4,351 research outputs found
LUNES: Agent-based Simulation of P2P Systems (Extended Version)
We present LUNES, an agent-based Large Unstructured NEtwork Simulator, which
allows to simulate complex networks composed of a high number of nodes. LUNES
is modular, since it splits the three phases of network topology creation,
protocol simulation and performance evaluation. This permits to easily
integrate external software tools into the main software architecture. The
simulation of the interaction protocols among network nodes is performed via a
simulation middleware that supports both the sequential and the
parallel/distributed simulation approaches. In the latter case, a specific
mechanism for the communication overhead-reduction is used; this guarantees
high levels of performance and scalability. To demonstrate the efficiency of
LUNES, we test the simulator with gossip protocols executed on top of networks
(representing peer-to-peer overlays), generated with different topologies.
Results demonstrate the effectiveness of the proposed approach.Comment: Proceedings of the International Workshop on Modeling and Simulation
of Peer-to-Peer Architectures and Systems (MOSPAS 2011). As part of the 2011
International Conference on High Performance Computing and Simulation (HPCS
2011
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
Scalable Peer-to-Peer Indexing with Constant State
We present a distributed indexing scheme for peer to peer networks. Past work on distributed indexing traded off fast search times with non-constant degree topologies or network-unfriendly behavior such as flooding. In contrast, the scheme we present optimizes all three of these performance measures. That is, we provide logarithmic round searches while maintaining connections to a fixed number of peers and avoiding network flooding. In comparison to the well known scheme Chord, we provide competitive constant factors. Finally, we observe that arbitrary linear speedups are possible and discuss both a general brute force approach and specific economical optimizations
Supermarket Model on Graphs
We consider a variation of the supermarket model in which the servers can
communicate with their neighbors and where the neighborhood relationships are
described in terms of a suitable graph. Tasks with unit-exponential service
time distributions arrive at each vertex as independent Poisson processes with
rate , and each task is irrevocably assigned to the shortest queue
among the one it first appears and its randomly selected neighbors. This
model has been extensively studied when the underlying graph is a clique in
which case it reduces to the well known power-of- scheme. In particular,
results of Mitzenmacher (1996) and Vvedenskaya et al. (1996) show that as the
size of the clique gets large, the occupancy process associated with the
queue-lengths at the various servers converges to a deterministic limit
described by an infinite system of ordinary differential equations (ODE). In
this work, we consider settings where the underlying graph need not be a clique
and is allowed to be suitably sparse. We show that if the minimum degree
approaches infinity (however slowly) as the number of servers approaches
infinity, and the ratio between the maximum degree and the minimum degree in
each connected component approaches 1 uniformly, the occupancy process
converges to the same system of ODE as the classical supermarket model. In
particular, the asymptotic behavior of the occupancy process is insensitive to
the precise network topology. We also study the case where the graph sequence
is random, with the -th graph given as an Erd\H{o}s-R\'enyi random graph on
vertices with average degree . Annealed convergence of the occupancy
process to the same deterministic limit is established under the condition
, and under a stronger condition ,
convergence (in probability) is shown for almost every realization of the
random graph.Comment: 32 page
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