Service discovery in the Internet of Things: review of current trends and research challenges

Recent technologies have made the life of people more comfortable and more straightforward than it was before. With the development of information technology, the Internet of Things (IoT) as an emerging technology has been entered into a lane of development. With the advent of IoT, data sharing, and connections among systems, devices, and people have been facilitated, and daily devices have been equipped with sensors and applications to provide their functionality through services. As a matter of fact, IoT provides a platform where everyday objects become smarter than before, everyday communication becomes informative, and everyday processes become intelligent. In this regard, to provide novel IoT services, numerous heterogeneous frameworks and protocols have been proposed. Since the number of IoT devices or objects is growing day by day, and the number of services is also increasing, discovering and locating appropriate services becomes a vital challenge, and the traditional service discovery strategies are not efficient enough to handle this issue. Service discovery refers to the process of finding suitable services according to clients' requests. Although the service discovery problem has essential impacts on the IoT, there is not any detailed and systematic study of the existing methods in this field. Therefore, this paper aims to find, categorize, and investigate all the effective and valid papers in the field of service discovery in the IoT using a systematic method. The selected papers are discussed based on various service discovery metrics and other criteria such as adopted architecture, search method, service description, discovery scope, adopted simulation tools, and datasets. The advantages and weaknesses of each reviewed paper are specified. Moreover, an abreast comparison of the selected papers is presented, in which the aforementioned methods are evaluated considering the mentioned metrics and criteria. Finally, future research directions and challenging problems are outlined to help researchers improve their innovations.