309 research outputs found
The Competition for Shortest Paths on Sparse Graphs
Optimal paths connecting randomly selected network nodes and fixed routers
are studied analytically in the presence of non-linear overlap cost that
penalizes congestion. Routing becomes increasingly more difficult as the number
of selected nodes increases and exhibits ergodicity breaking in the case of
multiple routers. A distributed linearly-scalable routing algorithm is devised.
The ground state of such systems reveals non-monotonic complex behaviors in
both average path-length and algorithmic convergence, depending on the network
topology, and densities of communicating nodes and routers.Comment: 4 pages, 4 figure
Empirical studies on the network of social groups: the case of Tencent QQ
Participation in social groups are important but the collective behaviors of
human as a group are difficult to analyze due to the difficulties to quantify
ordinary social relation, group membership, and to collect a comprehensive
dataset. Such difficulties can be circumvented by analyzing online social
networks. In this paper, we analyze a comprehensive dataset obtained from
Tencent QQ, an instant messenger with the highest market share in China.
Specifically, we analyze three derivative networks involving groups and their
members -- the hypergraph of groups, the network of groups and the user network
-- to reveal social interactions at microscopic and mesoscopic level. Our
results uncover interesting behaviors on the growth of user groups, the
interactions between groups, and their relationship with member age and gender.
These findings lead to insights which are difficult to obtain in ordinary
social networks.Comment: 18 pages, 9 figure
Distributed optimization in transportation and logistics networks
Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralized algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message-passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids
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