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An efficient algorithm for partially matched services in internet of services

机译:服务互联网中部分匹配服务的高效算法

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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.
机译:物联网(IoT)以类似互联网的结构连接数十亿个设备。每个设备都封装为一个现实世界的服务,该服务提供功能并与其他设备交换信息。这种大规模的信息交换导致了物与人之间的新交互。与传统的Web服务不同,服务互联网是高度动态的,并且由于设备的不断降级,消失和可能重新出现而不断变化,这在资源发现和选择过程中提出了新的挑战。响应于发现和选择过程中服务数量的增加,服务使用者的数量相应增加,并且随之而来的是可用的服务质量(QoS)多样性。双方的增加导致服务需求和供应的多样性,这将导致需求和报价的部分匹配。通过考虑多个QoS要求并允许将部分匹配的服务视为选择过程的候选者,提出了IoT服务排名和选择算法。物联网感官数据的应用之一吸引了许多研究者,其中交通是紧急情况服务,尤其是紧急事件服务。实际服务的实验结果表明,该方法在选择过程中的准确性和性能上有了显着提高。

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