Recovering from a lost digital wallet: A smart cards perspective extended abstract

Multi-application smart cards enable a user to potentially have a diverse set of applications on her smart card. The growing trend of services convergence fuelled by Near Field Communication and smart phones has made multi-application smart cards a tangible reality. In such an environment, cardholders might have a number of applications on their smart cards and if a card is lost, all of the applications would be lost with it. In addition, consumers might decide to upgrade their smart cards and require a seamless and secure framework to migrate their applications from the old smart card to the new one. Currently, the recovery of a smart card-based service might take from a day to a week at best as each of the lost cards can only be replaced by the respective card issuer, during which time the card issuer might lose business from the user because she is not able to access the provisioned services. Similarly, there is at present no migration mechanism proposed for smart card applications. The proposed framework in this paper enables a user to acquire a new smart card as she desires and then migrate/restore all of her applications onto it—allowing her to recover from her lost digital wallet in a secure, efficient, seamless and ubiquitous manner.     

Adaptive and context-aware service composition for IoT-based smart cities

Smart Cities are advancing towards an instrumented, integrated, and intelligent living space, where Internet of Things (IoT), mobile technologies and next generation networks are expected to play a key role. In smart cities, numerous IoT-based services are likely to be available and a key challenge is to allow mobile users perform their daily tasks dynamically, by integrating the services available in their vicinity. Semantic Service Oriented Architectures (SSOA) abstract the environment’s services and their functionalities as Semantic Web Services (SWS). However, existing service composition approaches based on SSOA do not support dynamic reasoning on user tasks and service behaviours to deal with the heterogeneity of IoT domains. In this paper, we present an adaptive service composition framework that supports such dynamic reasoning. The framework is based on wEASEL, an abstract service model representing services and user tasks in terms of their signature, specification (i.e., context-aware pre-conditions, post-conditions and effects) and conversation (i.e., behaviour with related data-flow and context-flow constraints). To evaluate our composition framework, we develop a novel OWLS-TC4-based testbed by combining simple and composite services. The evaluation shows that our wEASEL-based system performs more accurate composition and allows end-users to discover and investigate more composition opportunities than other approaches.     

Context Management for Adaptive Information Systems

Modern technologies enable users accessing services using multiple channels. In the service design phase, this poses additional requirements for high software adaptivity along different technical requirements and different user expectations. During execution, services are usually dynamically selected; this service selection phase requires the identification of the most suitable service along the context that characterizes the users in the time instant in which they send the service request. This paper focuses on the selection phase and it aims at providing a framework to define and manage the context in a general environment characterized by adaptivity and multichannel access. An example to demonstrate the suitability and feasibility of the framework is provided referring to the MAIS (Multichannel Adaptive Information Systems) architecture and considering services related to the tourism domain. The MAIS architecture aims at providing automatically and efficiently services with the appropriate features by choosing among many provider offerings.     

A framework for human-centered provisioning of ambient media services

The provisioning of ambient media in the user’s environment requires that a system handles the different aspects related to the media selection process. For example, ambient media is delivered to the user depending on their context and hence, the system needs to dynamically determine the context and provide media that are relevant therein. To set the premise of ambient media, a system may also need to customize the physical environment, for example, by dimming the lighting level or by lowering the volume. Besides, users’ need for media services changes over time and space that requires mechanisms to continually update their preferences based on their mobility in the environment. In this paper, we propose an ambient media service provisioning framework that incorporates the above requirements while keeping the user at the center of the media selection loop. To demonstrate the usefulness of this framework, we show experimental results by considering real-life scenario in a smart home environment.

Adaptive interaction support in ambient-aware environments based on quality of context information

Ambient-aware environments are technologically augmented with myriad sensors, devices and other emerging services in order to support users. However, users find it complex in interacting with such environments due to the presence of numerous devices and services. In this situation, providing context-aware implicit or automatic interaction support may help reducing the cognitive load of the users and facilitate easy access of the available devices and services. However, due to the imprecision in context information, implicit interactions performed by the environment often leads to mis-automation. The result of such impaired implicitness causes distrust and dissatisfaction to the user. In order to address this issue, we propose a system that considers quality of information to dynamically adjust the level of implicit interaction and allows a system to operate in different modes such as full-automation, action suggestion, simple notification, or null action. We conduct experiment in a smart home scenario in order to elicit users’ acceptance and trust regarding the proposed system. Our experiment shows that dynamic and alternative mode of interaction not only increases the satisfaction of users but also helps to avoid distrust in automated actions carried out by the environment under varying contexts.     

An effective monitoring framework and user interface design

A distributed environment requires a monitoring system to oversee the operation of various distributed nodes. A monitoring service is crucial because it ensures a high‐quality computing environment and a reliable service. The interface and framework determine the effectiveness of a monitoring system. This paper uses the concept of user‐adaptive visualization to design its interface and proposes a flexible modular framework. Designers can use the proposed modular framework to flexibly extend existing modules, design visual interfaces to satisfy user requirements, and improve system failover schemes. The implementation of such a monitoring system for monitoring data preservation nodes is also provided. The system including fault‐tolerance and notification functions supports full monitoring services for Storage Resource Broker (SRB) or integrated Rule‐Oriented Data System (iRODS) based systems. The experimental results show that the proposed framework is suitable for data preservation services and is robust and responsive when faced with system failures. Copyright © 2014 John Wiley & Sons, Ltd.     

A time-aware Bayesian approach for optimal manufacturing service recommendation in distributed manufacturing environments

With the growing emergence of distributed collaborative manufacturing systems, the utilization of service-oriented manufacturing to offer seamless access to a variety of complex, distributed and dynamic manufacturing resources has become a challenging issue. This paper presents a novel time-aware probabilistic Bayesian approach for recommending a few optimal manufacturing services based on the user preference for an initial manufacturing service. The Bayesian approach operates over a comprehensive, formal representation of manufacturing services, which adds the time-aware probability of satisfied service execution in manufacturing service ontology to take into account the statistical nature of the dynamic manufacturing environment. The Bayesian approach is useful because it infers a few top ranked hypotheses of manufacturing service that have the largest probability as the optimal selection in a specified context of user preference. A prototype system is built and validated with an illustrative example from manufacturing industry to demonstrate the feasibility of the proposed approach for optimal service recommendation.     

移动边缘计算中资源受限的动态服务部署策略

移动边缘计算（MEC）的出现使移动用户能够以低延迟访问部署在边缘服务器上的服务。然而,MEC仍然存在各种挑战,尤其是服务部署问题。边缘服务器的数量和资源通常是有限的,只能部署数量有限的服务;此外,用户的移动性改变了不同服务在不同地区的流行度。在这种情况下,为动态请求部署合适的服务就成为一个关键问题。针对该问题,通过了解动态用户请求来部署适当的服务以最小化交互延迟,将服务部署问题表述为一个全局优化问题,并提出了一种基于集群划分的资源聚合算法,从而在计算、带宽等资源约束下初步部署合适的服务。此外,考虑动态用户请求对服务流行度及边缘服务器负载的影响,开发了动态调整算法来更新现有服务,以确保服务质量（QoS）始终满足用户期望。通过一系列仿真实验验证了所提出策略的性能。仿真结果表明,与现有基准算法相比,所提出的策略可以降低服务交互延迟并实现更稳定的负载均衡。     

Context-driven personalized service discovery in pervasive environments

Pervasive environments are characterized by a large number of embedded devices offering their services to the user. Which of the available services are of most interest to the user considerably depends on the user’s current context. User context is often rich and very dynamic; making an explicit, user-driven discovery of services impractical. Users in such environments would instead like to be continuously informed about services relevant to them. Implicit discovery requests triggered by changes in the context are therefore prevalent. This paper proposes a proactive service discovery approach for pervasive environments addressing these implicit requests. Services and user preferences are described by a formal context model called Hyperspace Analogue to Context, which effectively captures the dynamics of context and the relationship between services and context. Based on the model, we propose a set of algorithms that can continuously present the most relevant services to the user in response to changes of context, services or user preferences. Numeric coding methods are applied to improve the algorithms’ performance. The algorithms are grounded in a context-driven service discovery system that automatically reacts to changes in the environment. New context sources and services can be dynamically integrated into the system. A client for smart phones continuously informs users about the discovery results. Experiments show, that the system can efficiently provide the user with continuous, up-to-date information about the most useful services in real time.     

设备端基于深度学习的智能家居服务推荐框架

随着智能家居的普及,用户期望通过自然语言指令实现智能设备的控制,并希望获得个性化的智能家居服务。然而,现有的挑战包括智能设备的互操作性和对用户环境的全面理解。针对上述问题,提出一个支持设备端用户智能家居服务推荐个性化的框架。首先,构建智能家居的运行时知识图谱,用于反映特定智能家居中的上下文信息,并生成用例场景语句;其次,利用预先收集的通用场景下,用户的自然语言指令和对应的用例场景语句训练出通用推荐模型;最后,用户在设备端以自然语言管理智能家居设备和服务,并通过反馈微调通用模型的权重得到个人模型。在基本指令集、复述集、场景指令集三个数据集上的实验表明,用户的个人模型相比于词嵌入方法的准确率提升了6.5%~30%,与Sentence-BERT模型相比准确率提升了2.4%~25%,验证了设备端基于深度学习的智能家居服务框架具有较高的服务推荐准确率,能够有效地管理智能家居设备和服务。     

G-TOPSIS: a cloud service selection framework using Gaussian TOPSIS for rank reversal problem

The dynamic resource requirement of applications has forced a large number of business organizations to join the cloud market and provide cloud services. It has posed a challenge for cloud users to select the best service providers and to minimize losses occurring due to its improper selection. This paper aims to propose a robust rank reversal technique for order of preference by similarity to ideal solution (TOPSIS) method based on Gaussian distribution and used to develop a cloud service selection framework. The proposed framework ranks cloud services based on the quality of services provided by cloud service providers and cloud user’s priority. A case study is performed on a real dataset obtained from CloudHarmony to show the effectiveness and correctness of the proposed framework. The results obtained demonstrate that the proposed framework ranks cloud services similar to TOPSIS-based frameworks. A sensitivity analysis has also been performed to check its robustness in six different cases causing rank reversal and found that the proposed framework is robust to handle rank reversal phenomenon in all the scenarios in comparison with other studies available in the literature.

     

Self-adaptable media service architecture for guaranteeing reliable multimedia services

The main objective of this paper is to design and develop a Self-Adaptable Media Service Architecture (SAMSA) for providing reliable dynamic composite multimedia service through policy-based actions. The multimedia services such as media retrieval, transcoding, scaling and display services are combined based on the preferences of the user to create a dynamic composite multimedia service called as Video-on-Demand service. Such distributed multimedia services deployed using Service Oriented Architecture (SOA) can be accessed in heterogeneous environments that are prone to changes during run-time. To provide reliable and adaptive multimedia services, a powerful self-adaptable architecture with dynamic compositions of multimedia services is necessary to adapt during run-time and react to the environment. The adaptability in this proposed architecture is achieved by enabling the service providers to Monitor, Analyze and Act on the defined policies that support customization of compositions of multimedia services and guarantee the Quality of Service (QoS) provisioning. The Media Service Monitor (MSM) observes the business and quality metrics associated with the multimedia services during run-time. The monitored results are analyzed by Monitored Results Analyzer (MRA) which identifies the type and location of the fault. The Adaptive Media Service Manager (AMSM) takes corrective actions based on the monitored results, through the policies defined as an extension of WS-Policy (Web Service—Policy framework). The effectiveness of the proposed Self-Adaptable Media Service Architecture (SAMSA) has been evaluated on Dynamic Composite Real-time Video-on-Demand Web Service (DCRVoDWS) for a maximum of 200 simultaneous client’s requests. The analysis of results shows that the proposed architecture provides better improvement on reliability, response time and user satisfaction.     

一种面向多用户的负载感知动态服务选择模型

在面向多用户的动态环境中进行基于QoS 的服务选择需要面临诸多挑战,而动态的服务负载就是其中之一.当前的服务选择方法难以在多用户多业务的开放环境下应对服务执行时的负载动态变化,缺乏实时感知负载的应变能力.针对这一问题,首先,提出一种基于负载等级的服务多维QoS 模型（load level based multidimensional QoS,简称LLBMQoS）;在此基础上,提出了一种面向多用户的负载感知的动态服务选择模型（load-aware dynamic serviceselection model,简称LADSSM）以实现动态负载环境下的服务优化选择.该模型采用两阶段服务选择：在组合服务规划阶段,生成候选服务队列;在组合服务执行阶段,依据当前负载状态实现服务的动态选择;最后,仿真实验的结果表明：该模型较好地适应了多用户动态环境下的服务负载变化,能够在保证用户端到端QoS需求的前提下,及时而有效地提供效用优化的服务选择方案.     

一种基于自适应框架的Web服务选择算法

在服务组合中,动态环境的变化可能导致参与组合的Web服务行为发生变化。为此,提出基于自适应框架的Web服务选择算法,用于获取公共服务注册处的信息,并将其记录在本地绑定库中,利用链接分析算法获得绑定库某一时刻高链接度的Web服务,实现服务选择。实验结果证明,该算法可在服务组合中动态选择高质量的Web服务,降低由服务质量变化造成的服务组合失败率。     

移动计算环境下的个人化服务发布和组装

随着移动计算技术的发展,移动设备用户可以服务的方式共享移动设备及其周围设备的计算能力和计算资源.然而,移动设备的私有性、资源受限性以及移动性等特征使得这种基于移动设备提供的个人化服务在发布和组装方面存在着一些特殊问题,例如用户隐私、移动设备资源消耗、网络环境变化引起的失效问题等.针对以上这些问题,提出一种移动计算环境下的个人化服务发布和组装方法.该方法在个人化服务发布过程中引入了服务意愿的概念,并在服务选择过程中综合考虑了服务意愿和服务效用.此外,还提出了资源感知的心跳机制来定期更新服务选择所依赖的设备及服务状态信息,从而解决由于网络环境变化等引起的服务失效问题.基于该方法,提出了一个基于JADE和OSGi的实现框架.通过一个案例分析,验证了所提出的实现框架的有效性以及在移动计算环境下考虑服务意愿的合理性.     

面向普适计算环境的嵌入式系统研究

服务提供与用户界面自适应问题是普适计算中的重要研究课题。嵌入式系统提供的服务对普适计算的服务起到了重要的支持作用;普适计算任务要获取用户的服务也需要自适应的用户界面来显示服务项目,嵌入式系统的自适应界面是合适的选择。但是,传统的嵌入式系统服务软件不能很好地实现上述目标。针对传统嵌入式系统服务模型的不足,首先总结了面向普适计算的嵌入式系统硬件结构,并将这种结构命名为计算元。随后提出了一种新的嵌入式系统服务提供模型,统一了用户上下文交互的标准信息格式。最后研究了该服务模型的实现。     

Robust one-time password authentication scheme using smart card for home network environment

Due to the exponential growth of the Internet users and wireless devices, interests on home networks have been enormously increased in recent days. In digital home networks, home services including remote access and control to home appliances as well as services offered by service providers are alluring. However, the remote control services cause digital home networks to have various security threats. Hence, for digital home networks, robust security services, especially remote user authentication, should be considered. This paper presents a robust and efficient authentication scheme based on strong-password approach to provide secure remote access in digital home network environments. The proposed scheme uses lightweight computation modules including hashed one-time password and hash-chaining technique along with low-cost smart card technology. It aims to satisfy several security requirements including stolen smart card attack and forward secrecy with lost smart card as well as functional requirements including no verification table and no time synchronization. Comparing with the existing representative schemes, it can be validated that the proposed scheme is more robust authentication mechanism having better security properties. We have conducted formal verification of the proposed scheme.     

基于协同过滤的个性化Web服务选择方法

对传统的Web服务选择算法进行分析,并指出其在动态环境下存在的问题。为了解决该问题,提出了基于协同过滤算法的个性化Web服务选择方法,并设计了一个动态的Web服务选择架构,架构使用协同过滤算法对Web服务的服务质量(QoS)值进行预测并选择最优的Web服务以满足用户的需求。使用150万条真实Web服务的QoS数据与其他4类算法进行了对比实验,结果表明所提方法的可行性和准确性。     

物联网环境下基于情境的语义Web服务选择

当前Web服务海量增加，物联网应用技术快速发展、不断普及，而现有的Web服务选择算法低效、用户匹配度低。针对该问题提出一种物联网环境下基于情境的语义Web服务选择方法。该方法应用QoS参数的无量纲化与语义Web服务动态选择方式，将物联网环境下服务与语义Web服务相结合，并根据用户需求针对QoS选择最优的服务集。实验表明，该方法能有效地提高用户服务动态选择的成功率。     

智能电网中基于MQTT协议的ABAC访问控制方案

在智能电网环境中,电力运营商和消费者通过智能电表进行大量高精度的用电数据的实时监测,用户机密数据持续暴露于未经授权的访问,在这种传统通信模式下,智能电表对家庭用户能源消耗的细粒度测量造成了严重的隐私安全问题,而现有的静态访问控制方法并不满足智能电网环境基于上下文的动态访问特性。针对此问题,提出一种基于物联网通信协议（MQTT协议）的访问控制方案,通过在MQTT协议中对树型结构的主题列表设计基于ABAC访问控制模型的动态上下文授权策略,并在WSO2系统使用XACML策略语言实现了提出的访问控制方案。性能评估结果表明,该方案能在较低的通信开销内支持动态的访问控制,以解决智能电网中用户的用电信息未经授权而泄露的隐私安全问题。