Optical flow using color information: preliminary results

AIRES, Kelson R. T.; SANTANA, André M.; MEDEIROS, Adelardo A. D. Optical flow using color information: preliminary results. In: ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, 23., 2008, Fortaleza. Proceedings... Fortaleza: SAC, 2008.

Enterprise systems modeling: The ERP5 development process

The design and implementation of an ERP system involves capturing the information necessary for implementing the system's structure and behavior that support enterprise management. This process should start on the enterprise modeling level and finish at the coding level, going down through different abstraction layers. For the case of Free/Open Source ERP, the lack of proper modeling methods and tools jeopardizes the advantages of source code availability. Moreover, the distributed, decentralized decision-making, and source-code driven development culture of open source communities, generally doesn't rely on methods for modeling the higher abstraction levels necessary for an ERP solution. The aim of this paper is to present a model driven development process for the open source ERP ERP5. The proposed process covers the different abstraction levels involved, taking into account well established standards and common practices, as well as new approaches, by supplying Enterprise, Requirements, Analysis, Design, and Implementation workflows. Copyright 2008 ACM.

Evaluating genetic algorithms with different population structures on a lot sizing and scheduling problem

This paper studies the use of different population structures in a Genetic Algorithm (GA) applied to lot sizing and scheduling problems. The population approaches are divided into two types: single-population and multi-population. The first type has a non-structured single population. The multi-population type presents non-structured and structured populations organized in binary and ternary trees. Each population approach is tested on lot sizing and scheduling problems found in soft drink companies. These problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. Computational results are reported allowing determining the better population structure for the set of problem instances evaluated. Copyright 2008 ACM.

Service-centric Networking Extensions

This paper discusses several issues of Service-Centric Networking (SCN) as an extension of the Information-Centric Networking (ICN) paradigm. SCN allows extended caching, where not exactly the same content as requested can be read from caches, but similar content can be used to produce the content requested, e.g., by filtering or transcoding. We discuss the issue of naming and routing for general dynamic services for both tightly coupled and decoupled ICN approaches. Challenges and solutions for service management are identified, in particular for composed services, which allow distributed in-network processing of service requests. We introduce the term Software-Defined Service-Centric Networking as an extension of Software-Defined Networking. A prototype implementation for SCN proofs its validity and feasibility and underlines its potential benefits.

Feasibility of Information-Centric Networking Integration into LTE Mobile Networks

With the current growth of mobile devices usage, mobile net- works struggle to deliver content with an acceptable Quality of Experience. In this paper, we propose the integration of Information Centric Networking into 3GPP Long Term Evolution mobile networks, allowing its inherent caching feature to be explored in close proximity to the end users by deploying components inside the evolved Node B. Apart from the advantages brought by Information-Centric Networking’s content requesting paradigm, its inherent caching features enable lower latencies to access content and reduce traffic at the core network. Results show that the impact on the evolved Node B performance is low and ad- vantages coming from Information-Centric Networking are considerable. Thus, mobile network operators reduce operational costs and users end up with a higher perceived network quality even in peak utilization periods.

A multi-resource load balancing algorithm for cloud cache systems

With the advent of cloud computing model, distributed caches have become the cornerstone for building scalable applications. Popular systems like Facebook [1] or Twitter use Memcached [5], a highly scalable distributed object cache, to speed up applications by avoiding database accesses. Distributed object caches assign objects to cache instances based on a hashing function, and objects are not moved from a cache instance to another unless more instances are added to the cache and objects are redistributed. This may lead to situations where some cache instances are overloaded when some of the objects they store are frequently accessed, while other cache instances are less frequently used. In this paper we propose a multi-resource load balancing algorithm for distributed cache systems. The algorithm aims at balancing both CPU and Memory resources among cache instances by redistributing stored data. Considering the possible conflict of balancing multiple resources at the same time, we give CPU and Memory resources weighted priorities based on the runtime load distributions. A scarcer resource is given a higher weight than a less scarce resource when load balancing. The system imbalance degree is evaluated based on monitoring information, and the utility load of a node, a unit for resource consumption. Besides, since continuous rebalance of the system may affect the QoS of applications utilizing the cache system, our data selection policy ensures that each data migration minimizes the system imbalance degree and hence, the total reconfiguration cost can be minimized. An extensive simulation is conducted to compare our policy with other policies. Our policy shows a significant improvement in time efficiency and decrease in reconfiguration cost.

INDICIa: a new distributed clustering protocol

Many data streaming applications produces massive amounts of data that must be processed in a distributed fashion due to the resource limitation of a single machine. We propose a distributed data stream clustering protocol. Theoretical analysis shows preliminary results about the quality of discovered clustering. In addition, we present results about the ability to reduce the time complexity respect to the centralized approach.

STONE: a stream-based DDoS defense framework

An effective Distributed Denial of Service (DDoS) defense mechanism must guarantee legitimate users access to an Internet service masking the effects of possible attacks. That is, it must be able to detect threats and discard malicious packets in a online fashion. Given that emerging data streaming technology can enable such mitigation in an effective manner, in this paper we present STONE, a stream-based DDoS defense framework, which integrates anomaly-based DDoS detection and mitigation with scalable data streaming technology. With STONE, the traffic of potential targets is analyzed via continuous data streaming queries maintaining information used for both attack detection and mitigation. STONE provides minimal degradation of legitimate users traffic during DDoS attacks and it also faces effectively flash crowds. Our preliminary evaluation based on an implemented prototype and conducted with real legitimate and malicious traffic traces shows that STONE is able to provide fast detection and precise mitigation of DDoS attacks leveraging scalable data streaming technology.

Ampliación de un portal Wordpress para el diseño de cursos basados en la metodología PBL

La metodología PBL propone el aprendizaje basado en problemas. A grandes rasgos sugiere que el estudiante sea el protagonista de su propio aprendizaje mediante el desarrollo de proyectos. Con esa idea, el grupo de innovación educativa DMAE-DIA (Desarrollo de nuevas Metodologías de Aprendizaje/Evaluación del Departamento de Informática Aplicada), comenzó la construcción de un portal web para mostrar los principios de dicha metodología, que permitiese a los usuarios del mismo conocerla y aprender a utilizarla en un entorno colaborativo. El objetivo de este trabajo es ampliar este portal para que los usuarios sean capaces de crear, eliminar y mantener sus propios proyectos para posteriormente utilizarlos como base para su práctica docente. El trabajo se ha planteado siguiendo el paradigma de la orientación a objetos, mediante la metodología UML y siguiendo el ciclo de vida del software y se ha implementado utilizando como base el CMS Wordpress y desarrollando con los lenguajes que más adelante se especificarán. Wordpress por su parte es un sistema de gestión de contenidos dotado de gran potencia que permite, de una manera muy sencilla, construir entornos web con el mínimo esfuerzo. ABSTRACT The PBL methodology proposed problem-based learning. Roughly suggests that the student is the protagonist of their own learning by developing projects. With that, the group of educational innovation DMAE-DIA (Development of new Learning/Assessment methodologies, Department of Applied Computing) began building a web portal to show the principles of this methodology, which would allow users to know and learn to use it in a collaborative environment. The aim of this work is to extend this website so that users are able to create, delete and maintain their own projects for later use as the basis for their teaching practice. The work has been raised following the paradigm of object orientation, by following the UML methodology and software life cycle and has been implemented using as a basis the CMS Wordpress and developed with the languages that will be specified later. Meanwhile Wordpress is a content management system endowed with great power that allows,in a very simple way to build web environments with minimal effort.

Computational cost of GNG3D algorithm for mesh simplification

In this paper we present a study of the computational cost of the GNG3D algorithm for mesh optimization. This algorithm has been implemented taking as a basis a new method which is based on neural networks and consists on two differentiated phases: an optimization phase and a reconstruction phase. The optimization phase is developed applying an optimization algorithm based on the Growing Neural Gas model, which constitutes an unsupervised incremental clustering algorithm. The primary goal of this phase is to obtain a simplified set of vertices representing the best approximation of the original 3D object. In the reconstruction phase we use the information provided by the optimization algorithm to reconstruct the faces thus obtaining the optimized mesh. The computational cost of both phases is calculated, showing some examples.

Cloud adoption:prioritizing obstacles and obstacles resolution tactics using AHP

The enormous potential of cloud computing for improved and cost-effective service has generated unprecedented interest in its adoption. However, a potential cloud user faces numerous risks regarding service requirements, cost implications of failure and uncertainty about cloud providers' ability to meet service level agreements. These risks hinder the adoption of cloud. We extend the work on goal-oriented requirements engineering (GORE) and obstacles for informing the adoption process. We argue that obstacles prioritisation and their resolution is core to mitigating risks in the adoption process. We propose a novel systematic method for prioritising obstacles and their resolution tactics using Analytical Hierarchy Process (AHP). We provide an example to demonstrate the applicability and effectiveness of the approach. To assess the AHP choice of the resolution tactics we support the method by stability and sensitivity analysis. Copyright 2014 ACM.

Dynamic decision-making based on NFR for managing software variability and configuration selection

Due to dynamic variability, identifying the specific conditions under which non-functional requirements (NFRs) are satisfied may be only possible at runtime. Therefore, it is necessary to consider the dynamic treatment of relevant information during the requirements specifications. The associated data can be gathered by monitoring the execution of the application and its underlying environment to support reasoning about how the current application configuration is fulfilling the established requirements. This paper presents a dynamic decision-making infrastructure to support both NFRs representation and monitoring, and to reason about the degree of satisfaction of NFRs during runtime. The infrastructure is composed of: (i) an extended feature model aligned with a domain-specific language for representing NFRs to be monitored at runtime; (ii) a monitoring infrastructure to continuously assess NFRs at runtime; and (iii) a exible decision-making process to select the best available configuration based on the satisfaction degree of the NRFs. The evaluation of the approach has shown that it is able to choose application configurations that well fit user NFRs based on runtime information. The evaluation also revealed that the proposed infrastructure provided consistent indicators regarding the best application configurations that fit user NFRs. Finally, a benefit of our approach is that it allows us to quantify the level of satisfaction with respect to NFRs specification.