internet to connect thousands, or even millions, of users into a single large virtual computer based on the sharing of computational resources. One of the most critical aspects to the design of P2P computing systems is the development of scheduling techniques to manage the computational resources efficiently and in a scalable way. This paper proposes a cooperative scheduling mechanism with a two-level topology designed to work on large-scale distributed computing P2P systems. Our main contribution is proposing three criteria that only use local information to schedule tasks thus providing scalability to the overall scheduling system. By setting up these three criteria, the system can be easily adapted to work efficiently with very different kinds of distributed applications. The extensive experimentation carried out justifies the importance of good scheduling in such heterogeneous systems, but also emphasizes the importance of having a scheduling algorithm capable of being adapted to the requirements of different kinds of application.

CoDiP2P: A Peer-to-Peer Architecture for Sharing Computing Resources

Peer-to-Peer (P2P) computing, the harnessing of idle compute cycles through the Internet, offers new research challenges in the domain of distributed computing. This paper presents CoDiP2P, a Computing Distributed architecture using the P2P paradigm. CoDiP2P allows computing resources from ordinary users to be shared in an open access by means of creating dynamic areas of computing resources in a completely distributed, scalable and fault tolerant way. This paper discusses its system architecture and evaluates its functionality by means of simulation.

Coscheduling and Multiprogramming Level in a Non-dedicated Cluster

Our interest is oriented towards keeping both local and parallel jobs together in a time-sharing non-dedicated cluster. In such systems, dynamic coscheduling techniques, without memory restriction, that consider the MultiProgramming Level for parallel applications (MPL), is a main goal in current cluster research. In this paper, a new technique called Cooperating Coscheduling (CCS), that combines a dynamic coscheduling system and a resource balancing schema, is applied.

Analyzing locality over a P2P computing architecture

A characteristic of Peer-to-Peer (P2P) computing networks is their huge number of different computational resources scattered across the Internet. Gathering peers into markets according to their multi-attribute computational resources makes it easier to manage these environments. This solution is known as market overlay. In this context, the closeness of the markets with similar resources, known as locality, is a key feature for ensuring good P2P resource management. Thus, the locality feature over a market overlay allows a lack of resources in a given market to be compensated quickly by any other market with similar resources, whenever these are close to each other. Consequently, locality becomes an essential challenge. This paper addresses the analysis of the locality of P2P market over-lays. According to this, a new procedure for measuring locality is applied together with an extensive analysis of some well-known structured P2P overlays. Based on this analysis, a new P2P computing architecture, named DisCoP, oriented towards optimizing locality is proposed. Our proposal gathers the peers into markets according to their computational resources. A Hilbert function is used to arrange multi-attribute markets in an ordered and mono-dimensional space and the markets are linked by means of a Bruijn graph. In order to maintain the DisCoP locality whenever the overlay is not completed, a solution based on the virtualization of markets is also proposed. Finally, the DisCoP locality is tested together with the proposed virtualization method for approximate searches over uncompleted overlays. The simulation results show that approximate searches exploit the DisCoP locality efficiently.

Implementing Explicit and Implicit Coscheduling in a PVM Environment

Our efforts are directed towards the understanding of the coscheduling mechanism in a NOW system when a parallel job is executed with local workloads, balancing parallel efficiency against the local interactive response. Explicit and implicit coscheduling techniques in a PVM-Linux NOW (or cluster) has been implemented. Their performance and overheads executing local tasks and representative distributed benchmarks have been analyzed and compared.

Predictive Coscheduling Implementation in a Non-dedicated Linux Cluster

Our research is focussed on keeping both local and parallel jobs together in a non-dedicated cluster or NOW (Network Of Workstations) and efficiently scheduling them by means of coscheduling mechanisms. A real implementation of a predictive coscheduling technique in a Linux cluster is presented in this article and its performance analyzed and compared with other coscheduling algorithms in the literature.