Protocolo de roteamento para redes oportunistas utilizando otimização por enxame de partículas

In this research work, a new routing protocol for Opportunistic Networks is presented. The proposed protocol is called PSONET (PSO for Opportunistic Networks) since the proposal uses a hybrid system composed of a Particle Swarm Optimization algorithm (PSO). The main motivation for using the PSO is to take advantage of its search based on individuals and their learning adaptation. The PSONET uses the Particle Swarm Optimization technique to drive the network traffic through of a good subset of forwarders messages. The PSONET analyzes network communication conditions, detecting whether each node has sparse or dense connections and thus make better decisions about routing messages. The PSONET protocol is compared with the Epidemic and PROPHET protocols in three different scenarios of mobility: a mobility model based in activities, which simulates the everyday life of people in their work activities, leisure and rest; a mobility model based on a community of people, which simulates a group of people in their communities, which eventually will contact other people who may or may not be part of your community, to exchange information; and a random mobility pattern, which simulates a scenario divided into communities where people choose a destination at random, and based on the restriction map, move to this destination using the shortest path. The simulation results, obtained through The ONE simulator, show that in scenarios where the mobility model based on a community of people and also where the mobility model is random, the PSONET protocol achieves a higher messages delivery rate and a lower replication messages compared with the Epidemic and PROPHET protocols.

Problem-Based SRS: método para especificação de requisitos de software baseado em problemas

Requirements specification has long been recognized as critical activity in software development processes because of its impact on project risks when poorly performed. A large amount of studies addresses theoretical aspects, propositions of techniques, and recommended practices for Requirements Engineering (RE). To be successful, RE have to ensure that the specified requirements are complete and correct what means that all intents of the stakeholders in a given business context are covered by the requirements and that no unnecessary requirement was introduced. However, the accurate capture the business intents of the stakeholders remains a challenge and it is a major factor of software project failures. This master’s dissertation presents a novel method referred to as “Problem-Based SRS” aiming at improving the quality of the Software Requirements Specification (SRS) in the sense that the stated requirements provide suitable answers to real customer ́s businesses issues. In this approach, the knowledge about the software requirements is constructed from the knowledge about the customer ́s problems. Problem-Based SRS consists in an organization of activities and outcome objects through a process that contains five main steps. It aims at supporting the software requirements engineering team to systematically analyze the business context and specify the software requirements, taking also into account a first glance and vision of the software. The quality aspects of the specifications are evaluated using traceability techniques and axiomatic design principles. The cases studies conducted and presented in this document point out that the proposed method can contribute significantly to improve the software requirements specification.