5,516 research outputs found
Paid Peering, Settlement-Free Peering, or Both?
With the rapid growth of congestion-sensitive and data-intensive
applications, traditional settlement-free peering agreements with best-effort
delivery often do not meet the QoS requirements of content providers (CPs).
Meanwhile, Internet access providers (IAPs) feel that revenues from end-users
are not sufficient to recoup the upgrade costs of network infrastructures.
Consequently, some IAPs have begun to offer CPs a new type of peering
agreement, called paid peering, under which they provide CPs with better data
delivery quality for a fee. In this paper, we model a network platform where an
IAP makes decisions on the peering types offered to CPs and the prices charged
to CPs and end-users. We study the optimal peering schemes for the IAP, i.e.,
to offer CPs both the paid and settlement-free peering to choose from or only
one of them, as the objective is profit or welfare maximization. Our results
show that 1) the IAP should always offer the paid and settlement-free peering
under the profit-optimal and welfare-optimal schemes, respectively, 2) whether
to simultaneously offer the other peering type is largely driven by the type of
data traffic, e.g., text or video, and 3) regulators might want to encourage
the IAP to allocate more network capacity to the settlement-free peering for
increasing user welfare
On Optimal Service Differentiation in Congested Network Markets
As Internet applications have become more diverse in recent years, users
having heavy demand for online video services are more willing to pay higher
prices for better services than light users that mainly use e-mails and instant
messages. This encourages the Internet Service Providers (ISPs) to explore
service differentiations so as to optimize their profits and allocation of
network resources. Much prior work has focused on the viability of network
service differentiation by comparing with the case of a single-class service.
However, the optimal service differentiation for an ISP subject to resource
constraints has remained unsolved. In this work, we establish an optimal
control framework to derive the analytical solution to an ISP's optimal service
differentiation, i.e. the optimal service qualities and associated prices. By
analyzing the structures of the solution, we reveal how an ISP should adjust
the service qualities and prices in order to meet varying capacity constraints
and users' characteristics. We also obtain the conditions under which ISPs have
strong incentives to implement service differentiation and whether regulators
should encourage such practices
Sampling Online Social Networks via Heterogeneous Statistics
Most sampling techniques for online social networks (OSNs) are based on a
particular sampling method on a single graph, which is referred to as a
statistics. However, various realizing methods on different graphs could
possibly be used in the same OSN, and they may lead to different sampling
efficiencies, i.e., asymptotic variances. To utilize multiple statistics for
accurate measurements, we formulate a mixture sampling problem, through which
we construct a mixture unbiased estimator which minimizes asymptotic variance.
Given fixed sampling budgets for different statistics, we derive the optimal
weights to combine the individual estimators; given fixed total budget, we show
that a greedy allocation towards the most efficient statistics is optimal. In
practice, the sampling efficiencies of statistics can be quite different for
various targets and are unknown before sampling. To solve this problem, we
design a two-stage framework which adaptively spends a partial budget to test
different statistics and allocates the remaining budget to the inferred best
statistics. We show that our two-stage framework is a generalization of 1)
randomly choosing a statistics and 2) evenly allocating the total budget among
all available statistics, and our adaptive algorithm achieves higher efficiency
than these benchmark strategies in theory and experiment
Will mobile video become the killer application for 3G? - an empirical model for media convergence
Mobile carriers have continually rolled out 3G mobile video applications to increase their revenue and profits. The presumption is that video is superior to the already successful SMS, ringtones, and pictures, and can create greater value to users. However, recent market surveys revealed contradicting results. Motivated by this discrepancy, we propose in this paper a parsimonious model for user acceptance of mobile entertainment as digital convergence. Integrating research on Information Systems, Flow, and Media Psychology, we take a unique approach to user acceptance of digital convergence - platform migration. Our key proposition is that the interaction between media types and the platform-specific constraints is the key determinant of user evaluation. Particularly, users' involvement in the media is determined by both the entertaining time span on the original platform and the attentional constraint of the new platform. The mismatch between the two spans can result in lower level involvement, which in turn cause no or even negative user emotional responses. The model was tested with empirical data. We discuss the theoretical contributions, strategic and design implications, and future research directions derived from this theoretical framewor
A new parametric equation of state and quark stars
It is still a matter of debate to understand the equation of state of cold
supra-nuclear matter in compact stars because of unknown on-perturbative strong
interaction between quarks. Nevertheless, it is speculated from an
astrophysical view point that quark clusters could form in cold quark matter
due to strong coupling at realistic baryon densities. Although it is hard to
calculate this conjectured matter from first principles, one can expect the
inter-cluster interaction to share some general features to nucleon-nucleon
interaction. We adopt a two-Gaussian component soft-core potential with these
general features and show that quark clusters can form stable simple cubic
crystal structure if we assume Gaussian form wave function. With this
parameterizing, Tolman-Oppenheimer-Volkoff equation is solved with reasonable
constrained parameter space to give mass-radius relation of crystalline solid
quark star. With baryon densities truncated at 2 times nuclear density at
surface and range of interaction fixed at 2fm we can reproduce similar
mass-radius relation to that obtained with bag model equations of state. The
maximum mass ranges from about 0.5 to 3 solar mass. Observed maximum pulsar
mass (about 2 solar mass) is then used to constrain parameters of this simple
interaction potential.Comment: 5 pages, 2 figure
Mutual selection in network evolution: the role of the intrinsic fitness
We propose a new mechanism leading to scale-free networks which is based on
the presence of an intrinsic character of a vertex called fitness. In our
model, a vertex is assigned a fitness , drawn from a given probability
distribution function . During network evolution, with rate we add a
vertex of fitness and connect to an existing vertex of fitness
selected preferentially to a linking probability function
which depends on the fitnesses of the two vertices involved and, with rate
we create an edge between two already existed vertices with fitnesses
and , with a probability also preferential to the connection
function . For the proper choice of , the resulting networks
have generalized power laws, irrespective of the fitness distribution of
vertices.Comment: ws-ijmpc.te
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