CAJ | 학술논문

基于XMPP协议的网络是由大量部署在网络中的客户端，服务器和网关三种实体节点共同组成。高负载条件下，节点规模的不确定性、节点运算性能的可变性、最长路由跳数的不确定性，导致在现有的算法和有限时间下，无法预知源节点发出的数据包是否能够到达目标节点。本文利用遗传算法对高负载下XMPP网络的路径进行优化推导求解，得出本算法的应用可行性，从而为提高路径运行效率提供参考。
기우XMPP협의적망락시유대량부서재망락중적객호단，복무기화망관삼충실체절점공동조성。고부재조건하，절점규모적불학정성、절점운산성능적가변성、최장로유도수적불학정성，도치재현유적산법화유한시간하，무법예지원절점발출적수거포시부능구도체목표절점。본문이용유전산법대고부재하XMPP망락적로경진행우화추도구해，득출본산법적응용가행성，종이위제고로경운행효솔제공삼고。
The network based on the XMPP protocol is composed of huge number of client, server and gateway entity nodes, which are widely deployed. Under high load conditions, because of variability of the node counts, the node computing performance and the hops, we can’t predict whether or not the data packets from source node can be sent to end node in finite time, if we depend on the off-the-shelf path algorithms. In this paper, we just study the optimization path problems based on genetic algorithm, and supply the result for high-load XMPP network routing. The conclusion for practice proves the optimization path can improve the routing efficiency.