Moving SCADA systems to IaaS clouds

SCADA systems allow users to monitor and/or control physical devices, processes and events remotely. As these systems are critical to industrial processes, they are often run on highly reliable and dedicated hardware. Moving these SCADA systems to an Infrastructure as a Service (IaaS) cloud, allows for: cheaper deployments, system redundancy support, and increased uptime, however it is not clear to what degree clouds can support the real-time requirements. Experiments were carried out to examine the effects of using cloud resources and public networks have on SCADA systems. Using the "Life-and-Shift" approach, eclipseSCADA was deployed to the NeCTAR research cloud. Performance metrics were collected from the deployed eclipseSCADA system under different loads. From these collected metrics, a series of recommendations are provided for deploying and modifying a SCADA system on IaaS cloud resources.

An energy-aware virtual machine scheduling method for service QoS enhancement in clouds over big data

Because of the strong demands of physical resources of big data, it is an effective and efficient way to store and process big data in clouds, as cloud computing allows on-demand resource provisioning. With the increasing requirements for the resources provisioned by cloud platforms, the Quality of Service (QoS) of cloud services for big data management is becoming significantly important. Big data has the character of sparseness, which leads to frequent data accessing and processing, and thereby causes huge amount of energy consumption. Energy cost plays a key role in determining the price of a service and should be treated as a first-class citizen as other QoS metrics, because energy saving services can achieve cheaper service prices and environmentally friendly solutions. However, it is still a challenge to efficiently schedule Virtual Machines (VMs) for service QoS enhancement in an energy-aware manner. In this paper, we propose an energy-aware dynamic VM scheduling method for QoS enhancement in clouds over big data to address the above challenge. Specifically, the method consists of two main VM migration phases where computation tasks are migrated to servers with lower energy consumption or higher performance to reduce service prices and execution time. Extensive experimental evaluation demonstrates the effectiveness and efficiency of our method.

An algorithm for finding the minimum cost of storing and regenerating datasets in multiple clouds

The proliferation of cloud computing allows users to flexibly store, re-compute or transfer large generated datasets with multiple cloud service providers. However, due to the pay-As-you-go model, the total cost of using cloud services depends on the consumption of storage, computation and bandwidth resources which are three key factors for the cost of IaaS-based cloud resources. In order to reduce the total cost for data, given cloud service providers with different pricing models on their resources, users can flexibly choose a cloud service to store a generated dataset, or delete it and choose a cloud service to regenerate it whenever reused. However, finding the minimum cost is a complicated yet unsolved problem. In this paper, we propose a novel algorithm that can calculate the minimum cost for storing and regenerating datasets in clouds, i.e. whether datasets should be stored or deleted, and furthermore where to store or to regenerate whenever they are reused. This minimum cost also achieves the best trade-off among computation, storage and bandwidth costs in multiple clouds. Comprehensive analysis and rigid theorems guarantee the theoretical soundness of the paper, and general (random) simulations conducted with popular cloud service providers' pricing models demonstrate the excellent performance of our approach.

Personalized search over encrypted data with efficient and secure updates in mobile clouds

Mobile cloud computing has been involved as a key enabling technology to overcome the physical limitations of mobile devices towards scalable and flexible mobile services. In the mobile cloud environment, searchable encryption, which enables directly search over encrypted data, is a key technique to maintain both the privacy and usability of outsourced data in cloud. On addressing the issue, many research efforts resolve to using the searchable symmetric encryption (SSE) and searchable public-key encryption (SPE). In this paper, we improve the existing works by developing a more practical searchable encryption technique, which can support dynamic updating operations in the mobile cloud applications. Specifically, we make our efforts on taking the advantages of both SSE and SPE techniques, and propose PSU, a Personalized Search scheme over encrypted data with efficient and secure Updates in mobile cloud. By giving thorough security analysis, we demonstrate that PSU can achieve a high security level. Using extensive experiments in a realworld mobile environment, we show that PUS is more efficient compared with the existing proposals.

Modern feminist dialogue wears ladylike veneer (Book review)

Book review of "The mystery of Rosa Morland, Melbourne: Clouds of Magellan" by Diane Fahey. ISBN: 9780980298338

Determining service trustworthiness in inter loud computing environments

Deployment of applications and scientific workflows that require resources from multiple distributed platforms are fuelling the federation of autonomous clouds to create cyber infrastructure environments. As the scope of federated cloud computing enlarges to ubiquitous and pervasive computing, there will be a need to assess and maintain the trustworthiness of the cloud computing entities. In this paper, we present a fully distributed framework that enable interested parties determine the trustworthiness of federated cloud computing entities.

Energy-efficient management of data center resources for cloud computing : a vision, architectural elements, and open challenges

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.

Toward a framework for cloud security

While the emergence of cloud computing has made it possible to rent information technology infrastructures on demand, it has also created new security challenges. The primary security concern is trusting data (or resources in general) on another organization’s system. This document seeks to examine the current state of security in cloud computing and presents a set of challenges to address the security needs of clouds. The end result is a framework to help the design and implementation of effective cloud security infrastructures.

Toward ease of discovery, selection and use of clusters within a cloud

While the emergence of clouds had lead to a significant paradigm shift in business and research, cloud computing is still in its infancy. Specifically, there is no effective publication and discovery service nor are cloud services easy to use. This paper presents a new technology for offering ease of discovery, selection and use of clusters hosted within clouds. By improving these services, cloud clusters become easily accessible to all clients, software services to noncomputing human user.

A technology to expose a cluster as a service in a cloud

Clouds refer to computational resources (in particular, clusters) that are accessible as scalable, on demand, pay-as- you-go services provided in the Internet. However, clouds are in their infancy and lack a high level abstraction. Specifically, there is no effective discovery and selection service for clusters and offer little to no ease of use for clients. Here we show a technology that exposes clusters as Web services in the form of a Cluster as a Service for publishing via WSDL, discovering, selecting and using clusters.

Toward higher level abstractions for cloud computing

The general idea of cloud computing is offering computational resources as scalable, on demand services accessible over the internet. However, this new realisation of on demand computing is hindered by the amount of user involvement. Currently, high level abstractions in cloud computing only exist in the form of services. In particular, there is no effective means to publish, discover and finally use required services in clouds. In response, we propose a user level abstraction on top of already available cloud abstraction layers, present its concept using the resources via web services (RVWS) framework and demonstrate its feasibility by simplifying the exposure and use of clusters, a commonly used resource in cloud computing.

Dealing with rogue virtual machines in a cloud services environment

In current cloud services hosting solutions, various mechanisms have been developed to minimize the possibility of hosting staff from breaching security. However, while functions such as replicating and moving machines are legitimate actions in clouds, we show that there are risks in administrators being able to perform them. We describe three threat scenarios related to hosting staff on the cloud architecture and indicate how an appropriate accountability architecture can mitigate these risks in the sense that the attacks can be detected and the perpetrators identified. We identify requirements and future research and development needed to protect cloud service environments from these attacks.