面向5G演进的多目标模糊优化网络切片算法

Multi-objective Fuzzy Optimization Network Slice Algorithm for 5G Evolution

针对复杂网络环境网络切片化改造不完全不充分条件下的多因素多目标资源分配难题,提出一种基于多目标模糊优化算法,以实现网络切片适应网络演进过程,并提供高度的健壮性.首先,多个节点测量并共享网络参数指标,依据指标形成约束条件,建立资源分配目标函数,生成计算模型;其次,通过加权型模糊最优判决函数求出最优解;最终,面向同一应用的不同客户分别建立网络切片,依据最优解分配每个切片的资源占用,实现精确到用户的网络切片通信保障系统.模拟实验表明,该算法以及相关优化手段有效降低了网络切片的资源占用,提升了网络各项参数指标.

Aiming at the problem of multi-objective and multi-factor resource allocation under the condition of incomplete and insufficient network slicereconstructionproject in complex network environment,the paper proposes an algorithm based on multi-objective fuzzy optimization to adjust network slice adapting the network evolution and providing a high degree of robustness.Firstly,measuring network indicators and sharing among distributed nodes,algorithm forms constraints according to the indicators,and generates computing models according to the resource allocation objective function.Secondly,the optimal solution is obtained through the weighted fuzzy optimal decision function.Finally,network slices are established for different customers of the application,and the resource occupation of each slice is allocated according to the optimal solution,so as to realize a network slice communication guarantee system that is accurate to the user and their various network conditions.Simulation experiments show that this algorithm and related optimization methods effectively reduce the resource occupation of network slice and improve the performance of the network.