Analysis of Edge Computing Model for Real-Time Self-Organizing Push of Data in Wireless LAN Environment
Yingying Feng, Shasha Zhao · IEEE Access · 2019
Wireless self-organizing networks have received extensive attention and research because they do not require fixed infrastructure support. Due to the complexity of data transmission in edge computing, the core cloud data center is very far away from the user, resulting in a very large delay in obtaining data from the mobile terminal. In view of this, this paper provides a nearby computing and processing service for user services by deploying multiple mobile edge computing servers on the base station side near the user's mobile core network edge. Firstly, this paper establishes an accurate DCF (Distributed Coordination Function) analysis model under unsaturated conditions. An analytical model for the statistical characteristics of service time is constructed. This model distinguishes the different effects of successfully transmitted packets and discarded packets. Secondly, this paper uses the maximum centrality theory of data aggregation transmission algorithm to determine the degree of influence of nodes by degree centrality theory to generate a fixed unbalanced spanning tree. On the basis of the spanning tree, a relatively large set of parallel nodes can be obtained, thereby reducing the delay time in the entire data transmission process. Finally, this paper studies two resource joint scheduling strategies of mobile terminals and MEC (Mobile Edge Computing) servers in mobile cellular networks based on MEC system. The performance of two collaborative scheduling strategies is verified by simulation. The simulation results show that the collaborative scheduling strategy proposed in this paper can effectively reduce the service cost of the system under the condition of ensuring the user service experience.