A FUNCTIONAL SKETCH FOR RESOURCES MANAGEMENT IN COLLABORATIVE SYSTEMS FOR BUSINESS

This paper presents a functional design sketch for the resource management module of a highly scalable collaborative system. Small and medium enterprises require such tools in order to benefit from and develop innovative business ideas and technologies. As computing power is a modern increasing demand and no easy and cheap solutions are defined, especially small companies or emerging business projects abide a more accessible alternative. Our work targets to settle a model for how P2P architecture can be used as infrastructure for a collaborative system that delivers resource access services. We are focused on finding a workable collaborative strategy between peers so that the system offers a cheap, trustable and quality service. Thus, in this phase we are not concerned about solutions for a specific type of task to be executed by peers, but only considering CPU power as resource. This work concerns the resource management module as a part of a larger project in which we aim to build a collaborative system for businesses with important resource demandsresource management, p2p, open-systems, service oriented computing, collaborative systems

Multi-criteria and satisfaction oriented scheduling for hybrid distributed computing infrastructures

International audienceAssembling and simultaneously using different types of distributed computing infrastructures (DCI) like Grids and Clouds is an increasingly common situation. Because infrastructures are characterized by different attributes such as price, performance, trust, greenness, the task scheduling problem becomes more complex and challenging. In this paper we present the design for a fault-tolerant and trust-aware scheduler, which allows to execute Bag-of-Tasks applications on elastic and hybrid DCI, following user-defined scheduling strategies. Our approach, named Promethee scheduler, combines a pull-based scheduler with multi-criteria Promethee decision making algorithm. Because multi-criteria scheduling leads to the multiplication of the possible scheduling strategies, we propose SOFT, a methodology that allows to find the optimal scheduling strategies given a set of application requirements. The validation of this method is performed with a simulator that fully implements the Promethee scheduler and recreates an hybrid DCI environment including Internet Desktop Grid, Cloud and Best Effort Grid based on real failure traces. A set of experiments shows that the Promethee scheduler is able to maximize user satisfaction expressed accordingly to three distinct criteria: price, expected completion time and trust, while maximizing the infrastructure useful employment from the resources owner point of view. Finally, we present an optimization which bounds the computation time of the Promethee algorithm, making realistic the possible integration of the scheduler to a wide range of resource management software

E-Fast & CloudPower: Towards High Performance Technical Analysis for Small Investors

International audienceAbout 80% of the financial market investors fail, the main reason for this being their poor investment decisions. Without advanced financial analysis tools and the knowledge to interpret the analysis, the investors can easily make irrational investment decisions. Moreover, investors are challenged by the dynamism of the market and a relatively large number of indicators that must be computed. In this paper we propose E-Fast, an innovative approach for on-line technical analysis for helping small investors to obtain a greater e on the market by increasing their knowledge. The E-Fast technical analysis platform prototype relies on High Performance Computing (HPC), allowing to rapidly develop and extensively validate the most sophisticated finance analysis algorithms. In this work, we aim at demonstrating that the E-Fast implementation , based on the CloudPower HPC infrastructure, is able to provide small investors a realistic, low-cost and secure service that would otherwise be available only to the large financial institutions. We describe the architecture of our system and provide design insights. We present the results obtained with a real service implementation based on the Exponential Moving Average computational method, using CloudPower and Grid5000 for the computations' acceleration. We also elaborate a set of interesting challenges emerging from this work, as next steps towards high performance technical analysis for small investors

D 3 -MapReduce: Towards MapReduce for Distributed and Dynamic Data Sets

International audienceSince its introduction in 2004 by Google, MapRe-duce has become the programming model of choice for processing large data sets. Although MapReduce was originally developed for use by web enterprises in large data-centers, this technique has gained a lot of attention from the scientific community for its applicability in large parallel data analysis (including geographic, high energy physics, genomics, etc.). So far MapReduce has been mostly designed for batch processing of bulk data. The ambition of D 3-MapReduce is to extend the MapReduce programming model and propose efficient implementation of this model to: i) cope with distributed data sets, i.e. that span over multiple distributed infrastructures or stored on network of loosely connected devices; ii) cope with dynamic data sets, i.e. which dynamically change over time or can be either incomplete or partially available. In this paper, we draw the path towards this ambitious goal. Our approach leverages Data Life Cycle as a key concept to provide MapReduce for distributed and dynamic data sets on heterogeneous and distributed infrastructures. We first report on our attempts at implementing the MapReduce programming model for Hybrid Distributed Computing Infrastructures (Hybrid DCIs). We present the architecture of the prototype based on BitDew, a middleware for large scale data management, and Active Data, a programming model for data life cycle management. Second, we outline the challenges in term of methodology and present our approaches based on simulation and emulation on the Grid'5000 experimental testbed. We conduct performance evaluations and compare our prototype with Hadoop, the industry reference MapReduce implementation. We present our work in progress on dynamic data sets that has lead us to implement an incremental MapReduce framework. Finally, we discuss our achievements and outline the challenges that remain to be addressed before obtaining a complete D 3-MapReduce environment

Using Promethee Methods for Multi-Criteria Pull-based Scheduling on DCIs

International audienc

INTEGRATED DOCUMENT MANAGEMENT SOLUTION FOR THE LOCAL GOVERNMENT

In this paper we present system analysis and design elements for the integrated document management solution at local governing authorities in the rural areas. While specifically dealing with the actual management of the Agricultural Register, an important primary unitary evidence document, we also keep a general character of the discussion, in order to argue for the generality of the proposed solution. Hence, for the identified and described problem space we propose an administrative and software infrastructure solution. This work is an empirical research in which our aim is primarily to identify key problems within the local governing authorities from several perspectives concerning the management of the Agricultural Register then to address those problems with an integrated document management system. For the proposed solution we give and argue the general system architecture and describe the key-mechanisms that support quality requirements. The relevance of this research concern is given by the impact of the actual Agricultural Register management on important stakeholders. This can be measured as the satisfaction felt by taxpayers and the performance of the local governing authorities, the Financial Administration, the Agency of Payments and Intervention in Agriculture and the Ministry of Agriculture and Rural Development. This work is also intended as a start-point for a new, modern thinking of the governing authorities in their pursue to improve public services. For this, in our work we highlight the importance of complete system analysis at all administrative levels as a main priority concern for all public managers. Our aim is the improvement of the public service by rising the awareness of the decision makers on the necessity of using integrated document management solutions for the provided services. Also, our work aims at increasing the efficiency with which nowadays, governing authorities invest public funds in various IT projects for the management of their services. For this, we highlight the importance of documenting quality requirements during system analysis

Data Confidentiality in Cloud Storage Protocol Based on Secret Sharing Scheme: A Brute Force Attack Evaluation

Part 3: Short PapersInternational audienceOutsourcing a company’s data storage and management system increases data security risk and generates a mistrust among adopters, that their data will remain secure and undisclosed. Due to limitations of the SLAs in this direction, the challenge is to build mechanisms that provides data security by design and assures data nondisclosure protection implicitly. In this paper we present an evaluation of the Data Confidentiality in Cloud Storage using a brute-force setup with the aim of studying its effectiveness. Through experimentation on the CloudSim environment we found that the probability of unauthorized data reconstruction can be exponentially decreased by using a sufficiently large number of chunks. Also, increasing the number of used storage volumes leads to a linear decrease of unauthorized data reconstruction

THE ROMANIAN CONSUMER PROFILES IN PROCESSING ONLINE BOOKINGS

Tourism is considered [WTTC] one of the top three industries as importance in the global economy of the 21st century. With the development of information technology and electronic commerce, the electronic (online) booking seems to be a popular way to facilitate access to certain goods and tourism services via the Internet. The literature clearly indicates that online booking vacations, transportation and other services related to tourism package developed and diversified nearly at the same degree with advances made in Information Technology and Communication (ITC). However, “there are wide variations in online usage levels between different countries … Australian’s online usage is 44 % and Spain’s online usage is 14% from all transactions†[online-booking from WCT]. Regarding the consumer profile using 'online booking ', the literature does not provide a generally accepted set of evaluation attributes. In the world is talking today about "Generation Y", in other words about those who have reached maturity in the early millennium. Basically it's about consumers born between 1980 and 1995, hence with ages between 18 and 33 years. In this context, in our exploratory research we conducted a statistical study on students, tomorrow's economic specialists with knowledge in ITC from minimal to advanced levels. The hypothesis of the study are: a. Humans with advanced computer skills using the Internet for booking holidays; b. Humans with low ITC skills choose the classical method of booking holidays by contacting a tour company. The results of our survey showed that the choice of online tools for booking holidays becomes an increasingly used method in Romania but consumers still lack confidence in the online environment. This phenomenon often motivates the consumers to contact a tour company regardless of their ITC skills or travel experience. We also proved that there is no strong connection between people with good ITC knowledge and the employment of online booking as well as between the tourism experts and booking through tour companies. Our study shows that: on-line booking for Y Generation is not an independent process, but is considered a stage of the process of making reservations for travel packages

Advanced Promethee-based Scheduler Enriched with User-Oriented Methods

International audienceEfficiently scheduling tasks in hybrid Distributed Computing Infrastructures (DCI) is a challenging pursue because the scheduler must deal with a set of parameters that simultaneously characterize the tasks and the hosts originating from different types of infrastructure.In this paper we propose a scheduling method for hybrid DCIs, based on advanced multi-criteria decision methods. The scheduling decisions are made using pairwise comparisons of the tasks for a set of criteria like expected completion time and price charged for computation. The results are obtained with an XtremWeb-like pull-based scheduler simulator using real failure traces from [1] for a combination of three types of infrastructure. We also show how such a scheduler should be configured to enhance user satisfaction regardless their profiles, while maintaining good values for makespan and cost.We validate our approach with a statistical analysis on empirical data and show that our proposed scheduling method improves performance by 12-17% compared to other scheduling methods. Experimenting on large time-series and using realistic scheduling scenarios lead us to conclude about time consistency results of the method