Mapping functions and data redistribution for parallel files

Data distribution in memory or on disks is an important factor influencing the performance of parallel applications. On the other hand, programs or systems, like a parallel file system, frequently redistribute data between memory and disks. This paper presents a generalization of previous approaches of the redistribution problem. We introduce algorithms for mapping between two arbitrary distributions of a data set. The algorithms are optimized for multidimensional array partitions. We motivate our approach and present potential utilizations. The paper also presents a case study, the employment of mapping functions, and redistribution algorithms in a parallel file system.

Understanding and capturing people’s privacy policies in a mobile social networking application

A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the extent that these concerns are adequately addressed. In this article, we report on our work on PeopleFinder, an application that enables cell phone and laptop users to selectively share their locations with others (e.g. friends, family, and colleagues). The objective of our work has been to better understand people’s attitudes and behaviors towards privacy as they interact with such an application, and to explore technologies that empower users to more effectively and efficiently specify their privacy preferences (or “policies”). These technologies include user interfaces for specifying rules and auditing disclosures, as well as machine learning techniques to refine user policies based on their feedback. We present evaluations of these technologies in the context of one laboratory study and three field studies.

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Supporting ordering and consistency in a distributed Event Heap for Ubiquitous Computing

The Stanford Event Heap has been shown to provide appropriate support for constructing interactive workspace applications. Given this success it is natural to consider the Event Heap as a platform to support other classes of Ubiquitous Computing applications. In this paper we argue that the distributed, spontaneous nature of these applications places additional demands on the Event Heap that require extensions to both the engineering and API. Suitable extensions are described and their use to support a typical Ubicomp application is discussed.

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Acoustic environment as an indicator of social and physical context

Acoustic environments provide many valuable cues for context-aware computing applications. From the acoustic environment we can infer the types of activity, communication modes and other actors involved in the activity. Environmental or background noise can be classified with a high degree of accuracy using recordings from microphones commonly found in PDAs and other consumer devices. We describe an acoustic environment recognition system incorporating an adaptive learning mechanism and its use in a noise tracker. We show how this information is exploited in a mobile context framework. To illustrate our approach we describe a context-aware multimodal weather forecasting service, which accepts spoken or written queries and presents forecast information in several forms, including email, voice and sign languages.

Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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Customer-centered design for mobile applications

Designing applications for mobile platforms presents unique and harder challenges than traditional software design. Users of such devices expect to be able to run such applications with no training, no traditional packaging elements such as quick start cards, and no help system. Customer-centered design is probably the only way such applications can be designed successfully. This paper presents our experience using customer-centered design to create a sophisticated mobile application—mSports Baseball. We describe the application and detail how we modified contextual Design (CD), our customer-centered design process, to produce an application users could enjoy with no training and no help.

The design and implementation of Visuel performance monitoring and analysis toolkit for cluster and grid environments

The computing power provided by high performance and low-cost PC-based clusters with Grid platforms are attractive and they are equal or superior to supercomputers and mainframes. In this paper, we present implementation and design rationale of Visuel toolkit for MPI parallel program performance measurement and analysis in cluster and grid environments. Most of performance visualization tools available today for high-performance platforms show solely system performance data (e.g., CPU load, memory usage, network bandwidth, server average load), and thus, being suitable for computing system activity visualization. The Visuel (Visuel (in French language) = to visualize) toolkit is web-based interface designed to show performance activities of all computing nodes of a distributed environment involved in the execution of MPI parallel program, such as CPU load level and memory usage of each computing node. In addition, this toolkit is able to display comparative performance data charts of MPI parallel applications and multiple executions under investigation. The usage of this toolkit shows that it outperforms in easing the process of investigation of parallel applications.

High performance power control and opportunistic fair scheduling in TH-PPM UWB ad-hoc multimedia networks

Ultra wideband (UWB) systems are currently an important wireless infrastructure for high performance short-range communications and mobile applications. Indeed, forming ad-hoc networks among various UWB enabled devices is considered as an important mobile data exchange operating environment. In our study, we explore the problem of jointly optimizing the power level and data rate used in the devices in such a UWB based ad-hoc network. We propose a practical optimization algorithm based on judicious power control for real-time applications and opportunistic scheduling for non-real-time applications. Simulation results indicate that our proposed techniques are effective under various practical scenarios.

Rapid prototyping of social group dynamics in multiagent systems

In this article we present an engineering approach for the integration of social group dynamics in the behavior modeling of multiagent systems. To this end, a toolbox was created that brings together several theories from the social sciences, each focusing on different aspects of group dynamics. Due to its modular approach, the toolbox can either be used as a central control component of an application or it can be employed temporarily to rapidly test the feasibility of the incorporated theories for a given application domain. This is exemplified by applying the toolbox to different applications.

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Connecting the family with awareness systems

Awareness systems have attracted significant research interest for their potential to support interpersonal relationships. Investigations of awareness systems for the domestic environment have suggested that such systems can help individuals stay in touch with dear friends or family and provide affective benefits to their users. Our research provides empirical evidence to refine and substantiate such suggestions. We report our experience with designing and evaluating the ASTRA awareness system, for connecting households and mobile family members. We introduce the concept of connectedness and its measurement through the Affective Benefits and Costs of communication questionnaire (ABC-Q). We inform results that testify the benefits of sharing experiences at the moment they happen without interrupting potential receivers. Finally, we document the role that lightweight, picture-based communication can play in the range of communication media available.

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Automatically wrapping legacy software into services: A grid case study

The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing for solving large-scale data and computationally intensive problems. Peer-to-peer (P2P) systems have emerged as an infrastructure enabling technologies for enhanced scalability and reliability in file sharing and content distribution. It is envisioned that P2P enabled service-oriented grid systems would virtualize various resources as services with high scalability and reliability. Many legacy software resources exist nowadays, but making them grid aware services for effective resource sharing has become an issue of vital importance. This paper presents GSLab, a toolkit for automatically wrapping legacy software into services that can be published, discovered and reused in grid environments. GSLab employs Sun Grid Engine (SGE) to enhance its performance in execution of wrapped services. Using GSLab, we have automatically wrapped a legacy computer animation rendering code written in C as a service that can be discovered and accessed in a SGE environment. The evaluation results show that the performance of GSLab improves with an increase in the number of computing nodes involved.

HERMES: embedded file system design for A/V application

Embedded systems such as PVR, set-top box, HDTV put unique demand on I/O subsystem design. Underlying software, particularly file system, needs to be elaborately designed so that it can meet tight constraints of consumer electronics platform: performance, price, reliability, and etc. In this work, we develop state-of-art file system elaborately tailored for A/V workload. There are two design objectives in our file system: performance and support for logical level abstraction. For performance, we develop a number of novel features: extent based allocation, single level file structure with block index augmentation scheme, aggressive free block allocation to minimize disk fragmentation, elaborate file system meta data layout, separation of name space data and file data and etc. HERMES enables the user to view file as a collection of semantic units (frame or audio samples). HERMES file system encompasses most of state-of-the-art file system technologies published in preceding works. Via extensive physical experiment, we verify that HERMES file system successfully addresses the original issues: good scalability, predictable I/O latency (minimizing variability in I/O latency), efficient disk head movement and etc. This is the result of harmonious effort of large I/O size, aggressive free block allocation algorithm, data block placement strategy, file organization, layout of HERMES file system and etc. The result of performance experiments indicate that HERMES file system prototype successfully meets the file system constraints for high volume and high bandwidth multimedia application. HERMES file system exhibits superior performance to EXT2 file system (Linux) and XFS file system (SGI).

Fault tolerant file models for parallel file systems: introducing distribution patterns for every file

Parallelism in file systems is obtained by using several independent server nodes supporting one or more secondary storage devices. This approach increases the performance and scalability of the system, but a fault in one single node can stop the whole system. To avoid this problem, data must be stored using some kind of redundant technique, so any data stored in a faulty element can be recovered. Fault tolerance can be provided in I/O systems by using replication or RAID based schemes. However, most of the current systems apply the same technique for all files in the system. This paper describes the fault tolerance support provided by Expand, a parallel file system based on standard servers. This support can be applied to other parallel file systems with many benefices: fault tolerance at file level, flexible definition of fault tolerance scheme to be used, possibility to change the fault tolerant support used for a file, etc.

Methods for quantitative usability requirements: a case study on the development of the user interface of a mobile phone

Quantitative usability requirements are a critical but challenging, and hence an often neglected aspect of a usability engineering process. A case study is described where quantitative usability requirements played a key role in the development of a new user interface of a mobile phone. Within the practical constraints of the project, existing methods for determining usability requirements and evaluating the extent to which these are met, could not be applied as such, therefore tailored methods had to be developed. These methods and their applications are discussed.

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The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

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Protecting business intelligence and customer privacy while outsourcing data mining tasks

Nowadays data mining plays an important role in decision making. Since many organizations do not possess the in-house expertise of data mining, it is beneficial to outsource data mining tasks to external service providers. However, most organizations hesitate to do so due to the concern of loss of business intelligence and customer privacy. In this paper, we present a Bloom filter based solution to enable organizations to outsource their tasks of mining association rules, at the same time, protect their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off the storage requirement. This research was supported by the USA National Science Foundation Grants CCR-0310974 and IIS-0546027.

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Multimodal support to group dynamics

The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole. A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.

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Using enhanced genetic programming techniques for evolving classifiers in the context of medical diagnosis

There are several data based methods in the field of artificial intelligence which are nowadays frequently used for analyzing classification problems in the context of medical applications. As we show in this paper, the application of enhanced evolutionary computation techniques to classification problems has the potential to evolve classifiers of even higher quality than those trained by standard machine learning methods. On the basis of five medical benchmark classification problems taken from the UCI repository as well as the Melanoma data set (prepared by members of the Department of Dermatology of the Medical University Vienna) we document that the enhanced genetic programming approach presented here is able to produce comparable or even better results than linear modeling methods, artificial neural networks, kNN classification, support vector machines and also various genetic programming approaches.