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Wireless sensor networks (WSNs) are commonly used to monitor changes in an environment and prevent disasters such as structural instability, forest fires, and tsunami. WSNs should rapidly respond to changes, and must process and analyze sensor data in a distributed way to minimize battery consumption. On the other hand, machine learning (ML) algorithms are a powerful tool for data analyzing. However,...
In this paper we study the channel selection problem with dynamic users in distributed opportunistic spectrum access systems. Different with the ordinary assumption that users have data to transmit all the time, we assume that users transmit data randomly in each slot. The dynamical transmitting model makes the active number of users time-varying and channel interference levels dynamic. It makes a...
This article investigates the problem of distributed spectrum resource allocation in the ultra-dense small cell networks, which takes the different loads of small cell base stations (SBSs) into consideration. Here, we simplify the load as the number of active users served by a SBS. We formulate the problem of load-aware channel selection as a graphical game and propose a distributed learning algorithm...
The population migration algorithm is a very effective evolutionary algorithm to solve optimization problem, but there are little application in solving the multi-objective optimization problem. On the basis of vector evaluated method and Dynamic Weighted Aggregation combined those advantage, this paper presents a population migration algorithm based on vector evaluated method and Dynamic Weighted...
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