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千葉大学校友会SNS「Curio」の現状と今後の計画 (入力インタフェース,SNS,ライフログ活用技術,オフィスインフォメーションシステム,ライフインテリジェンス,一般)[あらまし] 千葉大学校友会が運営しているCurioは卒業生,現役学生,教職員などの千葉大学関係者を対象とした実名開示型SNSとして運用してきた.実名開示型のSNSが一般的になった現在,その方向性の検討が必要となっている.各学部同窓会では,名簿発行や会報の発行をオンライン化しようとする動きが見られる.特に名簿については住所録というよりも,他の常用システムへのリンクを持つ同窓生の名前の一覧としての機能が求められている.これを踏まえ,他のシステムと連携した名簿機能や会報のための同窓会専用スペースの設置,登録申請受付のオンライン化などを計画している.将来的には運営会社によるクラウドとしての構成も検討している.
A Framework for Access Control and Resource Allocation for FederationsIn this thesis we address the access control and resource allocation problems in computational federations, such as testbeds and cloud computing federations. The computational federations of today are growing in their number of participant organizations, where one challenge is to allow organizations participate autonomously by expressing how much of their resources should be used and by whom, through complex policies. In addition, such organizations should be able to exchange resources with any other organizations without necessarily knowing all of them beforehand. We introduce our federation framework which allows to build federations in varying complexities easily, by synthesizing trust management, policy languages and resource discovery into a single system. Although these three have been studied separately in the past, we show that they are in fact related, and can be viewed as separate layers of a more general system. We argue that complex agreements that involve indirect trust relationships is one key way to enable resource exchange in a federation with numerous organizations, and this can be realized by our synthesis architecture that provides usability as well as expressiveness. As part of our framework, federation policy language (FPL) is used to express both the security and allocation policies, by providing simple primitives such as contracts that hide the underlying complexity. FPL primitives allow system administrators to express policies such as indirect trust and resource restrictions within the same construct. Underneath, FPL uses our distributed trust management system (CERTDIST) to implement and impose policy primitives. CERTDIST uses digital certificates to allow or deny resource requests and a DHT for complex distributive proofs in an e!cient way. The Resource discovery part of our framework (CODAL) is layered on top of FPL, and uses contracts to discover peers, FPL security and allocation policies to authorize for resources that are located possibly in many di↵erent organizations. We evaluate the federation framework with a realistic emulation of a large scale federation using real PlanetLab traces, that shows that complex policies can be expressed with a minimal amount of code, and we can e!ciently perform the access control and resource discovery operations in a federation.
Improving Cloud System Reliability Using Autonomous Agent TechnologyCloud computing platforms provide efficient and flexible ways to offer services and computation facilities to users. Service providers acquire resources according to their requirements and deploy their services in cloud. Service consumers can access services over networks. In cloud computing, virtualization techniques allow cloud providers provide computation and storage resources according to users’ requirement. However, reliability in the cloud is an important factor to measure the performance of a virtualized cloud computing platform. Reliability in cloud computing includes the usability and availability. Usability is defined as cloud computing platform provides functional and easy-to-use computation resources to users. In order to ensure usability, configurations and management policies have to be maintained and deployed by cloud computing providers. Availability of cloud is defined as cloud computing platform provides stable and reliable computation resources to users. My research concentrates on improving usability and availability of cloud computing platforms. I proposed a customized agent-based reliability monitoring framework to increase reliability of cloud computing.
Availability-aware mobile edge application placement in 5G networksMobile edge computing (MEC) literally pushes cloud computing from remote datacenters to the life radius of end users. By leveraging the widely adopted ETSI network function virtualization (NFV) architecture, MEC provisions elastic and resilient mobile edge applications with proximity. Typical MEC virtualization infrastructure allows configurable placement policy to deploy mobile edge applications as virtual machines (VMs): affinity can be used to put VMs on the same host for inter-VM networking performance, while anti-affinity is to separate VMs for high availability. In this paper, we propose a novel model to track the availability and cost impact from placement policy changes of the mobile edge applications. We formulate our model as a stochastic programming problem. To minimize complexity challenge, we also propose a heuristic algorithm. With our model, the unit resource cost increases when there are less resources left on a host. Applying affinity would take up more resources of the host but saves network bandwidth cost because of co-location. When enforcing anti-affinity, experimental results show increases of both availability and inter-host network bandwidth cost. For applications with different resource requirements, our model is able to find their sweet points with the consideration of both resource cost and application availability, which is vital in a less robust MEC cloud environment.
A hierarchical context dissemination framework for managing federated cloudsThe growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.