A general cloud firewall framework with dynamic resource allocation

Cloud is becoming a dominant computing platform. However, we see few work on how to protect cloud data centers. As a cloud usually hosts many different type of applications, the traditional packet level firewall mechanism is not suitable for cloud platforms in case of complex attacks. It is necessary to perform anomaly detection at the event level. Moreover, protecting objects are more diverse than the traditional firewall. Motivated by this, we propose a general framework of cloud firewall, which features event level detection chain with dynamic resource allocation. We establish a mathematical model for the proposed framework. Moreover, a linear resource investment function is proposed for economical dynamical resource allocation for cloud firewalls. A few conclusions have been extracted for the reference of cloud service providers and designers.

A good place to raise a family? Comparing parents, service-providers', and media perspectives of the inner and outer suburban areas of Melbourne

In Australia, the suburbs have historically been the favoured place to raise children. However this is being challenged both by social change and government policy encouraging innerurban renewal. We examined how inner-urban areas compare with more traditional suburban locations as places to raise a family. Recognising that there are many influences on perceptions of place, we included the opinions of parents, service-providers and the media in the two locations.

Research focused on two municipalities in Melbourne, one located >25km and the other <10km from the CBD. Themes were obtained and compared from in-depth interviews with parents, serviceproviders and analysis of municipality-specific and state-wide newspaper articles.

Service provision was the only theme common at all levels of analysis. For all other themes, differences occurred between perspectives of service-providers, media and parents, as well as between the two residential locations. These in-depth snapshots on the challenges and rewards of raising children in different urban locations can help inform government in planning healthy neighbourhoods that better serve the needs of contemporary Australian families.

Dynamic cloud service selection using an adaptive learning mechanism in multi-cloud computing

Cloud service selection in a multi-cloud computing environment is receiving more and more attentions. There is an abundance of emerging cloud service resources that makes it hard for users to select the better services for their applications in a changing multi-cloud environment, especially for online real time applications. To assist users to efficiently select their preferred cloud services, a cloud service selection model adopting the cloud service brokers is given, and based on this model, a dynamic cloud service selection strategy named DCS is put forward. In the process of selecting services, each cloud service broker manages some clustered cloud services, and performs the DCS strategy whose core is an adaptive learning mechanism that comprises the incentive, forgetting and degenerate functions. The mechanism is devised to dynamically optimize the cloud service selection and to return the best service result to the user. Correspondingly, a set of dynamic cloud service selection algorithms are presented in this paper to implement our mechanism. The results of the simulation experiments show that our strategy has better overall performance and efficiency in acquiring high quality service solutions at a lower computing cost than existing relevant approaches.

Service providers' experiences and needs in working with refugees in the Geelong region: a qualitative study

Service providers in Geelong, one of the priority locations for the resettlement of refugees in regional Australia, were interviewed to explore their perceptions of the health and wellbeing needs of refugees, and the capacity of service providers in a regional area to meet these. In all, 22 interviews were conducted with health and human service professionals in a range of organisations offering refugee-specific services, culturally and linguistically diverse (CALD) services in general, and services to the wider community, including refugees. The findings revealed that a more coordinated approach would increase the effectiveness of existing services; however, the various needs of refugees were more than could be met by organisations in the region at current resource levels. More staff and interpreting services were required, as well as professional development for staff who have had limited experience in working with refugees. It should not be assumed that service needs for refugees resettled in regional Australia will be the same as those of refugees resettled in capital cities. Some services provided in Melbourne were not available in Geelong, and there were services not currently provided to refugees that may be critical in facilitating resettlement in regional and rural Australia.

Security and privacy concerns for Australian SMEs cloud adoption: empirical study of metropolitan vs regional SMEs

New national infrastructure initiatives such as the National Broadband Network (NBN) allow small and medium-sized enterprises (SMEs) in Australia to have greater access to cost effective Cloud computing. However, the ability of Cloud computing to store data remotely and share services in a dynamic environment brings with it security and privacy concerns. Evaluating these concerns is critical to address the Cloud computing underutilisation issue and leverage the benefits of costly NBN investment. This paper examines the influence of privacy and security factors on Cloud adoption by Australian SMEs in metropolitan and regional area. Data were collected from 150 Australian SMEs (specifically, 79 metropolitan SMEs and 71 regional SMEs) and structural equation modelling was used for the analysis. The findings reveal that privacy and security factors do not significantly influence the decision-making of Australian SMEs in the adoption of Cloud computing. Moreover, the results indicate that Cloud computing adoption is not influenced by the geographical location (i.e., metropolitan or regional location) of the SMEs. The findings extend the current understanding of Cloud computing adoption by Australian SMEs. The results will be useful to SMEs, Cloud service providers and policy makers devising Cloud security and privacy policies.

Cloud omnibus system for evaluating cloud market services

Rapid expansion in numbers of cloud service providers (CSPs) has resulted in the introduction of various brokering services and cloud marketplaces designed to help customers to assess and choose CSPs. The problem of evaluating marketplaces and also separate sub-offerings supplied by cloud service providers (CSPs) has become vitally important because cloud marketplaces can now incorporate sub-offerings from different CSPs into a combined package tailored for each customer. In this paper, we introduce a new concept which we refer to as a cloud omnibus system (COS) and which we define as a cloud marketing system evaluating whole cloud marketplaces, CSPs, brokers and separate service sub-offerings from CSPs (sometimes combined into packages tailored for customers). COS is based on trust and management of trust and is beyond the state-of-the-art in providing a formal trust measuring mechanism for customers by introducing three types of trust which we refer to as ‘direct’, ‘relative’ and ‘transparent’.

Automating performance and energy consumption analysis for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure, enabling cloud service providers to deploy applications as services according to user QoS (Quality of Service) requirements. One consequence of this cloud model is the huge amount of energy consumption and significant carbon footprints caused by large cloud infrastructures. A key and common objective of cloud service providers is thus to develop cloud application deployment and management solutions with minimum energy consumption while guaranteeing performance and other QoS specified in Service Level Agreements (SLAs). However, finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance is an extremely challenging task, which requires the evaluation of system performance and energy consumption under various workloads and deployment configurations. In order to simplify this process we have developed Stress Cloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. Stress Cloud supports the modelling of realistic cloud application workloads, the automatic generation of load tests, and the profiling of system performance and energy consumption. We demonstrate the utility of Stress Cloud by analysing the performance and energy consumption of a cloud application under a broad range of different deployment configurations.

Converged network-cloud service composition with end-to-end performance guarantee

The crucial role of networking in Cloud computing calls for federated management of both computing and networkin resources for end-To-end service provisioning. Application of the Service-Oriented Architecture (SOA) in both Cloud computing an networking enables a convergence of network and Cloud service provisioning. One of the key challenges to high performanc converged network-Cloud service provisioning lies in composition of network and Cloud services with end-To-end performanc guarantee. In this paper, we propose a QoS-Aware service composition approach to tackling this challenging issue. We first present system model for network-Cloud service composition and formulate the service composition problem as a variant of Multi-Constraine Optimal Path (MCOP) problem. We then propose an approximation algorithm to solve the problem and give theoretical analysis o properties of the algorithm to show its effectiveness and efficiency for QoS-Aware network-Cloud service composition. Performanc of the proposed algorithm is evaluated through extensive experiments and the obtained results indicate that the proposed metho achieves better performance in service composition than the best current MCOP approaches Service (QoS).

Cloud computing adoption by SMEs in Australia.

This study aims to examine the important factors that influence SMEs’ adoption of cloud computing technology. The results showing that SMEs were influenced by factors related to advantaging their organizational capability rather than risk-related factors. The findings are useful to SMEs owners, Cloud service providers and government in establishing Cloud computing adoption strategies for SMEs.

A general communication cost optimization framework for big data stream processing in geo-distributed data centers

With the explosion of big data, processing large numbers of continuous data streams, i.e., big data stream processing (BDSP), has become a crucial requirement for many scientific and industrial applications in recent years. By offering a pool of computation, communication and storage resources, public clouds, like Amazon's EC2, are undoubtedly the most efficient platforms to meet the ever-growing needs of BDSP. Public cloud service providers usually operate a number of geo-distributed datacenters across the globe. Different datacenter pairs are with different inter-datacenter network costs charged by Internet Service Providers (ISPs). While, inter-datacenter traffic in BDSP constitutes a large portion of a cloud provider's traffic demand over the Internet and incurs substantial communication cost, which may even become the dominant operational expenditure factor. As the datacenter resources are provided in a virtualized way, the virtual machines (VMs) for stream processing tasks can be freely deployed onto any datacenters, provided that the Service Level Agreement (SLA, e.g., quality-of-information) is obeyed. This raises the opportunity, but also a challenge, to explore the inter-datacenter network cost diversities to optimize both VM placement and load balancing towards network cost minimization with guaranteed SLA. In this paper, we first propose a general modeling framework that describes all representative inter-task relationship semantics in BDSP. Based on our novel framework, we then formulate the communication cost minimization problem for BDSP into a mixed-integer linear programming (MILP) problem and prove it to be NP-hard. We then propose a computation-efficient solution based on MILP. The high efficiency of our proposal is validated by extensive simulation based studies.