Remarkable prevalence of cloud computing has enabled smart cars to provide infotainment services. However, retrieving infotainment contents from long-distance data centers poses a significant delay. Consequently, hindering to offer stringent latency-aware infotainment services. Alternatively, Multi-access Edge Computing is a promising option to meet strict latency requirements. However, it imposes severe resource constraints with respect to caching and computation. Similarly, communication resources utilized to fetch the infotainment contents are scarce. In this paper, we jointly consider communication, caching, and computation (3C) to reduce infotainment content retrieval delay for smart cars. We formulate the problem as a mix-integer, non-linear, and non-convex optimization to minimize the latency. Furthermore, we relax the formulated problem from NP-hard to linear programming. Then, we propose a joint solution (3C) based on the alternative direction method of multipliers technique which operates in a distributed manner. We compare the proposed 3C solution with various approaches, namely, greedy, random, and centralized. Simulation results reveal that the proposed solution reduces delay up to 9% and 28% compared to the greedy and random approaches, respectively.

The articles in this special section present the most recent advances in amateur drone surveillance network architecture and technologies. The advancement in communication, networking and sensing technologies has attracted researchers, hobbyists, and investors to deploy mini-drones, a.k.a. unmanned air vehicles (UAVs). Drones have boundless viable applications due to their small size and ability to fly without an on-board pilot such as in agriculture, surveillance, and numerous public services. The use of drones for achieving high speed wireless communication is one of the most significant applications for next-generation communication systems (5G). However, their deployment poses several public safety threats to national institutions such as atomic plants, historic places, and the homes of public officials because of their ability to carry explosives and other destructive chemicals. To cope with these security threats, the deployment of surveillance drones is required to monitor amateur drones. The main motivation of deploying surveillance drones is to keep an eye on amateur drones, which can cause serious disasters if no precautionary measures are taken on time. The increasing use of surveillance drones presents challenges such as robust detection, tracking, intruder localization, and jamming. The accuracy of detection is a basic requirement of the system. In general, accurate detection is time-consuming. In fact, a precise moving object detection method makes tracking more reliable and faster, and supports correct classification, which is quite important for surveillance drones to be successful.