Resource allocation in sparsely connected networks, a representative problem of systems with real variables, is studied using the replica and Bethe approximation methods. An efficient distributed algorithm is devised on the basis of insights gained from the analysis and is examined using numerical simulations,showing excellent performance and full agreement with the theoretical results. The physical properties of the resource allocation model are discussed
In this thesis, we study distributed algorithms in the context of two fundamental problems in distri...
A central challenge in networked and distributed systems is resource management: how can we partitio...
Optimal paths connecting randomly selected network nodes and fixed routers are studied analytically ...
The problem of resource allocation in sparse graphs with real variables is studied using methods of ...
Inference and optimization of real-value edge variables in sparse graphs are studied using the Bethe...
The problem of resource allocation in sparse graphs with real variables is studied using methods of...
We apply statistical physics to study the task of resource allocation in random sparse networks with...
Inference and optimisation of real-value edge variables in sparse graphs are studied using the tree ...
The optimization of resource allocation in sparse networks with real variables is studied using meth...
We study the equilibrium states of energy functions involving a large set of real variables, defined...
Many fundamental algorithmic techniques have roots in applications to computer networks. We consider...
A distributed algorithm is presented, for allocating a large number of identical resources (such as ...
We apply statistical physics to study the task of resource allocation in random networks with limite...
We apply statistical physics to study the task of resource allocation in random networks with limite...
Inference and optimisation of real-value edge variables in sparse graphs are studied using the tree ...
In this thesis, we study distributed algorithms in the context of two fundamental problems in distri...
A central challenge in networked and distributed systems is resource management: how can we partitio...
Optimal paths connecting randomly selected network nodes and fixed routers are studied analytically ...
The problem of resource allocation in sparse graphs with real variables is studied using methods of ...
Inference and optimization of real-value edge variables in sparse graphs are studied using the Bethe...
The problem of resource allocation in sparse graphs with real variables is studied using methods of...
We apply statistical physics to study the task of resource allocation in random sparse networks with...
Inference and optimisation of real-value edge variables in sparse graphs are studied using the tree ...
The optimization of resource allocation in sparse networks with real variables is studied using meth...
We study the equilibrium states of energy functions involving a large set of real variables, defined...
Many fundamental algorithmic techniques have roots in applications to computer networks. We consider...
A distributed algorithm is presented, for allocating a large number of identical resources (such as ...
We apply statistical physics to study the task of resource allocation in random networks with limite...
We apply statistical physics to study the task of resource allocation in random networks with limite...
Inference and optimisation of real-value edge variables in sparse graphs are studied using the tree ...
In this thesis, we study distributed algorithms in the context of two fundamental problems in distri...
A central challenge in networked and distributed systems is resource management: how can we partitio...
Optimal paths connecting randomly selected network nodes and fixed routers are studied analytically ...