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There has been increasing interests in processing large-scale real-world graphs, and recently many graph systems have been proposed. Vertex-centric GAS (Gather-Apply-Scatter) and Edge-centric GAS are two graph computation models being widely adopted, and existing graph analytics systems commonly follow only one computation model, which is not the best choice for real-world graph processing. In fact,...
A common property of many networks, including the Internet, biological networks, and social networks, is that the degree distribution approximately follows a power law. Such networks are found to be naturally divided into communities of densely connected nodes, known as the community structure. Despite that the existence of the community structure has been clearly indicated through experiments, there...
Finding the ground states of Sherrington-Kirkpatrick (SK) spin glass, the mean-filed spin glass model with strongly connected variables, is well known as a typical NP-hard problem. This paper presents a modified extremal optimization (EO) framework to approximate its grounds states. The basic idea behind the proposed framework is to generalize the evolutionary probability distribution of the original...
The existing literature deals with the problems dealing with decentralized content-based P2P community formation and community-based search separately. Contrary to this approach, in this paper we propose a novel search algorithm that has both the capability to form the community structure as well as search it with maximum efficiency. The key contribution is to design a self-organized and adaptive...
Apart from files, P2P Networks can be used for sharing non-replicable and reusable (e.g. computational) resources. This paper explains why existing discovery mechanisms have low performance searching for those resources in random power-law degree distributions. While high-degree nodes become more popular, their resources are consumed, resulting into a power-law network topology with no more useful...
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