Fisheye: Topology aware choice of peers for overlay networks

Constructing a topology aware overlay network is an open research topic. In this paper we propose a novel protocol for building overlay networks - a distributed fisheye view. Similar to round trip time (RTT) prediction approaches, we consider the end systems to be embedded in a virtual metric space. Unlike other approaches, we use only the distances (measured RTTs) to build an RTT proximity aware overlay network. Therefore, we are able to construct a fisheye view without performing the embedding. At the same time we are still able to guarantee the geographical diversity of the neighbors. Once built, the fisheye views on the end systems are continuously refined as information about new potential neighbors is available. This makes our overlay network adaptive to changes in the network topology. To evaluate our approach, we compared it with an existing topology aware overlay network construction approach - binning. We based this comparison on RTT measurements obtained using the King RTT measurement method and from the Planet Lab ?all site ping? experiment. Our evaluation shows that the overlay network built using our approach outperforms binning in terms of relative RTT stretch. We also show that for increasing number of neighbors the performance of our approach converges towards an optimal solution.