Addressing the cyber safety challenge: from risk to resilience

Addressing the cyber safety challenge: from risk to resilience describes the cyber safety issues emerging from a range of technology trends, how different populations are using technologies and the risks they face, and how we can effectively respond to each group’s unique cyber safety needs. Written by the University of Western Sydney for Telstra Corporation Ltd, the report advocates for continuing to move cyber safety from a ‘risk and protection’ framework to one that focuses on building digital resilience, as well as fostering trust and confidence in the online environment. To do this we need to: Address the needs of populations often neglected by current policies and programs – including adults, seniors, parents, and small to medium enterprises Continue to build the digital literacy skills of all populations, because digital literacy strongly influences users’ ability to engage safely online – this is best achieved by a hands-on learning approach Keep risk in perspective – the risks and benefits of digital participation go hand in hand Broaden the focus from awareness-raising to long-term behaviour change. As digital technologies become further integrated into the everyday lives of Australians, users are potentially exposed to greater risks. However, the risks and benefits of digital participation go hand in hand. The challenge, therefore, is to support users to minimise the risks without limiting their digital participation and their capacity to derive the full benefits of connectivity. If Australians are to benefit as either consumers or providers of online services and products in the e-commerce environment, consumer safety and trust need to be improved. Cyber safety needs to be considered against a transforming backdrop of technology trends, products and practices. While the rise of social media has tended to dominate recent debate and developments in cyber safety, particularly in relation to young people, a range of other trends is also shaping how users engage online, the risks they potentially face in the new media landscape, and the strategies used to address them. These trends include the rise of user generated content and content sharing platforms; the uptake of mobile technologies and, in particular, the adoption of smartphones; cloud computing; platform integration and single sign-on mechanisms; and the rise of GPS and location based services

Market-Based Scheduling in Distributed Computing Systems

In verteilten Rechensystemen (bspw. im Cluster und Grid Computing) kann eine Knappheit der zur Verfügung stehenden Ressourcen auftreten. Hier haben Marktmechanismen das Potenzial, Ressourcenbedarf und -angebot durch geeignete Anreizmechanismen zu koordinieren und somit die ökonomische Effizienz des Gesamtsystems zu steigern. Diese Arbeit beschäftigt sich anhand vier spezifischer Anwendungsszenarien mit der Frage, wie Marktmechanismen für verteilte Rechensysteme ausgestaltet sein sollten

Provably near-optimal algorithms for multi-stage stochastic optimization models in operations management

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 157-165).Many if not most of the core problems studied in operations management fall into the category of multi-stage stochastic optimization models, whereby one considers multiple, often correlated decisions to optimize a particular objective function under uncertainty on the system evolution over the future horizon. Unfortunately, computing the optimal policies is usually computationally intractable due to curse of dimensionality. This thesis is focused on providing provably near-optimal and tractable policies for some of these challenging models arising in the context of inventory control, capacity planning and revenue management; specifically, on the design of approximation algorithms that admit worst-case performance guarantees. In the first chapter, we develop new algorithmic approaches to compute provably near-optimal policies for multi-period stochastic lot-sizing inventory models with positive lead times, general demand distributions and dynamic forecast updates. The proposed policies have worst-case performance guarantees of 3 and typically perform very close to optimal in extensive computational experiments. We also describe a 6-approximation algorithm for the counterpart model under uniform capacity constraints. In the second chapter, we study a class of revenue management problems in systems with reusable resources and advanced reservations. A simple control policy called the class selection policy (CSP) is proposed based on solving a knapsack-type linear program (LP). We show that the CSP and its variants perform provably near-optimal in the Halfin- Whitt regime. The analysis is based on modeling the problem as loss network systems with advanced reservations. In particular, asymptotic upper bounds on the blocking probabilities are derived. In the third chapter, we examine the problem of capacity planning in joint ventures to meet stochastic demand in a newsvendor-type setting. When resources are heterogeneous, there exists a unique revenue-sharing contract such that the corresponding Nash Bargaining Solution, the Strong Nash Equilibrium, and the system optimal solution coincide. The optimal scheme rewards every participant proportionally to her marginal cost. When resources are homogeneous, there does not exist a revenue-sharing scheme which induces the system optimum. Nonetheless, we propose provably good revenue-sharing contracts which suggests that the reward should be inversely proportional to the marginal cost of each participant.by Cong Shi.Ph.D

Financing of the European Union Budget.

This study is concerned with the future financing of the EU budget, including possible budgetary correction mechanisms, and is intended to feed into the budget review. The revenue side of the EU budget comprises several elements, all of which need to be assessed in appraising the functioning of the current system and whether it should be reformed. They include the revenue instruments used - the ‘own resources’ (OR) - and how they are set, the means by which net contributions deemed to be excessive are adjusted, and how to ensure that the EU’s revenue balances its expenditure as required by Art. 268 TEC. Such balanced budget rules are often applied to control the expenditure of sub-national governments in multi-level fiscal systems Work done in the course of this study has included an extensive literature survey and examination of relevant previous work, empirical research and policy analysis. The empirical work comprised a mix of qualitative and quantitative analysis, extensive dialogue with practitioners, and a survey directed to officials (mainly, but by no means exclusively, in finance ministries) in Member States. This research has been used to investigate both how well the current system is working and to try to provide a systematic basis for analysing options for reform.

Multi-objective reinforcement learning for responsive grids

The original publication is available at www.springerlink.comInternational audienceGrids organize resource sharing, a fundamental requirement of large scientific collaborations. Seamless integration of grids into everyday use requires responsiveness, which can be provided by elastic Clouds, in the Infrastructure as a Service (IaaS) paradigm. This paper proposes a model-free resource provisioning strategy supporting both requirements. Provisioning is modeled as a continuous action-state space, multi-objective reinforcement learning (RL) problem, under realistic hypotheses; simple utility functions capture the high level goals of users, administrators, and shareholders. The model-free approach falls under the general program of autonomic computing, where the incremental learning of the value function associated with the RL model provides the so-called feedback loop. The RL model includes an approximation of the value function through an Echo State Network. Experimental validation on a real data-set from the EGEE grid shows that introducing a moderate level of elasticity is critical to ensure a high level of user satisfaction

A framework for Traffic Engineering in software-defined networks with advance reservation capabilities

298 p.En esta tesis doctoral se presenta una arquitectura software para facilitar la introducción de técnicas de ingeniería de tráfico en redes definidas por software. La arquitectura ha sido diseñada de forma modular, de manera que soporte múltiples casos de uso, incluyendo su aplicación en redes académicas. Cabe destacar que las redes académicas se caracterizan por proporcionar servicios de alta disponibilidad, por lo que la utilización de técnicas de ingeniería de tráfico es de vital importancia a fin de garantizar la prestación del servicio en los términos acordados. Uno de los servicios típicamente prestados por las redes académicas es el establecimiento de circuitos extremo a extremo con una duración determinada en la que una serie de recursos de red estén garantizados, conocido como ancho de banda bajo demanda, el cual constituye uno de los casos de uso en ingeniería de tráfico más desafiantes. Como consecuencia, y dado que esta tesis doctoral ha sido co-financiada por la red académica GÉANT, la arquitectura incluye soporte para servicios de reserva avanzada. La solución consiste en una gestión de los recursos de red en función del tiempo, la cual mediante el empleo de estructuras de datos y algoritmos específicamente diseñados persigue la mejora de la utilización de los recursos de red a la hora de prestar este tipo de servicios. La solución ha sido validada teniendo en cuenta los requisitos funcionales y de rendimiento planteados por la red GÉANT. Así mismo, cabe destacar que la solución será utilizada en el despliegue piloto del nuevo servicio de ancho de banda bajo demanda de la red GÉANT a finales del 2017

Leveraging Tribal Sovereignty for Economic Opportunity: A Strategic Negotiations Perspective

Part II of this Article discusses the sovereign nature of tribal governments and reviews the history of tribal sovereignty, concluding with an examination of tribal-state compacting outside of the gaming context. Part III examines the origins of Indian gaming, focusing on the development of the legal framework which governs tribal gaming activities and necessitates the negotiation of tribal-state gaming compacts. Given the need for tribal-state negotiations, Part IV presents a framework for structuring and analyzing negotiations. Part V applies that framework in the retelling of the first part of the Foxwoods story, the negotiations regarding the original gaming compact. The story of Foxwoods, however, has a second chapter involving the subsequent negotiations over installing slot machines at the casino, and Part VI uses the same analytic framework. Part VII evaluates the change in the negotiation landscape in response to the Foxwoods negotiations and assesses the impact of technological changes on Indian gaming. Part VIII concludes by arguing that, although the relative tribal-state positions may have changed, much of the fundamental negotiation dynamic remains the same, and thus many of the lessons of Foxwoods are applicable today

Integrating Consumer Flexibility in Smart Grid and Mobility Systems - An Online Optimization and Online Mechanism Design Approach

Consumer flexibility may provide an important lever to align supply and demand in service systems. However, harnessing dispersed flexibility endowments in the presence of self-interested agents requires appropriate incentive structures. This thesis quantifies the potential value of consumers\u27 flexibility in smart grid and mobility systems. In order to include incentives, online optimization approaches are augmented with methods from online mechanism design