Digital curation and the cloud

Digital curation involves a wide range of activities, many of which could benefit from cloud deployment to a greater or lesser extent. These range from infrequent, resource-intensive tasks which benefit from the ability to rapidly provision resources to day-to-day collaborative activities which can be facilitated by networked cloud services. Associated benefits are offset by risks such as loss of data or service level, legal and governance incompatibilities and transfer bottlenecks. There is considerable variability across both risks and benefits according to the service and deployment models being adopted and the context in which activities are performed. Some risks, such as legal liabilities, are mitigated by the use of alternative, e.g., private cloud models, but this is typically at the expense of benefits such as resource elasticity and economies of scale. Infrastructure as a Service model may provide a basis on which more specialised software services may be provided. There is considerable work to be done in helping institutions understand the cloud and its associated costs, risks and benefits, and how these compare to their current working methods, in order that the most beneficial uses of cloud technologies may be identified. Specific proposals, echoing recent work coordinated by EPSRC and JISC are the development of advisory, costing and brokering services to facilitate appropriate cloud deployments, the exploration of opportunities for certifying or accrediting cloud preservation providers, and the targeted publicity of outputs from pilot studies to the full range of stakeholders within the curation lifecycle, including data creators and owners, repositories, institutional IT support professionals and senior manager

Technical Report on Deploying a highly secured OpenStack Cloud Infrastructure using BradStack as a Case Study

Cloud computing has emerged as a popular paradigm and an attractive model for providing a reliable distributed computing model.it is increasing attracting huge attention both in academic research and industrial initiatives. Cloud deployments are paramount for institution and organizations of all scales. The availability of a flexible, free open source cloud platform designed with no propriety software and the ability of its integration with legacy systems and third-party applications are fundamental. Open stack is a free and opensource software released under the terms of Apache license with a fragmented and distributed architecture making it highly flexible. This project was initiated and aimed at designing a secured cloud infrastructure called BradStack, which is built on OpenStack in the Computing Laboratory at the University of Bradford. In this report, we present and discuss the steps required in deploying a secured BradStack Multi-node cloud infrastructure and conducting Penetration testing on OpenStack Services to validate the effectiveness of the security controls on the BradStack platform. This report serves as a practical guideline, focusing on security and practical infrastructure related issues. It also serves as a reference for institutions looking at the possibilities of implementing a secured cloud solution.Comment: 38 pages, 19 figures

Trusted Computing and Secure Virtualization in Cloud Computing

Large-scale deployment and use of cloud computing in industry is accompanied and in the same time hampered by concerns regarding protection of data handled by cloud computing providers. One of the consequences of moving data processing and storage off company premises is that organizations have less control over their infrastructure. As a result, cloud service (CS) clients must trust that the CS provider is able to protect their data and infrastructure from both external and internal attacks. Currently however, such trust can only rely on organizational processes declared by the CS provider and can not be remotely verified and validated by an external party. Enabling the CS client to verify the integrity of the host where the virtual machine instance will run, as well as to ensure that the virtual machine image has not been tampered with, are some steps towards building trust in the CS provider. Having the tools to perform such verifications prior to the launch of the VM instance allows the CS clients to decide in runtime whether certain data should be stored- or calculations should be made on the VM instance offered by the CS provider. This thesis combines three components -- trusted computing, virtualization technology and cloud computing platforms -- to address issues of trust and security in public cloud computing environments. Of the three components, virtualization technology has had the longest evolution and is a cornerstone for the realization of cloud computing. Trusted computing is a recent industry initiative that aims to implement the root of trust in a hardware component, the trusted platform module. The initiative has been formalized in a set of specifications and is currently at version 1.2. Cloud computing platforms pool virtualized computing, storage and network resources in order to serve a large number of customers customers that use a multi-tenant multiplexing model to offer on-demand self-service over broad network. Open source cloud computing platforms are, similar to trusted computing, a fairly recent technology in active development. The issue of trust in public cloud environments is addressed by examining the state of the art within cloud computing security and subsequently addressing the issues of establishing trust in the launch of a generic virtual machine in a public cloud environment. As a result, the thesis proposes a trusted launch protocol that allows CS clients to verify and ensure the integrity of the VM instance at launch time, as well as the integrity of the host where the VM instance is launched. The protocol relies on the use of Trusted Platform Module (TPM) for key generation and data protection. The TPM also plays an essential part in the integrity attestation of the VM instance host. Along with a theoretical, platform-agnostic protocol, the thesis also describes a detailed implementation design of the protocol using the OpenStack cloud computing platform. In order the verify the implementability of the proposed protocol, a prototype implementation has built using a distributed deployment of OpenStack. While the protocol covers only the trusted launch procedure using generic virtual machine images, it presents a step aimed to contribute towards the creation of a secure and trusted public cloud computing environment

Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

Calm before the storm: the challenges of cloud computing in digital forensics

Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying their infrastructure into remote, virtualized environments, often hosted and managed by third parties. This development has significant implications for digital forensic investigators, equipment vendors, law enforcement, as well as corporate compliance and audit departments (among others). Much of digital forensic practice assumes careful control and management of IT assets (particularly data storage) during the conduct of an investigation. This paper summarises the key aspects of cloud computing and analyses how established digital forensic procedures will be invalidated in this new environment. Several new research challenges addressing this changing context are also identified and discussed

StackInsights: Cognitive Learning for Hybrid Cloud Readiness

Hybrid cloud is an integrated cloud computing environment utilizing a mix of public cloud, private cloud, and on-premise traditional IT infrastructures. Workload awareness, defined as a detailed full range understanding of each individual workload, is essential in implementing the hybrid cloud. While it is critical to perform an accurate analysis to determine which workloads are appropriate for on-premise deployment versus which workloads can be migrated to a cloud off-premise, the assessment is mainly performed by rule or policy based approaches. In this paper, we introduce StackInsights, a novel cognitive system to automatically analyze and predict the cloud readiness of workloads for an enterprise. Our system harnesses the critical metrics across the entire stack: 1) infrastructure metrics, 2) data relevance metrics, and 3) application taxonomy, to identify workloads that have characteristics of a) low sensitivity with respect to business security, criticality and compliance, and b) low response time requirements and access patterns. Since the capture of the data relevance metrics involves an intrusive and in-depth scanning of the content of storage objects, a machine learning model is applied to perform the business relevance classification by learning from the meta level metrics harnessed across stack. In contrast to traditional methods, StackInsights significantly reduces the total time for hybrid cloud readiness assessment by orders of magnitude

VIRTUALIZED BASEBAND UNITS CONSOLIDATION IN ADVANCED LTE NETWORKS USING MOBILITY- AND POWER-AWARE ALGORITHMS

Virtualization of baseband units in Advanced Long-Term Evolution networks and a rapid performance growth of general purpose processors naturally raise the interest in resource multiplexing. The concept of resource sharing and management between virtualized instances is not new and extensively used in data centers. We adopt some of the resource management techniques to organize virtualized baseband units on a pool of hosts and investigate the behavior of the system in order to identify features which are particularly relevant to mobile environment. Subsequently, we introduce our own resource management algorithm specifically targeted to address some of the peculiarities identified by experimental results