With the advent of the Internet of Things (IoT), the count of gadgets connected to the Internet has been increased. IoT, as a modern paradigm, has been used to describe the future in which physical things like RFID tags, sensors, actuators, and cellphones can intermingle for achieving shared purposes. Also, we can employ cloud computing for storing the things' information in the IoT. However, this information has been replicated through the network for increasing availability. In this paper, due to the NP‐hard nature of the replica selection problem, an improved version of ant colony optimization (IACO) has been applied. The impact of pheromone on the chosen path is converted by ants to invert the underlying logic of ACO. Due to the existence of different IoT centers, the IACO has been employed for selecting the replicated data in the IoT where the load balancing among IoT centers has been considered. In this method, an ant chooses the ideal point for its movement; then others may not pass the track that the preceding ants have been passed. The obtained outcomes have shown that the method has outperformed the ACO, HQFR, and RTRM approaches regarding the waiting time and load balancing.

中文翻译：

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物联网中基于元启发式的副本选择方法

随着物联网（IoT）的出现，连接到Internet的小工具数量有所增加。物联网作为一种现代范例，已被用来描述未来的现实，其中诸如RFID标签，传感器，致动器和手机之类的物理事物可以相互融合以实现共同的目的。此外，我们可以采用云计算将物联网信息存储在物联网中。但是，此信息已通过网络复制，以提高可用性。在本文中，由于副本选择问题的NP难点性质，已应用了改进版本的蚁群优化（IACO）。信息素对所选路径的影响被蚂蚁转换，从而反转了ACO的基本逻辑。由于存在不同的物联网中心，IACO已被用于在IoT中选择复制数据，考虑了IoT中心之间的负载平衡。在这种方法中，蚂蚁为其运动选择了理想点；那么其他人可能无法通过前面的蚂蚁已被传递的轨道。获得的结果表明，在等待时间和负载平衡方面，该方法优于ACO，HQFR和RTRM方法。