A novel ANN-based service selection model for ubiquitous computing environments

How to choose an appropriate service from all the usable services regardless of user's location and heterogeneous architecture of underlying software and hardware infrastructure is the most important study content in ubiquitous computing domain. In order to overcome the shortcomings of blindness and randomicity in traditional and improved trust-mechanism-based service selection models, we propose a novel ANN-based (Artificial Neural Network) service selection model (called the ANNSS model). We adopt a novel method which according to the earlier information of the cooperation between the devices and the context information, an ANN-based evaluation standard for the service quality of service provider is given out so that user can acquire an effective guidance and choose the most appropriate service. At the same time, we improved the traditional BP algorithm based on three-term method (called the TTMBP algorithm) consisting of a learning rate (LR), a momentum factor (MF) and a proportional factor (PF) in order to satisfy the requirements of time issue in real-time system. The convergence speed and stability were enhanced by adding the proportional factor. The self-adjusting architecture method is adopted so that a moderate scale of neural network can be obtained. We have implemented the ANNSS algorithm in an actual power supply system for communication devices and fulfilled various simulations. The results of simulation show that the proposed service selection scheme is not only scalable but also efficient, and that the novel BP algorithm based on three-term has high convergence speed and good convergence stability. The novel service selection scheme superior to the traditional and improved trust-mechanism-based service selection scheme. The novel scheme can exactly choose a most appropriate service from many service providers and provide the most perfect service performance to users.     

Trust management in ubiquitous computing: A Bayesian approach

Designing a trust management scheme that can effectively evaluate the relationships among devices in pervasive computing environments is a challenging task. This paper continues the investigation of our recently proposed probabilistic trust management scheme for pervasive computing environments. We argue that in addition to allowing a device to find other appropriate devices with which to interact, while detecting those that are malicious, our trust management scheme is also capable of (1) allowing a device to judge the trustworthiness of another device it interacts with, while making a better use of the received recommendations and (2) behaving as expected when a device has little or enough experience of interactions with other devices and changes dynamically occur in the proportion of malicious devices. Simulation experiments are provided to assess the achievement of the stated goals, using some representative performance metrics.     

A robotic service framework supporting automated integration of ubiquitous sensors and devices

In recent years, due to the emergence of ubiquitous computing technology, a new class of networked robots called ubiquitous robots has been introduced. The Ubiquitous Robotic Companion (URC) is our conceptual vision of ubiquitous service robots that provides its user with the services the user needs, anytime and anywhere, in the ubiquitous computing environments. There are requirements to be met for the vision of URC. One of the essential requirements is that the robotic systems must support ubiquity of services. This means that a robot service must always be available even though there are changes in the service environment. More specifically, a robotic system needs to be interoperable with sensors and devices in its current service environments automatically, rather than statically pre-programmed for its environment. In this paper, the design and implementation of an infrastructure for URC called Ubiquitous Robotic Service Framework (URSF) is presented. URSF enables automated integration of networked robots in a ubiquitous computing environment by the use of Semantic Web Services Technologies.     

Service discovery for GRID computing using LCAN-mapped hierarchical directories

Hierarchical Directories were introduced to provide Service Address Routing (Scherson, Valencia in: Proceedings of the international symposium on parallel architectures, algorithms and networks (I-SPAN), Las Vegas, USA, 2005) embedded in a class of Hierarchical Interconnection Networks known as Least Common Ancestor Networks (LCANs). The algorithms for service discovery in SAR are shown to extend to the GRID when the LCAN is effectively mapped onto the loosely coupled Internet connected computing cluster. In SAR, nodes (programs) communicate by invoking services from the network itself. It is the network-embedded service discovery and addressing mechanism that provides the physical binding. Even though the SAR concept was conceived for tightly coupled interconnection networks, it can also be applied to an Internet GRID system by mapping the SAR network directory (considered to be LCAN-embedded) onto the loosely coupled GRID. Once the network is successfully mapped to the subjacent network, all scalability, fault-tolerance, functionality, and every other advantage of an LCAN-SAR system are automatically available in the resulting implementation. We present a novel way to perform a completely distributed and dynamic service discovery that not only performs faster lookups by avoiding well known bottlenecks in centralized systems, but has inherent fault tolerance mechanisms.     

Access control management for ubiquitous computing

The purpose of ubiquitous computing is anywhere and anytime access to information within computing infrastructures that is blended into a background and no longer be reminded. This ubiquitous computing poses new security challenges while the information can be accessed at anywhere and anytime because it may be applied by criminal users. Additionally, the information may contain private information that cannot be shared by all user communities. Several approaches are developed to protect information for pervasive environments against malicious users. However, ad hoc mechanisms or protocols are typically added in the approaches by compromising disorganized policies or additional components to protect from unauthorized access.In this paper, we present a usage control model to protect services and devices in ubiquitous computing environments, which allows the access restrictions directly on services and object documents. The model not only supports complex constraints for pervasive computing, such as services, devices and data types but also provides a mechanism to build rich reuse relationships between models and objects. Finally, comparisons with related works are analysed.     

A trustworthy QoS-based collaborative filtering approach for web service discovery

Many network services which process a large quantity of data and knowledge are available in the distributed network environment, and provide applications to users based on Service-Oriented Architecture (SOA) and Web services technology. Therefore, a useful web service discovery approach for data and knowledge discovery process in the complex network environment is a very significant issue. Using the traditional keyword-based search method, users find it difficult to choose the best web services from those with similar functionalities. In addition, in an untrustworthy real world environment, the QoS-based service discovery approach cannot verify the correctness of the web services’ Quality of Service (QoS) values, since such values guaranteed by a service provider are different from the real ones. This work proposes a trustworthy two-phase web service discovery mechanism based on QoS and collaborative filtering, which discovers and recommends the needed web services effectively for users in the distributed environment, and also solves the problem of services with incorrect QoS information. In the experiment, the theoretical analysis and simulation experiment results show that the proposed method can accurately recommend the needed services to users, and improve the recommendation quality.     

On location models for ubiquitous computing

Common queries regarding information processing in ubiquitous computing are based on the location of physical objects. No matter whether it is the next printer, next restaurant, or a friend is searched for, a notion of distances between objects is required. A search for all objects in a certain geographic area requires the possibility to define spatial ranges and spatial inclusion of locations. In this paper, we discuss general properties of symbolic and geometric coordinates. Based on that, we present an overview of existing location models allowing for position, range, and nearest neighbor queries. The location models are classified according to their suitability with respect to the query processing and the involved modeling effort along with other requirements. Besides an overview of existing location models and approaches, the classification of location models with respect to application requirements can assist developers in their design decisions.     

Ubicon and its applications for ubiquitous social computing

The combination of ubiquitous and social computing is an emerging research area which integrates different but complementary methods, techniques, and tools. In this paper, we focus on the Ubicon platform, its applications, and a large spectrum of analysis results. Ubicon provides an extensible framework for building and hosting applications targeting both ubiquitous and social environments. We summarize the architecture and exemplify its implementation using four real-world applications built on top of Ubicon. In addition, we discuss several scientific experiments in the context of these applications in order to give a better picture of the potential of the framework, and discuss analysis results using several real-world data sets collected utilizing Ubicon.     

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.

ARMCO: Advanced topics in resource management for ubiquitous cloud computing: An adaptive approach

Cloud Computing can be seen as one of the latest major evolution in computing offering unlimited possibility to use ICT in various domains: business, smart cities, medicine, environmental computing, mobile systems, design and implementation of cyber-infrastructures. The recent expansion of Cloud Systems has led to adapting resource management solutions for large number of wide distributed and heterogeneous datacenters. The adaptive methods used in this context are oriented on: self-stabilizing, self-organizing and autonomic systems; dynamic, adaptive and machine learning based distributed algorithms; fault tolerance, reliability, availability of distributed systems. The pay-per-use economic model of Cloud Computing comes with a new challenge: maximizing the profit for service providers, minimizing the total cost for customers and being friendly with the environment.This special issue presents advances in virtual machine assignment and placement, multi-objective and multi-constraints job scheduling, resource management in federated Clouds and in heterogeneous environments, dynamic topology for data distribution, workflow performance improvement, energy efficiency techniques and assurance of Service Level Agreements.     

Location-based services in ubiquitous computing environments

This paper presents a framework for providing dynamically deployable services in ubiquitous computing settings. The goal of the framework is to provide people, places, and objects with computational functionalities to support and annotate them. Using RFID-based tracking systems, the framework detects the locations of physical entities, such as people or things, and deploys services bound to the entities at proper computing devices near where they are located. It enables location-based and personalized information services to be implemented as mobile agents and operated at stationary or mobile computing devices, which are at appropriate locations, even if the services do not have any location-information. This paper presents the rationale, design, implementation, and applications of our prototype infrastructure.     

An incentive compatible reputation mechanism for ubiquitous computing environments

The vision of ubiquitous computing is becoming a reality thanks to the advent of portable devices and the advances in wireless networking technologies. It aims to facilitate user tasks through seamless utilization of services available in the surrounding environments. In such distributed environments featuring openness, interactions such as service provision and consumption between entities that are unknown or barely known to each other, are commonplace. Trust management through reputation mechanism for facilitating such interactions is recognized as an important element of ubiquitous computing. It is, however, faced by the problems of how to stimulate reputation information sharing and enforce honest recommendation elicitation. We present in this paper an incentive compatible reputation mechanism to facilitate the trustworthiness evaluation of entities in ubiquitous computing environments. It is based on probability theory and supports reputation evolution and propagation. Our reputation mechanism not only shows robustness against lies, but also stimulates honest and active recommendations. The latter is realized by ensuring that active and honest recommenders, compared to inactive or dishonest ones, can obtain the most number of honest (helpful) recommendations and thus suffer the least number of wrong trust decisions, as validated by simulation based evaluation. The proposed reputation mechanism is also implemented as part of a QoS-aware Web service discovery middleware and evaluated regarding its overhead on service discovery latency.     

Context-aware active task discovery for pervasive computing

Task computing is mainly involved with how to interact with equipment and services for users. In such new mode users can only concern with the task need to be completed, without having to consider how to complete it. In recent years, this new mode has been considered the preferred choice under the environment of pervasive computing. Active task discovery is the key to task computing, which depends on context and automatically relates the corresponding services to complete the given operation. In this paper, based on active task computing model we present a new context-aware active task discovery mode and raise a good algorithm for discovering and executing task.     

Using ubiquitous computing in interactive mobile marketing

Unique features of handheld devices, including their mobility, personalization and location-awareness engender new types of applications for mobile commerce, such as mobile advertising. Mobile marketing and advertising applications deliver promotional information to consumers based on their preferences and location. In this paper, we present SMMART, a context-aware, adaptive and personalized m-commerce application designed to deliver targeted promotions to the users of mobile devices about the products they like while guarding the users’ identity and protecting them from any unsolicited messages. Promotions distributed by SMMART are personalized by performing intelligent matching of the user’s shopping interests to current promotions available at a retail site. SMMART can adapt to changing preferences of its user by inconspicuously monitoring his or her shopping habits. We describe a fully functional prototype of SMMART built for Pocket PCs running Windows CE with .NET Compact Framework. This paper also presents a study demonstrating end-user usability and economic viability of SMMART.     

DaaS: Cloud-based mobile Web service discovery

The proliferation of smartphones and the recent advancement in ubiquitous wireless access have made mobile Web services more possible than ever before. However, finding relevant Web services that can match requests and fit user context remains a major concern. The challenges facing Web service discovery are further magnified by the stringent constraints of mobile devices and the inherit complexity of wireless heterogeneous networks. Cloud computing, with its flexible design and theoretically unlimited computing resources, is a viable approach to bootstrapping Web service discovery. The cloud can build bridges between mobile devices, as a convenient ubiquitous interface, and a backbone infrastructure with abundant computing resources. This paper introduces “Discovery as a service (Daas)”, a novel cloud-based discovery framework that addresses the core components of mobile Web service discovery. The DaaS framework lays the foundation of efficient mobile Web service discovery that takes into consideration user preferences and context. The experimental validation and performance evaluation demonstrate that DaaS can effectively rank relevant services according to the various user context and preferences, in addition to enhancing the precision of the discovered services. The prototype also shows that Web service clustering for discovery significantly improves the overall response time, while the cloud maintains scalability according to prespecified performance criteria.     

Context-awareness in wearable and ubiquitous computing

A common focus shared by researchers in mobile, ubiquitous and wearable computing is the attempt to break away from the traditional desktop computing paradigm. Computational services need to become as mobile as their users. Whether that service mobility is achieved by equipping the user with computational power or by instrumenting the environment, all services need to be extended to take advantage of the constantly changing context in which they are accessed. This paper will report on work carried out by the Future Computing Environments Group at Georgia Tech to provide infrastructure for context-aware computing. We will describe some of the fundamental issues involved in contextaware computing, solutions we have generated to provide a flexible infrastructure and several applications that take advantage of context awareness to allow freedom from traditional desktop computing.     

A location model for smart environments

This paper presents a location model for location-aware and user-aware services in smart environments. It can be dynamically organized like a tree based on geographical containment, such as that in a user–room–floor–building hierarchy and each node in the tree can be constructed as an executable software component. The model is unique in existing approaches because it enables location-aware services to be managed without any database servers, it can be managed by multiple computers, and it can provide a unified view of the locations of not only physical entities and spaces, including users and objects, but also computing devices and services. A prototype implementation of this approach was constructed on a Java-based mobile agent system. This paper presents the rationale, design, implementation, and applications of the prototype system.     

基于功能语义标注的Web服务发现方法*

针对Web服务发现中存在的语义异构、逻辑推理复杂、应用实施代价较大以及查准率有待进一步提高等问题,提出了一种基于功能语义标注的Web服务发现方法。定义了领域功能语义模型和本体映射机制,对服务进行功能语义标注以增加语义信息;服务发现时,先对其功能进行语义相似度匹配,满足给定阈值的服务再进行接口匹配。仿真实验表明,提出的方法在保证服务匹配效率的同时,有效避免了语义异构问题,相比传统方法查准率提高了34.1%。     

S-Club: an overlay-based efficient service discovery mechanism in CROWN Grid

Information service plays a key role in grid system, handles resource discovery and management process. Employing existing information service architectures suffers from poor scalability, long search response time, and large traffic overhead. In this paper, we propose a service club mechanism, called S-Club, for efficient service discovery. In S-Club, an overlay based on existing Grid Information Service (GIS) mesh network of CROWN is built, so that GISs are organized as service clubs. Each club serves for a certain type of service while each GIS may join one or more clubs. S-Club is adopted in our CROWN Grid and the performance of S-Club is evaluated by comprehensive simulations. The results show that S-Club scheme significantly improves search performance and outperforms existing approaches. Chunming Hu is a research staff in the Institute of Advanced Computing Technology at the School of Computer Science and Engineering, Beihang University, Beijing, China. He received his B.E. and M.E. in Department of Computer Science and Engineering in Beihang University. He received the Ph.D. degree in School of Computer Science and Engineering of Beihang University, Beijing, China, 2005. His research interests include peer-to-peer and grid computing; distributed systems and software architectures. Yanmin Zhu is a Ph.D. candidate in the Department of Computer Science, Hong Kong University of Science and Technology. He received his B.S. degree in computer science from Xi’an Jiaotong University, Xi’an, China, in 2002. His research interests include grid computing, peer-to-peer networking, pervasive computing and sensor networks. He is a member of the IEEE and the IEEE Computer Society. Jinpeng Huai is a Professor and Vice President of Beihang University. He serves on the Steering Committee for Advanced Computing Technology Subject, the National High-Tech Program (863) as Chief Scientist. He is a member of the Consulting Committee of the Central Government’s Information Office, and Chairman of the Expert Committee in both the National e-Government Engineering Taskforce and the National e-Government Standard office. Dr. Huai and his colleagues are leading the key projects in e-Science of the National Science Foundation of China (NSFC) and Sino-UK. He has authored over 100 papers. His research interests include middleware, peer-to-peer (P2P), grid computing, trustworthiness and security. Yunhao Liu received his B.S. degree in Automation Department from Tsinghua University, China, in 1995, and an M.A. degree in Beijing Foreign Studies University, China, in 1997, and an M.S. and a Ph.D. degree in computer science and engineering at Michigan State University in 2003 and 2004, respectively. He is now an assistant professor in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology. His research interests include peer-to-peer computing, pervasive computing, distributed systems, network security, grid computing, and high-speed networking. He is a senior member of the IEEE Computer Society. Lionel M. Ni is chair professor and head of the Computer Science and Engineering Department at Hong Kong University of Science and Technology. Lionel M. Ni received the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, Indiana, in 1980. He was a professor of computer science and engineering at Michigan State University from 1981 to 2003, where he received the Distinguished Faculty Award in 1994. His research interests include parallel architectures, distributed systems, high-speed networks, and pervasive computing. A fellow of the IEEE and the IEEE Computer Society, he has chaired many professional conferences and has received a number of awards for authoring outstanding papers.