Utility-Based Adaptation, Dynamic Provisioning and Incentive Engineering Techniques for Internet and its Wireless Extensions

Utility-Based Adaptation, Dynamic Provisioning and Incentive Engineering Techniques for Internet and its Wireless Extensions Raymond Rui-Feng Liao Over the past decade network bandwidth has become a commodity item putting pressure on Internet Service Providers (ISPs) to differentiate their service offerings to customers in order to maintain market share. However, realizing service differentiation in IP networks is a board, multi-dimensional and challenging problem. This thesis address this problem and proposes new approaches for bandwidth service management for Internet and its wireless extensions that include: (i) utilitybased adaptation mechanisms, which capture applications needs and address the technical challenges of supporting controlled service degradation in differentiated service networks; (ii) dynamic provisioning for core networks, which resolves the technical issues associated with managing complex traffic aggregates and delivering quantitative differentiated services in networks with limited state information and control mechanisms; and (iii) incentive engineering, which effectively deals with the arbitrage problem inherent in differentiated services models. We take a systems approach to these problems and investigate new policy modelling, algorithm, and protocol design techniques. We evaluate our research ideas using a combination of analysis, simulation, and results from an experimental wireless testbed. This thesis makes a number of contributions. Our study is founded on bandwidth utility functions, which are capable of capturing the intrinsic adaptability of applications to bandwidth changes. First, we propose a unified formulation of bandwidth utility functions for application aggregates including TCP, small audio flows, and individual video flows. We discuss experiments using the online generation of utility functions from video traces and present a utility prediction algorithm that addresses the time scale mismatch that exits between video content changes and network adaptation time-scales. Next, we present two groups of utility-based link allocation algorithms that provide a foundation for utility differentiating and utility maximizing bandwidth management. The utility maximizing algorithm leverages the piecewise linear quantization of utility functions and uses the Kuhn-Tucker condition to significantly reduce the algorithm execution time. Our utility differentiating algorithm supports utility fair allocation that allows individual utility functions to have different maximum utility values. We extend these results to the problem of multi-hop utility-based flow control by augmenting the max-min flow control algorithm to support utility functions. We study, propose and evaluate a utility-based max-min fair allocation and renegotiation protocol in the context of an edge-based wireless access network taking into consideration convergence speed, protocol state reduction, and the management of application adaptation states. Third, we present a dynamic bandwidth provisioning model for quantitative service differentiation in core networks that comprises node and core provisioning algorithms. The node provisioning algorithm prevents transient violations of Service Level Agreements (SLAs) by predicting the onset of service level violations based on a multi-class virtual queue technique, self-adjusting per-class service weights, and packet dropping thresholds at core routers. Persistent service level violations are reported to a dynamic core provisioning algorithm, which dimensions traffic aggregates at the network ingress taking into account fairness issues not only across different traffic aggregates but also within the same aggregate whose packets can take different routes in the core IP network. We solve the unique problem of rate regulation for point-to-multipoint flow aggregates with the use of matrix inverse operations. We demonstrate that our model is capable of delivering capacity provisioning in an efficient manner providing quantitative delay-bounds with differentiated loss across per-aggregate service classes. Finally, we propose incentive engineering techniques and design two incentivebased allocation service classes that effectively constrain subscribers’ strategy space to a set of cooperative behaviors that include the truthful selection of service class and truthful declaration of bandwidth demands. Our design minimizes protocol messaging overhead imposed on wireless subscribers while possessing a number of beneficial properties including Nash bargaining fairness for the instantaneous allocation service, and incentive compatibility for mobile users promoting the truthfully declaration of service class.