Crime risks of three-dimensional virtual environments

Three-dimensional virtual environments (3dves) are the new generation of digital multi-user social networking platforms. Their immersive character allows users to create a digital humanised representation or avatar, enabling a degree of virtual interaction not possible through conventional text-based internet technologies. As recent international experience demonstrates, in addition to the conventional range of cybercrimes (including economic fraud, the dissemination of child pornography and copyright violations), the 'virtual-reality' promoted by 3dves is the source of great speculation and concern over a range of specific and emerging forms of crime and harm to users. This paper provides some examples of the types of harm currently emerging in 3dves and suggests internal regulation by user groups, terms of service, or end-user licensing agreements, possibly linked to real-world criminological principles. This paper also provides some directions for future research aimed at understanding the role of Australian criminal law and the justice system more broadly in this emerging field.

How social is the virtual design studio? A case study of a third year design studio

With the advent of social networks, it became apparent that the social aspect of designing and learning plays a crucial role in students’ education. Technologies and skills are the base on which learners interact. The ease of communication, leadership opportunity, democratic interaction, teamwork, and the sense of community are some of the aspects that are now in the centre of design interaction. The paper examines Virtual Design Studios (VDS) that used media-rich platforms and analyses the influence the social aspect plays in solving all problems on the sample of a design studio at Deakin University. It studies the effectiveness of the generated social intelligence and explores the facilitation of students’ self-directed learning. Hereby the paper studies the construction of knowledge via social interaction and how blended learning environments foster motivation and information exchange. It presents its finding based on VDS that were held over the past three years.

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.