5,516 research outputs found

    Paid Peering, Settlement-Free Peering, or Both?

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    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

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    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

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    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

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    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

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    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

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    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 ii is assigned a fitness xix_i, drawn from a given probability distribution function f(x)f(x). During network evolution, with rate pp we add a vertex jj of fitness xjx_j and connect to an existing vertex ii of fitness xix_i selected preferentially to a linking probability function g(xi,xj)g(x_i,x_j) which depends on the fitnesses of the two vertices involved and, with rate 1−p1-p we create an edge between two already existed vertices with fitnesses xix_i and xjx_j, with a probability also preferential to the connection function g(xi,xj)g(x_i,x_j). For the proper choice of gg, the resulting networks have generalized power laws, irrespective of the fitness distribution of vertices.Comment: ws-ijmpc.te
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