The Internet of Things (IoT) aims to connect everyday physical objects to the internet. These objects will produce asignificant amount of data. The traditional cloud computing architecture aims to process data in the cloud. As a result, a significantamount of data needs to be communicated to the cloud. This creates a number of challenges, such as high communication latencybetween the devices and the cloud, increased energy consumption of devices during frequent data upload to the cloud, high bandwidthconsumption, while making the network busy by sending the data continuously, and less privacy because of less control on thetransmitted data to the server. Fog computing has been proposed to counter these weaknesses. Fog computing aims to process dataat the edge and substantially eliminate the necessity of sending data to the cloud. However, combining the Service OrientedArchitecture (SOA) with the fog computing architecture is still an open challenge. In this paper, we propose to decompose services tocreate linked-microservices (LMS). Linked-microservices are services that run on multiple nodes but closely linked to theirlinked-partners. Linked-microservices allow distributing the computation across different computing nodes in the IoT architecture.Using four different types of architectures namely cloud, fog, hybrid and fog+cloud, we explore and demonstrate the effectiveness ofservice decomposition by applying four experiments to three different type of datasets. Evaluation of the four architectures shows thatdecomposing services into nodes reduce the data consumption over the network by 10% - 70%. Overall, these results indicate that theimportance of decomposing services in the context of fog computing for enhancing the quality of service.
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