Over recent years, we experienced a huge diffusion of internet connected computing devices. As a consequence, this leaded to research for efficient and scalable approaches for managing the burden caused by the highly increased volume of data to be exchanged and processed. Efficient communication protocols are fundamental building blocks for realizing such approaches [1], [2]. Thus, several peer-to-peer protocols have been proposed. Gossip protocols [3]-[7] are a family of peer-to-peer protocols that proved to be well-suited for supporting a scalable and decentralized strategy for peer and data aggregation and diffusion. However, one of the typical limitation of Gossip protocols consists in the selfish behavior adopted by peers in defining their neighborhood and, as a consequence, the topology of the overlay they build. GROUP [8] is a Gossip protocol we conceived to overcome this limitation. It builds explicit defined communities of peers that are identified by their leaders, each one elected in a distributed fashion. This protocol experimentally proved to be efficient and effective with respect to its aim. Anyhow, no analytical study has been realized so far. This work presents a currently ongoing work we are conducting for exploring the properties of GROUP in a more formal way. We conduct this preliminary investigation using a formalization based on Markov chains.
Towards GROUP protocol formalization
Baraglia R;Dazzi P;
2013
Abstract
Over recent years, we experienced a huge diffusion of internet connected computing devices. As a consequence, this leaded to research for efficient and scalable approaches for managing the burden caused by the highly increased volume of data to be exchanged and processed. Efficient communication protocols are fundamental building blocks for realizing such approaches [1], [2]. Thus, several peer-to-peer protocols have been proposed. Gossip protocols [3]-[7] are a family of peer-to-peer protocols that proved to be well-suited for supporting a scalable and decentralized strategy for peer and data aggregation and diffusion. However, one of the typical limitation of Gossip protocols consists in the selfish behavior adopted by peers in defining their neighborhood and, as a consequence, the topology of the overlay they build. GROUP [8] is a Gossip protocol we conceived to overcome this limitation. It builds explicit defined communities of peers that are identified by their leaders, each one elected in a distributed fashion. This protocol experimentally proved to be efficient and effective with respect to its aim. Anyhow, no analytical study has been realized so far. This work presents a currently ongoing work we are conducting for exploring the properties of GROUP in a more formal way. We conduct this preliminary investigation using a formalization based on Markov chains.File | Dimensione | Formato | |
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