클라우드 서비스 연합 장려 모델

학위논문 (석사)-- 서울대학교 대학원 공과대학 협동과정 기술경영·경제·정책전공, 2017. 8. Jorn Altmann.In cloud computing, big service providers rule the market due to the economies of scale. A cloud federation presents a possible solution that allows small cloud providers to increase their competitiveness by making alliances with one another, thus forming a network with shared resources. Previous research suggests several different variables that may incentivize the participation of a selfish cloud provider, such as cost disparity, big competitors, and an efficient revenue sharing mechanism. It can be assumed that each individual cloud provider aims to maximize its profits and will choose to make alliances that provide it a constant benefit. For deciding on whether to federate or not, cloud providers take into consideration whether the federation-underlying revenue sharing will yield them an increase in profits. The proposed study models the interactions between selfish heterogeneous agents in a repeated game that aims to maximize individual profits. Each agent starts off as an individual and is allowed to change its strategies and federate with other providers in order to improve its own performance. By looking at the speed of collaboration and overall profit of individuals, we can determine which specific incentives encourage the creation of cloud federations.Chapter 1 Introduction 1 1.1 Cloud Computing 1 1.2 Problem Description 2 1.3 Research Objective 3 Chapter 2 Related Work.. 4 Chapter 3 Experiment Formulation 8 3.1 Model 8 3.2 Experiment Setup 10 3.2.1 Revenue Sharing. 11 3.2.2 Capacity Disparity 14 3.2.3 Cost Disparity. 15 3.2.4 Big Competitor. 16 3.2.5 Volatile Demand. 17 Chapter 4 Results 17 4.1 Revenue Sharing Scenario 18 4.2 Capacity Disparity Scenario 19 4.3 Cost Disparity Scenario. 21 4.4 Big Competitor Scenario 22 4.5 Federation Behavior in Demand Peaks. 23 Chapter 5 Conclusions.. 24 5.1 Summary. 24 5.2 Discussion and Implications. 25 5.3 Limitations and Future Work 26 Bibliography. 27 Abstract. 29Maste

Sla Management in a Collaborative Network Of Federated Clouds: The Cloudland

Cloud services have always promised to be available, flexible, and speedy. However, not a single Cloud provider can deliver such promises to their distinctly demanding customers. Cloud providers have a constrained geographical presence, and are willing to invest in infrastructure only when it is profitable to them. Cloud federation is a concept that collectively combines segregated Cloud services to create an extended pool of resources for Clouds to competently deliver their promised level of services. This dissertation is concerned with studying the governing aspects related to the federation of Clouds through collaborative networking. The main objective of this dissertation is to define a framework for a Cloud network that considers balancing the trade-offs among customers’ various quality of service (QoS) requirements, as well as providers\u27 resources utilization. We propose a network of federated Clouds, CloudLend, that creates a platform for Cloud providers to collaborate, and for customers to expand their service selections. We also define and specify a service level agreement (SLA) management model in order to govern and administer the relationships established between different Cloud services in CloudLend. We define a multi-level SLA specification model to annotate and describe QoS terms, in addition to a game theory-based automated SLA negotiation model that supports both customers and providers in negotiating SLA terms, and guiding them towards signing a contract. We also define an adaptive agent-based SLA monitoring model which identifies the root causes of SLA violations, and impartially distributes any updates and changes in established SLAs to all relevant entities. Formal verification proved that our proposed framework assures customers with maximum optimized guarantees to their QoS requirements, in addition to supporting Cloud providers to make informed resource utilization decisions. Additionally, simulation results demonstrate the effectiveness of our SLA management model. Our proposed Cloud Lend network and its SLA management model paves the way to resource sharing among different Cloud providers, which allows for the providers’ lock-in constraints to be broken, allowing effortless migration of customers’ applications across different providers whenever is needed

Social-Aware Clustered Federated Learning with Customized Privacy Preservation

A key feature of federated learning (FL) is to preserve the data privacy of end users. However, there still exist potential privacy leakage in exchanging gradients under FL. As a result, recent research often explores the differential privacy (DP) approaches to add noises to the computing results to address privacy concerns with low overheads, which however degrade the model performance. In this paper, we strike the balance of data privacy and efficiency by utilizing the pervasive social connections between users. Specifically, we propose SCFL, a novel Social-aware Clustered Federated Learning scheme, where mutually trusted individuals can freely form a social cluster and aggregate their raw model updates (e.g., gradients) inside each cluster before uploading to the cloud for global aggregation. By mixing model updates in a social group, adversaries can only eavesdrop the social-layer combined results, but not the privacy of individuals. We unfold the design of SCFL in three steps. \emph{i) Stable social cluster formation. Considering users' heterogeneous training samples and data distributions, we formulate the optimal social cluster formation problem as a federation game and devise a fair revenue allocation mechanism to resist free-riders. ii) Differentiated trust-privacy mapping}. For the clusters with low mutual trust, we design a customizable privacy preservation mechanism to adaptively sanitize participants' model updates depending on social trust degrees. iii) Distributed convergence}. A distributed two-sided matching algorithm is devised to attain an optimized disjoint partition with Nash-stable convergence. Experiments on Facebook network and MNIST/CIFAR-10 datasets validate that our SCFL can effectively enhance learning utility, improve user payoff, and enforce customizable privacy protection

Trustworthy Federated Learning: A Survey

Federated Learning (FL) has emerged as a significant advancement in the field of Artificial Intelligence (AI), enabling collaborative model training across distributed devices while maintaining data privacy. As the importance of FL increases, addressing trustworthiness issues in its various aspects becomes crucial. In this survey, we provide an extensive overview of the current state of Trustworthy FL, exploring existing solutions and well-defined pillars relevant to Trustworthy . Despite the growth in literature on trustworthy centralized Machine Learning (ML)/Deep Learning (DL), further efforts are necessary to identify trustworthiness pillars and evaluation metrics specific to FL models, as well as to develop solutions for computing trustworthiness levels. We propose a taxonomy that encompasses three main pillars: Interpretability, Fairness, and Security & Privacy. Each pillar represents a dimension of trust, further broken down into different notions. Our survey covers trustworthiness challenges at every level in FL settings. We present a comprehensive architecture of Trustworthy FL, addressing the fundamental principles underlying the concept, and offer an in-depth analysis of trust assessment mechanisms. In conclusion, we identify key research challenges related to every aspect of Trustworthy FL and suggest future research directions. This comprehensive survey serves as a valuable resource for researchers and practitioners working on the development and implementation of Trustworthy FL systems, contributing to a more secure and reliable AI landscape.Comment: 45 Pages, 8 Figures, 9 Table

Payment for Environmental Services: First Global Inventory of Schemes Provisioning Water for Cities

In the perspective of the World Water Day 2011 - "Water for Cities" (March 22, 2011), the Natural Resources Land and Water Division (NRL) of FAO has launched an inventory of environmental schemes provisioning water to cities. Up to date there have been several studies addressing the payment for watershed services around the world, conducted by various UN agencies, NGOs, etc. None of these studies so far has focused on the PES schemes providing the water supply for cities and industries, i.e. urban areas. In that sense this inventory is unique. The report offers a very useful inventory of identified PES - "water for cities" schemes around the world. The report can be used as basis for further pursuit of information and analysis of the most relevant cases at least, and possible replication of these cases, primarily in East Africa that has become an area of interest lately for the potential development of this market based scheme in order to address the water issues of the region

New Sources of Development Finance

"As their Millennium Development Goals, world leaders have pledged by 2015 to halve the number of people living in extreme poverty and hunger, to achieve universal primary education, to reduce child mortality, to halt the spread of HIV/AIDS, and to halve the number of people without safe drinking water. Achieving these goals requires a large increase in the flow of financial resources to developing countries – double the present development assistance from abroad. In examining innovative ways to secure these resources, this book, which is part of the UNU–WIDER Studies in Development Economics series, sets out a framework for the economic analysis of different sources of funding and applying the tools of modern public economics to identify the key issues. It examines the role of new sources of overseas aid, considers the fiscal architecture and the lessons that can be learned from federal fiscal systems, asks how far increased transfers impose a burden on donors, and investigates how far the raising of resources can be separated from their use. In turn, the book examines global environmental taxes (such as a carbon tax), the taxation of currency transactions (the Tobin tax), a development‐focused allocation of Special Drawing Rights by the International Monetary Fund (IMF), the UK Government proposal for an International Finance Facility, increased private donations for development purposes, a global lottery (or premium bond), and increased remittances by emigrants. In each case, it considers the feasibility of the proposal and the resources that it can realistically raise, and offers new perspectives and insights into these new and controversial proposals.

Incentives and Two-Sided Matching - Engineering Coordination Mechanisms for Social Clouds

The Social Cloud framework leverages existing relationships between members of a social network for the exchange of resources. This thesis focuses on the design of coordination mechanisms to address two challenges in this scenario. In the first part, user participation incentives are studied. In the second part, heuristics for two-sided matching-based resource allocation are designed and evaluated

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate