Smart home technology—comparing householder expectations at the point of installation with experiences 1 year later

This study, with 19 households, set out to analyse the expected benefits and anticipated challenges to the introduction of smart home technology (SHT), and to compare these to post-use experiences after living with the technology for 1 year. Contextual interviews were undertaken with householders during the installation of a range of SHT, and again approximately 1 year later, when householders had the option to keep the technology or have some or all of it removed. This identified whether initial expectations were met, whether initial concerns persisted and whether new issues, concerns, and benefits (that had not been initially anticipated) arose after an extended period of use. Initial expectations from all households were high—related to comfort, convenience, improved control, energy demand reduction, and integration of technologies. There were also many initial concerns, including reliability, usability, and how these systems would be ‘domesticated’ to fit existing routines. After living with the systems for 1 year, many expectations were met, but the added value (and hence the match between expectations and reality) was higher for households with varied routines and large, partially occupied houses. Some of the anticipated challenges—such as concerns over aesthetics—largely disappeared, issues to do with the awkward location of network components persisted and new issues arose relating to the usability of some components and the time and effort required to configure them. Recommendations are given to maximise the added value that SHT can provide to householders

An architecture for the autonomic curation of crowdsourced knowledge

Human knowledge curators are intrinsically better than their digital counterparts at providing relevant answers to queries. That is mainly due to the fact that an experienced biological brain will account for relevant community expertise as well as exploit the underlying connections between knowledge pieces when offering suggestions pertinent to a specific question, whereas most automated database managers will not. We address this problem by proposing an architecture for the autonomic curation of crowdsourced knowledge, that is underpinned by semantic technologies. The architecture is instantiated in the career data domain, thus yielding Aviator, a collaborative platform capable of producing complete, intuitive and relevant answers to career related queries, in a time effective manner. In addition to providing numeric and use case based evidence to support these research claims, this extended work also contains a detailed architectural analysis of Aviator to outline its suitability for automatically curating knowledge to a high standard of quality

On Trustworthiness of CPU Usage Metering and Accounting

Abstract—In the envisaged utility computing paradigm, a user taps a service provider’s computing resources to accom-plish her tasks, without deploying the needed hardware and software in her own IT infrastructure. To make the service profitable, the service provider charges the user based on the resources consumed. A commonly billed resource is CPU usage. A key factor to ensure the success of such a business model is the trustworthiness of the resource metering scheme. In this paper, we provide a systematic study on the trustworthiness of CPU usage metering. Our results show that the metering schemes in commodity operating systems should not be used in utility computing. A dishonest server can run various attacks to cheat the users. Many of the attacks are surprisingly simple and do not even require high privileges or sophisticated techniques. To demonstrate that, we experiment with several types of attacks on Linux and show their adversarial effects. We also suggest that source integrity, execution integrity and fine-grained metering are the necessary properties for a trustworthy metering scheme in utility computing. Keywords-CPU time metering; attack; utility computing I

The Montclarion, February 21, 2002

Student Newspaper of Montclair State Universityhttps://digitalcommons.montclair.edu/montclarion/2096/thumbnail.jp

Financial Market Models for the Grid

The existing network of computing devices around the world created by the Internet gives the possibility of establishing a global market for computing power, where anybody connected to this network can acquire computing power or sell his own spare computing resources in exchange for real money. This potential global market for computing power, which does not exist yet, is what we study in this thesis. Specifically, we study the market with both analytic and simulated models. This thesis predicts how a future global market for Grid computing will behave. We give arguments that such a large market, together with its potential indefinite growth, would not be able to scale if it were organized with a central server, and therefore we study a peer-to-peer market model in our simulations. We create a high-level model with the most relevant characteristics of the market, where buyers and sellers trade a single commodity. In our simulations, the parameters of the volume of contracts, proportion of satisfied agents and number of messages in the network achieve stable values in the long run. We also derive analytically the conditions that make the price get stable over time; we then implement these conditions in the simulation as local mechanisms of the market participants, which make the whole system achieve a stable price evolution. We are also confident that, as soon as the Grid market emerges, a parallel market of derivatives will be created as well. This market of derivatives will be important due to the non-storability nature of computing power. We develop a futures market for computing power based on Markov chains, where we initially model the behaviour of each participant with a particular Markov chain, and then we derive a global transition probability matrix that models the market as a whole. Furthermore, we analyse the performance of a futures trader operating in such a market, and we obtain an optimal trading strategy with the use of Markov Decision Processes. We finally develop a stochastic differential equation model that captures the essence of the spot price evolution of computing power observed in our market simulations. This model is based on a previously one proposed for the electricity market, and consists of the use of a Markov regime-switching mechanism in order to model the existence of spikes in the spot price. We then estimate the parameters in the model with the output data of our simulation program; the estimation is carried out both by maximum likelihood and the generalised method of moments