Research On Ad Hoc Multicast Energy Optimization Based On Ant Colony Algorithm

In order to guarantee the Quality of Service(Qo S)of mobile Ad Hoc networks,choosing the appropriate Qo S routing algorithm is one of the important issues to be studied.However,the research shows that the Qo S multicast routing problem under multi-constrained conditions is an Non-deterministic Polynomial Complete Problem(NPC),which is difficult to solve by traditional algorithms.Therefore,the Qo S multicast routing problem solved by heuristic algorithm has become a new research direction.The ant colony algorithm is suitable for Qo S multicast routing algorithms due to its distributed computing,simple implementation of a single agent,and support for multipath.At present,the research on Qo S multicast routing in mobile Ad Hoc networks mainly focuses on delay suppression minimum cost multicast routing problem,bandwidth suppression minimum cost multicast routing problem and minimum cost multicast routing problem of delay jitter suppression.There are fewer considerations for energy consumption,multicast lifetime,and network lifetime.The energy of mobile Ad Hoc networks is very limited.If reasonable control of energy consumption is not considered,it is likely to affect the overall performance of the network.In this paper,the focus of research is on the optimization of multicast routing energy in mobile Ad Hoc networks.The following are the main research contents and innovations of this paper:(1)This paper first studies the conceptual characteristics and network structure of mobile Ad Hoc networks,analyzes the current problems faced by Qo S multicast routing,compares the existing Qo S multicast routing algorithms,and studies the energy optimization ideas of mobile Ad Hoc networks in detail.(2)Then the paper studies the principle of basic ant colony algorithm and its classic improvement scheme.In order to study the improvement of ant colony algorithm based on multi-constraint problem,this paper introduces urban congestion value as one of the constraint parameters in the Traveling Salesman Problem,and based on This multiconstrained TSP problem proposes an improved scheme for the ant colony algorithm.Instead of using the equivalent initial pheromone concentration,the scheme uses the normalized value of the congestion value parameter as the initial pheromone concentration,which can reduce the blindness of the ant colony algorithm in the initial search,so that the ants tend to choose a path with a small congestion value.Simulations show that the algorithm can search for the least cost path with less congestion value at a higher speed.(3)Finally,referring to the energy optimization idea of multicast routing,this paper improves the Qo S multicast routing algorithm based on ant colony algorithm.The improvement scheme is based on the idea of the improved ant colony algorithm described in(2).The link energy level is introduced as one of the Qo S constraints in the Qo S multicast routing algorithm,and is used as a factor affecting the ant pheromone update..This can guide the algorithm to select nodes with sufficient energy in the path construction process,thereby achieving the purpose of promoting the balanced use of the network energy.The simulation shows that the scheme can optimize the energy of the multicast network under the premise of ensuring the cost and delay of the multicast routing algorithm.