50,956 research outputs found
Highly intensive data dissemination in complex networks
This paper presents a study on data dissemination in unstructured
Peer-to-Peer (P2P) network overlays. The absence of a structure in unstructured
overlays eases the network management, at the cost of non-optimal mechanisms to
spread messages in the network. Thus, dissemination schemes must be employed
that allow covering a large portion of the network with a high probability
(e.g.~gossip based approaches). We identify principal metrics, provide a
theoretical model and perform the assessment evaluation using a high
performance simulator that is based on a parallel and distributed architecture.
A main point of this study is that our simulation model considers
implementation technical details, such as the use of caching and Time To Live
(TTL) in message dissemination, that are usually neglected in simulations, due
to the additional overhead they cause. Outcomes confirm that these technical
details have an important influence on the performance of dissemination schemes
and that the studied schemes are quite effective to spread information in P2P
overlay networks, whatever their topology. Moreover, the practical usage of
such dissemination mechanisms requires a fine tuning of many parameters, the
choice between different network topologies and the assessment of behaviors
such as free riding. All this can be done only using efficient simulation tools
to support both the network design phase and, in some cases, at runtime
Coverage centralities for temporal networks
Structure of real networked systems, such as social relationship, can be
modeled as temporal networks in which each edge appears only at the prescribed
time. Understanding the structure of temporal networks requires quantifying the
importance of a temporal vertex, which is a pair of vertex index and time. In
this paper, we define two centrality measures of a temporal vertex based on the
fastest temporal paths which use the temporal vertex. The definition is free
from parameters and robust against the change in time scale on which we focus.
In addition, we can efficiently compute these centrality values for all
temporal vertices. Using the two centrality measures, we reveal that
distributions of these centrality values of real-world temporal networks are
heterogeneous. For various datasets, we also demonstrate that a majority of the
highly central temporal vertices are located within a narrow time window around
a particular time. In other words, there is a bottleneck time at which most
information sent in the temporal network passes through a small number of
temporal vertices, which suggests an important role of these temporal vertices
in spreading phenomena.Comment: 13 pages, 10 figure
Minimizing Seed Set Selection with Probabilistic Coverage Guarantee in a Social Network
A topic propagating in a social network reaches its tipping point if the
number of users discussing it in the network exceeds a critical threshold such
that a wide cascade on the topic is likely to occur. In this paper, we consider
the task of selecting initial seed users of a topic with minimum size so that
with a guaranteed probability the number of users discussing the topic would
reach a given threshold. We formulate the task as an optimization problem
called seed minimization with probabilistic coverage guarantee (SM-PCG). This
problem departs from the previous studies on social influence maximization or
seed minimization because it considers influence coverage with probabilistic
guarantees instead of guarantees on expected influence coverage. We show that
the problem is not submodular, and thus is harder than previously studied
problems based on submodular function optimization. We provide an approximation
algorithm and show that it approximates the optimal solution with both a
multiplicative ratio and an additive error. The multiplicative ratio is tight
while the additive error would be small if influence coverage distributions of
certain seed sets are well concentrated. For one-way bipartite graphs we
analytically prove the concentration condition and obtain an approximation
algorithm with an multiplicative ratio and an
additive error, where is the total number of nodes in the social graph.
Moreover, we empirically verify the concentration condition in real-world
networks and experimentally demonstrate the effectiveness of our proposed
algorithm comparing to commonly adopted benchmark algorithms.Comment: Conference version will appear in KDD 201
A Novel Airborne Self-organising Architecture for 5G+ Networks
Network Flying Platforms (NFPs) such as unmanned aerial vehicles, unmanned
balloons or drones flying at low/medium/high altitude can be employed to
enhance network coverage and capacity by deploying a swarm of flying platforms
that implement novel radio resource management techniques. In this paper, we
propose a novel layered architecture where NFPs, of various types and flying at
low/medium/high layers in a swarm of flying platforms, are considered as an
integrated part of the future cellular networks to inject additional capacity
and expand the coverage for exceptional scenarios (sports events, concerts,
etc.) and hard-to-reach areas (rural or sparsely populated areas). Successful
roll-out of the proposed architecture depends on several factors including, but
are not limited to: network optimisation for NFP placement and association,
safety operations of NFP for network/equipment security, and reliability for
NFP transport and control/signaling mechanisms. In this work, we formulate the
optimum placement of NFP at a Lower Layer (LL) by exploiting the airborne
Self-organising Network (SON) features. Our initial simulations show the NFP-LL
can serve more User Equipment (UE)s using this placement technique.Comment: 5 pages, 2 figures, conference paper in IEEE VTC-Fall 2017, in
Proceedings IEEE Vehicular Technology Conference (VTC-Fall 2017), Toronto,
Canada, Sep. 201
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
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