With the continuous improvement of material life and spiritual life, people continue to innovate in business and put forward various demands for network. Network slice can be used to construct virtual logical network according to the needs of different application scenarios, such as network rate, delay and reliability, etc., according to the needs of business for network function and security, etc., which is one of the key technologies of 5G. Aiming at the QoS demand of network slice diversification, a resource allocation method of network slice based on discrete binary particle swarm optimization algorithm is proposed. This paper proposes an adaptive dynamic resource adjustment strategy based on bat algorithm. Faced with huge resource allocation and its characteristics of dynamic, it is no longer enough to balance the advantages and disadvantages of resource allocation strategy from a single aspect. Aiming at these problems, from two aspects of the user and resource provider, introduces the bat algorithm in resource allocation strategy, set up the minimum resource utilization and resources adjustment cost as the double constraints of resources adjustment quantity decision model, the simulation results show that the bat algorithm can effectively solve the network section of dynamic allocation of resources to improve the utilization ratio of resources.
As one of the development directions of the mobile Internet, the Internet of Vehicles is how to quickly and efficiently communicate between vehicles (V2V). Wireless communication is facing unprecedented challenges and opportunities. In CCN, network caching enables content to be cached on network nodes, reducing the delay for users to obtain content, and increasing the circulation of network content. This article proposes a CCN dwell time collaborative caching strategy based on V2V scenarios. It considers the mobility, relevance of vehicles in a connected vehicle, and the dwell time of content on network nodes under the request of Poisson arrival Collaborative caching. Through simulation, the cache hit rate, average delay, average hop count of the entire network is compared with the traditional CCN cache strategy, which effectively improves the network cache efficiency and network gain.
At present, many branches of computer science research have emerged, among which artificial intelligence is a very popular topic in the entire computer science field. With the development of science and technology in recent years, computer artificial intelligence recognition technology has gradually been applied to people's daily life. In order to deepen the public's understanding of intelligent recognition, this article studies its development process and application. First introduced the concept of artificial intelligence and its 5 development stages, and then gave an overview of computer artificial intelligence recognition technology. We explained its concept, development status and key technologies, and then analyzed its applications, including its five application types and current problems in voice recognition and visual recognition applications. In the context of today's information technology, only the shortcomings are overcome can make artificial intelligence technology mature.
