首页> 外文会议>International Conference on Instrumentation, Measurement, Circuits and Systems >A NEW METHOD FOR BUILDING DATA AGGREGATION TREE IN WIRELESS SENSOR NETWORKS USING SIMULATED ANNEALING ALGORITHM
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A NEW METHOD FOR BUILDING DATA AGGREGATION TREE IN WIRELESS SENSOR NETWORKS USING SIMULATED ANNEALING ALGORITHM

机译:一种使用模拟退火算法在无线传感器网络中构建数据聚合树的新方法

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Wireless sensor networks look like mobile ad hoc networks based on many aspects, but protocols which are used for ad hoc networks, are not suitable for wireless sensor networks. In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages' number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In fact, SA is derived from melting process and re-cooling of materials, so it is called Simulated Annealing. SA does not present the best result necessarily, but sake one good answer that can also be optimum. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency.
机译:无线传感器网络根据许多方面看起来像移动临时网络,但用于临时网络的协议,不适用于无线传感器网络。在Ad Hoc网络中,关于协议的设计的主要问题是服务质量,因此在无线传感器网络中,设计协议中的主要约束是传感器的能量有限。事实上,在无线传感器网络中更加苛刻传感器中功耗的协议。减少无线传感器网络中能量消耗的一种方法是减少在网络中传输的包数。收集相关数据的数据和防止网络中的附加包传输的数据可以有效地减少传输的包装的号码。根据该事实,信息处理消耗的功率低于信息发送,数据聚合非常重要,并且由于这一技术在许多协议中使用该技术。其中一个数据聚合技术是使用数据聚合树。但是找到一个最佳的数据聚合树来收集带有一个水槽的网络中的数据是NP难题。在数据聚合技术中,相关信息包在中间节点中组合并形成一个包。因此,在网络中传输的包数减少,因此,较少的能量将消耗最后导致网络寿命的改善。使用启发式方法来解决这些优化方法之一是解决模拟退火问题之一的NP难题。事实上,SA源自熔化过程并重新冷却材料,所以它被称为模拟退火。 SA并不一定呈现最好的结果,但是缘故也是最佳的答案。在本文中,我们将提出新方法,以便通过使用模拟退火算法在无线传感器网络中构建数据收集树,我们将评估其效率。

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