CAJ | 학술논문

在半汇聚数据收集网络中,越靠近Sink的节点数据转发量越大越容易过早死亡而造成网络分割。如何均衡能耗和数据延迟达到较优的数据收集是NP完全问题。基此将问题公式化为构造一棵路径树问题,并设计了一个近似最优的算法MMLAT。 MMLAT算法可以在多项式时间内完成。实验结果表明,MMLAT与现有的算法相比,能够较好的均衡网络生命周期和数据延迟。
재반회취수거수집망락중,월고근Sink적절점수거전발량월대월용역과조사망이조성망락분할。여하균형능모화수거연지체도교우적수거수집시NP완전문제。기차장문제공식화위구조일과로경수문제,병설계료일개근사최우적산법MMLAT。 MMLAT산법가이재다항식시간내완성。실험결과표명,MMLAT여현유적산법상비,능구교호적균형망락생명주기화수거연지。
One of the most basic functions in wireless sensor networks is data collection. The Sink collects data from each sensor node through one hop or multi-hop mode. In semi-convergent data collection network, the nodes closer to the Sink need to relay more data, so they are easier to die soon, which makes the network disconnected. Therefore, how to balance the energy consumption and data latency in the network is a NP-complete problem, which is the focus of the paper. The problem is formalized to construct a data semi-aggregation tree that minimizes the total energy cost and time of data transmission. An approximate optimal algorithm named MMLAT that solves the problem in polynomial time is proposed. Simulation results show that MMLAT algorithm can achieve shorter time delay and longer network lifetime than existing algorithms.