Internet of Things (IoT) enable both traditional electronics and everyday “things” embedded with sensors, computing, and networking capabilities to connect to the Internet as well as to send and receive data. Currently, IoT has been applied in many emerging applications, such as smart city and big data. It is no doubt that the power of typical IoT applications roots on their abilities to collect, understand, and interact with a user’s life in a pervasive and intimate fashion. Furthermore, the future IoT is doomed to be more complicated in terms of capability, adaptability, security, privacy, and usability. On the other hand, obviously, empowering intelligent IoT systems with massive private data can raise serious security and privacy issues. However, the industry has no effective ways to fully secure IoT, and the research for IoT systems is still at the very initial phase. Therefore, the investigation on IoT security and privacy is attracting more and more attentions from both industry and academia. The central theme of this special issue is to investigate novel methodologies and theories for IoT security and privacy. This special issue encourages submissions of high-quality unpublished papers reporting original works in both theoretical and experimental research in the area of recent advances in IoT.
Optimization methods are applied widely to several problems to wireless communications and information processing in general. These, among others, include convex optimization, heuristic methods, evolutionary algorithms (EAs), machine learning methods, and artificial neural networks (ANNs). The use of all of the above has an increasing impact to key enabling technologies. Additionally, hybrid combinations of Artificial Intelligence (AI) techniques and other optimization methods are also emerging.
Edited by: Wei Li, Meng Han, Sanish Rai, Chunqiang Hu, Dongxiao Yu