An Architecture for the Integration of Physical and Informational Spaces

While computer processing power, storage capacity, and bandwidth are continuing to experience exponential growth, individual human processing capabilities are not increasing significantly. Pervasive computing offers an opportunity for applications to interact with the physical environment and to provide a task-centric and mobile infrastructure for the user. However, this rich environment can also be distracting, in part because of a lack of convergence between the physical infrastructure observed by users and the information space seen by applications. In this paper we introduce AIPIS, an architecture that bridges the physical and informational realms of the human and the computer, respectively. The purpose of AIPIS is two-fold: (1) provide users with a hands-free computing environment that automates much of the drudgery associated with the use of computers; and (2) require human attention for only critical aspects of task execution that require their input. We also describe the Aura desktop, a first prototype of the AIPIS architecture.     

普适计算中间件技术的研究与进展

当前,普适计算已经成为计算机科学中一个极具活力和影响力的研究领域。普适计算环境规模很大并且具有高度异构性,如网络架构的异构性、硬件平台的异构性、操作系统的异构性、应用服务的异构性等,而普适计算中间件技术可以解决异构性和跨平台特征,提供不同服务的集成应用,因此成为普适计算中的一个研究热点。基于此,本文对于目前国外关于普适计算中间件技术的研究现状做了一个总结;通过分析和比较,给出了普适计算中间件的设计原则;探讨了普适计算中间件技术的未来发展方向。     

基于本体的上下文感知系统

普适计算自20世纪90年代中期被提出以后得到了普遍的关注。上下文感知作为实现普适计算的关键技术已成为重要的研究课题。在分析上下文感知系统以及组成模块的基础上,借鉴软件方法学中的快速原型模型思想,通过本体标记语言OWL给出了系统中感应模块搭建的实例。     

A reliable recommendation and privacy-preserving based cross-layer reputation mechanism for mobile cloud computing

Mobile cloud computing (MCC) is gaining popularity due to anywhere anytime data access. However, at the same time it also introduces the new privacy and security threats that have become an obstacle to the widespread use and popularity of MCC. In this paper, we propose a reliable recommendation and privacy preserving based cross-layer reputation mechanism (RP-CRM) to provide secure and privacy-aware communication process in wireless mesh networks (WMNs) based MCC (WM-MCC). RP-CRM integrates the cross-layer design with recommendation reputation reliability evaluation mechanism and the privacy preserving scheme to identify and manage the internal malicious nodes and protect the security and privacy against internal multi-layer attack, bad mouthing attack and information disclosure attack. Simulation results and performance analysis demonstrate that RP-CRM can provide rapid and accurate malicious node identification and management, and provide security and privacy protection against aforementioned attacks more effectively and efficiently.     

普适计算环境下基于中间件的上下文质量管理框架研究

随着信息技术的快速发展,分布式计算技术逐渐向普适计算技术演化,从而达到信息空间和物理空间融合的最终目标,为用户提供普适的智能化服务。为了达到这个目标,一个主要的困难就是如何有效地连续监测、才甫获与解释环境相关的上下文信息来确保精确的上下文感知性。很多研究者已先后投身于上下文感知的普适应用的研究工作中,但大多数往往直接针对原始上下文进行处理,没有考虑上下文质量(QoC)的影响。因此,提出了一种基于中间件的上下文质量管理框架,即通过上下文的质量门阂管理、重复与不一致的上下文丢弃等不同层次的控制机制,为上下文感知服务和应用用户提供有效而可靠的上下文服务。     

A comprehensive approach to model and use context for adapting applications in pervasive environments

With an increasing diversity of pervasive computing devices integrated in our surroundings and an increasing mobility of users, it will be important for computer systems and applications to be context-aware. Lots of works have already been done in this direction on how to capture context data and how to carry it to the application. Among the remaining challenges are to create the intelligence to analyze the context information and deduce the meaning out of it, and to integrate it into adaptable applications. Our work focuses on these challenges by defining generic context storage and processing model and by studying its impact on the application core. We propose a reusable context ontology model that is based on two levels: a generic level and a domain specific level. We propose a generic adaptation framework to guarantee adaptation of applications to the context in a pervasive computing environment. We also introduce a comprehensive adaptation approach that involves content adaptation and presentation adaptation inline with the adaptation of the core services of applications. Our case study shows that the context model and the application adaptation strategies provide promising service architecture.     

普适计算面临的安全挑战

分析了普适计算面临的安全挑战,给出了普适计算需要解决的几个安全问题,它们分别是：动态信任模型、认证、访问控制和隐私保护。并指出了这些安全问题的一些解决思路。     

A data-mining approach to preference-based data ranking founded on contextual information

The term information overload was already used back in the 1970s by Alvin Toffler in his book Future Shock, and refers to the difficulty to understand and make decisions when too much information is available. In the era of Big Data, this problem becomes much more dramatic, since users may be literally overwhelmed by the cataract of data accessible in the most varied forms. With context-aware data tailoring, given a target application, in each specific context the system allows the user to access only the view which is relevant for that application in that context. Moreover, the relative importance of information to the same user in a different context or, reciprocally, to a different user in the same context, may vary enormously; for this reason, contextual preferences can be used to further refine the views associated with contexts, by imposing a ranking on the data of each context-aware view. In this paper, we propose a methodology and a system, PREMINE (PREference MINEr), where data mining is adopted to infer contextual preferences from the past interaction of the user with contextual views over a relational database, gathering knowledge in terms of association rules between each context and the relevant data.     

Human-to-Human authorization for resource sharing in SHAD: Roles and protocols

One aim of pervasive computing is to allow users to share their resources so that they seem to be part of a single pervasive computer. This is just an illusion, the result of the synergy between different systems and resources. SHAD, introduced in PerCom 2007, is the first architecture that offers actual Single Sign-On to avoid authentication obtrusiveness and maintain the illusion of a single, pervasive computer. This paper describes how SHAD allows users to securely share their resources in a easy, natural, and intuitive way. It also describes its role-based Human-to-Human architecture, the threat model, and the protocols involved. Last but not the least, it presents results of further evaluation for our working implementation.     

Data-centric middleware for context-aware pervasive computing

The complexity of developing and deploying context-aware pervasive-computing applications calls for distributed software infrastructures that assist applications to collect, aggregate, and disseminate contextual data. In this paper, we motivate a data-centric design for such an infrastructure to support context-aware applications. Our middleware system, Solar, treats contextual data sources as stream publishers. The core of Solar is a scalable and self-organizing peer-to-peer overlay to support data-driven services. We describe how different services can be systematically integrated on top of the Solar overlay and evaluate the resource discovery and data-dissemination services. We also discuss our experience and lessons learned when using Solar to support several implemented scenarios. We conclude that a data-centric infrastructure is necessary to facilitate both the development and deployment of context-aware pervasive-computing applications.     

The ECORA framework: A hybrid architecture for context-oriented pervasive computing

An infrastructure approach to support context-aware pervasive computing is advantageous for rapid prototyping of context-aware distributed applications and beneficial for unifying modelling of context and reasoning in uncertain conditions. This paper presents the ECORA framework for context-aware computing, which is designed with a focus on reasoning about context under uncertainty and addressing issues of heterogeneity, scalability, communication and usability. The framework follows an agent-oriented hybrid approach, combining centralized reasoning services with context-aware, reasoning capable mobile software agents. The use of a centralized reasoning engine provides powerful reasoning capabilities and deploying context-aware mobile agents enables agility and robustness of components in the pervasive system. The design and implementation of the framework at different levels, as well as three case studies, are presented.     

觉察上下文计算环境中上下文服务器的设计

介绍了觉察上下文计算的基本概念和上下文以及上下文服务器的定义,阐述了实现上下文服务器所需要解决的问题,介绍一个上下文服务原型系统(Context Server for Web-based Mobile Service,CS4WMS)的系统架构、设计及实现。     

移动社交网络环境下的真实社会关系估计

移动设备的普及促进了移动社会网络的形成。移动社会网络基于用户的物理特征为其提供虚拟交互,而用户在真实世界中的社会关系知识可有效地用于改善移动社会网络服务质量。提出一种基于用户物理特征(包括由GPS坐标代表的位置特征和由蓝牙检测代表的邻近特征)估计其真实社会关系的方法。该方法首先基于用户的GPS轨迹挖掘语义化访问地点(如家、工作地点等),然后结合语义化访问地点和邻近特征估计用户间的社会关系类型。实验结果表明该方法可准确估计三种类型的真实社会关系(包括家人、同事和朋友)。     

A privacy mechanism for mobile-based urban traffic monitoring

In mobile-based traffic monitoring applications, each user provides real-time updates on their location and speed while driving. This data is collected by a centralized server and aggregated to provide participants with current traffic conditions. Successful participation in traffic monitoring applications utilizing participatory sensing depends on two factors: the information utility of the estimated traffic condition, and the amount of private information (position and speed) each participant reveals to the server. We assume each user prefers to reveal as little private information as possible, but if everyone withholds information, the quality of traffic estimation will deteriorate. In this paper, we model these opposing requirements by considering each user to have a utility function that combines the benefit of high quality traffic estimates and the cost of privacy loss. Using a novel Markovian model, we mathematically derive a policy that takes into account the mean, variance and correlation of traffic on a given stretch of road and yields the optimal granularity of information revelation to maximize user utility. We validate the effectiveness of this policy through real-world empirical traces collected during the Mobile Century experiment in Northern California. The validation shows that the derived policy yields utilities that are very close to what could be obtained by an oracle scheme with full knowledge of the ground truth.     

Improving the match between callers and receivers: A study on the effect of contextual information on cell phone interruptions

A problem with the location-free nature of cell phones is that callers have difficulty predicting receivers' states, leading to inappropriate calls. One promising solution involves helping callers decide when to interrupt by providing them contextual information about receivers. We tested the effectiveness of different kinds of contextual information by measuring the degree of agreement between receivers' desires and callers' decisions. In a simulation, five groups of participants played the role of 'Callers', choosing between making calls or leaving messages, and a sixth group played the role of 'Receivers', choosing between receiving calls or receiving messages. Callers were provided different contextual information about Receivers' locations, their cell phones' ringer state, the presence of others, or no information at all. Callers provided with contextual information made significantly more accurate decisions than those without it. Our results suggest that different contextual information generates different kinds of improvements: more appropriate interruptions or better avoidance of inappropriate interruptions. We discuss the results and implications for practice in the light of other important considerations, such as privacy and technological simplicity.     

Improving the match between callers and receivers: A study on the effect of contextual information on cell phone interruptions

A problem with the location-free nature of cell phones is that callers have difficulty predicting receivers' states, leading to inappropriate calls. One promising solution involves helping callers decide when to interrupt by providing them contextual information about receivers. We tested the effectiveness of different kinds of contextual information by measuring the degree of agreement between receivers' desires and callers' decisions. In a simulation, five groups of participants played the role of ‘Callers’, choosing between making calls or leaving messages, and a sixth group played the role of ‘Receivers’, choosing between receiving calls or receiving messages. Callers were provided different contextual information about Receivers' locations, their cell phones' ringer state, the presence of others, or no information at all. Callers provided with contextual information made significantly more accurate decisions than those without it. Our results suggest that different contextual information generates different kinds of improvements: more appropriate interruptions or better avoidance of inappropriate interruptions. We discuss the results and implications for practice in the light of other important considerations, such as privacy and technological simplicity.     

Activity-based computing: support for mobility and collaboration in ubiquitous computing

This paper presents the design philosophy of activity-based computing (ABC), which addresses mobility and cooperation in human work activities. Furthermore, it presents the ABC framework, which is a ubiquitous computing infrastructure supporting ABC. The idea of ABC and the aim of the ABC framework is to: (1) support human activity by managing its collection of work tasks on a computer, (2) support mobility by distributing activities across heterogeneous computing environments, (3) support asynchronous collaboration by allowing several people to participate in an activity, and (4) support synchronous, real-time collaboration by enabling desktop conferencing by sharing the activity across several clients. During a period of two years, the ABC framework has been co-designed and evaluated in close cooperation with a range of clinicians in a hospital.

Uncertainty handling in rule-based mobile context-aware systems

Uncertainty handling is one of the most important aspects of modelling of context-aware systems. It has direct impact on the adaptability, understood as an ability of the system to adjust to changing environmental conditions or hardware configuration (missing data), changing user habits (ambiguous concepts), or imperfect information (low quality sensors). In mobile context-aware systems, data is most often acquired from device’s hardware sensors (like GPS, accelerometer), virtual sensors (like activity recognition sensor provided by the Google API) or directly from the user. Uncertainty of such data is inevitable, and therefore it is obligatory to provide mechanisms for modelling and processing it. In this paper, we propose three complementary methods for dealing with most common uncertainty types present in mobile context-aware systems. We combine modified certainty factors algebra, probabilistic interpretation of rule-based model, and time-parametrised operators into a comprehensive toolkit for modelling and building robust mobile context-aware systems. Presented approach was implemented and evaluated on the practical use-case.     

智能空间研究综述

智能空间是一个将物理世界和信息空间融合起来的重要研究领域,着重于自然的人机交互、适应用户和设备的动态演化,以高效地帮助用户完成任务.本文简要叙述了智能空间的概念、目的、要求、特点和应用,介绍了其主要组成部分的硬件设备、普适网络和系统软件,并且从信息采集、上下文感知计算、中间件、智能决策和执行、安全性五个方面对研究热点进行了详细分析.在描述几个实例的基础上指出智能空间面临的挑战,最后对研究工作做了总结和展望.