7,698 research outputs found
Evaluating Connection Resilience for the Overlay Network Kademlia
Kademlia is a decentralized overlay network, up to now mainly used for highly
scalable file sharing applications. Due to its distributed nature, it is free
from single points of failure. Communication can happen over redundant network
paths, which makes information distribution with Kademlia resilient against
failing nodes and attacks. This makes it applicable to more scenarios than
Internet file sharing. In this paper, we simulate Kademlia networks with
varying parameters and analyze the number of node-disjoint paths in the
network, and thereby the network connectivity. A high network connectivity is
required for communication and system-wide adaptation even when some nodes or
communication channels fail or get compromised by an attacker. With our
results, we show the influence of these parameters on the connectivity and,
therefore, the resilience against failing nodes and communication channels.Comment: 12 pages, 14 figures, accepted to ICDCS2017. arXiv admin note:
substantial text overlap with arXiv:1605.0800
HSkip+: A Self-Stabilizing Overlay Network for Nodes with Heterogeneous Bandwidths
In this paper we present and analyze HSkip+, a self-stabilizing overlay
network for nodes with arbitrary heterogeneous bandwidths. HSkip+ has the same
topology as the Skip+ graph proposed by Jacob et al. [PODC 2009] but its
self-stabilization mechanism significantly outperforms the self-stabilization
mechanism proposed for Skip+. Also, the nodes are now ordered according to
their bandwidths and not according to their identifiers. Various other
solutions have already been proposed for overlay networks with heterogeneous
bandwidths, but they are not self-stabilizing. In addition to HSkip+ being
self-stabilizing, its performance is on par with the best previous bounds on
the time and work for joining or leaving a network of peers of logarithmic
diameter and degree and arbitrary bandwidths. Also, the dilation and congestion
for routing messages is on par with the best previous bounds for such networks,
so that HSkip+ combines the advantages of both worlds. Our theoretical
investigations are backed by simulations demonstrating that HSkip+ is indeed
performing much better than Skip+ and working correctly under high churn rates.Comment: This is a long version of a paper published by IEEE in the
Proceedings of the 14-th IEEE International Conference on Peer-to-Peer
Computin
Physics-inspired Performace Evaluation of a Structured Peer-to-Peer Overlay Network
In the majority of structured peer-to-peer overlay networks a graph
with a desirable topology is constructed. In most cases, the graph is
maintained by a periodic activity performed by each node in the graph
to preserve the desirable structure in face of the continuous change
of the set of nodes. The interaction of the autonomous periodic
activities of the nodes renders the performance analysis of such
systems complex and simulation of scales of interest can be
prohibitive. Physicists, however, are accustomed to dealing with
scale by characterizing a system using intensive variables,
i.e. variables that are size independent. The approach has proved its
usefulness when applied to satisfiability theory. This
work is the first attempt to apply it in the area of distributed
systems. The contribution of this paper is two-fold. First, we
describe a methodology to be used for analyzing the performance of
large scale distributed systems. Second, we show how we applied the
methodology to find an intensive variable that describe the
characteristic behavior of the Chord overlay network, namely, the
ratio of the magnitude of perturbation of the network (joins/failures)
to the magnitude of periodic stabilization of the network
The essence of P2P: A reference architecture for overlay networks
The success of the P2P idea has created a huge diversity
of approaches, among which overlay networks, for example,
Gnutella, Kazaa, Chord, Pastry, Tapestry, P-Grid, or DKS,
have received specific attention from both developers and
researchers. A wide variety of algorithms, data structures,
and architectures have been proposed. The terminologies
and abstractions used, however, have become quite inconsistent since the P2P paradigm has attracted people from many different communities, e.g., networking, databases, distributed systems, graph theory, complexity theory, biology, etc. In this paper we propose a reference model for overlay networks which is capable of modeling different approaches in this domain in a generic manner. It is intended to allow researchers and users to assess the properties of concrete systems, to establish a common vocabulary for scientific discussion, to facilitate the qualitative comparison of the systems, and to serve as the basis for defining a standardized API to make overlay networks interoperable
Mathematical problems for complex networks
Copyright @ 2012 Zidong Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is made available through the Brunel Open Access Publishing Fund.Complex networks do exist in our lives. The brain is a neural network. The global economy
is a network of national economies. Computer viruses routinely spread through the Internet. Food-webs, ecosystems, and metabolic pathways can be represented by networks. Energy is distributed through transportation networks in living organisms, man-made infrastructures, and other physical systems. Dynamic behaviors of complex networks, such as stability, periodic oscillation, bifurcation, or even chaos, are ubiquitous in the real world and often reconfigurable. Networks have been studied in the context of dynamical systems in a range of disciplines. However, until recently there has been relatively little work that treats dynamics as a function of network structure, where the states of both the nodes and the edges can change, and the topology of the network itself often evolves in time. Some major problems have not been fully investigated, such as the behavior of stability, synchronization and chaos control for complex networks, as well as their applications in, for example, communication and bioinformatics
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