While various models have been proposed for generating social/friendship network graphs, the dynamics of user interactions through online social network (OSN) based applications remain largely unexplored. We previously developed a growth model to capture static weekly snapshots of user activity graphs (UAGs) using data from popular Facebook gifting applications. This paper presents a new continuous graph evolution model aimed to capture microscopic user-level behaviors that govern the growth of the UAG and collectively define the overall graph structure. We demonstrate the utility of our model by applying it to forecast the number of active users over time as the application transitions from initial growth to peak/mature and decline/fatique phase. Using empirical evaluations, we show that our model can accurately reproduce the evolution trend of active user population for gifting applications, or other OSN applications that employ similar growth mechanisms. We also demonstrate that the predictions from our model can guide the generation of synthetic graphs that accurately represent empirical UAG snapshots sampled at different evolution stages.

We employ user activity data from three highly popular gifting applications on Facebook to study the evolution of user activity on applications through the most commonly-used growth mechanism, namely Application Requests. We find user activity graphs differ from friendship graphs in large part due to the inherent directionality of user activity, and node transience. Our results show that, unlike degree distributions in friendship graphs, activity graphs exhibit strong asymmetry in in- and out-degree distributions, and that out-degrees are not accurately described by currently known parametric distributions. As such, user activity graphs cannot be simulated through existing intent- and feature-driven algorithms that can model friendship graphs.

With over half a billion users, Online Social Networks (OSNs) are the major new applications on the Internet. Little information is available on the network impact of OSNs, although there is every expectation that the volume and diversity of traffic due to OSNs is set to explode. In this paper, we examine the specific role played by a key component of OSNs: the extremely popular and widespread set of third-party applications on some of the most popular OSNs. With over 81,000 third-party applications on Facebook alone, their impact is hard to predict and even harder to study.

Online social networking sites such as Facebook and MySpace have become increasingly popular, with close to 500 million users as of August 2008. The introduction of the Facebook Developer Platform and OpenSocial allows third-party developers to launch their own applications for the existing massive user base. The viral growth of these social applications can potentially influence how content is produced and consumed in the future Internet.

Ethernet is a low-cost, flexible and high-speed transport technology, which has traditionally seen success in local area networks and is rapidly gaining popularity in metro networks. However, its control plane, primarily based on spanning tree protocol, is not well-suited for the metro and core networks. For such networks, the IETF is evaluating a proposed framework called GELS which uses GMPLS as the control plane for Ethernet data plane. In this paper, we provide a quantitative assessment of GELS for service provider networks. In particular, we perform simulations using COST239 and COST266 networks to evaluate the performance of GELS under normal network conditions, as well as under failure conditions. Under normal network conditions, we find that the use of GELS results in placement of up to 46.4% more bandwidth when compared with native Ethernet control such as RSTP. In terms of LSP acceptance, GELS shows a 45.5% improvement over RSTP. Similarly, average link utilization using GELS is significantly better than the average link utilization when the native Ethernet control plane is used. When considering single element failures, RSTP recovers by converging to a potentially new spanning tree, which may take unacceptably long. In contrast, well-known restoration and protection mechanisms of GMPLS control plane result in much faster recovery. We And that the convergence times exhibited by GELS after single element failures are orders of magnitude better than those obtained when RSTP is used.