From a future perspective and with the current advancements in technology, deep reinforcement learning (DRL) is set to play an important role in several areas like transportation, automation, finance, medical and in many more fields with less human interaction. With the popularity of its fast‐learning algorithms there is an exponential increase in the opportunities for handling dynamic environments without any explicit programming. Additionally, DRL sophisticatedly handles real‐world complex problems in different environments. It has grasped great attention in the areas of natural language processing (NLP), speech recognition, computer vision and image classification which has led to a drastic increase in solving complex problems like planning, decision‐making and perception. This survey provides a comprehensive analysis of DRL and different types of neural network, DRL architectures, and their real‐world applications. Recent and upcoming trends in the field of artificial intelligence (AI) and its categories have been emphasized and potential challenges have been discussed.
This article proposes a microstrip bandpass filter patch antenna for remote access, particularly for vehicular applications. The antenna comprises split ring resonator (SRR) defected ground structure. The antenna design and filter are integrated to collaboratively work as filtenna (integrated filter antenna) for enhanced performance by reducing the total power consumption in the system. The objective of this paper is to carry out a detailed study of the effects of SRR parameters on the proposed filtenna. The investigation is carried out on the width of the slit opening of the SRR slot and the rotation of the inner square shaped ring structure in clockwise direction. The proposed filtenna is designed to provide a tuneable frequency operation. Simulation is performed on high frequency structural simulator which demonstrates good output response making filtenna design suitable for intelligent vehicular communication, particularly dedicated short-range communication-based applications at 5.9 GHz band and wireless local area network applications. The proposed filtenna is smaller in size, has low insertion loss, displays high selectivity and exhibits brilliant out of-band execution.
Mobile Ad hoc NETworks (MANETs) are composed of mobile nodes with limited resources and unpredictable node movement. With the on-going evolution in MANETs, provision of Quality of Service (QoS) has become a challenging task. In this paper, a node disjoint Bandwidth Constrained Multipath Routing (BCMR) protocol is proposed which considers bandwidth as the key factor to discover multiple paths for QoS provisioning. BCMR accommodates required bandwidth function in flooding route request packets. Extensive simulation study is carried out to investigate the performance of BCMR. Simulation results reveal that BCMR significantly reduces overheads, minimizes overall end to end delay and significantly improves packet delivery ratio.
Background & Objective:
There are some challenging issues such as providing Quality of
Service (QoS), restricted usage of channels and shared bandwidth pertaining to ad-hoc networks in a
dynamic topology. Hence, there is a requirement to support QoS for the application environment and
multimedia services in ad-hoc networks with the fast growing and emerging development of information
technology. Eventually, bandwidth is one of the key elements to be considered.
Methods:
Energy aware QoS routing protocol in an ad-hoc network is presented in this article.
Results and Conclusion:
The simulation results indicate that the improved protocol outperforms Adhoc
On-Demand Distance Vector (AODV) routing protocol in terms of QoS metric such as throughput,
packet delivery ratio, loss rate and average delay.
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