Swarm intelligence for next-generation networks: Recent advances and applications

In next-generation networks (NGN), a very large number of devices and applications are emerged, along with the heterogeneity of technologies, architectures, mobile data, etc., and optimizing such a network is of utmost importance. Besides convex optimization and game theory, swarm intelligence (SI) has recently appeared as a promising optimization tool for wireless networks. As a new subdivision of artificial intelligence, SI is inspired by the collective behaviors of societies of biological species. In SI, simple agents with limited capabilities can achieve intelligent strategies for high-dimensional and challenging problems, and thus SI has recently found many applications in NGN. However, SI techniques have still not fully investigated in the literature, especially in the contexts of wireless networks. In this work, our primary focus will be the integration of these two domains, i.e., NGN and SI. Firstly, we provide an overview of SI techniques from fundamental concepts to well-known optimizers. Secondly, we review the applications of SI to settle emerging issues in NGN, including spectrum management and resource allocation, wireless caching and edge computing, network security, and several other miscellaneous issues. Finally, we highlight challenges and issues in the literature, and introduce some interesting directions for future research.