Optimizing on-demand resource deployment for peer-assisted content delivery (PhD thesis)

Increasingly, content delivery solutions leverage client resources in exchange for service in a peer-to-peer (P2P) fashion. Such peer-assisted service paradigms promise significant infrastructure cost reduction, but suffer from the unpredictability associated with client resources, which is often exhibited as an imbalance between the contribution and consumption of resources by clients. This imbalance hinders the ability to guarantee a minimum service fidelity of these services to the clients. In this thesis, we propose a novel architectural service model that enables the establishment of higher fidelity services through (1) coordinating the content delivery to optimally utilize the available resources, and (2) leasing the least additional cloud resources, available through special nodes (angels) that join the service on-demand, and only if needed, to complement the scarce resources available through clients. While the proposed service model can be deployed in many settings, this thesis focuses on peer-assisted content delivery applications, in which the scarce resource is typically the uplink capacity of clients. We target three applications that require the delivery of fresh as opposed to stale content. The first application is bulk-synchronous transfer, in which the goal of the system is to minimize the maximum distribution time -- the time it takes to deliver the content to all clients in a group. The second application is live streaming, in which the goal of the system is to maintain a given streaming quality. The third application is Tor, the anonymous onion routing network, in which the goal of the system is to boost performance (increase throughput and reduce latency) throughout the network, and especially for bandwidth-intensive applications. For each of the above applications, we develop mathematical models that optimally allocate the already available resources. They also optimally allocate additional on-demand resource to achieve a certain level of service. Our analytical models and efficient constructions depend on some simplifying, yet impractical, assumptions. Thus, inspired by our models and constructions, we develop practical techniques that we incorporate into prototypical peer-assisted angel-enabled cloud services. We evaluate those techniques through simulation and/or implementation. (Major Advisor: Azer Bestavros

Optimizing on-demand resource deployment for peer-assisted content delivery

Increasingly, content delivery solutions leverage client resources in exchange for services in a pee-to-peer (P2P) fashion. Such peer-assisted service paradigm promises significant infrastructure cost reduction, but suffers from the unpredictability associated with client resources, which is often exhibited as an imbalance between the contribution and consumption of resources by clients. This imbalance hinders the ability to guarantee a minimum service fidelity of these services to clients especially for real-time applications where content can not be cached. In this thesis, we propose a novel architectural service model that enables the establishment of higher fidelity services through (1) coordinating the content delivery to efficiently utilize the available resources, and (2) leasing the least additional cloud resources, available through special nodes (angels) that join the service on-demand, and only if needed, to complement the scarce resources available through clients. While the proposed service model can be deployed in many settings, this thesis focuses on peer-assisted content delivery applications, in which the scarce resource is typically the upstream capacity of clients. We target three applications that require the delivery of real-time as opposed to stale content. The first application is bulk-synchronous transfer, in which the goal of the system is to minimize the maximum distribution time - the time it takes to deliver the content to all clients in a group. The second application is live video streaming, in which the goal of the system is to maintain a given streaming quality. The third application is Tor, the anonymous onion routing network, in which the goal of the system is to boost performance (increase throughput and reduce latency) throughout the network, and especially for clients running bandwidth-intensive applications. For each of the above applications, we develop analytical models that efficiently allocate the already available resources. They also efficiently allocate additional on-demand resource to achieve a certain level of service. Our analytical models and efficient constructions depend on some simplifying, yet impractical, assumptions. Thus, inspired by our models and constructions, we develop practical techniques that we incorporate into prototypical peer-assisted angel-enabled cloud services. We evaluate these techniques through simulation and/or implementation

Food safety : analyzing the connection between government and industrial influence.

The purpose of this study was to examine the leaders within the U.S. food safety agencies and the top U.S. food producing companies, including meat, grain, and seed, and determine the presence of connectivity between the separate organizations. This involved looking at detailed biographical information on each leader, including previous and current employment, educational background and board memberships. Following identification of the agencies, companies, and their leaders, social network analysis was utilized to locate visual and quantitative links. Using the theories of C. Wright Mills and William Domhoff, the results showed a powerful argument that the power elite is still active in the current food system and that there is an interlocking structure between the government and private sector. Finding this \u27power food chain\u27 that was formed by connectivity and overlap of leaders should be researched further and gives concern to the overall structure of the U.S. food system

On the synergy of network science and artificial intelligence,”

Abstract Traditionally science is done using the reductionism paradigm. Artificial intelligence does not make an exception and it follows the same strategy. At the same time, network science tries to study complex systems as a whole. This Ph.D. research takes an alternative approach to the reductionism strategy, and tries to advance both fields, i.e. artificial intelligence and network science, by searching for the synergy between them, while not ignoring any other source of inspiration, e.g. neuroscience

How does the spatial and social dynamics of the Natterer's bat Myotis nattereri affect disease transmission and conservation?

PhD ThesisNatterer’s bats (Myotis nattereri) are typical of many Bat species in that they participate in a variety of distinct seasonal communities and behaviours. In summer adult females are thought to be largely philopatric to their natal community/landscape where they rear their young and form largely matrilineal communities. Bat foraging behaviour and social participation is largely unquantified, as is our understanding of how age/maturity and sex may mediate their social behaviour. Crucially, the rate of female dispersal between communities is completely unquantified. A much better understanding of bat spatial and social dynamics is necessary to inform statutory functions, effective conservation and epidemiological modelling. We have mapped and quantified the spatial and social dynamics of three communities of Natterer’s bats. Uniquely our roost switching data comes from a community roosting entirely in natural roosts. Radio-tracking, ringing and DNA evidence can be combined at one site, whilst ringing and DNA can be combined at two others. In addition, DNA samples from a further two sites could be included to complete the comparison of 183 Natterer’s bats from 5 sites. Microsatellite data (based on 15 markers) was used to describe relatedness at two functional scales (between roosts within a community and between communities). Relatedness and population structure was also compared to home range analysis and roost use to determine if related individuals forage close to each other or share a roosts more frequently than unrelated individuals. Novel descriptions of demographic and epidemiological rates for this species were determined, which has been incorporated into predictive models of how both the community may respond to changes in the environment, or diseases may spread within the community which will help improve bat Conservation

Optimization and Communication in UAV Networks

UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects

Command and Control in the Information Age: A Case Study of a Representative Air Power Command and Control Node

As operations command structures change, it is important to be able to explore and understand their fundamental nature; researchers should unearth the gestalt nature of the operational node. The organizational structure and the infrastructure can significantly affect overall command and control (C2) performance. Thus, it is necessary to develop understanding of effectiveness of the technical network and the people using the system as a whole. The purpose of this research is to conduct an analysis of a representative Air Power Operational C2 node, create and use a repeatable method, and present the results as a case study to elicit fundamental understanding. I posit that there is a recognizable (and discoverable) relationship between the social (human) network and technical supporting network. Examining the system under change can result in an understanding of this relationship. In this work, I enhanced an existing simulation tool to investigate the effects of organizational structure on task effectiveness. The primary research question examined is how a representative AOC system changes varying noise and system fragmentation when operating in two different organizational constructs. Network-Enabled Capability (as the term is used in NATO), Network Centric Operations, or Edge Organizations, is a core C2 transformation predicated upon a set of network-centric tenets. These tenets form the intellectual foundation for ongoing transformations. The secondary research question is to determine if these tenets are unbound, and what elucidation results if they are not. This research produces four significant contributions to Operational Command and Control and Engineering Management disciplines. First, I combined social networking theory and information theory into a single lens for evaluation. By using this new concept, I will be able to accomplish a quantitative evaluation by something other than mission treads, field exercise, historical evaluation, or actual combat. Second, I used both information theory and social networking concepts in a non-traditional setting. Third, I hope this research will start the process required to gain the knowledge to achieve some sort of future C2 structure. Fourth, this research suggests directions for future research to enhance understanding of core Operational Command and Control concepts