Research On Load Balancing For Topology Evolution Of Multi-sink Internet Of Things

The 5G communication technology provides strong support for the connect and real-time control of massive devices in Internet of Things(Io T)due to the lower latency.Io T has been applied to various production processes to improve economic benefits.However,the unbalanced communication load causes some nodes to quickly consume a lot of energy,which severely restricts the further improvement of network performance.Therefore,how to construct a load-balanced Io T heterogeneous topology has become a critical issue.The multi-sink network has been proven to effectively avoid the energy hole problem.The deployment of multiple sink nodes can effectively relieve the data pressure on some nodes close to the single sink nodes.Therefore,this paper studies an effective scheme for constructing a load-balanced topology based on a multi-sink network.According to different application requirements,three-dimensional topology evolution strategy(3D-TES)for mine production environment and multi-objective joint optimization strategy(TEML)for 5G ultra-dense network topology are respectively proposed.In 3D-TES,Gaussian curve is used to build a mine terrain model,and slope and aspect are introduced to quantify the impact of mine terrain on nodes.Based on the ant colony algorithm,a long link is constructed between the super node and the sink node to reduce the average number of hops.Through the reduction of the k-median,it can prove that the evolution of the multi-sink network topology is an NP-hard problem.In TEML,this paper introduces information entropy to measure load balancing on multiple sink nodes.And the energy efficiency,robustness and load balancing of the network are optimized jointly based on NSGA-II algorithm.The layered-cooperation mechanism is designed to strengthen the gene exchange,and avoid evolution falling into premature convergence.In this paper,load balancing optimization is carried out for multi-sink Io T topology under the mine terrain and ultra-dense network.The results show that 3D-TES can effectively reduce the hop number of data forwarding,and extend the life cycle of the network.In addition,by refining the energy consumption on nodes and using a fine-grained attack strategy,TEML significantly improves the quality of the network compared to other algorithms.