Biblio

In the information age, computer network technology has covered different areas of social life and involved various fields, and artificial intelligence, as an emerging technology with a very rapid development momentum in recent years, is important in promoting the development of computer network systems. This article explains the concept of artificial intelligence technology, describes the problems faced by computer networks, further analyses the advantages of artificial intelligence and the inevitability of application in network technology, and then studies the application of artificial intelligence in computer network technology.

The subsystem of IoMT (Internet of Military of Things) called IoBT (Internet of Battle of Things) is the major resource of the military where the various stack holders of the battlefield and different categories of equipment are tightly integrated through the internet. The proposed architecture mentioned in this paper will be helpful to design IoBT effectively for warfare using irresistible technologies like information technology, embedded technology, and network technology. The role of Machine intelligence is essential in IoBT to create smart things and provide accurate solutions without human intervention. Non-Destructive Testing (NDT) is used in Industries to examine and analyze the invisible defects of equipment. Generally, the ultrasonic waves are used to examine and analyze the internal defects of materials. Hence the proposed architecture of IoBT is enhanced by ultrasonic based NDT to study the properties of the things of the battlefield without causing any damage.

With the gradual progress of cloud computing, big data, network virtualization and other network technology. The traditional network architecture can no longer support this huge business. At this time, the clean slate team defined a new network architecture, SDN (Software Defined Network). It has brought about tremendous changes in the development of today's networks. The controller sends the flow table down to the switch, and the data flow is forwarded through matching flow table items. However, the current flow table resources of the SDN switch are very limited. Therefore, this paper studies the technology of the latest SDN Flow table optimization at home and abroad, proposes an efficient optimization scheme of Flow table item on the betweenness centrality through the main road selection algorithm, and realizes related applications by setting up experimental topology. Experiments show that this scheme can greatly reduce the number of flow table items of switches, especially the more hosts there are in the topology, the more obvious the experimental effect is. And the experiment proves that the optimization success rate is over 80%.

The Internet of Things leads to the inter-connectivity of a wide range of devices. This heterogeneity of hardware and software poses significant challenges to security. Constrained IoT devices often do not have enough resources to carry the overhead of an intrusion protection system or complex security protocols. A typical initial step in network security is a network scan in order to find vulnerable nodes. In the context of IoT, the initiator of the scan can be particularly interested in finding constrained devices, assuming that they are easier targets. In IoT networks hosting devices of various types, performing a scan with a high discovery rate can be a challenging task, since low-power networks such as IEEE 802.15.4 are easily overloaded. In this paper, we propose an approach to increase the efficiency of network scans by combining them with active network measurements. The measurements allow the scanner to differentiate IoT nodes by the used network technology. We show that the knowledge gained from this differentiation can be used to control the scan strategy in order to reduce probe losses.