An efficient scalable scheduling mac protocol for underwater sensor networks

Underwater Sensor Networks (UWSNs) utilise acoustic waves with comparatively lower loss and longer range than those of electromagnetic waves. However, energy remains a challenging issue in addition to long latency, high bit error rate, and limited bandwidth. Thus, collision and retransmission should be efficiently handled at Medium Access Control (MAC) layer in order to reduce the energy cost and also to improve the throughput and fairness across the network. In this paper, we propose a new reservation-based distributed MAC protocol called ED-MAC, which employs a duty cycle mechanism to address the spatial-temporal uncertainty and the hidden node problem to effectively avoid collisions and retransmissions. ED-MAC is a conflict-free protocol, where each sensor schedules itself independently using local information. Hence, ED-MAC can guarantee conflict-free transmissions and receptions of data packets. Compared with other conflict-free MAC protocols, ED-MAC is distributed and more reliable, i.e., it schedules according to the priority of sensor nodes which based on their depth in the network. We then evaluate design choices and protocol performance through extensive simulation to study the load effects and network scalability in each protocol. The results show that ED-MAC outperforms the contention-based MAC protocols and achieves a significant improvement in terms of successful delivery ratio, throughput, energy consumption, and fairness under varying offered traffic and number of nodes

Library and Information Science Research; A Scopus-based Bibliometric Analysis from 2014 to 2023

Aim: The purpose of this study is to the highlight research growth in Library and Information Science (LIS) for the last decade (2014-2023) at the global level as indexed in the Scopus database. Methodology: The retrospective research approach has been used on the dataset retrieved from the Scopus database. We used the “advanced document search” technique, selected the targeted period and typed the “Library and Information Sciences”. We chose only “Article” and “Review” from the document type filter and English from the language filter. The selected bibliometric properties were analyzed and tabular demonstrations of the periodic growth with citation impact, top journals, institutions, countries, authors and keywords, have been presented. VOSviewer software has been used for data visualization. Results: A total of 32,395 articles on LIS was indexed during the period of 10-year from January 2014 to December 2023 with an average of 3,239 articles per year. An average annual growth was recorded at 12.69 and these articles were cited with an average of 10.90 citations per article. More than one-fifth of the articles were published in the top-20 journals. One-third of the research contributed by the authors of the United States and the University of South Africa emerged as the most productive research producing organization followed by the University of Illinois Urbana-Champaign. The majority of research was performed on the subject of Higher Education, and Academic Libraries. Abrizah Abdullah of Universiti Malaya, Malaysia emerged as the most prolific researcher. Conclusion: The current study highlighted the prominent bibliometric indicators of LIS research published during the last decade. The majority of the literature was contributed by the developed countries but Nigeria, Iran and Pakistan also produced promising contributions. The findings will be valuable for LIS practitioners, researchers, and academics, and will serve as a benchmark for the future studie

Dynamic Hand Gesture Recognition Using 3D-CNN and LSTM Networks

Recognition of dynamic hand gestures in real-time is a difficult task because the system can never know when or from where the gesture starts and ends in a video stream. Many researchers have been working on vision-based gesture recognition due to its various applications. This paper proposes a deep learning architecture based on the combination of a 3D Convolutional Neural Network (3D-CNN) and a Long Short-Term Memory (LSTM) network. The proposed architecture extracts spatial-temporal information from video sequences input while avoiding extensive computation. The 3D-CNN is used for the extraction of spectral and spatial features which are then given to the LSTM network through which classification is carried out. The proposed model is a light-weight architecture with only 3.7 million training parameters. The model has been evaluated on 15 classes from the 20BN-jester dataset available publicly. The model was trained on 2000 video-clips per class which were separated into 80% training and 20% validation sets. An accuracy of 99% and 97% was achieved on training and testing data, respectively. We further show that the combination of 3D-CNN with LSTM gives superior results as compared to MobileNetv2 + LSTM

Energy-Efficient Collision Avoidance MAC Protocols for Underwater Sensor Networks: Survey and Challenges

The Medium Access Control (MAC) layer protocol is the most important part of any network, and is considered to be a fundamental protocol that aids in enhancing the performance of networks and communications. However, the MAC protocol’s design for underwater sensor networks (UWSNs) has introduced various challenges. This is due to long underwater acoustic propagation delay, high mobility, low available bandwidth, and high error probability. These unique acoustic channel characteristics make contention-based MAC protocols significantly more expensive than other protocol contentions. Therefore, re-transmission and collisions should effectively be managed at the MAC layer to decrease the energy cost and to enhance the network’s throughput. Consequently, handshake-based and random access-based MAC protocols do not perform as efficiently as their achieved performance in terrestrial networks. To tackle this complicated problem, this paper surveys the current collision-free MAC protocols proposed in the literature for UWSNs. We first review the unique characteristic of underwater sensor networks and its negative impact on the MAC layer. It is then followed by a discussion about the problem definition, challenges, and features associated with the design of MAC protocols in UWANs. Afterwards, currently available collision-free MAC design strategies in UWSNs are classified and investigated. The advantages and disadvantages of each design strategy along with the recent advances are then presented. Finally, we present a qualitative comparison of these strategies and also discuss some possible future directions