Name
Abstract | ||
|---|---|---|
With the realization of the Internet of Things from theory to practical application, the work of ensuring high reliability of the system has become the key to system design, and it is also the obstacle to further promotion of the Internet of Things. This paper makes an in-depth study on the Internet of Things transmission and network reliability in complex environments. In this paper, we use the artificial bee colony algorithm to get the shortest path analysis of each cluster head node. The simulation results show that the algorithm proposed in this paper can effectively reduce the amount of data transmitted to sink by the sensor nodes through cluster head node fusion, improve the efficiency of data collection, energy consumption balance and network reliability, and extend the network life cycle. In addition, the index model of Internet of things reliability index system is established, and the comprehensive evaluation method of using the index is explained. The simulation results show that the proposed algorithm reduces the amount of data transmission and network energy consumption, prolongs the network life cycle, improves the efficiency of data fusion and data transmission reliability. Aodv-sms (abc-pso) routing recovery protocol shows that compared with other routing recovery strategies, packet transmission delay time is less, and the gap between them is more and more large; aiming at the end-to-end reliability and the network capacity, the paper focuses on the analysis of the impact of the change of communication link on the network capacity under the mobile node. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.comcom.2019.11.054 | Computer Communications |
Keywords | Field | DocType |
Internet of Things transmission,Network reliability,Data transmission,Transmission path,Index system | Artificial bee colony algorithm,Data collection,Data transmission,Shortest path problem,Computer science,Computer network,Systems design,Sensor fusion,Reliability (computer networking),Energy consumption | Journal |
Volume | ISSN | Citations |
150 | 0140-3664 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |