Network Resource Allocation And Its Application In Heterogeneous Networks

Wireless network technology is rapidly evolving and infiltrating into all aspects of human social activities.Its development has changed the way we live our,and it is an important thrust for the development of social economy and the level of informatization.With the rapid development of wireless communication technology and wireless services,user traffic demand,user service and user terminals have proliferated,but spectrum resources are scarce and utilization is low,which has become a major bottleneck restricting the development of wireless networks.Even if the next generation network increases the available spectrum resources,the spectrum resources are still very valuable.At the same time,a single communication network can no longer meet the needs of differentiated users business.The future wireless communication network must be the coexistence,integration and complementary advantages of multiple networks,which is also the development trend of the next generation wireless communication network.Therefore,how to improve the utilization of spectrum resources to alleviate the contradiction between the surge in user traffic demand and the shortage of low-utilization spectrum resources?How to integrate multiple heterogeneous wireless networks,dynamically select access networks and allocate resources between users reasonably and efficiently,and optimize network performance and servic9 quality on the basis of ensuring multiple service requirements of users,which is an important problem that wireless networks need to solve.Based on the analysis of heterogeneous network overlap coverage complex scenarios,current processing challenges and existing research results,this paper conducts in-depth research on wireless resource allocation technology in wireless heterogeneous network and heterogeneous sensor network deployment optimization technology.A series of idle spectrum resource allocation strategies for cognitive heterogeneous wireless networks,network association and spectrum resource allocation for heterogeneous network overlap coverage scenarios,and composite event collaborative detection methods in heterogeneous sensor networks are proposed and designed.The main work and achievements of this paper are as follows:(1)Aiming at the problem that it is difficult to allocate spectrum resources to secondary users efficiently in cognitive heterogeneous wireless networks with heterogeneous spectrum attributes,dynamic channel conditions and diverse service requirements,a spectrum resource allocation strategy with maximum transmission rate was proposed.Firstly,the strategy aimed at maximizing the total transmission rate,and constrained the limited spectrum resources and user service requirements to construct a non-linear multi-constrained spectrum resource allocation 0-1 planning model.Then a polynomial time complexity simplification method was designed.According to idle spectrum information,channel conditions,business requirements and allocation decision history information,the benefit matrix was constructed and modified to achieve constraint simplification,and the execution efficiency was improved by improving the coefficient matrix transformation strategy of the traditional Hungarian algorithm.Finally,the performance of the method was compared and analyzed by experiments.Experimental results show that the proposed method has higher transmission rate and execution efficiency(2)Aiming at the problem of multi-objective optimization of resource allocation in cognitive heterogeneous networks,in the context of comprehensive consideration of user service requirements and differences in spectrum resource attributes.Aiming at maximizing the total transmission rate of the secondary users and minimizing the total cost,a dual objective optimization mathematical model of idle spectrum allocation is established.By simplifying the mathematical model,the bi-objective optimization problem is transformed into single-objective optimization and the constraints are simplified,and the improved Hungarian algorithm is used to solve the problem.Secondly,a multi-objective intelligent optimization method based on improved non-dominated sorting genetic algorithm is designed to solve The experimental results show that the simplified method has higher efficiency,and the INSGA-?(improved Non-dominated Sorting Genetic Algorithm ?)algorithm can obtain higher transmission rate,especially the transmission rate priority strategy.(3)Aiming at the problem that multi-heterogeneous network overlap coverage and multi-user multi-service coexistence environment,users maximizing the transmission rate may cause the network load to be unbalanced,a service access control method based on non-dominated sorting genetic algorithm is proposed.The strategy firstly takes the maximum transmission rate and the load balance of the system as the objective function,and the bandwidth resource limitation as the constraint condition,and constructs the two-objective optimization model with maximum transmission rate and most balanced network load.Then the service access control problem is solved based on the multi-objective optimization Non-dominated Sorting Genetic Algorithm ?(NSGA-?).The simulation results show that the proposed algorithm takes into account the user's transmission rate requirements and load balancing between networks,and achieves better results.(4)The joint detection of composite events in heterogeneous sensor networks is a research hotspot in sensor networks.How to use as few sensor nodes as possible to detect composite event in large area is a difficult problem because multiple heterogeneous sensor nodes are required for detecting the composite event which consists of several atomic events,and the detection accuracy would be worse if there are no enough sensor nodes.Most of the traditional methods are focusing on atomic event detection which only needs one type of homogeneous node.Considering costs,weights,and sensing capability of different types of heterogeneous sensor nodes,a deployment cost minimization problem for composite event is put forward,and its corresponding mathematical model is given in this article,with the purpose of minimizing deployment costs subject to the constraint of achieving a required coverage quality.Different from traditional methods,according to the temporal and spatial association of heterogeneous nodes,two novel models for atomic event and composite event are proposed,respectively,and the coverage quality which is very important to the detection accuracy is analyzed based on these two models.Then,based on the composite event model and the coverage quality model,an exact algorithm and a greedy strategy approximation algorithm are proposed to solve the optimization problem.Also,the time complexity and approximability of these two algorithms are analyzed.The experimental results show that the proposed approximation algorithm has lower deployment cost and higher execution efficiency under the same coverage quality.Finally,the paper is summarized and the next research work is forecasted.