A lightweight distributed super peer election algorithm for unstructured dynamic P2P systems

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de ComputadoresNowadays with the current growth of information exchange, and the increasing mobility of devices, it becomes essential to use technology to monitor this development. For that P2P networks are used, the exchange of information between agencies is facilitated, these now being applied in mobile networks, including MANETs, where they have special features such as the fact that they are semi-centralized, where it takes peers more ability to make a greater role in the network. But those peer with more capacity, which are used in the optimization of various parameters of these systems, such as optimization\to research, are difficult to identify due to the fact that the network does not have a fixed topology, be constantly changing, (we like to go online and offline, to change position, etc.) and not to allow the exchange of large messages. To this end, this thesis proposes a distributed election algorithm of us greater capacity among several possible goals, enhance research in the network. This includes distinguishing characteristics, such as election without global knowledge network, minimal exchange of messages, distributed decision made without dependence on us and the possibility of influencing the election outcome as the special needs of the network

Using Aggregation for Adaptive Super-Peer Discovery on the Gradient Topology

Peer-to-peer environments exhibit a very high diversity in individual peer characteristics ranging by orders of magnitude in terms of uptime, available bandwidth, and storage space. Many systems attempt to exploit this resource heterogeneity by using the best performing and most reliable peers, called super-peers, for hosting system services. However, due to inherent decentralisation, scale, dynamism, and complexity of P2P environments, self-managing super-peer selection is a challenging problem. In this paper, decentralised aggregation techniques are used to reduce the uncertainty about system properties by approximating the peer utility distribution allowing peers to calculate adaptive thresholds in order to discover appropriate super-peers. Furthermore, a heuristic search algorithm is described that allows super-peers, above a certain utility threshold, to be efficiently discovered and utilised by any peer in the system

Using aggregation for adaptive super-peer discovery on the gradient topology

Abstract. Peer-to-peer environments exhibit a very high diversity in individual peer characteristics ranging by orders of magnitude in terms of uptime, available bandwidth, and storage space. Many systems attempt to exploit this resource heterogeneity by using the best performing and most reliable peers, called super-peers, for hosting system services. However, due to inherent decentralisation, scale, dynamism, and complexity of P2P environments, self-managing super-peer selection is a challenging problem. In this paper, decentralised aggregation techniques are used to reduce the uncertainty about system properties by approximating the peer utility distribution allowing peers to calculate adaptive thresholds in order to discover appropriate super-peers. Furthermore, a heuristic search algorithm is described that allows super-peers, above a certain utility threshold, to be eOEciently discovered and utilised by any peer in the system.