This thesis examines the consequences of an increased institutional involvement in the recently emerging lending business known as peer-to-peer lending (P2PL). Since the P2PL business itself is a type of originate-to-distribute (OTD) lending model – in which the originator never carries the risk for the loans – this thesis investigates the effects it can have on the quality of the screening of potential borrowers, and if it could create a misalignment of interests between different stakeholders in the P2PL market. It also examines how the information asymmetry in the screening process is affecting moral hazard behavior and adverse selection problems. From the empirical research – which was gathered from interviews with significant participants in the Swedish P2PL market and the financial market as a whole – the authors find that an increased institutional involvement seems to come hand-in-hand with an increased loan volume, which creates incentives for the P2PL companies to ease their screening of borrowers and thus decreasing the average quality of the loans they originate. Furthermore, it shows evidence of great similarities between the current P2PL market and the sub-prime mortgage market that was the cause of the financial crisis in 2008. By comparing different geographic P2PL markets the thesis is providing the reader with four development phases that the P2PL markets seem to follow.

This thesis targets at modeling and resolving practical problems using mathematical tools in two representative networking systems nowadays, i.e., peer-to-peer (P2P) video streaming system and cloud computing system. In the first part, we study how to mitigate the following tussle between content service providers and ISPs in P2P video streaming systems: network-agnostic P2P protocol designs bring lots of inter-ISP traffic and increase traffic relay cost of ISPs; in turn, ISPs start to throttle P2P packets, which significantly deteriorates P2P streaming performance. First, we investigate the problem in a mesh-based P2P live streaming system. We use end-to-end streaming delays as performance, and quantify the amount of inter-ISP traffic with the number of copies of the live streams imported into each ISP. Considering multiple ISPs at different bandwidth levels, we model the generic relationship between the volume of inter-ISP traffic and streaming performance, which provides useful insights on the design of effective locality-aware peer selection protocols and server deployment strategies across multiple ISPs. Next, we study a similar problem in a hybrid P2P-cloud CDN system for VoD streaming. We characterize the relationship between the costly bandwidth consumption from the cloud CDN and the inter-ISP traffic. We apply a loss network model to derive the bandwidth consumption under any given chunk distribution pattern among peer caches and any streaming request dispatching strategy among ISPs, and derive the optimal peer caching and request dispatching strategies which minimize the bandwidth demand from the cloud CDN. Based on the fundamental insights from our analytical results, we design a locality-aware, hybrid P2P-cloud CDN streaming protocol. In the second part, we study the profit maximization and cost minimization problems in Infrastructure-as- a- Service (IaaS) cloud systems. The first problem is how a geo-distributed cloud system should price its datacenter resources at different locations, such that its overall profit is maximized over long-term operation. We design an efficient online algorithm for dynamic pricing of VM resources across datacenters, together with job scheduling and server provisioning in each datacenter, to maximize the cloud's profit over the long run. Theoretical analysis shows that our algorithm can schedule jobs within their respective deadlines, while achieving a time-averaged overall profit closely approaching the offline maximum, which is computed by assuming perfect information on future job arrivals is freely available. The second problem is how federated clouds should trade their computing resources among each other to reduce the cost, by exploiting diversities of different clouds' workloads and operational costs. We formulate a global cost minimization problem among multiple clouds under the cooperative scenario where each individual cloud's workload and cost information is publicly available. Taking into considerations jobs with disparate length, a non-preemptive approximation algorithm for leftover job migration and new job scheduling is designed. Given to the selfishness of individual clouds, we further design a randomized double auction mechanism to elicit clouds' truthful bidding for buying or selling virtual machines. The auction mechanism is proven to be truthful, and to guarantee the same approximation ratio to what the cooperative approximation algorithm achieves. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

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We are witnessing a proliferation of video in the Internet; YouTube is the most bandwidth intensive service of today’s Internet. It accounts for 20 - 35% of the Internet traffic with 35 hours of videos uploaded every minute and more than 700 billion playbacks in 2010. Netflix, a web service that streams premium contents such as TV series, shows, and movies, consumes 30% of the network bandwidth in North America at peak time. Recently, leveraging the content distribution networks (CDNs), a new paradigm for video streaming on the Internet has emerged, namely, Adaptive HTTP Streaming (AHS). AHS has become the industry standard for video streaming over the Internet adopted by broadcast networks as well as VoD services such as YouTube, Netflix, Hulu, etc. In the 90’s and early 2000’s, Internet-based video streaming for high-bitrate video was challenging due to hardware limitations. In that era, to cover the hardware limitations, every software component of a video server needed to be carefully optimized to support the real-time guarantees for jitter-free video delivery. However, most of the software solutions have become less important with the remarkable hardware improvements over the past two decades. There is 100× speedup in CPU speeds; RAM capacity has increased by 1,000×; hard disk drive (HDD) capacity has grown by 10,000×. Today, CPU is no longer a bottleneck for video streaming. On the other hand, storage bandwidth and network bandwidth are still serious bottlenecks for large scale on-demand video streaming. In this dissertation, we aim at a scalable video content distribution system that addresses both storage bottleneck and network bottleneck. The first part of the dissertation pertains to the storage system on the server side: A multi-tiered storage system that exploits a flash memory solid-state drive (SSD) can meet the bandwidth needs in a much more cost- effective way than a traditional two-tier storage system. We first identify the challenges in architecting such a system given the performance quirks of flash-based SSDs, and the lim- itations of state-of-the-art multi-tiered storage systems for video streaming. Armed with the knowledge of these challenges, we show how to construct such a storage system and implement a real web server with multi-tiered storage, evaluate the system with AHS work- loads, and demonstrate significant performance gains while reducing the TCO. The second part of the dissertation pertains to the network system on the client side: Integrating peer- to-peer (P2P) technology with the client-server paradigm results in a much more scalable video content distribution system. AHS is a paradigm for client-driven video streaming; its philosophy matches well with that of P2P video streaming. An adaptation mechanism is the most important component of AHS that determines overall video streaming quality and user experience. We show a throughput-smoothing-based adaptation mechanism that is designed for a client-server architecture does not work well for a P2P architecture. We pro- vide a buffer-based adaptation mechanism, evaluate our solution with OMNeT++/INET simulator, and demonstrate significant performance gains.

published_or_final_version / abstract / Electrical and Electronic Engineering / Master / Master of Philosophy

The Napster case has created a frenzy of controversy and confusion. The Peer to Peer technology developed by Napster creator Shawn Fanning, has forced the courts, the legislature, corporations, and individuals to reconsider the use of the Internet. Peer to peer networks create new challenges for the application of copyright law. However, these challenges are not that different from those which copyright law has evolved to accommodate in the past. Copyright law is intended to balance the interests of the creators and the public to promote the progress of science and useful arts. The premise behind copyright protection is to ensure that people continue creating, and that the public continues to enjoy those creations, through the mechanism of rewarding the creators with a temporary monopoly over their works. This balance of interests is fundamental to the interpretation of copyright law by the United States Congress and the Courts. This thesis focuses on the application and interpretation of copyright law through a case study of the law in the United States, in particular the Napster case. Although it now appears that the Internet can be subject to some form of regulation with the aid of technological innovation to enforce the regulation, the Courts in the Napster case have misinterpreted the previous judicial consideration attributed to copyright law. In essence, the fundamental principle of the balancing of interests has been lost. We are now left with an unequal balance in favor of large media conglomerates. It can be argued that the media conglomerates have used Napster as an example of their power to control the technology of peer to peer networking as a model of distribution. Napster demonstrates that peer to peer is an effective way of sharing information with an extremely large amount of people. This has the music industry scared, resulting in their legal battle to shut down the Napster technology. The claims of copyright misuse raise awareness of the need for regulation and a reassessment of copyright application in a digital age. There is a need for regulation. However, any attempts at further application of law and regulation to the Internet concerning copyright protection should consider the intent of the constitutional founders of the United States -- copyright law is intended to protect the interests of both the artists, and the public.

A covert communications network (CCN) is a connected, overlay peer-to-peer network used to support communications within a group in which the survival of the group depends on the confidentiality and anonymity of communications, on concealment of participation in the network to both other members of the group and external eavesdroppers, and finally on resilience against disconnection. In this dissertation, we describe the challenges and requirements for such a system. We consider the topologies of resilient covert communications networks that: (1) minimize the impact on the network in the event of a subverted node; and (2) maximize the connectivity of the survivor network with the removal of the subverted node and its closed neighborhood. We analyze the properties of resilient covert networks, propose measurements for determining the suitability of a topology for use in a covert communication network, and determine the properties of an optimal covert network topology. We analyze multiple topologies and identify two constructions that are capable of generating optimal topologies. We then extend these constructions to produce near-optimal topologies that can “grow” as new nodes join the network. We also address protocols for membership management and routing. Finally, we describe the architecture of a prototype system for instantiating a CCN.

In this dissertation we take a peer-to-peer approach to deal with two specific issues, fair trading and file distribution, arisen from data management for cloud computing. In mobile cloud computing environment cloud providers may collaborate with each other and essentially organize some dedicated resources as a peer to peer sharing system. One well-known problem in such peer to peer systems with exchange of resources is free riding. Providing incentives for peers to contribute to the system is an important issue in peer to peer systems. We design a reputation-based fair trading mechanism that favors peers with higher reputation. Based on the definition of the reputation used in the system, we derive a fair trading policy. We evaluate the performance of reputation-based trading mechanisms and highlight the scenarios in which they can make a difference. Distribution of data to the resources within a cloud or to different collaborating clouds efficiently is another issue in cloud computing. The delivery efficiency is dependent on the characteristics of the network links available among these network nodes and the mechanism that takes advantage of them. Our study is based on the Global Environment for Network Innovations (GENI), a testbed for researchers to build a virtual laboratory at scale to explore future Internets. Our study consists of two parts. First, we characterize the links in the GENI network. Even though GENI has been used in many research and education projects, there is no systematic study about what we can expect from the GENI testbeds from a performance perspective. The goal is to characterize the links of the GENI networks and provide guidance for GENI experiments. Second, we propose a peer to peer approach to file distribution for cloud computing. We develop a mechanism that uses multiple delivery trees as the distribution structure, which takes into consideration the measured performance information in the GENI network. Files are divided into chunks to improve parallelism among different delivery trees. With a strict scheduling mechanism for each chunk, we can reduce the overall time for getting the file to all relevant nodes. We evaluate the proposed mechanism and show that our mechanism can significantly reduce the overall delivery time.

Understanding information diffusion on complex networks is a key issue from a theoretical and applied perspective. Epidemiology-inspired SIR models have been proposed to model information diffusion. Recent papers have analyzed this question from a data-driven perspective. We complement these findings investigating if epidemic models calibrate with a systematic procedure are capable of reproducing key spreading cascade properties. We first identify a large-scale, rich dataset from which we can reconstruct the diffusion trail and the underlying network. Secondly, we examine the simple SIR model as a baseline model and conclude that it was unable to generate structurally realistic spreading cascades. We found the same result examining model extensions to which take into account heterogeneities observed in the data. In contrast, other models which take into account time patterns available in the data generate qualitatively more similar cascades. Although one key property was not reproduced in any model, this result highlights the importance of taking time patterns into account. We have also analyzed the impact of the underlying network structure on the models examined. In our data the observed cascades were constrained in time, so we could not rely on the theoretical results relating the asymptotic behavior of the epidemic and network topological features. Performing simulations we assessed the impact of these common topological properties in time-bounded epidemic and identified that the distribution of neighbors of seed nodes had the most impact among the investigated properties in our context. We conclude discussing identifying perspectives opened by this work.

The information era has brought upon us waves of change that brings affordable technology Within the reach of the average person. Computers connected to the Internet, part of our daily living, have led to the formation of online communities. In the spirit of communal efforts, a community cannot be controlled or managed into a specific form or direction. A community has a need to concentrate its efforts towards a common goal or vision, therefore sufficiently nonrestrictive infrastructure is needed to enable the community members to contribute towards their goal. We design and build infrastructure to support a virtual community, according to the needs of the community. Community members can easily locate and exchange files among each other, interact in private and public chat rooms by means of instant text messages, as well as make announcements and participate in group discussions in a Web based environment. Additional needs are identified and tended to by means of various value adding services. We also formulate a management strategy to lead the community towards self-sustenance / Thesis (M. Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2009.