Coordinating complex problem-solving among distributed intelligent agents

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet

Sharing the 620-790 MHz band allocated to terrestrial television with an audio-bandwidth social service satellite system

A study was carried out to identify the optimum uplink and downlink frequencies for audio-bandwidth channels for use by a satellite system distributing social services. The study considered functional-user-need models for five types of social services and identified a general baseline system that is appropriate for most of them. Technical aspects and costs of this system and of the frequency bands that it might use were reviewed, leading to the identification of the 620-790 MHz band as a perferred candidate for both uplink and downlink transmissions for nonmobile applications. The study also led to some ideas as to how to configure the satellite system

JXTA-Overlay: a P2P platform for distributed, collaborative, and ubiquitous computing

With the fast growth of the Internet infrastructure and the use of large-scale complex applications in industries, transport, logistics, government, health, and businesses, there is an increasing need to design and deploy multifeatured networking applications. Important features of such applications include the capability to be self-organized, be decentralized, integrate different types of resources (personal computers, laptops, and mobile and sensor devices), and provide global, transparent, and secure access to resources. Moreover, such applications should support not only traditional forms of reliable distributing computing and optimization of resources but also various forms of collaborative activities, such as business, online learning, and social networks in an intelligent and secure environment. In this paper, we present the Juxtapose (JXTA)-Overlay, which is a JXTA-based peer-to-peer (P2P) platform designed with the aim to leverage capabilities of Java, JXTA, and P2P technologies to support distributed and collaborative systems. The platform can be used not only for efficient and reliable distributed computing but also for collaborative activities and ubiquitous computing by integrating in the platform end devices. The design of a user interface as well as security issues are also tackled. We evaluate the proposed system by experimental study and show its usefulness for massive processing computations and e-learning applications.Peer ReviewedPostprint (author's final draft

Social Justice and Individual Choice

Consider a divisible resource or cost that is to be fairly distributed among a group, and suppose that various members of the group have different opinions about what a fair distribution might be. We exhibit a class of mechanisms that aggregate individual opinions into a group opinion, and which have the property that no one can manipulate the size of his own share. There is a unique such mechanism that satisfies a variant of Arrow's conditions for social choice functions. We illustrate its application to distributing dues among the member countries of IIASA. Other potential applications include distributing shares in formerly state-owned enterprises, and in allocating voting power among different states or regions in a federal system of government

Supporting Regularized Logistic Regression Privately and Efficiently

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Increasing concerns over data privacy make it more and more difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used machine learning model in various disciplines while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluation on several studies validated the privacy guarantees, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc

Appropriation of mobile cultural resources for learning

Copyright © 2010 IGI Global. This article proposes appropriation as the key for the recognition of mobile devices - as well as the artefacts accessed through, and produced with them - as cultural resources across different cultural practices of use, in everyday life and formal education. The article analyses the interrelationship of users of mobile devices with the structures, agency and practices of, and in relation to what the authors call the "mobile complex". Two examples are presented and some curricular options for the assimilation of mobile devices into settings of formal learning are discussed. Also, a typology of appropriation is presented that serves as an explanatory, analytical frame and starting point for a discussion about attendant issues

Security and Online learning: to protect or prohibit

The rapid development of online learning is opening up many new learning opportunities. Yet, with this increased potential come a myriad of risks. Usable security systems are essential as poor usability in security can result in excluding intended users while allowing sensitive data to be released to unacceptable recipients. This chapter presents findings concerned with usability for two security issues: authentication mechanisms and privacy. Usability issues such as memorability, feedback, guidance, context of use and concepts of information ownership are reviewed within various environments. This chapter also reviews the roots of these usability difficulties in the culture clash between the non-user-oriented perspective of security and the information exchange culture of the education domain. Finally an account is provided of how future systems can be developed which maintain security and yet are still usable

A framework for the forensic investigation of unstructured email relationship data

Our continued reliance on email communications ensures that it remains a major source of evidence during a digital investigation. Emails comprise both structured and unstructured data. Structured data provides qualitative information to the forensics examiner and is typically viewed through existing tools. Unstructured data is more complex as it comprises information associated with social networks, such as relationships within the network, identification of key actors and power relations, and there are currently no standardised tools for its forensic analysis. Moreover, email investigations may involve many hundreds of actors and thousands of messages. This paper posits a framework for the forensic investigation of email data. In particular, it focuses on the triage and analysis of unstructured data to identify key actors and relationships within an email network. This paper demonstrates the applicability of the approach by applying relevant stages of the framework to the Enron email corpus. The paper illustrates the advantage of triaging this data to identify (and discount) actors and potential sources of further evidence. It then applies social network analysis techniques to key actors within the data set. This paper posits that visualisation of unstructured data can greatly aid the examiner in their analysis of evidence discovered during an investigation

The intention to use mobile digital library technology: A focus group study in the United Arab Emirates

IGI Global (“IGI”) granted Brunel University London the permission to archive this article in BURA (http://bura.brunel.ac.uk).This paper presents a qualitative study on student adoption of mobile library technology in a developing world context. The findings support the applicability of a number of existing constructs from the technology acceptance literature, such as perceived ease of use, social influence and trust. However, they also suggest the need to modify some adoption factors previously found in the literature to fit the specific context of mobile library adoption. Perceived value was found to be a more relevant overarching adoption factor than perceived usefulness for this context. Facilitating conditions were identified as important but these differed somewhat from those covered in earlier literature. The research also uncovered the importance of trialability for this type of application. The findings provide a basis for improving theory in the area of mobile library adoption and suggest a number of practical design recommendations to help designers of mobile library technology to create applications that meet user needs