Interactive middleware architecture for lifelog based context awareness

Due to the development of IT convergence, a wide variety of information is being produced and distributed rapidly in digital form. Lifelog based context awareness is a technology that provides a service automatically based on perceived situational information in ubiquitous environments. To offer customized services to users, the technology of acquiring lifelog based context information in real time is the most important consideration. We propose the interactive middleware architecture for lifelog based context awareness in distributed and ubiquitous environments. Conventional middleware to support ubiquitous environments stores and manages the situational information and service content acquired by centralized storage or a DBMS. Centralized situational information and service content management may impede the autonomy of mobile nodes and the interoperation between different middle software. The proposed method designs a system that can distribute and manage situational information in mobile nodes using mobile devices in distributed and ubiquitous environments and share the service content between interactive middleware through publication. The application system designed in this study was used in a scenario providing situational perception based mobile service and proved to be useful.     

An innovative simulation environment for cross-domain policy enforcement

With the development of policy management systems, policy-based management has been introduced in cross-domain organization collaborations and system integrations. Theoretically, cross-domain policy enforcement is possible, but in reality different systems from different organizations or domains have very different high-level policy representations and low-level enforcement mechanisms, such as security policies and privacy configurations. To ensure the compatibility and enforceability of one policy set in another domain, a simulation environment is needed prior to actual policy deployment and enforcement code development. In most cases, we have to manually write enforcement codes for all organizations or domains involved in every collaboration activity, which is a huge task. The goal of this paper is to propose an enforcement architecture and develop a simulation framework for cross-domain policy enforcement. The entire environment is used to simulate the problem of enforcing policies across domain boundaries when permanent or temporary collaborations have to span multiple domains. The middleware derived from this simulation environment can also be used to generate policy enforcement components directly for permanent integration or temporary interaction. This middleware provides various functions to enforce policies automatically or semi-automatically across domains, such as collecting policies of each participant domain in a new collaboration, generating policy models for each domain, and mapping specific policy rules following these models to different enforcement mechanisms of participant domains.     

Context-adaptive and energy-efficient mobile transaction management in pervasive environments

Pervasive computing is a user-centric, scalable, parallel, and distributed computing paradigm, allowing users to access to their preferred services even while moving around. Transaction management for pervasive environments has to provide mobile users with reliable and transparent services anytime anywhere. To make such a vision a reality, the communication of pervasive transaction processing should be context-aware for adapting to dynamically changing execution environments, and energy-efficient for prolonging the lifetime of battery-powered mobile devices. In this paper, we propose a context model and a context-aware transaction model for pervasive transactions, and present a c\underline{\mathrm{c}} ontext-adaptive and e\underline{\mathrm{e}} nergy-efficient t\underline{\mathrm{t}} ransaction m\underline{\mathrm{m}} anagement mechanism (CETM) that can dynamically adjust transaction execution behaviors in terms of current context information. Moreover, we model and verify the correctness of the CETM through Petri nets. The simulation results have demonstrated that our transaction management mechanism CETM can significantly reduce the failed probability of concurrent pervasive transactions.     

Meteor: a middleware infrastructure for content‐based decoupled interactions in pervasive grid environments

Emerging pervasive information and computational environments require a content‐based middleware infrastructure that is scalable, self‐managing, and asynchronous. In this paper, we propose associative rendezvous (AR) as a paradigm for content‐based decoupled interactions for pervasive grid applications. We also present Meteor, a content‐based middleware infrastructure to support AR interactions. The design, implementation, and experimental evaluation of Meteor are presented. Evaluations include experiments using deployments on a local area network, the wireless ORBIT testbed at Rutgers University, and the PlanetLab wide‐area testbed, as well as simulations. Evaluation results demonstrate the scalability, effectiveness, and performance of Meteor to support pervasive grid applications. Copyright © 2007 John Wiley & Sons, Ltd.     

iCROSS: toward a scalable infrastructure for cross-domain context management

With the development of pervasive computing techniques, the world will be filled with interconnected context-aware domains (e.g., homes, offices, hospitals, etc.). While the previous studies focused solely on the management of contexts produced in a single domain, in this paper we discuss the challenges to be addressed for cross-domain context management. By analyzing the requirements from several scenarios, we identify two context producer–consumer patterns in multi-domain environments. Furthermore, to deal with the mobile entity problem raised in cross-domain context sharing, a transparent query mechanism that enables applications to obtain context information about mobile entities from remote domains is proposed. Two prototype applications—smart home and community services in a smart campus—have been developed to demonstrate the key features and usefulness of cross-domain context management. Initial experiments have also been conducted to evaluate the performance of our system.     

An integrated runtime QoS-aware middleware framework for distributed multimedia applications

Future-generation distributed multimedia applications are expected to be highly scalable to a wide variety of heterogeneous devices, and highly adaptive across wide-area distributed environments. This demands multiple stages of run-time support in QoS-aware middleware architectures, particularly, probing the performance of QoS parameters, instantiating the initial component configurations, and adapting to on-the-fly variations. However, few of the past experiences in related work have shown comprehensive run-time support in all of the above stages – they often design and build a middleware framework by focusing on only one of the run-time issues. In this paper, we argue that distributed multimedia applications need effective run-time middleware support in all these stages to be highly scalable and adaptive across a wide variety of execution environments. Nevertheless, the design of such a middleware framework should be kept as streamlined and simple as possible, leading to a novel and integrated run-time middleware platform to unify the probing, instantiation and adaptation stages. In addition, for each stage, the framework should enable the interaction of peer middleware components across host boundaries, so that the corresponding middleware function can be performed in a coordinated and coherent fashion. We present the design of such an integrated architecture, with a case study to illustrate how it is simple yet effective to monitor and configure complex multimedia applications.     

Generic support for distributed applications

In the late 1980s, software designers introduced middleware platforms to support distributed computing systems. Since then, the rapid evolution of technology has caused an explosion of distributed-processing requirements. Application developers now routinely expect to support multimedia systems and mobile users and computers. Timely response to asynchronous events is crucial to such applications, but current platforms do not adequately meet this need. Another need of existing and emerging applications is the secure interoperability of independent services in large-scale, widely distributed systems. Information systems serving organizations such as universities, hospitals, and government agencies require cross-domain interaction. To meet the needs of these applications, Cambridge University researchers developed middleware extensions that provide a flexible, scalable approach to distributed-application development. This article details the extensions they developed, explaining their distributed software approach and the support it has provided for emerging applications     

The Plan B OS for ubiquitous computing. Voice control, security, and terminals as case studies

The conventional approach to building pervasive environments relies on middleware to integrate different systems. Instead, we have built a system that can deal with these environments by exporting system resources through distributed virtual file systems. This requires no middleware, simplifies interoperation, and permits the application of general purpose tools to any system resource. A constraint-based file system import mechanism allows the system to adapt to changes in the environment and permits users to customize the environment and tailor adaptations according to their needs. The system has been in use for over a year to carry out our daily work and is underlying the smart space that we built for our department. The system, and some novel services, including ubiquitous voice interfaces, a distributed security architecture, and remote terminals for smart spaces, are also described in this paper.     

基于本体的上下文感知中间件框架

上下文感知是普适计算的核心技术之一,而描述和理解上下文信息是上下文感知的前提。由于上下文信息种类繁多、感知方式迥异,目前开发面向特定应用的上下文感知系统缺乏统一的机制和通用的架构,增加了系统开发的成本。引入语义Web技术,利用本体对上下文信息进行建模,采用本体描述语言描述上下文模型,提供了一个公共的上下文本体以实现多个独立开发的上下文感知系统对知识的共享和推理,构建了通用的上下文感知中间件框架,从而实现对域内上下文知识的共同理解。     

普适计算中间件技术

普适计算中间件通过软件基础设施重用支持上层应用的高效开发和便捷运行,是普适计算领域的研究热点。对普适计算中间件设计挑战进行了归纳,从上下文管理、中间件层自适应、面向自适应的公共服务和自适应软件体系结构支持等方面总结、阐述和分析了普适计算中间件的各项关键技术,分类介绍了主要普适计算中间件项目,给出了未来研究发展趋势。     

CoCaMAAL: A cloud-oriented context-aware middleware in ambient assisted living

Research into ambient assisted living (AAL) strives to ease the daily lives of people with disabilities or chronic medical conditions. AAL systems typically consist of multitudes of sensors and embedded devices, generating large amounts of medical and ambient data. However, these biomedical sensors lack the processing power to perform key monitoring and data-aggregation tasks, necessitating data transmission and computation at central locations. The focus here is on the development of a scalable and context-aware framework and easing the flow between data collection and data processing. The resource-constrained nature of typical wearable body sensors is factored into our proposed model, with cloud computing features utilized to provide a real-time assisted-living service. With the myriad of distributed AAL systems at play, each with unique requirements and eccentricities, the challenge lies in the need to service these disparate systems with a middleware layer that is both coherent and flexible. There is significant complexity in the management of sensor data and the derivation of contextual information, as well as in the monitoring of user activities and in locating appropriate situational services. The proposed CoCaMAAL model seeks to address such issues and implement a service-oriented architecture (SOA) for unified context generation. This is done by efficiently aggregating raw sensor data and the timely selection of appropriate services using a context management system (CMS). With a unified model that includes patients, devices, and computational servers in a single virtual community, AAL services are enhanced. We have prototyped the proposed model and implemented some case studies to demonstrate its effectiveness.     

Enabling portability in advanced information-centric services over structured peer-to-peer systems

A common factor among all the existing distributed, peer-to-peer systems is their lack of genericity. Typically, information-centric services (such as range queries) are deployed ad-hoc onto a specific peer-to-peer overlay. These kinds of solutions make them probably efficient but non-portable to other peer-to-peer infrastructures, and so the services and applications constructed over them. We do believe, instead, that a peer-to-peer-generic solution is feasible. In this paper, we tackle the genericity and portability issue specifically on structured peer-to-peer networks (SPNs).To do so, we introduce a distributed 3-layer architecture, which abstracts applications (on top of the architecture) and the peer-to-peer network currently in use (in the bottom layer). Our middleware appears in the middle layer, which is responsible to address two major challenges: (i) supporting complex, multi-dimensional application data domains and (ii) performing efficiently for a wide variety of information-centric services in the large scale.Broadly speaking, information-centric services are classified as data management (such as range or spatial queries) and content distribution services (like publish/subscribe), and our middleware is an umbrella for all them. Notice that data management services are based on the pull mode (i.e., a user lookups information previously stored in the system), whilst content distribution services obey to a push mode (i.e., the system delivers the information timely to users).The benefits of our approach are clear: (i) Our middleware can be easily deployed over existing SPNs, guaranteeing the portability of a critical mass of services and end-user applications; (ii) Several services can be added to the middleware, which will facilitate the appearance of new synergies; and (iii) our middleware deals with the application data domain transparently to services and applications, including the necessary algorithms for services to be efficiently deployed into our middleware.     

天空地一体化网络环境下多运动体系统跨域协同控制与智能决策

近年来,基于云控制技术的天空地异构多运动体系统的研究得到学界的关注,天空地跨域多运动体通过互联、互通、互操作,能够实现信息共享与融合、行为交互与协调、任务协同与合作,促进系统功能互补、效能倍增,从而提升面对复杂环境和任务的应对能力.鉴于此,详细阐述天空地异构多运动体系统的跨域协同控制与智能决策研究进展.首先,介绍天空地一体化网络环境下多运动体系统的内涵和云框架下的天空地移动云构成要素,以及代表性的研究进展;然后,从智能云控制和决策角度阐述天空地异构多运动体系统的研究现状,给出云控制与决策框架下的解决方案.最后,从集群管理、跨域协同感知、控制与决策等方面提出天空地异构多运动体系统需要解决的关键问题和技术,并对未来可能的研究方向进行讨论与展望.     

Middleware infrastructure for parallel and distributed programming models in heterogeneous systems

We introduce a middleware infrastructure that provides software services for developing and deploying high-performance parallel programming models and distributed applications on clusters and networked heterogeneous systems. This middleware infrastructure utilizes distributed agents residing on the participating machines and communicating with one another to perform the required functions. An intensive study of the parallel programming models in Java has helped identify the common requirements for a runtime support environment, which we used to define the middleware functionality. A Java-based prototype, based on this architecture, has been developed along with a Java object-passing interface (JOPI) class library. Since this system is written completely in Java, it is portable and allows executing programs in parallel across multiple heterogeneous platforms. With the middleware infrastructure, users need not deal with the mechanisms of deploying and loading user classes on the heterogeneous system. Moreover, details of scheduling, controlling, monitoring, and executing user jobs are hidden, while the management of system resources is made transparent to the user. Such uniform services are essential for facilitating the development and deployment of scalable high-performance Java applications on clusters and heterogeneous systems. An initial deployment of a parallel Java programming model over a heterogeneous, distributed system shows good performance results. In addition, a framework for the agents' startup mechanism and organization is introduced to provide scalable deployment and communication among the agents.     

Trust-based security in pervasive computing environments

Traditionally, stand-alone computers and small networks rely on user authentication and access control to provide security. These physical methods use system-based controls to verify the identity of a person or process, explicitly enabling or restricting the ability to use, change, or view a computer resource. However, these strategies are inadequate for the increased flexibility that distributed networks such as the Internet and pervasive computing environments require because such systems lack central control and their users are not all predetermined. Mobile users expect to access locally hosted resources and services anytime and anywhere, leading to serious security risks and access control problems. We propose a solution based on trust management that involves developing a security policy, assigning credentials to entities, verifying that the credentials fulfill the policy, delegating trust to third parties, and reasoning about users' access rights. This architecture is generally applicable to distributed systems but geared toward pervasive computing environments     

Inference management,trust and obfuscation principles for quality of information in emerging pervasive environments

The emergence of large scale, distributed, sensor-enabled, machine-to-machine pervasive applications necessitates engaging with providers of information on demand to collect the information, of varying quality levels, to be used to infer about the state of the world and decide actions in response. In these highly fluid operational environments, involving information providers and consumers of various degrees of trust and intentions, information transformation, such as obfuscation, is used to manage the inferences that could be made to protect providers from misuses of the information they share, while still providing benefits to their information consumers. In this paper, we develop the initial principles for relating to inference management and the role that trust and obfuscation plays in it within the context of this emerging breed of applications. We start by extending the definitions of trust and obfuscation into this emerging application space. We, then, highlight their role as we move from the tightly-coupled to loosely-coupled sensory-inference systems and describe how quality, value and risk of information relate in collaborative and adversarial systems. Next, we discuss quality distortion illustrated through a human activity recognition sensory system. We then present a system architecture to support an inference firewall capability in a publish/subscribe system for sensory information and conclude with a discussion and closing remarks.     

Immediate detection of predicates in pervasive environments

An important problem in pervasive environments is detecting predicates on sensed variables in an asynchronous distributed setting to determine context and to respond. We do not assume the availability of synchronized physical clocks because they may not be available or may be too expensive for predicate detection in such environments with a (relatively) low event occurrence rate. We address the problem of detecting each occurrence of a global predicate, at the earliest possible instant, by proposing a suite of three on-line middleware protocols having varying degrees of accuracy. We analyze the degree of accuracy for the proposed protocols. The extent of false negatives and false positives is determined by the run-time message processing latencies.     

Multiple-Agent Perspectives in Reasoning About Situations for Context-Aware Pervasive Computing Systems

In open heterogeneous context-aware pervasive computing systems, suitable context models and reasoning approaches are necessary to enable collaboration and distributed reasoning among agents. This paper proposes, develops, and demonstrates the following: 1) a novel context model and reasoning approach developed with concepts from the state-space model, which describes context and situations as geometrical structures in a multidimensional space; and 2) a context algebra based on the model, which enables distributed reasoning by merging and partitioning context models that represent different perspectives of computing entities over the object of reasoning. We show how merging and reconciling different points of view over context enhances the outcomes of reasoning about the context. We develop and evaluate our proposed algebraic operators and reasoning approaches with cases using real sensors and with simulations. We embed agents and mobile agents with these modeling and reasoning capabilities, thus facilitating context-aware and adaptive mobile agents operating in open pervasive environments.     

Models, methods and middleware for grid-enabled multiphysics oil reservoir management

Meeting the demands for energy entails a better understanding and characterization of the fundamental processes of reservoirs and of how human made objects affect these systems. The need to perform extensive reservoir studies for either uncertainty assessment or optimal exploitation plans brings up demands of computing power and data management in a more pervasive way. This work focuses on high performance numerical methods, tools and grid-enabled middleware systems for scalable and data-driven computations for multiphysics simulation and decision-making processes in integrated multiphase flow applications. The proposed suite of tools and systems consists of (1) a scalable reservoir simulator, (2) novel stochastic optimization algorithms, (3) decentralized autonomic grid middleware tools, and (4) middleware systems for large-scale data storage, querying, and retrieval. The aforementioned components offer enormous potential for performing data-driven studies and efficient execution of complex, large-scale reservoir models in a collaborative environment.     

Enhancing intelligence and dependability of a product line enabled pervasive middleware

To provide good support for user-centered application scenarios in pervasive computing environments, pervasive middleware must react to context changes and prepare services accordingly. At the same time, pervasive middleware should provide extended dependability via self-management capabilities, to conduct self-diagnosis of possible malfunctions using the current runtime context, and self-configuration and self-adaptation when there are service mismatches. In this article, we present an approach to combine the power of BDI practical reasoning and OWL/SWRL ontologies theoretical reasoning in order to improve the intelligence of pervasive middleware, supported by a set of Self-Management Pervasive Service (SeMaPS) ontologies featuring dynamic context, complex context, and self-management rules modeling. In this approach, belief sets are enriched with the results of OWL/SWRL theoretical reasoning to derive beliefs that cannot be obtained directly or explicitly. This is demonstrated with agents negotiating sports appointments. To cope with self-management, the corresponding monitoring, configuration, adaptation and diagnosis rules are developed based on OWL and SWRL utilizing SeMaPS ontologies. Evaluations show this combined reasoning approach can perform well, and that Semantic Web-based self-management is promising for pervasive computing environments.