Bandwidth Issues Research Articles

Machine Learning-Aided Energy Efficiency Strategy for Multiuser Cooperative Networks

Cooperative communication is widely seen as a promising key technology for improving the energy efficiency of battery-driven multiple mobile terminals (MTs). In this study, we investigate the use of machine learning (ML) in multiuser cooperative access networks. Because MT cooperation and bandwidth allocation are considered two main issues in such networks, we design an ML-aided method to solve the bandwidth issues so that the proposed method can maximize the network’s energy efficiency. Specifically, we use machine learning with artificial neural network (ANN) trained at base station (BS) (a) to decide whether MTs in the heterogeneous access network should cooperatively communicate and (b) to determine the optimal bandwidth allocation for this communication by distributing the trained ANN to all MTs. The computer simulation results show that under the described communication environment in this paper, the proposed method can provide 99.8% correct prediction for MT cooperation and output the optimal bandwidth allocation with at least 88% accuracy, which demonstrates the effectiveness of the proposed method. Besides, the simulations also show that the proposed method can provide about 14%–25% power consumption reduction, which validates the EE performance of the proposed method.

A paper on microstrip patch antenna for 5G applications

In today’s life, wireless communication is the key thing. Life will be difficult without wireless communication because everything is dependent on the internet, data transmission etc. Although there is an option of wired internet, there are many drawbacks to it, for example installation of wired internet is difficult, more time is required, cost is higher, due to wires, it looks less organized, less flexible etc.As we talk about data transmission over the internet there is data rate and bandwidth, which are key points to consider. Data rates and bandwidths in previous generations of mobile networks were limited. To solve this problem MIMO technology based on 5G is in its development phase. 5G provides high data rates over a limited bandwidth and with good channel capacity. Microstrip antennas are low- profile, high gain provider devices. By introducing MIMO technology in the microstrip patch antenna it increases the gain and efficiency of the antenna, which we really require. MIMO is used in low power and a no. of antennas together, which makes it more reliable, it also has low latency and high gain provider technology. 5G ranges between 3 and 300 GHz, so it may be very useful to solve the data rates and bandwidth issues. The lower range has already been used in many technologies like Wi-Fi, WLAN, Bluetooth, etc. The upper spectrum has some complications which can be solved by using the frequency reuse concept. The MIMO antenna is stimulated using CST software for the range of 32–46 GHz. The gain is 9.22dBi at 37.7 GHz in 3D dimensions. The efficiency is 70%.

AWE-Inspiring Electrically Small Antennas

Anytime-wireless-everywhere (AWE) aspirations for Internet-of-Things (IoT) applications to be enabled through current 5G and evolving 6G and beyond ecosystems necessitate the development of innovative electrically small antennas (ESAs). While a variety of ESA systems are reviewed, those realized from the near-field resonant parasitic (NFRP) antenna paradigm are emphasized. Efficiency, bandwidth and directivity issues are highlighted. Multifunctional, reconfigurable, passive and active systems that have been achieved are discussed and illustrated; their performance characteristics and advantages described. This overview finalizes by going back to the future and considers enterprising research areas of current and forward-looking interest.

An NVM SSD-based High Performance Query Processing Framework for Search Engines

Commercial search engines generally maintain hundreds of thousands of machines equipped with large sized DRAM which incurs high hardware cost since DRAM is expensive. Recently, NVM Optane SSD has been considered as a promising underlying storage device due to its price advantage and speed advantage. However, to achieve a comparable efficiency performance with in-memory index, applying NVM to both latency and I/O bandwidth critical applications still face non-trivial challenges, because NVM has much lower I/O speed and bandwidth compared to DRAM. In this paper, we propose an NVM SSD-optimized query processing framework, aiming to address both the latency and bandwidth issues of using NVM in search engines. First, we propose a pipelined query processing methodology which significantly reduces the I/O waiting time. Second, we propose a cache-aware query reordering algorithm which enables queries sharing more data to be processed adjacently. Third, we propose a data prefetching mechanism which reduces the extra thread waiting time and improves bandwidth utilization. Moreover, we propose intra-query parallel mechanisms for long-tail queries, including query subtask scheduling, heap concurrent access strategy, query parallelism prediction and adaptive pipelining. Extensive experimental studies show that our framework significantly outperforms the state-of-the-art baselines, which obtains comparable processing latency and throughput with DRAM in both inter-query and intra-query parallel scenarios.

HFBN: An Energy Efficient High Performance Hierarchical Interconnection Network for Exascale Supercomputer

Supercomputers are trying to be eco-friendly using their main components like- interconnection networks, processors, and shared memory through high power efficiency (GFlops/watts). The reason for this is the exascale systems, are on the horizon, require a 1000 times performance improvement over the petascale computers and energy efficiency has attracted as the key factor for to achieve exascale system. The main contribution of this paper is to introduce a new hierarchical interconnection network; considering simulations at the million processing cores especially for the exascale system. Moreover, our designed network claims the supremacy of high network performance and low power consumption over the conventional networks and ensuring the utmost preferability for exaFLOPS system. On the other hand, the performance per watt metric, used for the TOP500 list, doesn’t reflect the overall performance of a given system. Hence, one of the possible solutions to reach the next generation exascale performance is to redesign the "Interconnection Network", which holds the main responsibility for the intercommunication between the CPUs and also the power consumption for the supercomputers. This paper focuses on a redesigned new energy efficient interconnection network that mitigates the problems of high power consumption, longer wiring length, and low bandwidth issues. Our designed network (HFBN) has been compared against the Tofu network and in the case of 1M cores, HFBN can obtain about 87.26% better energy efficiency at the zero load latency with uniform traffic, about 86.32% with perfect shuffle traffic, and about 92.98% with the bit-compliment traffic.

‘I do not know what’s that word in English, but I will tell you about my cousin’: EFL learners’ communication strategies in online oral discussion tasks

ABSTRACT In a context in which opportunities for oral interaction are limited (English as a foreign language courses at a Saudi tertiary institution), we carried out an action research project evaluating the introduction of computer-mediated spoken language tasks with a group of intermediate learners. Although the students were confronted with multiple challenges ranging from unfamiliarity with educational technology, through recurrent bandwidth issues, to their own limited linguistic repertoires, they showed themselves able to participate in discussion with increasing facility and levels of responsibility for conversation management. In this paper, we focus on the communication strategies (CS) which they deployed to achieve this. While CSs were not the subject of explicit instruction, the students showed themselves able to draw on their repertoires and on the strategies implicitly modelled by their instructor over the six weeks of speaking activities using the SpeakApps platform. We examine what these strategies were: change in CSs over time; CS use in different conversational configurations (teacher-led group discussion; student-led group discussion and peer-peer pair discussion); impacts of the audio-only nature of discussion on CS choice. The paper points to promising directions for future practice and research.

A joint medical image compression and encryption using AMBTC and hybrid chaotic system

In wireless communications several imaging methods are developed. During this pandemic situation in worldwide due to COVID 19, telemedicine plays a vital role in maintaining social distancing. In telemedicine, there is demand for high compression and encryption approaches to overcome bandwidth and security issues. In this work, a joint compression and encryption (JCE) approach for images is proposed. The proposed model is more secure with faster computational time. For compression Absolute Moment Truncation Coding approach is used and furthermore for encryption two chaotic maps i.e., Arnold’s Cat and Henon Map are applied on the compressed image. Further, the experimental results were studied to measure the performance of the model for brute force, differential and statistical attack. The proposed schemes have shown good results for compression and even for security i.e., NPCR 99.86, UCAI=30.29, MSE= 108.91, PSNR=28.34, Correlation Coefficient = -0.0054 and Entropy 7.97 against the various other approaches.

Performance analysis of OFDM based FSO communication system with TCM codes

Various channel coding schemes have been used over free space optical (FSO) links to alleviate the effects of turbulence induced fading. In this paper, performance analysis for TCM coded orthogonal frequency division multiplexing (OFDM) based FSO communication systems, operating over atmospheric turbulence channels. Analysis have been done in terms of bit error rate (BER) as a function of signal to noise ratio (SNR), considering the log-normal distribution model during weak turbulence and gamma-gamma distribution model for moderate and strong turbulence conditions. The integration of TCM with OFDM can solve bandwidth issue and bit rate degradation during wireless communication. Various modulation schemes have been studied for the said system keeping in mind different requirements such as band width and data rate etc. The simulation results and analysis have shown that the TCM coder with 16-QAM provides considerable coding gain as compared to uncoded system during all turbulence conditions. This system acts as high-performance wireless communication system (HPWCS) by providing BER of 10−9 which is necessary for stable operation on communication system.

GPU based Image Compression with Scaling-Hard-Threshold Using HWT (Haar-Wavelet-Transform) + RL (Run-Length) Pair Encoding

In 5G MASSIVE MIMO the main problem for better video communication is of transmission bandwidth issues which in turn reflects in video conferencing, Mobile-learning, gaming, graphics applications etc. However, in regard to a versatile framework i.e. a computerized camera with web and correspondence office, at that point the transmission capacity for correspondence and additionally stockpiling are of genuine concern. Tremendous valuable data must be put away and recovered proficiently for down to earth purposes. This is the novel methodology that scaling technique has proposed for 2D Haar wavelet transform based compression of picture utilizing parameter CR- ratio of Compression with PSNR improvement, with maintaining picture quality, less bandwidth usage with better compression ratio which increase by increasing speed with the help of NVIDIA GPU.

THE AFTERMATH OF COVID-19 ON STUDENTS’ EDUCATION AND HEALTH IN INDIAN EDUCATIONAL INSTITUTIONS: A SURVEY

Aim. This paper aims to bring forth how the basic right of education got adversely affected due to the COVID-19 pandemic. The unplanned and immediate shift to online classes adversely affected the students’ physical and mental health as several issues that the students faced were related to the lack of adequate resources. Methods. The data for this paper were collected through a self-prepared and structured questionnaire, using Google forms, which was then circulated among different stakeholders of the educational institutes. The statistical analysis of the collected data was done using Microsoft Excel. Results and conclusion. According to the analysis of the survey, smartphones (75% of the total respondents) are relatively more accessible by students in comparison to computers or laptops (53%). And even if students had internet connectivity (57%), they faced issues of low data bandwidth (39%) leading to poor quality of online interaction in classes. Another important analysis suggested that 57% of students lacked a quiet room or space to attend the online classes in their homes. Finally, the negative impacts of online classes on the physical and mental health of students were also analysed. Cognitive value. The findings and the analysis of this paper would thus help teachers and institutions to understand students’ views and experiences of the pandemic. This understanding would help teachers to plan their teaching plans accordingly bridging the digital divide which would help students learn and grow.

Environment Optimization Scheme Based on Edge Computing Using PSO for Efficient Thermal Comfort Control in Resident Space

With the fast development of infrastructure and communication technology, the Internet of Things (IoT) has become a promising field. Ongoing research is looking at the smart home environment as the most promising sector that adopts IoT and cloud computing to improve resident live experiences. The IoT and cloud-dependent smart home services related to recent researches have security, bandwidth issues, and a lack of concerning thermal comfort of residents. In this paper, we propose an environment optimization scheme based on edge computing using Particle Swarm Optimization (PSO) for efficient thermal comfort control in resident space to overcome the aforementioned limitations of researches on smart homes. The comfort level of a resident in a smart home is evaluated by Predicted Mean Vote (PMV) that represents the thermal response of occupants. The PSO algorithm combined with PMV to improve the accuracy of the optimization results for efficient thermal comfort control in a smart home environment. We integrate IoT with edge computing to upgrade the capabilities of IoT nodes in computing power, storage space, and reliable connectivity. We use EdgeX as an edge computing platform to develop a thermal comfort considering PMV-based optimization engine with a PSO algorithm to generate the resident’s friendly environment parameters and rules engine to detects the environmental change of the smart home in real-time to maintain the indoor environment thermal comfortable. For evaluating our proposed system that maintenance resident environment with thermal comfort index based on PSO optimization scheme in smart homes, we conduct the comparison between the real data with optimized data, and measure the execution times of optimization function. From the experimental results, when our proposed system is applied, it satisfies thermal comfort and consumes energy more stably.

Online Pivot to Support Students' Learning Amid COVID-19

What problem was addressed? Amid Covid-19 colleges and universities are closed down, reorganization of student education raises concerns about timely graduation. [1] Therefore, there is a radical shift across colleges to remote and online teaching models. The current article shares an experience with online teaching at a Medical College located in western India. What was tried? During Covid-19 lockdown it was decided by faculty of first professional medical course of the medical college, viz; Anatomy, Physiology & Biochemistry to shift to teaching online for a batch of 200 students. Initially, videoconferencing (VC) call applications like zoom or Team Link were utilized and WhatsApp group was created to inform students regarding topics and time. This ran smoothly to start with and 160-170 participants could join. Within few days, internet connectivity and bandwidth issues started erupting from both the sides, hampering quality of teaching. The teachers then decided to record each session via screen recording software and started uploading the same in dedicated Google Drive, sharing the link via WhatsApp group. Additionally, a dedicated YouTube channel was created for students to download videos to watch as per their convenience. This helped to minimize the challenge faced due to internet connectivity and to safeguard against cyber-attack, likely to prop up with apps like Zoom that uses VC.

A Modified OMP Algorithm with Reduced Feedback Overhead for Massive MIMO System

Objectives: Massive Multiple-Input and Multiple-Output (MIMO) is the optimum way to enhance the bandwidth issue, in which the feedback overhead is a challenging concern when tested with Frequency Division Duplex (FDD) systems. Conventional greedy search algorithms like Matching Pursuit (MP) and Orthogonal Matching Pursuit (OMP) are based on the prior knowledge of the signal sparsity, which enhances overhead. So, the objective of this study is to develop a method with low complexity channel estimation and reduced feedback overhead. Methods: The proposed method is based on the residual vector which is updated after iteration and a threshold-based approach is utilized to decide the stopping criteria thereby controlling the number of iterations. The evaluation parameters used in the experimental analysis are Normalized Mean Square Error and channel capacity. Findings: The proposed method improves the effectiveness in signal recovery and reconstruction along with signal sparsity it also reduces the complexity of the estimation process and limits the feedback. This results in a high data rate and can be used in a massive MIMO system to optimize the channel estimation. Novelty : The proposed model is independent of the sparsity in the input vector and improves the effectiveness of the signal recovery and reduces the feedback burden. The proposed method is suitable for a 5G massive MIMO systems. Keywords: Feedback overhead; CSI; OMP; Residue vector

Power Efficient Biquadratic Filter designing using OTA

Objectives: To present a power efficient Universal Biquad Operational Transconductance Amplifier circuit. Methods: OTA (operational transconductance amplifier) based Biquad filter is analyzed using three different simulated tools three different tools (CADENCE, XILINX, ORCAD and MATLAB tools) are used for designing the circuit. The 0.18mm CMOS technique is used using the Cadence tool for plan and reproduction. The same circuit has been implemented on ORCAD tool as well as Xilinx tool. Findings: The proposed Biquad filter improves the frequency response, power dissipation and provides vary of the KHN biquadratic filter circuits it uses minimum numbers of Operational Transconductance phenomenon Amplifier (OTA) to realize an equivalent. The assorted parameters specifically Center frequency, dcgain, Bandwidth, Power Dissipation and Quality issue are all electronically tunable. OTA based Biquad filter is simulated in CADENCE Virtuoso tool. Opamp-RC Biquad filter offers a bandwidth of 425 kHz, pass band gain of zero DB, whereas Gm-C measuring system based mostly filter offers 85MHz, passband gain of zero DB. Over-all power dissipation of the Biquad filter is 4.3mW with 1.8V DC Supply has basing current of 50mA with gracefully voltage 2.5v. by keeping the supply voltage, bias current and load capacitor as 2.5V, 50mA and 10pFrespectively, it has been seen that the power is reduced using the CADENCE virtuoso tool. Novelty : This study presents a Universal Biquadratic filter having less power dissipation. The circuit was optimized for gain, GBP, slew rate, areas, voltage offset, phase margin, power area etc. compared to all the previous filter circuits (OTA GMC filters, OTA type-C filters) designed with the help of OTA. Keywords: OTA; CMOS; CADENCE Virtuoso; Static Power; Dynamic Power; MOSFET

An ISM Modeling of Barriers for Blockchain/Distributed Ledger Technology Adoption in Supply Chains towards Cybersecurity

Over the last few years, the increasing level of cyber risks derived from the growing connectedness of Industry 4.0 has led to the emergence of blockchain technology as a major innovation in supply chain cybersecurity. The main purpose of this study is to identify and rank the significant barriers affecting the implementation of blockchain technology as a key component of cyber supply chain risk management (CSCRM). This research relied on the “interpretive structural modeling (ISM)” technique in the structure of a hierarchical model to investigate the contextual relationships of identified challenges for blockchain adoption in CSCRM; it also classifies the influential challenges based on their driving and dependence powers. The results highlight that “cryptocurrency volatility” is the challenge at the top level of the hierarchy, implying weak driving power but it is strongly dependent on the other challenges. “Poor regulatory provisions”, “technology immaturity”, “dependent on input information from external oracles”, “scalability and bandwidth issues”, and “smart contract issues” are significant challenges for the adoption of blockchain in cyber supply chain risk management and are located at the bottom level of the hierarchy with higher driving power. The implications for theory and practice of the research are also highlighted.

Telemedicine Underutilized in Post COVID Lockdown Period

COVID-19 (Coronavirus disease) pandemic has put tremendous pressure on healthcare providers to seek for ways to provide a sustainable model of healthcare to the distantly located patients. The desired model needs to be easily accessible, affordable and effective enough to address the needs of the patients. Telehealth is one such way which can help a medical expert reach to the remotely located population. State government has taken multiple initiatives to start telehealth services in its tertiary care hospitals. Ours being a tertiary care hospital, telemedicine services were started in May 2020 and have continued till date. The response to this new service was good in the initial months when lockdown due to COVID-19 was in place and was expected to improve as its awareness spreads across the region. However, post lockdown the trend has not been very encouraging. In nephrology, from catering to 20-25 patients per session it went down to 4-5 patients per session. This called for an active search of possible elements operating behind this development and take remedial measures. A detailed discussion with the service providers was held. The physicians were quick to respond to the need of the system and were able to converse and write prescriptions to be uploaded in the pdf format. One resident and one consultant were present in each session. The frequency of the nephrology consultation sessions stood at once per week with provision of an increment as per response from the patients. Confidentiality related issues were well taken care by the trained manpower recruited by the hospital authorities. Internet connectivity issue rarely surfaced from the hospital side as the provided band width was usually 20-30 mbps. Though there were some poor bandwidth and connectivity issues at patients’ end, mostly from the rural areas. Limited internet access is a significant hurdle in preventing telemedicine usage by the rural population. [1,2]. A small survey among 106 patients visiting Nephrology OPD (Outpatient Department) revealed that only 15% of them were aware about the telemedicine services being offered by the hospital. This highlighted the need to relook into the effectiveness of the means of communication used to spread the information about this new service. The news was circulated primarily via newspapers and website of the hospital. The frequency of its publication was high in the initial months but declined later. In order to achieve a wider coverage, use of SMS (Short Message Service), e-mails and telephonic conversation giving details of tele-outpatient services may be of great help. Radio and television broadcast may further enhance awareness. Even after restoration of the regular physical OPD services, it may be useful to continue educating patients about this relatively new virtual service which is particularly useful in later follow-ups. Careful monitoring of the telemedicine programme with a watch on its smooth functioning and effectiveness in terms of patient numbers and their satisfaction scores can help improve the services. Goal oriented telemedicine programs are need of the hour. Our hospital didn’t have a running telemedicine department. The whole team worked in close collaboration with the personnel responsible for running the hospital information system. Setting a separate department or section to deal with telemedicine services can go a long way in its effective operation. Such departments can aid in laying down policies and plans to improve the utilization of the services. With the kind of impetus from the government in terms of manpower, hardware, software and electricity, an extra effort in spreading the awareness can provide the vital thrust the program needs. A change in mindset of the physicians about prescriptions sans physical examination will also be of help. A multidirectional and constant effort is required by physicians, administrators and policy holders to make the vision of providing telehealth to all, a success.

Malicious Traffic classification Using Long Short-Term Memory (LSTM) Model

Malicious traffic classification is the initial and primary step for any network-based security systems. This traffic classification systems include behavior-based anomaly detection system and Intrusion Detection System. Existing methods always relies on the conventional techniques and process the data in the fixed sequence, which may leads to performance issues. Furthermore, conventional techniques require proper annotation to process the volumetric data. Relying on the data annotation for efficient traffic classification may leads to network loops and bandwidth issues within the network. To address the above-mentioned issues, this paper presents a novel solution based on artificial intelligence perspective. The key idea of this paper is to propose a novel malicious classification system using Long Short-Term Memory (LSTM) model. To validate the efficiency of the proposed model, an experimental setup along with experimental validation is carried out. From the experimental results, it is proven that the proposed model is better in terms of accuracy, throughput when compared to the state-of-the-art models. Further, the accuracy of the proposed model outperforms the existing state of the art models with increase in 5% and overall 99.5% in accuracy.

Hierarchical cooperative-peers fog caching strategy to improve the performance of content centric networking

Content Centric Networking (CCN) is a novel paradigm to address challenges faced by traditional TCP/IP architecture. The motivation behind CCN is its inherent feature of caching. Caching at intermediate nodes is essential to reduce delay and to enhance performance of the network. However, determining as to how and where content should be cached to achieve this is the major challenge in CCN architecture. In this paper, we have proposed a Hierarchical Cooperative-peers Architecture (HCPA) and effective caching approaches to reduce the response time and increase the cache hit rate alleviating the server bottleneck and network traffic. The main idea is to utilize the resources of fog peer nodes near the user to deal with high latency and low bandwidth issues of the current communication pattern. This is achieved by pooling the cache space of cooperative fog peers of a region with a Regional demand-based fog Caching (RDFC) approach in two folds. First implementation is with replicated caching (RC) and the second one is using unique caching (UC). Both these approaches are implemented using CcnSim and the performance is evaluated based on cache hit rate, response time and bandwidth usage which has shown the significant improvement in the performance of the network.

Monitoring in fog computing: state-of-the-art and research challenges

Fog computing has rapidly become a widely accepted computing paradigm to mitigate cloud computing-based infrastructure limitations such as scarcity of bandwidth, large latency, security, and privacy issues. Fog computing resources and applications dynamically vary at run-time, and they are highly distributed, mobile, and appear-disappear rapidly at any time over the internet. Therefore, to ensure the quality of service and experience for end-users, it is necessary to comply with a comprehensive monitoring approach. However, the volatility and dynamism characteristics of fog resources make the monitoring design complex and cumbersome. The aim of this article is therefore three-fold: 1) to analyse fog computing-based infrastructures and existing monitoring solutions; 2) to highlight the main requirements and challenges based on a taxonomy; 3) to identify open issues and potential future research directions.

A lightweight authentication and secure data access between fog and IoT user

The advent of the internet of things (IoT) links millions of computers and sensors to each other, generating a massive volume of data, but due to latency, bandwidth and storage issues some computational paradigm is required near the edge devices. Within the IoT, fog computing offers computation, storage, and network resources to end-users. The assurance of protection is important because the services of fog computing are available to a wide number of IoT customers. This paper proposes an effective authentication and secure data access between fog and IoT users to achieve authentication and access to data and also a cipher policy-based homomorphic Paillier encryption (CP-HPE), for secure data access between fog node and user. The security and performance analysis show the scheme is apt for fog computing with IoT environment.