16,537 research outputs found
Fast Discrete Consensus Based on Gossip for Makespan Minimization in Networked Systems
In this paper we propose a novel algorithm to solve the discrete consensus problem, i.e., the problem of distributing evenly a set of tokens of arbitrary weight among the nodes of a networked system. Tokens are tasks to be executed by the nodes and the proposed distributed algorithm minimizes monotonically the makespan of the assigned tasks. The algorithm is based on gossip-like asynchronous local interactions between the nodes. The convergence time of the proposed algorithm is superior with respect to the state of the art of discrete and quantized consensus by at least a factor O(n) in both theoretical and empirical comparisons
Online Assignment Algorithms for Dynamic Bipartite Graphs
This paper analyzes the problem of assigning weights to edges incrementally
in a dynamic complete bipartite graph consisting of producer and consumer
nodes. The objective is to minimize the overall cost while satisfying certain
constraints. The cost and constraints are functions of attributes of the edges,
nodes and online service requests. Novelty of this work is that it models
real-time distributed resource allocation using an approach to solve this
theoretical problem. This paper studies variants of this assignment problem
where the edges, producers and consumers can disappear and reappear or their
attributes can change over time. Primal-Dual algorithms are used for solving
these problems and their competitive ratios are evaluated
One More Weight is Enough: Toward the Optimal Traffic Engineering with OSPF
Traffic Engineering (TE) leverages information of network traffic to generate
a routing scheme optimizing the traffic distribution so as to advance network
performance. However, optimize the link weights for OSPF to the offered traffic
is an known NP-hard problem. In this paper, motivated by the fairness concept
of congestion control, we firstly propose a new generic objective function,
where various interests of providers can be extracted with different parameter
settings. And then, we model the optimal TE as the utility maximization of
multi-commodity flows with the generic objective function and theoretically
show that any given set of optimal routes corresponding to a particular
objective function can be converted to shortest paths with respect to a set of
positive link weights. This can be directly configured on OSPF-based protocols.
On these bases, we employ the Network Entropy Maximization(NEM) framework and
develop a new OSPF-based routing protocol, SPEF, to realize a flexible way to
split traffic over shortest paths in a distributed fashion. Actually, comparing
to OSPF, SPEF only needs one more weight for each link and provably achieves
optimal TE. Numerical experiments have been done to compare SPEF with the
current version of OSPF, showing the effectiveness of SPEF in terms of link
utilization and network load distribution
Cross-layer optimization in TCP/IP networks
TCP-AQM can be interpreted as distributed primal-dual algorithms to maximize aggregate utility over source rates. We show that an equilibrium of TCP/IP, if exists, maximizes aggregate utility over both source rates and routes, provided congestion prices are used as link costs. An equilibrium exists if and only if this utility maximization problem and its Lagrangian dual have no duality gap. In this case, TCP/IP incurs no penalty in not splitting traffic across multiple paths. Such an equilibrium, however, can be unstable. It can be stabilized by adding a static component to link cost, but at the expense of a reduced utility in equilibrium. If link capacities are optimally provisioned, however, pure static routing, which is necessarily stable, is sufficient to maximize utility. Moreover single-path routing again achieves the same utility as multipath routing at optimality
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