Distributing long-tail content is a difficult task due to the low amortization of bandwidth transfer costs as such content has limited number of views. Two recent trends are making this problem harder. First, the increasing popularity of user-generated content and online social networks create and reinforce such popularity distributions. Second, the recent trend of geo-replicating content across multiple points of presence spread around the world, done for improving quality of experience (QoE) for users. In this paper, we analyze and explore the tradeoff involving the “freshness” of the information available to the users and WAN bandwidth costs, and we propose ways to reduce the latter through smart update propagation scheduling, by leveraging on the knowledge of the mapping between social relationships and geographic location, the timing regularities and time differences in end user activity. We first assess the potential of our approach by implementing a simple social-aware scheduling algorithm that operates under bandwidth budget constraints and by quantifying its benefits through a trace-driven analysis. We show that it can reduce WAN traffic by up to 55 percent compared to an immediate update of all replicas, with a minimal effect on information freshness and latency. Second, we build TailGate, a practical system that implements our social-aware scheduling approach, which distributes on the fly long-tail content across PoPs at reduced bandwidth costs by flattening the traffic. We evaluate TailGate by using traces from an OSN and show that it can decrease WAN bandwidth costs by as much as 80 percent and improve QoE. We deploy TailGate on PlanetLab and show that even in the case when imprecise social information is available, it can still decrease by a factor of 2 the latency for accessing long-tail YouTube videos.

Distributing long-tail content is an inherently difficult task due to the low amortization of bandwidth transfer costs as such content has limited number of views. Two recent trends are making this problem harder. First, the increasing popularity of user-generated content (UGC) and online social networks (OSNs) create and reinforce such popularity distributions. Second, the recent trend of geo-replicating content across multiple PoPs spread around the world, done for improving quality of experience (QoE) for users and for redundancy reasons, can lead to unnecessary bandwidth costs. We build TailGate, a system that exploits social relationships, regularities in read access patterns, and time-zone differences to efficiently and selectively distribute long-tail content across PoPs. We evaluate TailGate using large traces from an OSN and show that it can decrease WAN bandwidth costs by as much as 80% as well as reduce latency, improving QoE. We deploy TailGate on PlanetLab and show that even in the case when imprecise social information is available, TailGate can still decrease the latency for accessing long-tail YouTube videos by a factor of 2.

Human communication has changed by the advent of smartphones. Using commonplace mobile device features, they started uploading large amounts of content that increases. This increase in demand will overwhelm capacity and limits the providers' ability to provide the quality of service demanded by their users. In the absence of technical solutions, cellular network providers are considering changing billing plans to address this. Our contributions are twofold. First, by analyzing user content upload behavior, we find that the user-generated content problem is a user behavioral problem. Particularly, by analyzing user mobility and data logs of 2 million users of one of the largest US cellular providers, we find that: 1) users upload content from a small number of locations; 2) because such locations are different for users, we find that the problem appears ubiquitous. However, we find that: 3) there exists a significant lag between content generation and uploading times, and 4) with respect to users, it is always the same users to delay. Second, we propose a cellular network architecture. Our approach proposes capacity upgrades at a select number of locations called Drop Zones. Although not particularly popular for uploads originally, Drop Zones seamlessly fall within the natural movement patterns of a large number of users. They are therefore suited for uploading larger quantities of content in a postponed manner. We design infrastructure placement algorithms and demonstrate that by upgrading infrastructure in only 963 base stations across the entire US, it is possible to deliver 50% of content via Drop Zones.

Smartphones have changed the way people communicate. Most prominently, using commonplace mobile device features (e.g., high resolution cameras), they started producing and uploading large amounts of content that increases at an exponential pace. In the absence of viable technical solutions, some cellular network providers are considering to start charging special usage fees to address the problem. Our contributions are twofold. First, we find that the user-generated content problem is a user-behavioral problem. By analyzing user mobility and data logs of close to 2 million users of a cellular network, we find that (i) users upload content from a small number of locations, typically corresponding to their home or work locations; (ii) because such locations are different for different users, we find that the problem appears ubiquitous, since user-generated content uploads grow exponentially at most locations. However, we also find that (Hi) there exists a significant lag between content generation and uploading times. For example, we find that 55% of content that is uploaded via mobile phones is at least 1 day old. Second, based on the above insights, we propose a new cellular network architecture. Our approach proposes capacity upgrades at a select number of locations called Drop Zones. Although not particularly popular for uploads originally, Drop Zones seamlessly fall within the natural movement patterns of a large number of users. They are therefore better suited for uploading larger quantities of content in a postponed manner. We design infrastructure placement algorithms and demonstrate that by upgrading infrastructure in only 963 base-stations across the entire United States, it is possible to deliver 50% of total content via the Drop Zones.

Characterizing the relationship that exists between people's application interests and mobility properties is the core question relevant for location-based services, in particular those that facilitate serendipitous discovery of people, businesses and objects. In this paper, we apply rule mining and spectral clustering to study this relationship for a population of over 280,000 users of a 3G mobile network in a large metropolitan area. Our analysis reveals that (i) People's movement patterns are correlated with the applications they access, e.g., stationary users and those who move more often and visit more locations tend to access different applications. (ii) Location affects the applications accessed by users, i.e., at certain locations, users are more likely to evince interest in a particular class of applications than others irrespective of the time of day. (iii) Finally, the number of serendipitous meetings between users of similar cyber interest is larger in regions with higher density of hotspots. Our analysis demonstrates how cellular network providers and location-based services can benefit from knowledge of the inter-play between users and their locations and interests.

Understanding Internet access trends at a global scale, i.e., what do people do on the Internet, is a challenging problem that is typically addressed by analyzing network traces. However, obtaining such traces presents its own set of challenges owing to either privacy concerns or to other operational difficulties. The key hypothesis of our work here is that most of the information needed to profile the Internet endpoints is already available around us - on the web.

The paper presents a testbed for native IPv6 multicast and tries to evaluate the available routing protocols such as PIM-DM and PIM-SM. From an objective perspective we can measure the join latency, as well as multicast forwarding delay, its jitter and the control overhead. Having a calibrated software tool, we can evaluate later the existing alternative solution towards IPv6 multicast: CastGate and CastGate router. The proposed enhancements are referring to PIM-SM support and to the possibility of migrating from IPv4 to IPv6 on CastGate architectures