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.     

Research on the collaboration of service selection and resource scheduling for IoT simulation workflows

Cloud resources provide a promising way to efficiently perform the needed simulation tasks for a complex manufacturing process. Most of the existing work focuses only on how to effectively schedule computing resources to execute computing requirements of simulation workflows in Internet of Things (IoT) applications. Research on the scheduling of simulation workflows in consideration of task ordering, service selection, and resource allocation altogether has not been lacking. To fill in this void, this paper proposes a cloud-based 3-stage workflow scheduling model. Before scheduling computing resources to complete task requirements, the order of the tasks is determined and the services that can meet the task requirements are selected. In this model, the workload to satisfy task requirements is not fixed and takes on a different value depending upon the service selected with its unique complexity and accuracy. An optimization function that transforms and integrates makespan, cost, and accuracy in a unique way is proposed. For its solution, the relatively new symbiotic organisms search (SOS) algorithm is modified and two SOS-based optimization strategies are developed, i.e., joint optimization-based SOS (JOSOS) and split optimization-based SOS (SOSOS). The simulation results reveal that SOS-based algorithms, especially the SOSOS method, outperform all compared algorithms. Based on the proposed method, simulation services and computing resources can be rationally selected and scheduled to ensure the requirements of IoT applications.     

物联网应用中访问控制智能合约的形式化验证

蓝牙、WiFi等网络技术的进步推动物联网(IoT)的发展,然而IoT在方便了人们生活的同时也存在严重的安全隐患.若无安全的访问控制,非法接入IoT的访问可能给用户带来各方面的损失.传统的访问控制方法需要一个可信任的中心节点,不适合节点分散的IoT环境.区块链及智能合约的出现为IoT应用的访问控制提供了更有效的解决方案,...     

A structural service innovation approach for designing smart product service systems: Case study of smart beauty service

Smart Product-service systems (PSS) are the emerging type of PSS that offer market value and dynamic intelligence combining products and services as solutions to consumers based on digital technology. To design a smart PSS with an effective way, a structural design approach is required. Nevertheless, only a few existing researchers discussed this topic. Aiming to bridge this gap, an integrated way is proposed for smart PSS design. This study refines a generic approach for structural service innovation approach which integrates the advantage of PSS engineering and service engineering for designing smart product service systems. The structural design approach is based on the Theory of Inventive Problem Solving (TRIZ) incorporating with service blueprint named PRR method. Three design phases are demonstrated as verification of the PRR method by an elaborated case study of the smart beauty service. Based on PRR, three key design phases are integrated, i.e., (1) problem definition, (2) resolution generation, and (3) resolution design. Empirical results and implications are collected and discussed to obtain valuable insights for value creation.     

Achieving Knowledge-as-a-Service in IIoT-driven smart manufacturing: A crowdsourcing-based continuous enrichment method for Industrial Knowledge Graph

The rapid development of the industrial internet of things (IIoT) enlightened more tools and techniques to optimize the smart manufacturing service (SMS) paradigm, emphasizing the services based on pervasive IIoT products. However, the serviceability in the smart manufacturing environment is still limited since most of the conventional services are conducted in a passively reactive mode. The knowledge as a service (KaaS) model is hence to be introduced to emphasize the cognitive capability by actively utilizing massive knowledge, where industrial knowledge graph (IKG) plays as the core to generate context-awareness and proactive services for the optimization of serviceability and productivity. Meanwhile, as building IKGs for specific industrial cases is still plagued by the small scale and the lack of continuous enrichment, ensuring the quality and availability of the IKG are still challenging. Aiming to fill this gap with a practical and systematic approach, this paper proposes a generic crowdsourcing approach for continuously evolving the IKG. Through the IKG continuous enrichment approach, IKG-enabled systems indicate the higher value creation ability to utilize knowledge as a kind of service, rather than just a kind of resource. To further illustrate the proposed approach, a case study of a printed circuit board (PCB) processing machine is given with discussions. As an explorative study, future perspectives are also discussed to attract more open and in-depth studies for more robust applications of KaaS and IKG in the IIoT-driven smart manufacturing environment.     

Integrating crowd-/service-sourcing into digital twin for advanced manufacturing service innovation

In order to support advanced collaborations among smart products, services, users and service providers in a smart product and service ecosystem (S-PSS), this paper proposed a service-oriented hybrid digital twin (DT) and digital thread platform-based approach with embedded crowd-/service-sourcing mechanism for enabling advanced manufacturing services. This approach is well supported by the ecosystem interaction intelligence of digitally connected products, services, users, and service providers via Internet of Beings (IoB) (Things, Users and Service providers). First, driven by industrial application needs in heating industry, a conceptual model of the service-oriented hybrid platform integrated with crowdsourcing mechanism is developed, which supports the concepts of product DT, service DT and human user DT. Second, the key system realization techniques are developed to integrate service crowdsourcing and service recommendation for realizing smart services. Finally, a case study is carried out for evaluating and confirming its feasibility.     

Recommender systems for smart cities

Among other conceptualizations, smart cities have been defined as functional urban areas articulated by the use of Information and Communication Technologies (ICT) and modern infrastructures to face city problems in efficient and sustainable ways. Within ICT, recommender systems are strong tools that filter relevant information, upgrading the relations between stakeholders in the polity and civil society, and assisting in decision making tasks through technological platforms. There are scientific articles covering recommendation approaches in smart city applications, and there are recommendation solutions implemented in real world smart city initiatives. However, to the best of our knowledge, there is not a comprehensive review of the state of the art on recommender systems for smart cities. For this reason, in this paper we present a taxonomy of smart city features, dimensions, actions and goals, and, according to these variables, we survey the existing literature on recommender systems. As a result of our survey, we do not only identify and analyze main research trends, but also show current opportunities and challenges where personalized recommendations could be exploited as solutions for citizens, firms and public administrations.     

Semantic Web of Musical Things: Achieving interoperability in the Internet of Musical Things

The Internet of Musical Things (IoMusT) refers to the extension of the Internet of Things paradigm to the musical domain. Interoperability represents a central issue within this domain, where heterogeneous Musical Things serving radically different purposes are envisioned to communicate between each other. Automatic discovery of resources is also a desirable feature in IoMusT ecosystems. However, the existing musical protocols are not adequate to support discoverability and interoperability across the wide heterogeneity of Musical Things, as they are typically not flexible, lack high resolution, are not equipped with inference mechanisms that could exploit on board the information on the whole application environment. Besides, they hardly ever support easy integration with the Web. In addition, IoMusT applications are often characterized by strict requirements in terms of latency of the exchanged messages. Semantic Web of Things technologies have the potential to overcome the limitations of existing musical protocols by enabling discoverability and interoperability across heterogeneous Musical Things. In this paper we propose the Musical Semantic Event Processing Architecture (MUSEPA), a semantically-based architecture designed to meet the IoMusT requirements of low-latency communication, discoverability, interoperability, and automatic inference. The architecture is based on the CoAP protocol, a semantic publish/subscribe broker, and the adoption of shared ontologies for describing Musical Things and their interactions. The code implementing MUSEPA can be accessed at: https://github.com/CIMIL/MUSEPA/.     

Semantic communications between distributed cyber-physical systems towards collaborative automation for smart manufacturing

Machine-to-machine (M2M) communication is a crucial technology for collaborative manufacturing automation in the Industrial Internet of Things (IIoT)-empowered industrial networks. The new decentralized manufacturing automation paradigm features ubiquitous communication and interoperable interactions between machines. However, peer-to-peer (P2P) interoperable communications at the semantic level between industrial machines is a challenge. To address this challenge, we introduce a concept of Semantic-aware Cyber-Physical Systems (SCPSs) based on which manufacturing devices can establish semantic M2M communications. In this work, we propose a generic system architecture of SCPS and its enabling technologies. Our proposed system architecture adds a semantic layer and a communication layer to the conventional cyber-physical system (CPS) in order to maximize compatibility with the diverse CPS implementation architecture. With Semantic Web technologies as the backbone of the semantic layer, SCPSs can exchange semantic messages with maximum interoperability following the same understanding of the manufacturing context. A pilot implementation of the presented work is illustrated with a proof-of-concept case study between two semantic-aware cyber-physical machine tools. The semantic communication provided by the SCPS architecture makes ubiquitous M2M communication in a network of manufacturing devices environment possible, laying the foundation for collaborative manufacturing automation for achieving smart manufacturing. Another case study focusing on decentralized production control between machines in a workshop also proved the merits of semantic-aware M2M communication technologies.     

轻量级IPv6邻居发现协议及在网关中的实现

轻量级IPv6邻居发现协议是6LoWPAN （ IPv6 over Low power Wireless Personal Area Network,轻量级IPv6协议）的重要补充,旨在解决6LoWPAN无线传感网络初始化和网络维护过程中普遍存在的节点高消耗问题。文中归纳并总结了邻居发现轻量化的必要举措,在此基础上,提出了一套轻量级IPv6邻居发现协议在基于Linux操作系统的边界网关中的实现方案。通过在内核中邻居发现模块添加新特性,边界网关将负责处理大量原本需要传感节点分担的组网任务和网络维护任务,大大降低了域内节点开销。通过对原型系统的功能测试,方案完全符合协议标准,简单高效,并做到了与标准IPv6邻居发现协议的兼容。     

IoT-enabled smart appliances under industry 4.0: A case study

Manufacturers expect the extra value of Industry 4.0 as the world is experiencing digital transformation. Studies have proved the potential of the Internet of Things (IoT) for reducing cost, improving efficiency, quality, and achieving data-oriented predictive maintenance services. Collecting a wide range of real-time data from products and the environment requires smart sensors, reliable communications, and seamless integration. IoT, as a critical Industry 4.0 enabler emerges smart home appliances for higher customer satisfaction, energy efficiency, personalisation, and advanced Big data analytics. However, established factories with limited resources are facing challenges to change the longstanding production lines and meet customer’s requirements. This study aims to fulfil the gaps by transforming conventional home appliances to IoT-enabled smart systems with the ability to integrate into a smart home system. An industry-led case study demonstrates how to turn conventional appliances to smart products and systems (SPS) by utilising the state-of-the-art Industry 4.0 technologies.     

Location-based IoT applications on campus: The IoTtalk approach

The National Chiao Tung University is deploying several location-based IoT applications on campus based on an IoT device management platform called IoTtalk. The applications include dog tracking, emergency buttons, and indoor/outdoor environment conditions monitoring (PM2.5, temperature, CO₂, and so on). Some of the IoT devices for these applications have simple hardware structures to save energy, and therefore are not equipped with the positioning sensors (e.g., GPS or iBeacon). To support mobility management for these simple IoT devices, we develop a location finding mechanism in IoTtalk. By introducing the locator device in IoTtalk, we can effectively support mobility management for simple IoT devices that does not have location positioning capability. We describe how to develop the device applications to accommodate the location update feature, and show how to configure the location finding mechanism through the IoTtalk GUI. Then we conduct analytic analysis and simulation to investigate the accuracy of location tracking and power consumption for the dog tracking application.     

物联网体系结构研究与探讨

物联网是一个十分复杂而又庞大的系统,其体系结构是影响未来发展应用的关键所在。通过对现有物联网技术文献和体系结构实例的分析,提出了一种具有感知层、接入层、网络层和应用层的4层次物联网体系结构参考模型,并对各层所实现的主要功能进行了讨论阐述。这样一个通用的参考模型呈现出了泛在化、智能化的物联网基本特征。     

A hierarchical, agent-based service oriented architecture for smart environments

Service Oriented Architectures, which allow for the integration of different subsystems and of applications running on different devices and platforms, may be very suitable to solve the problem of service personalization in large smart environments like cities, where the number of potential users and potentially available services is rapidly growing. Taking this into account, we have designed an agent-based service oriented architecture for smart spaces. Two of the greatest challenges in the design of such a solution are providing effective device, service and context federation and composition mechanisms and handling user mobility. For the first challenge, we have designed a hierarchical architecture and developed a set of inheritance, aggregation and access mechanisms for devices, services and context. To handle user mobility, we have followed three different strategies, using stationary, mobile or nomadic agents. In this paper, we describe the main aspects of our architecture and perform an experimental evaluation to determine the advantages and drawbacks of the different strategies.     

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。     

Secure and privacy-preserving crowdsensing using smart contracts: Issues and solutions

The advent of Blockchain and smart contracts is empowering many technologies and systems to automate commerce and facilitate the exchange, tracking and the provision of goods, data and services in a reliable and auditable way. Crowdsensing systems is one type of systems that have been receiving a lot of attention in the past few years. In crowdsensing systems consumer devices such as mobile phones and Internet of Things devices are used to deploy wide-scale sensor networks. We identify some of the major security and privacy issues associated with the development of crowdsensing systems based on smart contracts and Blockchain. We also explore possible solutions that can address major security concerns with these systems.     

无源节点能量管理关键技术

能量管理是确保无源节点在不稳定供能环境下稳健运行的必要条件,但也带来了额外的计算负担,致使能量效率下降。为解决这一问题,研究了无源节点的能量理论,并针对性地提出无须本地计算辅助的“边端一体化”能量管理方案。首先,将高开销的细粒度能量规划从节点(端)解耦至网关(边),以降低节点上能量管理的复杂度。同时,创新性地提出了无采样感知和免计算决策电路的设计,解决了节点上无计算单元辅助下能量探测和决策执行所面临的两大关键技术挑战。至此,节点无须额外分配计算资源用于能量管理,从而在原理上避免了传统方式因将能量管理作为“附加任务”执行所导致的高开销问题。此外,在网关侧建立了远程开销预算模型,为多样化任务的供能需求实现了远程动态匹配。最后,实现了设计原型,并通过原型测试验证了设计的可行性。结果表明,与四种参考方式对比,该设计可降低92%的能量管理开销,并能对多变的供能环境作出灵活响应。     

Quantifying worker interactions and characterizing worker performance through ubiquitous IoT

Cloud technologies and artificial intelligence are transforming call centers into intelligent relationship hubs. Such transformation requires call-center employees to be strategically connected based on the distribution of expertise. However, today’s organizations lack a real-time method to agilely and pervasively map knowledge-distribution and optimize information flow. We present a pilot study showing that the interactions captured by Zigbee and infrared (IR) Internet of things (IoT) sensors on sociometric badges (a business-card-sized printed circuit board) worn by 36 employees in a call center can be used to characterize interactions and their impact on employee performance. Specifically, we quantify an employee’s centrality, weak ties, and strong ties from sensor network data and analyze the effects on average task-processing time. Further analysis reveals insights into interactions among workers that were previously limited by coarse qualitative data in survey studies. This study points to the potential of a “living lab” approach for investigating the effects of employee interactions and behaviors on their performance quantitatively in the real word using ubiquitous IoT.