Management Server Research Articles

3D Convolutional Neural Network-Based Multi-Parameter Video Quality Assessment Model on Cloud Platforms

In light of the rapid advancements in big data and artificial intelligence technologies, the trend of uploading local files to cloud servers to mitigate local storage limitations is growing. However, the surge of duplicate files, especially images and videos, results in significant network bandwidth wastage and complicates server management. To tackle these issues, we have developed a multi-parameter video quality assessment model utilizing a 3D convolutional neural network within a video deduplication framework. Our method, inspired by the analytic hierarchy process, thoroughly evaluates the effects of packet loss rate, codec, frame rate, bit rate, and resolution on video quality. The model employs a two-stream 3D convolutional neural network to integrate spatial and temporal streams for capturing video distortion details, with a coding layer configured to remove redundant distortion information. We validated our approach using the LIVE and CSIQ datasets, comparing its performance against the V-BLIINDS and VIDEO schemes across different packet loss rates. Furthermore, we simulated the client-server interaction using a subset of the dataset and assessed the scheme's time efficiency. Our results indicate that the proposed scheme offers a highly efficient solution for video quality assessment.

Pengujian High Availability pada Asynchronous DNS Berbasis Restknot menggunakan Algoritma Round Robin

The existence of the Domain Name System (DNS) through the role of the DNS Record, functions to translate domain addresses into IP addresses. High availability is an absolute condition so that the service from the DNS Server is still available and running well. To make this happen, it is necessary to have an asynchronous API on the DNS server and data management on the DNS record. This research designs and implements RESTKnot as an asynchronous API on DNS Server for DNS record management, accompanied by high availability testing using Load Balancing techniques and the Round Robin (RR) algorithm. The test results show that RESTKnot can help the DNS record management process dynamically, where DNS records can be made through the RESTKnot API and RESTKnot CLI, to be sent to the RESTKnot agent and executed by Knot DNS. The test results also show that RESTKnot can realize high availability through a ten-time system access test scenario, where heavy traffic on the first web server can be immediately diverted to the second web server to achieve high availability.

ANALISIS HUKUM EKONOMI SYARIAH TERHADAP KEHALALAN PRODUK MAKANAN ONLINE TANPA SERTIFIKAT HALAL MUI

This article aims to explain the results of the author's analysis of the implementation of halal certificates on food products sold online, inhibiting and supporting factors for the application of halal certificates to food sold online, and the impact of Sharia economic law on the haleness of food products sold online without halal certificates. The results of the 2021 survey on e-commerce statistics show that the types of goods and services sold the most online in Lampung are food and beverage groups, totaling 40.86 percent of all businesses sampled by e-commerce. The rapid progress of buying and selling food online has become an additional task for halal certificate implementation agencies in providing security and comfort, especially for Muslim consumers in Indonesia, so they can consume halal food that is traded online. The research methodology that the author uses is qualitative in terms of the type of research documentation, interviews, and observations. The author goes directly to the field to conduct observations and interviews with primary data derived from the results of interviews with the BPJPH task force and LPPOM MUI. The results of the study show that there are no special strategies for food sold online. Supporting factors include the existence of institutions assisting the halal product process for MSME business actors. The inhibiting factor is that there is no direct regulation of cooperation with online business application server managers, a lack of public understanding of halal certificates, Analysis of Sharia Economic Law on the haleness of food products sold online: the haleness of products sold online or offline without MUI halal certificates are categorized as syubhat. According to Imam Nawawi, doing syubhat is form of underestimating.the.law.without.realizing.that.they.have.done.haram.

Revolutionizing Application Monitoring : A Review of DizBoard's Unified Dashboard Approach

In today's software landscape, the continuous and flawless operation of applications stands as a pivotal requirement. The genesis of the "DizBoard: Server and Database Manager" project stemmed from a pressing necessity to guarantee the seamless functionality and resilience of client-server applications. This imperative emerged from firsthand encounters with the escalating intricacies inherent in modern application ecosystems. An exploration of the existing technological milieu unveiled a diverse array of tools and solutions dedicated to application monitoring. However, the discerned need for a unified dashboard catering to databases, web services, and application servers became increasingly apparent. Current fragmented solutions often resulted in monitoring gaps and an absence of holistic insights into overall application health. The implementation of the "DizBoard: Server and Database Manager" project is geared towards bridging these gaps, addressing limitations highlighted in the literature review. Through a fusion of frontend technologies, Python-backed backend logic, and the automation prowess of shell scripting, this endeavor endeavors to craft a unified dashboard offering real-time visibility into critical components' statuses. This review paper embarks on a journey to expound upon the aspirations and methodologies driving the "DizBoard" project. It aims not only to present a comprehensive view of application health but also to delineate the voids that prevailing technologies leave. Envisioned as a user-friendly and automated monitoring dashboard, "DizBoard: Server and Database Manager" aspires to redefine the paradigm of application health management. Its ultimate goal is to elevate reliability, proactively address issues, and ultimately augment user satisfaction in the realm of application management.

Implementasi Data Warehouse Pada Toko KC Boutique

Clothing needs are the main thing that must be met. One of them is KC Boutique. This shop sells various women's clothing and is located in West Jakarta. The aim of this research is to create a Data Warehouse because the KC boutique shop still uses the Excel application to input data. This makes it difficult for owners to combine all the data they have. Therefore ETL is the solution to this problem. Where ETL will integrate all databases in a Data Warehouse which, if connected the data will also continue to be automatically updated. Data collection methods are observation and interviews. The method used is the OLAP method with the process namely ETL. The tool used is SQL Server Management Studio. The result of this research is the design of a Data Warehouse that is connected to the KC Boutique store database so that the data is well integrated.

Enhancing QoS of Telecom Networks through Server Load Management in Software-Defined Networking (SDN)

In the modern era, with the emergence of the Internet of Things (IoT), big data applications, cloud computing, and the ever-increasing demand for high-speed internet with the aid of upgraded telecom network resources, users now require virtualization of the network for smart handling of modern-day challenges to obtain better services (in terms of security, reliability, scalability, etc.). These requirements can be fulfilled by using software-defined networking (SDN). This research article emphasizes one of the major aspects of the practical implementation of SDN to enhance the QoS of a virtual network through the load management of network servers. In an SDN-based network, several servers are available to fulfill users’ hypertext transfer protocol (HTTP) requests to ensure dynamic routing under the influence of the SDN controller. However, if the number of requests is directed to a specific server, the controller is bound to follow the user-programmed instructions, and the load on that server is increased, which results in (a) an increase in end-to-end user delay, (b) a decrease in the data transfer rate, and (c) a decrease in the available bandwidth of the targeted server. All of the above-mentioned factors will result in the degradation of network QoS. With the implementation of the proposed algorithm, dynamic active sensing server load management (DASLM), on the SDN controller, the load on the server is shared based on QoS control parameters (throughput, response time, round trip time, etc.). The overall delay is reduced, and the bandwidth utilization along with throughput is also increased.

A Review of Pool-Boiling Processes Based on Bubble-Dynamics Parameters

Immersion cooling is widely used for thermal management of servers. The two-phase immersion cooling, which transfers heat by boiling, possesses efficient temperature control ability under intensive heat generation. In the process of temperature control through boiling, the generation and transportation of bubbles play a crucial role in calculating the heat-transfer capacity. Therefore, it holds immense significance to obtain a profound understanding of the mechanisms underlying bubble formation and detachment. Currently, numerous mechanistic explanations and empirical correlations have been proposed to elucidate the various parameters of bubbles during the boiling process. These findings were considered to be valuable references when selecting appropriate boiling media and designing efficient heating surfaces. To comprehensively present the progress of bubble formation and heat transfer in the boiling system, the forces exerted on the bubbles are highlighted in this article. A meticulous review of bubble-force analysis and correlation formulae pertaining to various relevant parameters (e.g., nucleation sites density, bubble growth rate, bubble growth period, and detachment frequency) was conducted. This review article was also expected to provide a novel foundation for further exploration of enhanced boiling heat transfer.

Execution of Serverless Functions Lambda in AWS Serverless Environment

Serverless computing, epitomized by AWS Lambda, has revolutionized application development and deployment by abstracting away server management and offering auto-scalability. AWS Lambda's 15-minute maximum timeout for function execution, however, presents a unique challenge for users aiming to process longer tasks within the serverless framework. In this paper, we dive deep into the execution dynamics of AWS Lambda within the AWS serverless environment, with a particular focus on extended execution times. As serverless computing gains traction, understanding the nuances and limitations of AWS Lambda's default settings becomes paramount.
 This paper investigates different request handling mechanisms within AWS Lambda and presents empirical data to demystify the underlying processes. By addressing the challenges posed by long-running serverless functions, we aim to provide practical insights and potential solutions for developers and architects seeking to optimize their serverless applications. In the quest for efficient triggering mechanisms for extended serverless functions, this paper offers valuable guidance, empowering users to leverage AWS Lambda effectively while circumventing the default timeout constraints.

Cyberattacks and Security of Cloud Computing: A Complete Guideline

Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, key exposure, auditing, privacy preservability, and cloud-assisted IoT applications. We then propose security attacks and countermeasures specifically for the different cloud models based on the security trends and problems. In the end, we pinpoint some of the futuristic directions and implications relevant to the security of cloud models. The future directions will help researchers in academia and industry work toward cloud computing security.

A Cooperative PoW and Incentive Mechanism for Blockchain in Edge Computing

More and more works use blockchain to improve the data security of integrated edge computing and Internet of Things (IoT) system. However, there are some problems of Proof-of-Work (PoW) that hinder the application, such as high energy consumption, low resource utilization efficiency and insufficient incentive. In this paper, we present a cooperative PoW named relay mining based PoW (Relay-PoW) to reduce energy consumption and improve resource utilization efficiency, where the nodes can mine blocks together under the management of edge server. We further propose parallel relay mining method to increase the throughput, where the nodes can mine blocks with multiple heights in a pipeline manner. In addition, we design supervision group mechanism to ensure the security, where the edge server evaluates the trust values of the nodes according to the capability and quality, and eliminates abnormal nodes timely. Finally, we propose a Shapley-based reward allocation strategy (SRAS) to encourage node to participate in Relay-PoW. Experimental results show that Relay-PoW can effectively decrease the energy consumption, improve the throughput and resource utilization efficiency, SRAS can motivate nodes to cooperate, and they all have a better performance than other methods.

A novel cost-based replica server placement for optimal service quality in cloud-based content delivery network

<span lang="EN-US">Replica server placement is one of the crucial concerns for a given geographic diversity associated with placement problems in content delivery network (CDN). After reviewing the existing literatures, it is noted that studies are more for solving placement problem in conventional CDN and not much over cloud-based CDN architectures, which some few studies are reported towards replica selection are much in its nascent stages of development. Moreover, such models are not benchmarked or practically assessed to prove its effectiveness. Hence, the proposed study introduces a novel design of computational framework associated with cloud-based CDN which can facilitate cost-effective replica server management for enhanced service delivery. Implemented using analytical research methodology, the simulated study outcome shows that proposed scheme offers reduced cost, reduced resource dependencies, reduced latency, and faster processing time in contrast to existing models of replica server placement.</span>

BFSF: A secure IoT based framework for smart farming using blockchain

Many smart applications, including smart cities, healthcare, smart agriculture, manufacturing, etc., have widely adopted the Internet of Things (IoT). Smart Farming (SF) integrates a set of technologies, such as cloud and edge computing and greenhouse concepts, to improve agricultural processes. Due to its capacity to generate fresh agricultural products at an incredible pace of development and output, the greenhouse business has recently attracted the attention of the farming community. However, the cost of labor and energy consumption causes the greenhouse’s production cost to rise by roughly 40%–50%. To avoid this, SF concepts have been introduced. Data management in SF has received a lot of attention in recent years due to its high potential for more accurate and cost-effective agriculture. Traditional client–server and cloud-based data management systems are plagued by single faults, data protection, centralized data management, and system vulnerabilities. In this paper, an IoT-based framework is proposed for SF to improve the productivity of crops. AI-based precision model is introduced in the framework, which can be integrated with remote sensor data for correct prediction of crop growth in smart agriculture. The result shows that the random forest model works better with 97% accuracy compared to Support Vector Classifier (SVC) have 93%, K-Nearest Neighbors (KNN) have 90%, and Logistic Regression 84%. This technology helps to reduce costs while also improving the overall quality of the agricultural process and product management with blockchain-based supply chain management to enhance farmers’ economic backdrop. The blockchain performance is evaluated on gas consumption, execution time, throughput and latency.

Blockchain Application In Management Of Electricity Data

This paper presents a model of using smart electronic meters and network tools to store information about power, price, and customer code in information blocks of Blockchain applications to manage electricity bills. Price transactions will be stored as a data block. The following data block will be linked to the previous, eliminating third-party management. The web user interface is designed to allow customers and administrators to monitor and receive notifications of suspected data attacks. The web application is developed by using Visual Studio software, which supports the C# language, popular among programmers and web developers. The data obtained from the meter is stored using Microsoft SQL Server, a powerful and popular database management system widely used in web applications to improve database services and reduce problems encountered in application development. Experimental model on the EPM5500P meter offers high stability, transparent and secure data management, which can be applied to a large scale such as buildings or industrial areas.

Structure of data in cell biology research

Bioinformatics is a scientific field on the border between informatics and biology where problems in the field of biology are solved using statistical methods. Another part of it are database systems which serve to store data necessary for meta-analysis. In recent years, there has been a boom mainly thanks to enabling technologies that make it possible to obtain big data about the functioning of living cells of organisms. Bioinformatics tools are necessary to process these data and form an integral part of research in modern biological and medical sciences. Scientific research focused on molecular biology, as well as medicine, is increasingly focusing on data storage. It is understood that the correct structure of the database is important for the correct interpretation of the results of their research activities. For communication between tables in the database, it is essential to set the data type, assign Primary key and Foreign key, ensure data integrity, remove data plurality and understand the research logic. Based on these needs, we created a relational database using SQL Server 2017 and Microsoft SQL Server Management Studio 2017 (SSMS). We created the source code for programming the database and filling it with data in Structured Query Language (SQL) and T-SQL on the Microsoft platform. Of the data types, we used float for numbers with a floating decimal line, integer values were assigned an integer (int), date had a date data type, and text strings had a defined nvarchar data type. Our results bring new information in the field of bioinformatics about the creation of a database structure for data storage in cell biology research. These new insights will help big data in meta-analyses of data and applying scientific results to medical and scientific practice. The database will store data obtained in real time, which will ensure relevance in pointing out biological trends, regularities, relationships and links between cellular structures. All these aspects are very important for the spatial modeling of data and the creation of models of interactions of cell structures with use for applications in medical and biological practice.

Efficient Revenue-Based MEC Server Deployment and Management in Mobile Edge-Cloud Computing

Efficient Revenue-Based MEC Server Deployment and Management in Mobile Edge-Cloud Computing

Azure DevOps The Next Era of Application Lifecycle Management

The software development, testing, and deployment process is a series of actions that are carried out in order to achieve a particular result. highly manual process, resulting in a significant number of code errors and bugs. Development and operations (Support) teams can often be out of sync, slowing software delivery and disappointing business stakeholders. DevOps creates efficiency across all tasks involved in software development, deployment, and maintenance. Connecting development with operations leads to increased visibility, more accurate requirements, improved communication, and faster time to Industry. Azure DevOps supports a joint culture and set of multiple steps and processes that bring together the development team, managers, and contributors to build software quickly. It allows the software industry to improve software at a faster pace than they can with traditional software development approaches. Compared with ADO Server, ADO Services offers the following added benefits: • Easy for server management. • Fastest access to greatest features. • Improved faster connectivity for remote users. • A transition from capital expenditures (like servers) to operational expenditures (subscriptions). DevOps is becoming a software industry standard for multiple businesses. According to a report issued by Capgemini, 61% of businesses either adopted DevOps or planned to do so during 2018. Statistics like this demonstrate that DevOps is a necessary part of your business plan if you expect to respond quickly to the market's demands, improve your business’s time-to-market, and keep your software solutions updated regularly. DevOps creates efficiency across all tasks involved in software development, deployment, and maintenance. Connecting development with operations leads to increased visibility, more accurate requirements, improved communication, and faster time to Industry.

FaaSLight : General Application-level Cold-start Latency Optimization for Function-as-a-Service in Serverless Computing

Serverless computing is a popular cloud computing paradigm that frees developers from server management. Function-as-a-Service (FaaS) is the most popular implementation of serverless computing, representing applications as event-driven and stateless functions. However, existing studies report that functions of FaaS applications severely suffer from cold-start latency. In this article, we propose an approach, namely, FaaSLight , to accelerating the cold start for FaaS applications through application-level optimization. We first conduct a measurement study to investigate the possible root cause of the cold-start problem of FaaS. The result shows that application code loading latency is a significant overhead. Therefore, loading only indispensable code from FaaS applications can be an adequate solution. Based on this insight, we identify code related to application functionalities by constructing the function-level call graph and separate other code (i.e., optional code) from FaaS applications. The separated optional code can be loaded on demand to avoid the inaccurate identification of indispensable code causing application failure. In particular, a key principle guiding the design of FaaSLight is inherently general, i.e., platform - and language-agnostic . In practice, FaaSLight can be effectively applied to FaaS applications developed in different programming languages (Python and JavaScript), and can be seamlessly deployed on popular serverless platforms such as AWS Lambda and Google Cloud Functions, without having to modify the underlying OSes or hypervisors, nor introducing any additional manual engineering efforts to developers. The evaluation results on real-world FaaS applications show that FaaSLight can significantly reduce the code loading latency (up to 78.95%, 28.78% on average), thereby reducing the cold-start latency. As a result, the total response latency of functions can be decreased by up to 42.05% (19.21% on average). Compared with the state-of-the-art, FaaSLight achieves a 21.25× improvement in reducing the average total response latency.

Architecture and enhanced-algorithms to manage servers-processes into network: a management system.

This work investigates minimizing the makespan of multiple servers in the case of identical parallel processors. In the case of executing multiple tasks through several servers and each server has a fixed number of processors. The processors are generally composed of two processors (core duo) or four processors (quad). The meaningful format of the number of processors is 2k, and k≥0. The problem is to find a schedule that minimizes the makespan on 2k processors. This problem is identified as NP-hard one. A new network architecture is proposed based on the addition of server management. In addition, two novel algorithms are proposed to solve the addressed scheduling problems. The proposed algorithms are based on the decomposition of the main problem in several sub-problems that are applied to develop new heuristics. In each level of the generated tree, some results are saved and used to decompose the set of processes into subsets for the next level. The proposed methods are experimentally examined showing that the running time of the proposed heuristics is remarkably better than its best rival from the literature. The application of this method is devoted to the network case when there are several servers to be exploited. The experimental results show that in 87.9% of total instances, the most loaded and least loaded subset-sum heuristic (MLS) reaches the best solution. The best-proposed heuristic reaches in 87.4% of cases the optimal solution in an average time of 0.002 s compared with the best of the literature which reaches a solution in an average time of 1.307 s.

STUDY OF HIGH AVAILABILITY AND PERFORMACE OFF SERVER CLUSTER

The article analyzes selected software solutions for balancing traffic in the server cluster: Traefik, HAProxy, and NGINX. For the demonstration, a system model consists of a cluster of three servers connected to the management servers with load-balancing solutions that share a public IP address. The application servers use the same database available in a multi-master configuration and the management servers are connected via the BGP protocol. User requests reach the server cluster through redundant traffic balancing subsystems. After testing the designed system, it was found that HAProxy is the best among all selected load-balancing solutions and ensures high cluster availability. While setting up the HAProxy it is recommended to choose the dynamic Least-Connections load balancing algorithm. Keywords: a server cluster, load-balancing, Round Robin, Least connections, HAPoxy

Implementation of a Neural Network Approach for Predicting Sales Profit

The term "artificial neural network" (ANN) refers, in the majority of cases, to a piece of computing hardware that is impacted by the process, function, and cognitive growth that are comparable to that of a human brain. It does this by simulating the way neurons in the human brain carry out their functions. It is able to solve complicated and dynamic issues in real time with some realistic probability constraints because it understands, observes, and recognises the patterns in the data. This paper implements the Microsoft neural network in Microsoft SQL Server Management using visual studio on a dataset that is accessible to the public in order to demonstrate the efficacy of neural networks in transforming raw data into an in-depth understanding of the trends in a dataset that is difficult to visualise. The dataset was chosen because it is readily available to the public. In addition to that, the error margin or standard deviation in the value prediction of the method that was carried out on the database is shown in this work. The selected dataset contains a significant volume of bike sale records from throughout Europe. As a result, it may be categorised as "big data," which cannot be resolved by utilising a standard paper record method or a typical data mining algorithm that is incapable of learning. Additionally, optimizers and modifiers that have an influence on the prediction value that is processed by the SQL database are investigated in this study. Traditional techniques of data analysis, on the other hand, are unable to correctly access or interpret data that is both so complicated and so dynamic as to be able to deliver quality forecasting. Neural networks, on the other hand, are able to resolve the information contained in big data into valuable knowledge in the form of predictions.