Middleware for Internet of Things: Survey and Challenges

The Internet of things (IoT) applications span many potential fields. Furthermore, smart homes, smart cities, smart vehicular networks, and healthcare are very attractive and intelligent applications. In most of these applications, the system consists of smart objects that are equipped by sensors and Radio Frequency Identification (RFID) and may rely on other technological computing and paradigm solutions such as M2M (machine to machine) computing, Wifi, Wimax, LTE, cloud computing, etc. Thus, the IoT vision foresees that we can shift from traditional sensor networks to pervasive systems, which deliver intelligent automation by running services on objects. Actually, a significant attention has been given to designing a middleware that supports many features; heterogeneity, mobility, scalability, multiplicity, and security. This papers reviews the-state-of-the-art techniques for IoT middleware systems and reveals an interesting classification for these systems into service and agent-oriented systems. Therefore two visions have emerged to provide the IoT middleware systems: Via designing the middleware for IoT system as an eco-system of services or as an eco-system of agents. The most common feature of the two approaches is the ability to overcome heterogeneity issues. However, the agent approach provides context awareness and intelligent elements. The review presented in this paper includes a detailed comparison between the IoT middleware approaches. The paper also explores challenges that form directions for future research on IoT middleware systems. Some of the challenges arise, because some crucial features are not provided (or at most partially provided) by the existing middleware systems, while others have not been yet tackled by current research in IoT.     

Fog computing for next-generation Internet of Things: Fundamental,state-of-the-art and research challenges

In recent times, the Internet of Things (IoT) applications, including smart transportation, smart healthcare, smart grid, smart city, etc. generate a large volume of real-time data for decision making. In the past decades, real-time sensory data have been offloaded to centralized cloud servers for data analysis through a reliable communication channel. However, due to the long communication distance between end-users and centralized cloud servers, the chances of increasing network congestion, data loss, latency, and energy consumption are getting significantly higher. To address the challenges mentioned above, fog computing emerges in a distributed environment that extends the computation and storage facilities at the edge of the network. Compared to centralized cloud infrastructure, a distributed fog framework can support delay-sensitive IoT applications with minimum latency and energy consumption while analyzing the data using a set of resource-constraint fog/edge devices. Thus our survey covers the layered IoT architecture, evaluation metrics, and applications aspects of fog computing and its progress in the last four years. Furthermore, the layered architecture of the standard fog framework and different state-of-the-art techniques for utilizing computing resources of fog networks have been covered in this study. Moreover, we included an IoT use case scenario to demonstrate the fog data offloading and resource provisioning example in heterogeneous vehicular fog networks. Finally, we examine various challenges and potential solutions to establish interoperable communication and computation for next-generation IoT applications in fog networks.     

一种利用云环境实现Web服务组合容错的方法

随着Web服务迅猛发展,基于SOA的服务组合容错性研究成为了业界关注的焦点.服务组合中组件的失效,会导致整个组合执行失败,而资源不足、服务器负载过重是引发组件失效的主要原因之一.云计算作为一种新的计算泛型,其资源整合、动态分配的特点为解决传统SOA下因资源受限而引发的失效提供了新的容错思路.FTEL层将中间件技术应用到服务组合容错上,借助云环境完成服务替换,对传统SOA下较难解决的由于资源问题引起的组件失效进行了容错.     

System modelling and performance evaluation of a three-tier Cloud of Things

The emergent paradigm of fog computing advocates that the computational resources can be extended to the edge of the network, so that the transmission latency and bandwidth burden caused by cloud computing can be effectively reduced. Moreover, fog computing can support and facilitate some kinds of applications that do not cope well with some features of cloud computing, for instance, applications that require low and predictable latency, and geographically distributed applications. However, fog computing is not a substitute but instead a powerful complement to the cloud computing. This paper focuses on studying the interplay and cooperation between the edge (fog) and the core (cloud) in the context of the Internet of Things (IoT). We first propose a three-tier system architecture and mathematically characterize each tier in terms of energy consumption and latency. After that, simulations are performed to evaluate the system performance with and without the fog involvement. The simulation results show that the three-tier system outperforms the two-tier system in terms of the assessed metrics.     

IoT‐fog‐cloud based architecture for smart systems: Prototypes of autism and COVID‐19 monitoring systems

Making resources closer to the user might facilitate the integration of new technologies such as edge, fog, cloud computing, and big data. However, this brings many challenges shall be overridden when distributing a real‐time stream processing, executing multiapplication in a safe multitenant environment, and orchestrating and managing the services and resources into a hybrid fog/cloud federation. In this article, first, we propose a business process model and notation (BPMN) extension to enable the Internet of Things (IoT)‐aware business process (BP) modeling. The proposed extension takes into consideration the heterogeneous IoT and non‐IoT resources, resource capacities, quality of service constraints, and so forth. Second, we present a new IoT‐fog‐cloud based architecture, which (i) supports the distributed inter and intralayer communication as well as the real‐time stream processing in order to treat immediately IoT data and improve the entire system reliability, (ii) enables the multiapplication execution within a multitenancy architecture using the single sign‐on technique to guarantee the data integrity within a multitenancy environment, and (iii) relies on the orchestration and federation management services for deploying BP into the appropriate fog and/or cloud resources. Third, we model, by using the proposed BPMN 2.0 extension, smart autistic child and coronavirus disease 2019 monitoring systems. Then we propose the prototypes for these two smart systems in order to carry out a set of extensive experiments illustrating the efficiency and effectiveness of our work.     

基于三层架构的智慧教室设计

以学校数字化建设中的智慧教室研究为目的,基于物联网技术、云计算技术等按照感知层、网络层和应用层的架构体系进行智慧教室设计,具体分析了三层架构的组成、物理环境和软件环境的设计内容。研究表明,基于三层架构的智慧教室应用ZigBee技术组网能够实现教室内电气设备、教学资源等统一智能化管理与控制,采用云计算技术进行软件系统开发可以更加高效、安全地利用教室资源,为教师和学生提供优质的课堂环境,具有广泛的应用价值。     

Journey from cloud of things to fog of things: Survey,new trends,and research directions

With the advent of the Internet of Things (IoT) paradigm, the cloud model is unable to offer satisfactory services for latency-sensitive and real-time applications due to high latency and scalability issues. Hence, an emerging computing paradigm named as fog/edge computing was evolved, to offer services close to the data source and optimize the quality of services (QoS) parameters such as latency, scalability, reliability, energy, privacy, and security of data. This article presents the evolution in the computing paradigm from the client-server model to edge computing along with their objectives and limitations. A state-of-the-art review of Cloud Computing and Cloud of Things (CoT) is presented that addressed the techniques, constraints, limitations, and research challenges. Further, we have discussed the role and mechanism of fog/edge computing and Fog of Things (FoT), along with necessitating amalgamation with CoT. We reviewed the several architecture, features, applications, and existing research challenges of fog/edge computing. The comprehensive survey of these computing paradigms offers the depth knowledge about the various aspects, trends, motivation, vision, and integrated architectures. In the end, experimental tools and future research directions are discussed with the hope that this study will work as a stepping-stone in the field of emerging computing paradigms.     

SOA与云计算的融合

云计算是一种新型的网络服务计算模式,作为对SOA的继承与发展,现如今已成为网络研究领域的热点. 本文在介绍了SOA和云计算特征的基础上,对SOA与云计算之间的可融合性进行了分析,并提出了一种基于SOA的云计算体系架构模型. 最后通过数字图书馆进行平台实例应用,显示了基于SOA的云计算体系架构的可行性.     

Improving the Dependability of Web Services Integration

The WS-Mediator framework employs an off-the-shelf mediator architecture and resilience-explicit computing in pursuit of dependable, dynamic Web services integration. Web services and service-oriented architectures (SOAs) represent a new paradigm for building distributed computing applications. Web services offer advantages over conventional distributed computing middleware platforms. Web services' loosely coupled architecture, combined with their standardized interoperability, lead to a new computing paradigm that supports the construction of more flexible and dynamic distributed applications     

基于SOA的云计算框架模型的研究与实现

云计算是一种能够向各种互联网应用提供硬件服务、基础架构服务、平台服务、软件服务、存储服务的系统,而SOA是一个组件模型,它将依靠各服务之间定义良好的接口和契约的应用程序联系起来。将云计算与SOA紧密地结合起来,形成一种基于SOA的云计算框架模型。实验证明,该模型简单、实用,充分体现了云计算与面向服务的架构的优势。     

服务计算环境下一种基于机器学习的负载预测方法研究

随着计算机技术的迅速发展，分布式应用的规模迅速增加，越来越多的软件系统开始采用面向服务的体系结构SOA。为了提高SOA的可靠性和可扩展性，一种有效的方式就是提供服务副本，并通过基于中间件的负载平衡服务在不同的服务副本之间平衡负载。通过使用中间件，我们可以满足当前的面向服务应用对于性能、可扩展性和可用性的需求。然而，我们必须保证对于负载的计算具有一定的预测性以避免负载峰值的影响。对于复杂的面向服务应用来说，负载峰值意味着系统可能在短时间内具有极高的负载，而在大多数时间内负载较为平稳，从而因为负载取样的延时性导致系统过载而响应时间增加、总体吞吐量也受到影响。因此，为了降低响应时间，以及在负载频繁波动的情况下也能有效地利用服务副本，我们基于中间件为自适应和灵活的负载平衡机制的需求提出并实现了一种基于机器学习的预测机制。     

Internet of intelligent things and robot as a service

The development of computing and communication systems has gone through a spiral cycle of centralization and decentralization paradigms. The earliest computer systems are centralized mainframe computers. The paradigm moved to decentralized as networked stations became more dependable, extensible and cost-effective. The decentralized systems have their limitations and inconveniences. The virtualization and cloud computing paradigm creates a centralized system that appears to users to be a centralized system, where computing and communication resources are not in the client computers but in an integrated infrastructure that is accessible anywhere and anytime. Nevertheless, the implementation of the centralized infrastructure is equipped with decentralized and redundant resources, which makes the system more dependable as any component failures can be tolerated internally. The Internet of Things extends the cloud computing concept beyond computing and communication to include everything, particularly, the physical devices. This paper discusses the architectures, interfaces, and behaviors of intelligent devices connected to the cloud computing environment. Robot as a Service is the case study, which has all the key features of Internet of Intelligent Things: autonomous, mobile, sensing, and action taking. The goal is to further extend the centralized cloud computing environment into a decentralized system to complete another cycle of the spiral development. The idea of achieving the goal is through autonomous and intelligent mobile physical services or robots as services to form local pool of intelligent devices and that can make local decisions without communicate with the cloud.     

基于区块链的外包服务公平支付方案

随着外包计算服务的快速发展,云计算吸引了越来越多的个人和企业使用外包服务提供商的服务.而雾计算进一步将云计算扩展到网络边缘,在雾计算中,用户由于受计算资源的约束,所以将计算任务外包给雾节点.然而,用户和雾计算节点之间的相互不信任,将会导致公平支付的问题.现有的大多数解决方案采用的是传统的支付机制,需要依赖银行来实现支付.为了实现外包服务的公平支付问题,本文提出了基于区块链的外包服务公平支付方案,通过区块链智能合约支付报酬.同时本文提出的方案可以确保如果雾计算节点完成了计算任务,则用户必须支付报酬给雾计算节点.而如果雾计算节点没有完成计算任务,则用户可以获得赔偿.系统分析表明本方案实现了外包服务的正确性和公平性,并且其消耗在可接受范围内.     

Adaptive security architecture for protecting RESTful web services in enterprise computing environment

In this modern era of enterprise computing, the enterprise application integration (EAI) is a well-known industry-recognized architectural principle that is built based on loosely coupled application architecture, where service-oriented architecture (SOA) is the architectural pattern for the implementation of EAI, whose computational elements are called as “services.” Though SOA can be implemented in a wide range of technologies, the web services implementation of SOA becomes the current selective choice due to its simplicity that works on basic Internet protocols. Web service technology defines several supporting protocols and specifications such as SOAP and WSDL for communication with client and server for data interchange. A new architectural paradigm has emerged in SOA in recent years called REpresentational State Transfer (REST) that is also used to integrate loosely coupled service components, named RESTful web services, by system integration consortiums. This SOA implementation does not possess adequate security solutions within it, and its security is completely dependent on network/transport layer security that is obsolete owing to latest web technologies such as Web 2.0 and its upgraded version, Web 3.0. Vendor security products have major implementation constraints such as they need secured organizational environment and breach to SOA specifications, hence introducing new vulnerabilities. Herein, we examine the security vulnerabilities of RESTful web services in the view of popular OWASP rating methodologies and analyze the gaps in the existing security solutions. We hence propose an adaptive security solution for REST that uses public key infrastructure techniques to enhance the security architecture. The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named “intelligent security engine” is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. This paper is written to present one of such algorithms to prevent SOA attacks on RESTful web services along the discussion on the obtained results of the conducted proof-of-concept on the real-time SOA environment. A comparison of the proposed system with other competing solutions demonstrates its superiority.     

智能社区云服务平台及服务模式研究

为满足人们对家居系统智能化的要求,提出将云服务应用于智能家居系统,以实现智能家居物联网系统和外部云计算平台的对接,从而形成高度智能化的云枉区,最终达到一站式服务于用户的目的。文中结合云计算技术给出了一种云服务平台的构建方法,该方法可提供不同用户的多种云服务模式,达到用最少的资源提供最多的服务这一目标。     

An energy-efficient video transport protocol for personal cloud-based computing

Recently, we are surrounded by a collection of heterogeneous computing devices such as desktop computers, laptops, smart phones, smart televisions, and tablet PCs. Each device is operated with its own host operating system, has its own internal architecture, and performs its independent tasks with its own applications and data. A common property amongst these devices, namely that of internet-connectivity, allows them to configure personal virtual cloud system by interconnecting each other through an intermediate switching device. The personal cloud service should provide a seamlessly unified computing environment across multiple devices with synchronized data and application programs. As such, it allows users to freely switch their workspace from one device to another while continuing the interaction with the available applications. In order to support video applications, the cloud system should provide seamless video synchronization among the multiple devices. However, we note that the current cloud services do not provide efficient data flow among devices. In this paper, we propose and develop a new reliable transport protocol to support video synchronization for the personal virtual cloud system. In order to cope with battery limitation of many mobile devices in personal virtual cloud system, the proposed protocol is designed to provide energy efficient video communications. Our simulation results show that the proposed protocol can reduce end users power consumption up to 25 % compared to the legacy TCP with given packet loss probabilities and the average length of error bursts.     

Towards effective offloading mechanisms in fog computing

Fog computing is considered a formidable next-generation complement to cloud computing. Nowadays, in light of the dramatic rise in the number of IoT devices, several problems have been raised in cloud architectures. By introducing fog computing as a mediate layer between the user devices and the cloud, one can extend cloud computing's processing and storage capability. Offloading can be utilized as a mechanism that transfers computations, data, and energy consumption from the resource-limited user devices to resource-rich fog/cloud layers to achieve an optimal experience in the quality of applications and improve the system performance. This paper provides a systematic and comprehensive study to evaluate fog offloading mechanisms' current and recent works. Each selected paper's pros and cons are explored and analyzed to state and address the present potentialities and issues of offloading mechanisms in a fog environment efficiently. We classify offloading mechanisms in a fog system into four groups, including computation-based, energy-based, storage-based, and hybrid approaches. Furthermore, this paper explores offloading metrics, applied algorithms, and evaluation methods related to the chosen offloading mechanisms in fog systems. Additionally, the open challenges and future trends derived from the reviewed studies are discussed.

     

A reinforcement learning algorithm for rescheduling preempted tasks in fog nodes

Journal of Scheduling - The fog server in a fog computing paradigm extends cloud services to latency-sensitive tasks by employing fog nodes (FNs) near user devices. The resource-constrained FNs...     

基于离散过程跟踪的自动识别处理中间件

为解决通用中间件与应用层缺乏关联的问题,提出一种基于离散过程跟踪的自动识别处理中间件。给出中间件的体系结构,设计数据计算服务算法,采用面向服务架构,提供数据读入接口,以此实现数据过滤、Web计算服务、数据访问适配器、消息事件等功能。实验结果表明,该中间件具有较好的适应性。     

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs.