43,011 research outputs found
Optimal network topologies for local search with congestion
The problem of searchability in decentralized complex networks is of great
importance in computer science, economy and sociology. We present a formalism
that is able to cope simultaneously with the problem of search and the
congestion effects that arise when parallel searches are performed, and obtain
expressions for the average search cost--written in terms of the search
algorithm and the topological properties of the network--both in presence and
abscence of congestion. This formalism is used to obtain optimal network
structures for a system using a local search algorithm. It is found that only
two classes of networks can be optimal: star-like configurations, when the
number of parallel searches is small, and homogeneous-isotropic configurations,
when the number of parallel searches is large.Comment: 4 pages. Final version accepted in PR
Impact of community structure on information transfer
The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount
Datacenter Traffic Control: Understanding Techniques and Trade-offs
Datacenters provide cost-effective and flexible access to scalable compute
and storage resources necessary for today's cloud computing needs. A typical
datacenter is made up of thousands of servers connected with a large network
and usually managed by one operator. To provide quality access to the variety
of applications and services hosted on datacenters and maximize performance, it
deems necessary to use datacenter networks effectively and efficiently.
Datacenter traffic is often a mix of several classes with different priorities
and requirements. This includes user-generated interactive traffic, traffic
with deadlines, and long-running traffic. To this end, custom transport
protocols and traffic management techniques have been developed to improve
datacenter network performance.
In this tutorial paper, we review the general architecture of datacenter
networks, various topologies proposed for them, their traffic properties,
general traffic control challenges in datacenters and general traffic control
objectives. The purpose of this paper is to bring out the important
characteristics of traffic control in datacenters and not to survey all
existing solutions (as it is virtually impossible due to massive body of
existing research). We hope to provide readers with a wide range of options and
factors while considering a variety of traffic control mechanisms. We discuss
various characteristics of datacenter traffic control including management
schemes, transmission control, traffic shaping, prioritization, load balancing,
multipathing, and traffic scheduling. Next, we point to several open challenges
as well as new and interesting networking paradigms. At the end of this paper,
we briefly review inter-datacenter networks that connect geographically
dispersed datacenters which have been receiving increasing attention recently
and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial
Optimized network structure and routing metric in wireless multihop ad hoc communication
Inspired by the Statistical Physics of complex networks, wireless multihop ad
hoc communication networks are considered in abstracted form. Since such
engineered networks are able to modify their structure via topology control, we
search for optimized network structures, which maximize the end-to-end
throughput performance. A modified version of betweenness centrality is
introduced and shown to be very relevant for the respective modeling. The
calculated optimized network structures lead to a significant increase of the
end-to-end throughput. The discussion of the resulting structural properties
reveals that it will be almost impossible to construct these optimized
topologies in a technologically efficient distributive manner. However, the
modified betweenness centrality also allows to propose a new routing metric for
the end-to-end communication traffic. This approach leads to an even larger
increase of throughput capacity and is easily implementable in a
technologically relevant manner.Comment: 25 pages, v2: fixed one small typo in the 'authors' fiel
Efficient routing on scale-free networks based on local information
In this letter, we propose a new routing strategy with a single free
parameter only based on local information of network topology. In
order to maximize the packets handling capacity of underlying structure that
can be measured by the critical point of continuous phase transition from free
flow to congestion, the optimal value of is sought out. By
investigating the distributions of queue length on each node in free state, we
give an explanation why the delivering capacity of the network can be enhanced
by choosing the optimal . Furthermore, dynamic properties right after
the critical point are also studied. Interestingly, it is found that although
the system enters the congestion state, it still possesses partial delivering
capability which do not depend on . This phenomenon suggests that the
capacity of the network can be enhanced by increasing the forwarding ability of
small important nodes which bear severe congestion.Comment: 4 pages, 7 figure
Information transfer in community structured multiplex networks
The study of complex networks that account for different types of
interactions has become a subject of interest in the last few years, specially
because its representational power in the description of users interactions in
diverse online social platforms (Facebook, Twitter, Instagram, etc.). The
mathematical description of these interacting networks has been coined under
the name of multilayer networks, where each layer accounts for a type of
interaction. It has been shown that diffusive processes on top of these
networks present a phenomenology that cannot be explained by the naive
superposition of single layer diffusive phenomena but require the whole
structure of interconnected layers. Nevertheless, the description of diffusive
phenomena on multilayer networks has obviated the fact that social networks
have strong mesoscopic structure represented by different communities of
individuals driven by common interests, or any other social aspect. In this
work, we study the transfer of information in multilayer networks with
community structure. The final goal is to understand and quantify, if the
existence of well-defined community structure at the level of individual
layers, together with the multilayer structure of the whole network, enhances
or deteriorates the diffusion of packets of information.Comment: 13 pages, 6 figure
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