## 1 Introduction
The current host-oriented network architecture is not suitable for the emerging low latency applications (e.g., augmented reality (AR) and virtual reality (VR) applications, autonomous driving, V2X security, and real-time gaming), although EC is deployed at the edge of the network because it works on downstream data for cloud services and upstream data for IoT services. Therefore, downstream services may not ensure low latency services. ICN has the caching capabilities at each device in the network where we can also use the computing resources based on the collaboration between the service providers and the end-users. In addition, ICN has other various characteristics that help the end-users to get their expected services. We will describe the benefits of combined EC and ICN mechanism in detail in Section 2. The new characteristics of ICN accelerates it to become popular but there are some issues to be resolved, e.g., interest flooding, inefficient caching, naming, and so on. Basically, the objectives of ICN and EC are different, but there are some common functionalities (e.g., content caching). Therefore, the coexistence of them increases the network efficiencies in some scenarios (e.g., content delivery, content caching, preprocessing of the contents). Before discussing the integration of the EC and ICN concept, we first describe possible solutions to the existing ICN drawbacks and then we propose a combined platform based on EC and ICN. The caching mechanisms used in the existing ICN and the EC mechanism could not handle the duplicate content caching in the nearby devices, and their content popularity mechanism works in individual devices. Our proposed unique caching mechanism collaborates with neighboring devices to handle the duplicate content in the nearby devices and maintain a global content popularity mechanism. Therefore, the popular content is cached to the ICN-enabled devices based on their global content popularity. They did not address the problem of content request packets flooding in their proposedICN and EC mechanism. We addressed this problem and provided the solution based on the clustering mechanism. In addition, the combination of ICN and EC increases the network computing and cache resources, and those help to increase the network efficiencies. In summary the following characteristics are the uniqueness of our proposed ICN and EC mechanism. 1. Reduction of the content access time based on the proposed efficient and unique caching mechanism. 2. The flooding of the content request messages is handled by the clustering mechanism and the network congestion is reduced in a certain dense network area. 3. Increase of the probability of content availability from the nearby content providers based on our unique caching mechanism. 4. Increase the bandwidth efficiency by preprocessing of the contents before uploading to the content servers or clouds and control of the flooding of content request messages. The rest of the paper is organized as follows. Section 2 explains the motivation and background analysis of the integration of the EC and ICN concepts. Section 3 provides related studies on EC, ICN, combined EC and ICN strategies and mechanisms. Section 4 proposes an architecture for IoT and multimedia data handling based on clustering in ICN. Section 5 presents performance analysis. Finally, Section 6 concludes the paper with a summary.