Andri Lareida

Box2Box - A P2P-based file-sharing and synchronization application

Due to an increasing number of devices connected to the Internet, data synchronization becomes more important. Centrally managed storage services, such as Dropbox, are popular for synchronizing data between several devices. P2P-based approaches that run fully decentralized, such as BitTorrent-Sync, are starting to emerge. This paper presents Box2Box, a new P2P file synchronization application which supports novel features not present in BitTorrent-Sync. Box2Box is demonstrated in several use cases each targeted at another feature.

A Blockchain-Based Architecture for Collaborative DDoS Mitigation with Smart Contracts

The rapid growth in the number of insecure portable and stationary devices and the exponential increase of traffic volume makes Distributed Denial-of-Service (DDoS) attacks a top security threat to services provisioning. Existing defense mechanisms lack resources and flexibility to cope with attacks by themselves, and by utilizing other’s companies resources, the burden of the mitigation can be shared. Emerging technologies such as blockchain and smart contracts allows for the sharing of attack information in a fully distributed and automated fashion. In this paper, the design of a novel architecture is proposed by combining these technologies introducing new opportunities for flexible and efficient DDoS mitigation solutions across multiple domains. Main advantages are the deployment of an already existing public and distributed infrastructure to advertise white or blacklisted IP addresses, and the usage of such infrastructure as an additional security mechanism to existing DDoS defense systems, without the need to build specialized registries or other distribution mechanisms, which enables the enforcement of rules across multiple domains.

Overlay network measurements with distribution evolution and geographical visualization

Since Video-on-Demand (VoD) streaming and general overlay traffic, especially file sharing, are causing the main portion of todays Internet traffic, Internet Service Providers (ISP) face (a) challenges of network congestion during peak hours and (b) tussles between Video Content Providers (VCP) and ISPs, which can lead to congestion. However, dedicated traffic traces are not available today due to (a) the lacking interest of VCPs to share their internal data, e.g., avoiding problems with privacy issues, and (b) the unavailability of measurement studies for overlay networks that are neither too specific nor cover more than a snap-shot of the network, which does reflect the essential traffic evolution over time. Thus, this paper bridges this gap between suitable traffic data and a video consumption analysis by (1) the development and prototyping of a new system to continuously monitor Video Consumption in Overlay Networks (VIOLA), resulting in an extensive and comprehensive measurement data set for detailed network evolutions over time in case of BitTorrent, and (2) a generic and reusable geographic visualization approach termed GeoChart, which aggregates selected data into a generic data structure to visualize them on a map.

The BitTorrent Peer Collector Problem

Peer-to-Peer (P2P) systems measurements are still a relevant research topic, since insights in large swarm sizes and churn are not yet available for the BitTorrent network. To improve existing measurement methodology, this work here tackles the aspect of swarm size estimation and complete collection in the BitTorrent network. For this purpose the Coupon Collector Problem is modified and formulated as the BitTorrent Peer Collector (BTPC) Problem. Thus, (a) simulations are used to test simple and maximum likelihood estimation for hidden swarm sizes, (b) an analytical solution to the BTPC problem is presented, and (c) measurements are used to evaluate estimators of the BTPC model. Obtained results show that this estimation works well for classical trackers and that churn constantly influences measurements. Those results show that more peers use the Main-line DHT than a single tracker, however, client implementations challenge those models working well for trackers.

Abstracting .torrent content consumption into two-mode graphs and their projection to content networks (ConNet)

Video-on-demand and live streaming services are about to take over video discs. Video streaming services typically cannot compete with the content available in Peer-to-Peer (P2P) file sharing networks. Thus, content providers can use P2P systems to identify content to include in their offer. This work defines a novel method to apply Social Network Analysis (SNA) on video streaming or download traces. Those traces are abstracted int a two-mode graph, which is projected to a content-centric one mode graph (ConNet). SNA measures are used on a ConNet to classify a content-centric graph and provide a general interpretation and insights into the system the traces were collected from. To evaluate the proposed method, real world traces acquired from BitTorrent (BT) swarms sharing movies and television (TV) shows are used to construct 48 hourly graphs to show the evolution of the graph. The results show that the video network can be classified as scale-free, that SNA measures can be used as an alternative popularity indicator, and that the network evolves over time and exhibits diurnal patterns. Finally, this work shows that the proposed method can be applied to real world traces and provides a novel perspective on video consumption.

Towards Path Quality Metrics for Overlay Networks

Decentralized systems, such as overlay networks or content delivery networks, form a virtual network on top of a physical network leading to inefficiencies in handling network traffic as physical locations are not considered. Therefore, this work investigates, analyzes, and evaluates two feasible network locality metrics for decentralized systems to overcome such inefficiencies. Furthermore, those metrics to determine network locality have been implemented and evaluated within an international testbed. These metrics evaluated consider aspects of path stability and path symmetry. The evaluation performed did reveal that the stability and symmetry metrics provide accurate locality indication.

Automatic network configuration with dynamic churn prediction

Peer-to-Peer (P2P) systems have been deployed on millions of nodes worldwide in environments that range from static to very dynamic and therefore exhibit different churn levels. Typically, P2P systems introduce redundancy to cope with loss of nodes. In distributed hash tables, redundancy often fixed during development or at initial deployment of the system. This can limit the applicability of the system to stable environments or make them inefficient in such environments. Automatic network configuration can make a system more adaptable to changing environments and reduce manual configuration tasks. Therefore, this paper proposes an automatic replication configuration based on churn prediction that automatically adapts its replication configuration to its environment. The mechanism termed dynamic replication mechanism (dynamic RM) developed and evaluated in this paper is based on exponential moving averages to predict churn that is used itself to determine a replication factor meeting a certain reliability threshold. Simulations with synthetic data and experiments with data from torrent trackers show that the behavior can be predicted accurately in any environment, from low churn rates to diurnal and high churn rates.