Luciano Cavalheiro da Silva

GRAND: toward scalability in a Grid environment

One of the challenges in Grid computing research is to provide a means to automatically submit, manage, and monitor applications whose main characteristic is to be composed of a large number of tasks. The large number of explicit tasks, generally placed on a centralized job queue, can cause several problems: (1) they can quickly exhaust the memory of the submission machine; (2) they can deteriorate the response time of the submission machine due to these demanding too many open ports to manage remote execution of each of the tasks; (3) they may cause network traffic congestion if all tasks try to transfer input and/or output files across the network at the same time; (4) they make it impossible for the user to follow execution progress without an automatic tool or interface; (5) they may depend on fault‐tolerance mechanisms implemented at application level to ensure that all tasks terminate successfully. In this work we present and validate a novel architectural model, GRAND (Grid Robust ApplicatioN Deployment), whose main objective is to deal with the submission of a large numbers of tasks. Copyright

MultiS: A Context-Server for Pervasive Computing

Context-aware applications are capable of recognizing environmental changes and adapting their behavior to the new context. This process can be divided into three stages: monitoring, context recognition and adaptation. On the monitoring layer, raw information about the environment is collected from sensors. The context recognition layer processes the data acquired from the context and transforms it into information which can be useful for the adaptation process. With this information, the adaptation system can determine what behavior is correct for the application in each different context. This paper proposes a context server called MultiS, which has the goal of solving the problems arising from the context recognition layer, and which includes the following advantages: a) the production of new context data based on the information of several sensors and an ability to react to changes in the environment; b) definition of a composed language for the context data called CD-XML; c) support for mobility.