物联网服务发现初探:传统SOA的可行性和局限性

基于SOA(service-oriented architecture)的物联网(Internet of things,IoT)把设备的功能服务化,以一种统一和通用的接口向外界提供服务。由于物联网中设备的海量性、移动性和资源高度受限性,以及无线网络自身的不可靠性,设备服务与传统的Web服务相比具有不同的特点,现有的Web服务发现方法不能有效地满足物联网中服务发现的需求。从Web服务发现体系结构和匹配策略两个方面对典型的Web服务发现方法进行了分析;结合物联网中服务提供的特点,从可扩展性、资源有限性、异构性和环境的动态变化性四个方面,分析了将Web服务发现方法应用于物联网服务提供中所面临的问题,并讨论了可能的解决思路;探讨了物联网中服务发现需要解决的问题。     

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。     

情景感知的物联网服务推荐方法研究

如何根据用户实时的情景高效地为其推荐最为合适的物联网服务,已经成为当前服务计算与物联网领域亟需解决的关键问题之一。针对这一问题,提出了一种基于情景感知的物联网服务推荐方法。首先基于改进的FolkRank算法生成当前用户可用的物联网服务列表;之后,依据用户当前关键的情景构建用户情景信息模型,根据用户的情景模型从服务列表中筛选出最能满足用户当前情景的物联网服务。实验结果表明,所提出的情景感知的物联网服务推荐方法是可行的与有效的。     

A fast and scalable approach for IoT service selection based on a physical service model

Information Systems (ISs) have become one of the crucial tools for various organizations in managing and coordinating business processes. Now we are entering the era of the Internet of Things (IoT). IoT is a paradigm in which real-world physical things can be connected to the Internet and provide services through the computing devices attached. The IoT infrastructure is starting to be integrated with ISs thereby diminishing the boundaries between the physical world and the business IT systems. With the development of IoT technologies, the number of connected things and their available physical services are increasing rapidly. Thus, selecting an appropriate service that satisfies a user’s requirements from such services becomes a time-consuming challenge. To address this issue, we propose a Physical Service Model (PSM) as a common conceptual model to describe heterogeneous IoT physical services. PSM contains three core concepts (device, resource, and service) and specifies their relationships. Based on the proposed PSM, we define three types of Quality of Service (QoS) attributes and rate candidate services according to user requirements. To dynamically rate QoS values and select an appropriate physical service, we propose a Physical Service Selection (PSS) method that takes a user preference and an absolute dominance relationship among physical services into account. Finally, experiments are conducted to evaluate the performance of the proposed method.     

基于环境建模的物联网系统TAP规则生成方法

用户需求是物联网智能服务的根本驱动力,如IFTTT等很多物联网框架允许用户使用简单的触发-命令编程(TAP)规则进行编程,但它们描述的是设备调度程序,并不是用户服务需求.一些物联网系统提出采用面向目标的需求方法,支持服务目标的分解,但很难保证物联网不同服务间的一致性和服务部署的完整性.为了支持正确的“用户编程”并保证用...     

Topic-centric and semantic-aware retrieval system for internet of things

The Internet of things (IoT) has been considered as one of the promising paradigms that can allow people and objects to seamlessly interact. So far, numerous applications and services have been proposed, such as retrieval service. The retrieval, however, faces a big challenge in IoT because the data belongs to different domains and user interaction with the surrounding environment is constrained. This paper proposes Acrost, a retrieval system based on topic discovery and semantic awareness in IoT environment. The initial contents with interesting information is obtained through the combination of two topic centric collectors. The metadata is extracted by aggregating regular expression-based and conditional random fields-based approaches. Moreover, the semantic-aware retrieval is achieved by parsing the query and ranking the relevance of contents. In addition, we present a case study on academic conference retrieval to validate the proposed approaches. Experimental results show that the proposed system can significantly improve the response time and efficiency of topic self-adaptive retrieval manner.     

An efficient algorithm for partially matched services in internet of services

Internet of Things (IoT) connects billions of devices in an Internet-like structure. Each device encapsulated as a real-world service which provides functionality and exchanges information with other devices. This large-scale information exchange results in new interactions between things and people. Unlike traditional web services, internet of services is highly dynamic and continuously changing due to constant degrade, vanish and possibly reappear of the devices, this opens a new challenge in the process of resource discovery and selection. In response to increasing numbers of services in the discovery and selection process, there is a corresponding increase in number of service consumers and consequent diversity of quality of service (QoS) available. Increase in both sides’ leads to the diversity in the demand and supply of services, which would result in the partial match of the requirements and offers. This paper proposed an IoT service ranking and selection algorithm by considering multiple QoS requirements and allowing partially matched services to be counted as a candidate for the selection process. One of the applications of IoT sensory data that attracts many researchers is transportation especially emergency and accident services which is used as a case study in this paper. Experimental results from real-world services showed that the proposed method achieved significant improvement in the accuracy and performance in the selection process.     

基于BTM的物联网服务发现方法

针对物联网（IoT）服务描述文本篇幅较短、特征稀疏,直接采用传统的主题模型对IoT服务建模得到的聚类效果不佳,从而导致无法发现最佳服务的问题,提出了一种基于BTM的IoT服务发现方法。该方法首先利用BTM挖掘现有IoT服务的隐含主题,并通过全局主题分布和主题-词分布计算推理得到服务文档-主题概率分布;其次利用K-means算法对服务进行聚类,并返回服务请求的最佳匹配结果。实验结果分析表明,该方法能够有效提高IoT服务的聚类效果,从而得到匹配的最佳服务。与现有的HDP（Hierarchical Dirichlet Process）、基于K-means的隐狄利克雷分配（LDA-K）等方法相比,该方法进行最佳服务发现的准确度（Precision）和归一化折损累积增益（NDCG）均有一定幅度的提高。     

CycloidGrid: A proximity-aware P2P-based resource discovery architecture in volunteer computing systems

Volunteer computing which benefits from idle cycles of volunteer resources over the Internet can integrate the power of hundreds to thousands of resources to achieve high computing power. In such an environment the resources are heterogeneous in terms of CPU speed, RAM, disk capacity, and network bandwidth. So finding a suitable resource to run a particular job becomes difficult. Resource discovery architecture is a key factor for overall performance of peer-to-peer based volunteer computing systems. The main contribution of this paper is to develop a proximity-aware resource discovery architecture for peer-to-peer based volunteer computing systems. The proposed resource discovery algorithm consists of two stages. In the first stage, it selects resources based on the requested quality of service and current load of peers. In the second stage, a resource with higher priority to communication delay is selected among the discovered resources. Communication delay between two peers is computed by a network model based on queuing theory, taking into account the background traffic of the Internet. Simulation results show that the proposed resource discovery algorithm improves the response time of user’s requests by a factor of 4.04 under a moderate load.     

基于意图的物联网服务描述与发现

在物联网服务发现过程中,用户通常用自己的意图表达需求,而服务描述是对服务功能的说明,因此两者的不匹配会影响服务发现的准确率。同时随着服务的种类不断增多,服务发现的准确率不断降低。为了解决上述问题,提出在物联网服务描述中引入意图服务本体的方法,并在意图服务本体中扩展服务上下文和QoS。扩展后的意图服务本体存储在语义化服务描述OWL-S文件中,能够以意图的方式表达服务功能,丰富物联网服务描述的语义,提高服务发现的准确率。仿真结果表明,所提服务描述方法以及相应的服务发现算法相对于传统服务发现方法能提升6.7%的准确率。     

A systematic literature review on web service clustering approaches to enhance service discovery,selection and recommendation

With the advancement of web 2.0 and the development of the Internet of Things (IoT), all tasks can be handled with the help of handheld devices. Web APIs or web services are providing immense power to IoT and are working as a backbone in the successful journey of IoT. Web services can perform any task on a single click event, and these are available over the internet in terms of quantity, quality, and variety. It leads to the requirement of service management in the service repository. The well-managed and structured service repository is still challenging as services are dynamic, and documentation is limited. It is also not a piece of cake to discover, select and recommend services easily from a pool of services. Web service clustering (WSC) plays a vital role in enhancing the service discovery, selection, and recommendation process by analyzing the similarity among services. In this paper, with a systematic process total of 84 research papers are selected, and different state-of-the-art techniques based on web service clustering are investigated and analyzed. Furthermore, this Systematic Literature Review (SLR) also presents the various mandatory and optional steps of WSC, evaluation measures, and datasets. Research challenges and future directions are also identified, which will help the researchers to provide innovative solutions in this area.     

A resource oriented integration architecture for the Internet of Things: A business process perspective

The vision of the Internet of Things (IoT) foresees a future Internet incorporating smart physical objects that offer hosted functionality as IoT services. These services when integrated with the traditional enterprise level services form the creation of ambient intelligence for a wide range of applications. To facilitate seamless access and service life cycle management of large, distributed and heterogeneous IoT resources, service oriented computing and resource oriented approaches have been widely used as promising technologies. However, a reference architecture integrating IoT services into either of these two technologies is still an open research challenge. In this article, we adopt the resource oriented approach to provide an end-to-end integration architecture of front-end IoT devices with the back-end business process applications. The proposed architecture promises a programmer friendly access to IoT services, an event management mechanism to propagate context information of IoT devices, a service replacement facility upon service failure, and a decentralized execution of the IoT aware business processes.     

Deadline-aware multi-objective IoT services placement optimization in fog environment using parallel FFD-genetic algorithm

Nowadays, Internet of things has become as an inevitable aspect of humans’ IT-based life. A huge number of geo-distributed IoT enabled devices such as smart phones, smart cameras, health care systems, vehicles, etc. are connected to the Internet and manage users’ applications. The IoT applications are generally time sensitive, so that giving them up to Cloud and receiving the response may violate their required deadline, due to distance between user device and centralized Cloud data center and consequently increasing network latency. Fog environment, as an intermediate layer between Cloud and IoT devices, brings a smaller scales of Cloud capabilities closer to user location. Processing real time applications in Fog layer helps more deadlines to be met. Although Fog computing enhances quality of service parameters, limited resources and power of Fog nodes is a challenge in processing applications. Furthermore, the network latency is still an issue for communications between applications’ services and between user device and Fog node, which seriously threatens deadline condition. Regarding to mentioned points, this paper proposes a 3-partite deadline-aware applications’ services placement optimization model in Fog environment which optimizes total power consumption, total resources wastage, and total network latency, simultaneously. The proposed model prioritizes applications in 3 levels based on their associated deadline, and then the model is solved using a parallel model of first fit decreasing and genetic algorithm combination. Simulations results indicates the superiority of proposed approach against counterpart algorithms in terms of reducing power consumption, resource wastage, network latency, and service rejection rate.     

一种面向用户的Web服务组装方法

为了将分布在Internet上异构的Web服务组装成新的服务提供给用户,提出一种面向用户的Web服务组装方法,将组装过程分为需求拆分、服务选择、执行服务组装和服务结果合并四个阶段,并提出了基于组装模式的用户需求输入及拆分方法、基于QoS的服务选择模型和基于中间模式的异构消息转换模型。最后通过物流领域服务组装平台的设计与实现,验证了上述方法的可行性与有效性。     

一种面向主题的领域服务聚类方法

随着互联网上服务资源规模的快速增长,如何高效、准确地发现服务成为一个亟待解决的关键问题.服务聚类是促进服务发现的一种重要技术.但是,现有服务聚类方法只对单一类型的服务文档进行聚类,并且没有考虑服务的领域特性.针对该问题,在对服务进行领域分类的基础上,提出了一种基于概率、融合领域特性的服务聚类模型——领域服务聚类模型(domain service clustering model, DSCM),然后基于该模型提出了一种面向主题的服务聚类方法.最后通过ProgrammableWeb网站提供的真实服务集对提出的方法进行了验证.实验结果表明,该方法可以准确地对不同类型的服务文档进行聚类.与经典的潜在狄利克雷分配(latent Dirichlet allocation, LDA),K-means等方法相比,该方法在聚类纯度和F-measure指标上均具有更好的效果,从而为按需服务发现与服务组合提供更好的支持.     

物联网环境下一种基于人工能量势的服务获取方法

针对物联网环境下的服务获取问题,结合物联网节点能量有限、节点自组织、数据空间性等特点,提出了一种 基于人工能量势的物联网空间社区服务获取方法。首先给出了空间社区的概念,然后利用能量迁移方法,使物联网用 户能够通过空间节点在节点的最大有效传输范围内寻找最优节点作为下一跳节点,以减少节点的下一跳数和交互时 间,从而节省节点能耗,提高服务获取的效率。理论分析和仿真实验表明,提出的方法与Random Walk和1VIodificd- r}} s算法相比在减少节点能耗、延长网络生存周期及服务获取效率等方面有一定的改进。     

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.