Good QoS Research Articles

Design of Livestream Video System and Classification of Rice Disease

One of the agricultural products which is an important aspect of the life of Indonesian people is rice. Rice disease has a devastating effect on rice production, while detecting rice diseases in real-time is still difficult. Therefore, this study designed a Livestream video system that is equipped with a rice disease Classification system. The Livestream system utilizes 4G network communication and is assisted by the WebSocket protocol to communicate in real-time and for the rice disease Classification system using YOLO algorithm. In addition, Livestream uses the raspberry pi camera V2 to take video stream data. In analyzing the performance of the Livestream system, four tests were carried out, namely: functionality test, connectivity test, classification performance test, and implementation performance test. The test was carried out using the wireshark and conky tools, while the classification training used 5447 images from the Huy Minh do dataset that he provided on the Kaggle website. The results show that all programs run well and get a good QoS value according to the index of the parameter results, it is also found that sending non-base64 can reduce the size of the data to approximately 200,000 bytes/s and the performance of the classification system is good because it has an average accuracy of 80% even though it is quite burdening the raspberry pi. This system can still be optimized and developed further to support research in the field of data transmission and the performance of machine learning in a microcontroller.

Comparative Study of QoS on Video Meeting Tool Application in 4G LTE Network using Wireshark

Video meeting is a broadband internet-based service for long-distance communication, both visual and audio, in one room or in different rooms at the same time. Network testing using wireshark software connects to the Telkomsel operator's 4G LTE network. QoS parameters can display network quality such as throughput, packet loss, delay and jitter. The research experiment test used two conditions with different variables in the five types of video meeting tools being compared; zoho meeting, cisco webex meeting, google meet, zoom meeting and microsoft teams. First-condition uses random variables that do not consider the value of the number of participants and camera & microphone conditions to each client. Second-condition uses a fixed variable that the number of each client is 5 participants for each application (camera & microphone is on). The first-condition results showed that only Zoom Meeting which had a QoS value classified as Poor (index 1), especially the jitter value, compared to other applications. This application has an average jitter of 151,871 ms, that compared to TIPHON standard of 125 ms to 255 ms. The second-condition obtained Very Good QoS on throughput, packet loss and delay variables in all applications. Their variable jitter in each application is Zoho Meeting (0.101 ms), Cisco Webex meeting (0.074 ms), Google Meet (0.179 ms), Zoom meeting (0.021 ms), and Microsoft Teams (0.015 ms) which only in the standard 0 ms to/ d 75 ms. However, all applications according to the TIPHON standards are still in the Good category (index 3). The overall index average of all applications shows Good QoS.Keywords: video meeting, wireshark, quality of service, 4G LTE.

Successive Light Interference Cancellation and Allocation (SLICA) Algorithm for Indoor VLC System: A Backbone for 6G Network

This paper considers a successive light interference cancellation and allocation algorithm (SLICA) practicing interference cancellation for an indoor visible light communication (VLC) system based on successive interference cancellation (SIC) technique. The interference among users is cancelled with the help of the proposed approach to reduce computational complexity. VLC has become the cornerstone of intelligence in the current scenario. The data services allocated to the users are demand based and rely on their channel conditions. The data is allocated to user by modulating light waves via illuminated LEDs. The receiving end has photodiode installed in it to recover back the data. Better performance rate is achieved with lesser interference with the proposed approach. To guarantee good (quality-of service) QoS, considerable simulations are carried out considering real- time scenario which further demonstrates the high level performance of the proposed approach over conventional approach. Based on the analysis, the SINR and interference level is demonstrated for the conventional and the proposed approach and there is a hike in the performance rate of SINR and interference level of about 20 – 30 % with the applied proposed approach. The prior motto of this study is to enhance the system throughput and improve per user average performance rate and reducing the complexity of the system. This contributes to the total efficiency of the optical indoor VLC network. Our proposed algorithm will provide a strong backbone for the 6G deployment.

Enhanced Detectability Using Multi-Cycle Cyclostationary Detector in Cognitive Radio

RF spectrum decision is very crucial in cognitive radio. With the concept of interconnecting society by IoT, the spectrum demand has further raised exponentially and now it becomes very important to meet the problem of spectrum scarcity. Radio spectrum is a scarce commodity and due to shortage of radio spectrum, IoT networking has become very challenging in its implementation. Cyclostationary detection scheme, to able to sense RF spectrum and accordingly make decision to achieve good QoS and interference free communication is drawing the interest of researchers these days. In this paper, we propose to embed pilot subcarrier in OFDM signal to build the cyclic pattern in the signal of interest. This periodicity pattern is harnessed at the receiver end. Evaluation of this periodicity pattern forms the base regarding RF spectrum availability. The main aim of this paper is to show how cyclostationary detector performance can be improved. Pilot subcarriers are mainly used in this paper as a channel estimation parameter using different techniques to increase the detectability of detector.

When latency matters

Several emerging classes of interactive applications are demanding for extremely low-latency to be fully unleashed, with edge computing generally regarded as a key enabler thanks to reduced delays. This paper presents the outcome of a large-scale end-to-end measurement campaign focusing on task-offloading scenarios, showing that moving the computation closer to the end-users, alone, may turn out not to be enough. Indeed, the complexity associated with modern networks, both at the access and in the core, the behavior of the protocols at different levels of the stack, as well as the orchestration platforms used in data-centers hide a set of pitfalls potentially reverting the benefits introduced by low propagation delays. In short, we highlight how ensuring good QoS to latency-sensitive applications is definitely a multi-dimensional problem, requiring to cope with a great deal of customization and cooperation to get the best from the underlying network.

Systematic Literature Review of Challenges in Blockchain Scalability

Blockchain technology is fast becoming the most transformative technology of recent times and has created hype and optimism, gaining much attention from the public and private sectors. It has been widely deployed in decentralized crypto currencies such as Bitcoin and Ethereum. Bitcoin is the success story of a public blockchain application that propelled intense research and development into blockchain technology. However, scalability remains a crucial challenge. Both Bitcoin and Ethereum are encountering low-efficiency issues with low throughput, high transaction latency, and huge energy consumption. The scalability issue in public Blockchains is hindering the provision of optimal solutions to businesses and industries. This paper presents a systematic literature review (SLR) on the public blockchain scalability issue and challenges. The scope of this SLR includes an in-depth investigation into the scalability problem of public blockchain, associated fundamental factors, and state-of-art solutions. This project managed to extract 121 primary papers from major scientific databases such as Scopus, IEEE explores, Science Direct, and Web of Science. The synthesis of these 121 articles revealed that scalability in public blockchain is not a singular term. A variety of factors are allied to it, with transaction throughput being the most discussed factor. In addition, other interdependent vita factors include storages, block size, number of nodes, energy consumption, latency, and cost. Generally, each term is somehow directly or indirectly reliant on the consensus model embraced by the blockchain nodes. It is also noticed that the contemporary available consensus models are not efficient in scalability and thus often fail to provide good QoS (throughput and latency) for practical industrial applications. Our findings exemplify that the Internet of Things (IoT) would be the leading application of blockchain in industries such as energy, finance, resource management, healthcare, education, and agriculture. These applications are, however, yet to achieve much-desired outcomes due to scalability issues. Moreover, Onchain and offchain are the two major categories of scalability solutions. Sagwit, block size expansion, sharding, and consensus mechanisms are examples of onchain solutions. Offchain, on the other hand, is a lighting network.

Design of IoT-based System for Smart Temporary Waste Shelter

Internet of Things (IoT) is a concept where all products can interact with each other to help human activities by utilizing the internet. The IoT system can help solve problems such as the schedule-based retrieval system at a temporary shelter in Indonesia. This paper creates a web-based geographic information system along with the IoT-based waste temporary shelter prototype. The prototype also integrated with an Arduino Microcontroller so that it can sort the waste automatically into three types of waste, then record data in the form of height and weight, and send the results of the data to the database so that the geographic information system can display the results of the data. Node-RED serves as an Application Programming Interface (API) that sends data from the server to the database belonging to a web-based geographic information system. The results of the performance analysis are that the prototype has sorted waste well, and the system also produced good QoS by ETSI standards when looking at the network traffic from the MQTT server to the database, and from the end-user to the web. As for the QoE results for tools and systems have produced good results according to the ITU-T standard.

Perancangan Simulasi Hardware-in-The-Loop Untuk Sistem Manajemen Baterai

In a Microgrid system that relies on renewable energy generation, one of the most important constituent systems is the Battery Energy Storage System because of its vital role in maintaining the stability of the Microgrid in providing power to the load. However, to operate the battery, a Battery Management System is needed to ensure the battery operates at the desired working range, so that battery reliability can be maintained. To determine the behavior of the Microgrid and the designed BMS in accordance with the desired specifications, a Hardware-inthe-Loop (HIL) Simulation has been designed using Simulink to model a DC Microgrid which consists of several sub-systems such as: An ideally designed generator and load as a tester, a bidirectional buck and boost converter with a PI controller, and a battery system equipped with a Switched Shunt Resistor Cell Balancing type, all controlled using the BMS algorithm implemented on Arduino. From the test results, it is found that HIL can communicate with good QoS on various inputs as long as the Arduino sample time meets. Then the PI controller with HIL was able to improve converter performance and also succeeded in controlling cell balancing with the efficiency of charging and idle modes of 99% and 99.4% respectively. Finally, in testing the integrated system, the BMS can maintain the performance of the Microgrid with bus voltage and battery current parameters in various SoC conditions and generator voltage fluctuations, even though there are high voltage transients.

Multi-Agent Reinforcement Learning Framework in SDN-IoT for Transient Load Detection and Prevention

The fast emergence of IoT devices and its accompanying big and complex data has necessitated a shift from the traditional networking architecture to software-defined networks (SDNs) in recent times. Routing optimization and DDoS protection in the network has become a necessity for mobile network operators in maintaining a good QoS and QoE for customers. Inspired by the recent advancement in Machine Learning and Deep Reinforcement Learning (DRL), we propose a novel MADDPG integrated Multiagent framework in SDN for efficient multipath routing optimization and malicious DDoS traffic detection and prevention in the network. The two MARL agents cooperate within the same environment to accomplish network optimization task within a shorter time. The state, action, and reward of the proposed framework were further modelled mathematically using the Markov Decision Process (MDP) and later integrated into the MADDPG algorithm. We compared the proposed MADDPG-based framework to DDPG for network metrics: delay, jitter, packet loss rate, bandwidth usage, and intrusion detection. The results show a significant improvement in network metrics with the two agents.

Tunneling Pipe Mode Pada Jaringan Multi Protocol Label Switching

Along with the developing and the increasing of data communication users, service providers are required to always improve the quality of their services. QoS plays an important role since it is a parameter of the quality level of a service. Pipe Tunneling technique is one of the Qos methods that will guarantee a service will have its own priority level. With the help of the MPLS-VPN protocol, addressing of the IP will be much more flexible. In this thesis the simulation was done using GNS3 software while the results of the analysis were carried out using the WireShark software. There are two scenarios done by the author. For MPLS-VPN the author simulates 2 customers between companies 1 and 2 where both companies have centers in Jakarta and branches in Surabaya. And for Tunneling, both companies want their services to be given the highest priority among other services. From this scenario it can be obtained that with the presence of VRF on the network if there is the same network usage there will be no overlaps of IP. A service will have its own priority level according to the needs and requests. The results of the analysis are more focused on QoS, especially delay and throughput. From the results it shows that MPLS-VPN with Tunneling Pipe Mode integration is able to keep good QoS value. This can be seen from the average of the delay and throughput yield for Tunneling Pipe Mode that is equal to 84,51 ms and 67,858 Bytes / s.

Analisis kinerja Routing OSPF dan EIGRP dengan Teknik Redistribution

As the rapid development of technology, the demand to increase the network performance becomes higher. One of the parameters of a higher network performance is the increase of data rate by determining the faster and the best way for data delivery in any network. One method was used to determine that way dynamically by using OSPF and EIGRP protocol routing. Throughput, delay, jitter, packet loss, and speed performance were counted in this research. Based on the simulation using tracer packet software, the throughput was 45.75 bps, the delay was 5.91 ms, the jitter was 1.477 ms, and the loss packet was 0%. While the value of COST by data packet delivery in OSPF area was 781.25 kbps and the metric value of data packet delivery in EIGRP area was 20 kbps. With a good QoS value, the OSPF and EIGRP routing can be implemented for this network topology.

Self-select target neighboring base station assisted handover for natural disaster in LTE-A network

This paper presents Self-Select Target Neighboring Base Station Assisted Handover for Natural Disaster in LTE-A Network. In this study, two parameters have been introduced which are known as received signal strength of user (RSS) and left over power of base station (LoP) in order to maintained good QoS of UE and prolong battery life of base station when there is power outage. A distance fraction coefficient (α) with value 0.2 has been introduced to RSS expression to improve the signal strength by reducing the area that the UE’s covered. Both parameters are used to calculate weighted-average score (WAS) for selection of potential target base station to avoid more users to connect to the affected base station. From the results, sRSS=0.8 gave the highest WAS with value of WAS=0.84 for users from 1 to 100 compares to other value of sRSS. Moreover, by using no natural disaster condition as reference, Condition 1 (wRSS=80%, wLoP=20% ) with the lowest percentage of improvement (3.75%.) will be chosen as handover condition as it near to base station, avoid overloaded users to the affected base station, hence prolong battery life as it only use 20% of battery usage.

Node Behavior Classification for Traffic Prediction in Optical Burst Switched Networks using Machine Learning

Currently due to massive use of internet there is need of huge amount of bandwidth. The utilization of bandwidth can be managed up with optical burst switched networks. These networks cannot provide good QoS due to problems like wavelength contention and congestion problem. Also it is not necessary that contention in a network leads to congestion. It can be due to nodes behavior which affects the flow of traffic from source to destination. Hence there is a need to classify the traffic through the node at correct juncture to avoid congestion. This can be achieved using machine learning techniques. In this paper, support vector machine, AdaBoost classifier and Bagging classifier are evaluated .Experimental work is carried on Optical Burst Switched network dataset using 22 attributes which is available on UCI repository. The results show that bagging classifier performed better with accuracy of 95% in classifying the nodes behavior.

Extending SMS Service Coverage in Rural Areas by using LoRa Communication Technology

Mobile phone services are provided by operators in cities and along the roads in rural areas. In the last case, the coverage can reach a few kilometers far from the roads, depending on the available mobile technology. As a consequence, rural population have limited coverage or lack of message-based communication systems. In this work, we propose a solution based on low-power wide area network (LPWAN) technologies to extend the coverage of SMS service in rural areas in order to provide a message-based communication system for notification and telemetry. The proposal involves two devices called GSM node and remote node which form the complete system. The whole system uses three wireless communication technologies: GSM, LoRa and Bluetooth. To guarantee effective packet transmission, several computational strategies are implemented in each embedded communication hardware, such as algorithms that analyze the service availability before message transmission or guarantee delivery of messages. The proposed scheme takes advantage of both communication systems; those which operate on licensed bands in urban areas with good QoS and those which operate on non-licensed bands with high communication ranges. Several communication tests are implemented to evaluate the performance of the proposed solution. Results show the advantages of using low-consumption and long-range technologies to extend the SMS service coverage in rural areas. To the best of our knowledge, this is one of the first implementations and evaluations of a system that allows extending the SMS service coverage in rural areas based on LoRa technology.

QoS Guaranteed Resource Allocation for Live Virtual Machine Migration in Edge Clouds

Live Virtual Machine (VM) migration among geographically distributed edge clouds is an important strategy for providing low latency and reliable services for mobile end users. VM migration among edge clouds is more challenging than that in cloud computing, because the network bandwidth among edge clouds is more constrained than the cloud data center networks. In this paper, we study the bandwidth allocation among multiple concurrent live VM migrations in edge clouds. This problem is novel in that existing works aim to reduce the migration time for a single live VM migration among the edge clouds, and also ignores the QoS requirement for the service running on the VM in migration. However, our problem considers multiple VM migration tasks, and aims to maximize the average QoS while meeting the migration time constraint for each VM migration task. We formulate the problem as a Non-Linear Programming (NLP) problem which is also shown to be NP-Hard. We develop a new method to solve this problem. In our approach, we first transfer the problem into a Linear Programming (LP) problem by reducing the solution space. Taking the output from the LP solver as an initial solution, we then develop a heuristic to adjust it in order to find a better one to the original NLP problem. Finally, we design a set of evolutionary algorithms to select the optimal initial solution from the LP solver. Extensive simulations show that our proposed method can achieve good QoS and also has a fast convergence speed.

Multiclass Queueing Network Modeling and Traffic Flow Analysis for SDN-Enabled Mobile Core Networks With Network Slicing

The back-haul networks of 5G are formed by heterogeneous links which need to handle massive traffic. The service providers are not able to provide good QoS for their users. The technology like Software Defined Networks(SDN) and Network Slicing helps a little for a service provider to providing QoS for multiple links. The service providers face a challenge in the efficient utilization of resources to fulfill the QoS requirement of users to comply with the growth and thereby increasing the revenue. These problems require an accurate traffic model to determine the steady-state of the system. The proposed model uses an architecture that has the combination of two technologies: SDN and network slicing, which empowers an administrator a flexible, programmable network, and the best management of network resources. Heterogeneous application is well managed by creating multiple logical networks called slicing. The slicing can be modeled using multi-class queuing networks. These technologies encourage service providers to fulfill QoS and revenue growth. To leverage the benefits of these technologies in allocating QoS is to identify the performance of the system, which requires a precise model of traffic to decide the steady-state condition of the framework. In this paper, we focus on SDN and slicing in mobile networks and quantify the performance measure considering an in-band OpenFlow architecture for a single node and homogeneous traffic class, which is further extended to the multi-class heterogeneous class queuing model and analyzed. The results obtained help a service provider to monitor the utilization of resources in every node by every class of core network, which in turn helps to allocate the resources precisely to fulfill QoS requirements

Resource Allocation by Demand Based Optimization and Machine

In real-time multimedia usage the resource allocation for the modern communication is very much needed in-order to overcome certain problems or degradation happening in the communication channels. The quality of the communication is reduced due to the TVWS (Television White Space), variable BER signal requires variable channel allocation procedures and Qos depends on the various applications. These problems in the OFDM should be corrected continuously by keeping track of channel situation so that to provide a long term video streaming in good QoS. The energy distribution for the video is high the application requirement is higher also the occurrence of multiple BER will leads to the challenging environment to control. The main objective of this paper is to enhance a Game theory based algorithm incorporated with demand optimization algorithm and scheduling algorithm for machine learning to take decision in nonlinear space, which results in a system with good channel awareness and an adaptive resource allocation process. The effect of interference due to this procedure is checked and accordingly allocations are done.

92 NOVEL ULTRA-RARE EXONIC VARIANTS IDENTIFIED IN A FOUNDER POPULATION IMPLICATE CADHERINS, PROTOCADHERINS, AND AUTISM/ID GENES IN SCHIZOPHRENIA

Advances in wireless communication and ubiquitous mobile networks have resulted in location-based services (LBSs) contributing significantly to entertainment services for mobile users by utilizing their location data. However, for the request of a mobile user with a limited time frame, such as “where is the gas station nearest to me? The anonymous server should return the optimal result to me within a few minutes,” the anonymous server immediately generates the cloaking region based on the user’s current location information and the k-anonymity requirement privacy level to ensure location privacy protection when receiving the LBS request in most existing approaches. Unfortunately, mobility by the mobile user could cause the smaller cloaking region generated by the server. The existing algorithm would return the sub-optimal cloaking region. This problem prompted us to develop a novel probability-based prediction query (PBPQ) algorithm. On the server side, our method firstly predicts the probability of the mobile user being on each road, followed the final probability of the user entering the cloaking region. Our proposed algorithm can generate the optimal cloaking region generated within the limited time required by users. The experimental results show that our PBPQ algorithm can predict the optimal cloaking region effectively at the highly successful rate of more than 90%. Thus, the PBPQ algorithm can decrease the size of the cloaking region considerably while maintaining good QoS.

A Relative Survey on Handover Techniques in Mobility Management

Innovation is advancing at a speedier pace and necessity for web organizations at whatever point wherever is required. To impact this vision ever to better organizations open to a customer, effective mobility managing procedures must be composed. Two key intends to execute mobility administrations are Handover and area administration. Therefore, we need to have an efficient mobility management system among heterogeneous wireless networks where several wireless networks can interoperate to provide users with good QoS. In this paper, distinctive issues related to mobility administration in the coming period of frameworks are highlighted and besides throws a light on the uncertain zones to ensure proficient mobility management.

Maximizing the quality of service in distributed multimedia streaming in heterogeneous wireless network

In a distributed multimedia streaming, QoS plays an important role while transmitting videos from multiple servers to the client. A good QoS is required to provide videos at high resolution and to achieve better video quality, packet loss and delay have to be reduced. In this paper, combined throughput for multiple flows is proposed to increase the quality of service in distributed multimedia streaming (DMSHN). This scheme is used when the user receives the video packets from multiple servers where each connection forms a different flow. Through this scheme, the location where two or more flows combine is identified and the bandwidth in the channel is divided equally between the different flows, thereby increasing the network performance and dynamically adjusting the transmission rates of all the combined flows.