This study presents the proposed testbed implementation for the Advanced Technology Training Center (ADTEC) Batu Pahat, one of Malaysia’s industrial training institutes. The objectives of this study are to discover the issues regarding network congestion, propose a suitable method to overcome such issues, and generate output data for the comparison of the results before and after the proposed implementation. The internet is directly connected to internet service providers (ISPs), which neither impose any rule nor filter the traffic components; all connections comply on the basis of the base effort services provided by the ISP. The congestion problem has been raised several times and the information technology (IT) department has been receiving complaints about poor and sometimes intermittent internet connection. Such issues provide some ideas for a possible solution because the end client is a human resource core business. In addition, budget constraints contribute to this problem. After a comprehensive review of related literature and discussion with experts, the implementation of quality of service through add-on rules, such as traffic policing on network traffic, was proposed. The proposed testbed also classified the traffic. Results show that the proposed testbed is stable. After the implementation of the generated solution, the IT department no longer receives any complaints, and thus fulfills the goal of having zero internet connection issues.
In-network caching has evolved into a new paradigm, paving the way for the creation of Named Data Networking (NDN). Rather than simply being typical Internet technology, NDN serves a range of functions, with a focus on consumer-driven network architecture. The NDN design has been proposed as a method for replacing Internet Protocol (IP) addresses with identified content. This study adds to current research on NDN, artificial intelligence (AI), cloud computing, and the Internet of Things (IoT). The core contribution of this paper is the merging of cloud IoT (C-IoT) and NDN-AI-IoT. To be precise, this study provides possible methodological and parameter explanations of the technologies via three methods: KITE, a producer mobility support scheme (PMSS), and hybrid network mobility (hybrid NeMO). KITE uses the indirection method to transmit content using simple NDN communication; the PMSS improves producer operation by reducing handover latency; and hybrid NeMO provides a binding information table to replace the base function of forwarding information. This study also describes mathematical equations for signaling cost and handover latency. Using the network simulator ndnSIM NS-3, this study highlights producer mobility operation. Mathematical equations for each methodology are developed based on the mobility scenario to measure handover latency and signaling cost. The results show that the efficiency of signaling cost for hybrid NeMO is approximately 4% better than that of KITE and the PMSS, while the handover latency for hybrid NeMO is 46% lower than that of KITE and approximately 60% lower than that of the PMSS.
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