Web Server Cluster Research Articles

Optimized intuitionistic fuzzy enriched honey badger algorithm for cloud network-based work load scheduling

The difficulty of scheduling jobs or workloads increases due to the stochastic and transient characteristics of the cloud network. As a key prerequisite for establishing QoS, it asserts that effective work scheduling must be developed and executed. Maximum profit is made possible for cloud service providers by proper resource management. The most effective scheduling algorithm considers resources given by providers rather than the task set that users have accumulated. This paper developed a model that works in a two-level hierarchical model comprising global scheduling and local schedules to handle the heterogeneous type of request in real-time. These two levels of scheduling communicate with each other to produce an optimal scheduling scheme. Initially, all the requests are passed to the global scheduler, whose task is to categorize the type of request and pass it to the corresponding queue for assigning it to the related local scheduler using a parabolic intuitionistic fuzzy scheduler. In this work, the heterogeneous types of files are handled by maintaining different queues, in which each queue handles only a specific type of file like text doc, audio, image and video. Once the type of req is initiated by the clients, the global scheduler identifies the type of request and passes it to their relevant queue. In the next level, the local scheduler is assigned to each type of web server cluster. Once the work request is dispatched from the global workload scheduler, it is allocated to the local queue of the local scheduler, which allocates the resources of web servers by adapting the Quantum Honey Badger Algorithm, which searches the best-suited server for completing the assigned work based on the available resource parameters.

Design and Implementation of Dance Online Teaching System Based on Optimized Load Balancing Algorithm.

With the continuous improvement of the network hardware environment, people turn the demand target to the network application environment and the construction of information resources. How to build a network teaching platform for general undergraduate teaching to ensure the stability of the system and high-quality services during operation especially large-scale concurrent access will inevitably lead to the increase in the business volume of each core part of the network, the number of visits, and data traffic. With the growth of the network, the corresponding processing power and computing intensity also increase rapidly, which causes problems such as overloading of core network equipment, network bottlenecks, and network congestion. Simply pursuing high-performance hardware to solve problems will undoubtedly result in high cost investment; moreover, equipment with excellent performance cannot meet the needs of the current rapidly growing business volume. According to the design goal of the dance online teaching platform, to meet the online teaching load requirements of many people at the same time, the pressure of the web server cluster must be great. Because many people in online at the same time put too much pressure on the web server, this part of the network cannot be processed in time, which leads to the phenomenon that the performance of this part and even the whole network is degraded. In severe cases, it will even cause network communication services to come to a standstill, that is, the so-called deadlock phenomenon. If the protocol software cannot detect congestion and reduce the packet sending rate, the network will be paralyzed due to congestion. This situation will cause the problem of movement delay for online dance teaching, which will seriously affect the quality of teaching. Therefore, the dance online course system should be continuously improved, the quality of online courses should be continuously improved, and the study of the practical application of load balancing technology in the network teaching environment has become an important means to solve the relationship between supply and demand of network teaching. According to the experimental analysis, when the number of Worker' actuators is fixed, the execution time span of MakeSpan increases with the increase of tasks, while the time required by the optimized load balancing algorithm proposed in this paper increases by 1.32 s on average with the increase of tasks, and the time required by heuristic algorithm and bee colony algorithm increases by 3.68 s and 3.45 s on average with the increase of tasks. On the whole, the optimized load balancing algorithm proposed in this paper has obvious advantages.

Two-Tier Load Balancer as a Solution to a Huge Number of Servers

High number of users, connected devices and services on the Internet producing high traffic and load on the web servers causes a degradation of the quality of Internet services. A possible solution to this problem is to use a cluster of web servers. The cluster requires a load balancer to provide scalability and high performance of the services offered. The main load balancer is the only entry point to the server cluster in this architecture. In this paper, the researchers propose a two-tier load balancer rather than a single one to achieve more scalability and reduce the load on the main load balancer. The study also compared three features, Response Time Average, the load balancer CPU Utilization, and Servers’ CPU Utilization. The comparison uses three algorithms (Round Robin, Number of Connections, and Least Load) through two experiments. The results concluded that the Multi-Tier Load Balancing method offered better CPU utilization than a Single-Tier Load Balancing method for Round Robin and Server Load algorithms. However, the Single-Tier Load Balancing method provided better response time for all three algorithms. Moreover, the Round Robin and Server Load algorithms using a Multi-Tier method balanced the CPU utilization for all servers. This result shows the Multi-Tier method handles huge traffic and large number of servers with better CPU utilization.

Hardware Utilization by using Docker

Abstract —Developers and system administrators may use Docker to construct, ship, and operate distributed applications. Docker's main advantage is that it enables code to be quickly tested and deployed into production across a variety of applications. This article looks at the performance of Docker containers. They are judged on the effectiveness of their system. This is predicated on making the most of the system's resources. Docker Swarm is an open-source project that lets you build, deploy, and operate applications in a virtualized container environment. The goal of this research is to use the host computer's resources to spread web server traffic across a Docker swarm. Using this method, a single point of failure in a web server cluster is less probable.

PEMBUATAN FILE SYSTEM GLUSTERFS DISTRIBUTED- REPLICATED VOLUME DI SEKOLAH VOKASI IPB UNIVERSITY

College of Vocational IPB University (SV-IPB) uses a client-server system as an information technology architecture. The server provides several services that are used to assist the teaching and learning process at the IPB Vocational School. The application used to provide services is the Modular Object-Oriented Dynamic Learning Environment (MOODLE) which is used for e-learning. SV-IPB provides two Virtual Machines which are used as a web server and a database server. The use of a single web server to replace the request is certainly less stable because there is no web server to back it up so that the service will stop. This situation states that the use of a single web server does not have high information (high available). To overcome this problem, the cluster technology can be used to group several web servers in SV-IPB. The web server clustering technology used is the Gluster File System (GlusterFS) with the volume type used, namely Distributed-replicated volume. Based on the tests that have been carried out, this project can solve the problem that has been described earlier that "one web server is down, there is still another web server that can so that the client request process does not stop. In addition, the clustering technology used is required for the use of load balancing web servers so that it can reduce the load on each server because the request process will be sent alternately between web servers.

ChemBioServer 2.0: an advanced web server for filtering, clustering and networking of chemical compounds facilitating both drug discovery and repurposing.

SummaryChemBioServer 2.0 is the advanced sequel of a web server for filtering, clustering and networking of chemical compound libraries facilitating both drug discovery and repurposing. It provides researchers the ability to (i) browse and visualize compounds along with their physicochemical and toxicity properties, (ii) perform property-based filtering of compounds, (iii) explore compound libraries for lead optimization based on perfect match substructure search, (iv) re-rank virtual screening results to achieve selectivity for a protein of interest against different protein members of the same family, selecting only those compounds that score high for the protein of interest, (v) perform clustering among the compounds based on their physicochemical properties providing representative compounds for each cluster, (vi) construct and visualize a structural similarity network of compounds providing a set of network analysis metrics, (vii) combine a given set of compounds with a reference set of compounds into a single structural similarity network providing the opportunity to infer drug repurposing due to transitivity, (viii) remove compounds from a network based on their similarity with unwanted substances (e.g. failed drugs) and (ix) build custom compound mining pipelines.Availability and implementation http://chembioserver.vi-seem.eu.

ChemBioServer 2.0: an advanced web server for filtering, clustering and networking of chemical compounds facilitating both drug discovery and repurposing

ChemBioServer 2.0: an advanced web server for filtering, clustering and networking of chemical compounds facilitating both drug discovery and repurposing

Investigation on Reliability Estimation of Loosely Coupled Software as a Service Execution Using Clustered and Non-Clustered Web Server

Evaluating the reliability of loosely coupled Software as a Service through the paradigm of a cluster-based and non-cluster-based web server is considered to be an important attribute for the service delivery and execution. We proposed a novel method for measuring the reliability of Software as a Service execution through load testing. The fault count of the model against the stresses of users is deployed. A prototype application using Simple Object Access Protocol-based web service is developed and the study is carried out over there. The experimental setup, architecture, load testing results followed by a comparative study is discussed in this work. It is observed that the reliability of the service by using clustered and non-clustered web server degrades after a specific limit of stress level execution point. The comparative assessment predicts that the reliability of service by using a cluster-based web server is better than the service with a non-cluster based web server. With an increase in the stress level of usage in a multi-tenant environment, the service with clustered web server delivers better reliability than the service without a clustered web server. The occurrences of HyperText Transfer Protocol request failure in the service with a clustered web server is comparatively less than its counterpart service without a clustered web server. The study helps in identifying the applicability of the method and shows the effectiveness of such deployment.

A server-side accelerator framework for multi-core CPUs and Intel Xeon Phi co-processor systems

Processing-intensive web server requests can lead to low Quality of Service (QoS), such as longer mean response time and lower throughput, which calls for a new web server software framework that can improve the performance of web servers. The characteristic of request-level parallelism in web servers is fit for many-core architecture accelerators, such as GPU and Intel Xeon Phi co-processors, but traditional web server model cannot make full use of the performance of these accelerators. We proposed a new web server software framework— called MIC-based Server-side Accelerator Framework (MSAF)—for a machine with not only multi-core CPUs but also Intel Xeon Phi co-processors based on Staged Event Driven Architecture (SEDA). The framework can fully exploit the performance of Intel Xeon Phi co-processors and multi-core CPUs, and improve power/energy efficiency by offloading the stage of handling requests to Intel Xeon Phi co-processors. We implemented the web server simulation software based on MSAF framework on a machine with multi-core CPUs and Intel Xeon Phi co-processors, and evaluated it by means of Apache Benchmark (AB). Our evaluation of MSAF shows its performance is about equivalent to that of a web server cluster consisting of four to five computing nodes. This paper indicates that if MSAF is applied to, Intel Xeon Phi co-processors are suitable for server side software, such as web servers, DNS servers, and database servers, because of its characteristic of lower communication latency between Intel Xeon Phi co-processors and host, more powerful logic processing ability, and more energy efficiency.

Web-rMKL: a web server for dimensionality reduction and sample clustering of multi-view data based on unsupervised multiple kernel learning.

More and more affordable high-throughput techniques for measuring molecular features of biomedical samples have led to a huge increase in availability and size of different types of multi-omic datasets, containing, for example, genetic or histone modification data. Due to the multi-view characteristic of the data, established approaches for exploratory analysis are not directly applicable. Here we present web-rMKL, a web server that provides an integrative dimensionality reduction with subsequent clustering of samples based on data from multiple inputs. The underlying machine learning method rMKL-LPP performed best for clinical enrichment in a recent benchmark of state-of-the-art multi-view clustering algorithms. The method was introduced for a multi-omic cancer subtype discovery setting, however, it is not limited to this application scenario as exemplified by a presented use case for stem cell differentiation. web-rMKL offers an intuitive interface for uploading data and setting the parameters. rMKL-LPP runs on the back end and the user may receive notifications once the results are available. We also introduce a preprocessing tool for generating kernel matrices from tables containing numerical feature values. This program can be used to generate admissible input if no precomputed kernel matrices are available. The web server is freely available at web-rMKL.org.

Research on web server cluster load balancing algorithm in web education system

The load balancing algorithm of web server cluster in network education system is studied in this paper, and a new strategy based on server status and request information is proposed to reduce the response time. The mechanism of the algorithm is to classify the degree of influence of the client’s request content on the server, and set the corresponding weight. At the same time, it combines the server performance parameters and load conditions to allocate the request to the lightest load of the server. The overall framework structure of the hierarchy is proposed according to the MOOC education system, and the internal communication mechanism of the system and the monitoring program of the web server performance are studied in this paper. Experimental results show that the algorithm can fully utilize the existing software and hardware resources, effectively balance the load of the web cluster server, and fully utilize the service resources.

Weighted Round Robin Load Balancer to Enhance Web Server Cluster in OpenFlow Networks

Web server clusters require a reliable network management for increasing the quality of service (QoS). A load balancer system installed in a software-defined network (SDN) is one method that can improve the performance and availability of web server services. SDN is a dynamic and a programmable network management approach, and one protocol that supports it is OpenFlow. This research aims to design and analyse a model of a load balancer on OpenFlow networks, implementing a Weighted Round Robin (WRR) algorithm. The analysis process is conducted by measuring the value of a QoS web server performance parameters, such as response time, throughput, HTTP success, and loss connection. The results showed the WRR algorithm can be implemented for balancing a network system with dynamic resource allocation. The weight workload of each service can be obtained from the needs and existing network resources. The performance of a load balancer on an OpenFlow network is 57% better than in a traditional one for testing of response time conducted in a high connection. However, the throughput and HTTP success connection decreased by 2% and 10%, respectively, while HTTP loss connection increased by 49%.

A Client Proximity Based Load Balance Algorithm in Web Sever Cluster

Nowadays, the traffic to the popular site has increased dramatically. Some websites usually have different servers geographically distributed inconsistently can provide same service and these servers make up a web server cluster. In order to guarantee the QoE of clients, load balance scheme is necessary during the servers of the web server cluster. In this paper a novel load balancing algorithm which considers the proximity between client and server is proposed. We compare the Client Proximity Based Load Balancing algorithm (PBLB) with the Round Robin (RR) scheme and the Modified Random Allocation (MRA) scheme. Through the simulation results, we can see the PBLB algorithm has a better performance.

PERFORMANCE EVALUATION OF DYNAMIC LOAD BALANCING SYSTEM BY USING NUMBER OF EFFECTIVE PARAMETERS

Today, the World Wide Web is growing at an increasing rate and occupied a big percentage of the traffic in the Internet. These systems lead to overloaded and congested proxy servers. Load Balancing and Clustering of web servers helps in balancing this load among various web servers. In this paper we have given solution for load balancing among web servers and evaluated their performance using number of effective parameters. This paper explains the main objectives of proposed algorithm. It shows architecture diagram for load balancing in web server clusters. Proposed algorithm is explained using Pseudocode. Time complexity of proposed algorithm is also shown. Finally, it is concluded with experimental results andanalysis.

An Improved Dynamic Load-Balancing Model

With the rapid development of big data and the national big data strategy is put forward, the Web server cluster facing more complex and severe challenges. The traditional load balancing algorithm has obvious limitations. This paper proposes a dynamic load-balancing model based on the SSAWF (Strong Suspend And Weak Forecast) mechanism. This model uses strong suspend mechanism and cubic exponential smoothing prediction method based on AHP algorithm for dynamic load balancing scheduling. Results of the experiments show that the improved model has more positive influence on read/ write performance of the cluster under abnormal system transient performance, high concurrency and high system load interaction, that's to say the load balancing effect is better than the traditional load balancing.

Load Balancing Algorithm for Web Server Based on Weighted Minimal Connections

We have analyzed the clustering technology of Web server and studid the load balancing algorithm, due the lack of the existing load balancing algorithm can not accurately reflecting the size of the server load and manually setting the weight and other aspects, in this paper ,we propose an improved weighted minimum join Improved Load Balancing Algorithm for Web server cluster. On the one hand,The algorithm takes into account server utilization, memory utilization and network bandwidth mutilation and other factors, combined with web server’s own characteristics,Accouding to the real-time load of the server to dynamically change the size of the weight, and on the other hand, assigns the new connection request according to the weighted minimum connection number algorithm. Through the use of simulation software OPNET, the algorithm not only reduces server latency, reduces HTTP response time,and can effectively improve the load balancing efficiency.

A predictive framework for load balancing clustered web servers

Self-adaptation is the mechanism that is used automatically by some clustered web servers for resolving issues such as server bottleneck and overload. Such mechanisms are usually reactive meaning that they will be used when some issue occurs. However, taking an adaptation mechanism after arising a bottleneck or overload may be late and can cause some problems. Such problems could be resolved if we are able to predict future behavior of servers. To this end, based on our previous experiences, we presented a framework by which an adaptation strategy is selected based on a learning-based predictive method. Through the prediction, we are provided with a number of decision-making parameters for adaptation strategy selection. To show the effectiveness of our framework, we applied it for design and implementation of a differentiated cluster-based web server system and showed results. In such systems, each cluster is considered to serve a specific service. By comparison of simulation results between our predictive method and the reactive one, we found: (1) increase of the number of replied requests by servers, (2) decrease of average response time, and (3) increase of resource utilization of the system twofold to threefold.

An efficient load balancing approach for N-hierarchical web server cluster

Aiming at the load imbalance and poor scalability in single-tier Web server clusters, an efficient load balancing approach is proposed for constructing an N-hierarchical (multi-tier) Web server cluster. In each layer, multiple load balancers are set to receive the user requests simultaneously, and different load balancing algorithms are used to construct the high-scalable Web cluster system. At the same time, an improved load balancing algorithm is proposed, which can dynamically calculate weights according to the utilization of the server resources, and reasonably distribute the loads for each server according to the load status of the servers. The experimental results show that the proposed approach can greatly decrease the load imbalance among the Web servers and reduce the response time of the entire Web cluster system.

Multi-Level Load Balancing Methods for Hierarchical Web Server Clusters

With the need for scalability on web servers due to various demands of users and an explosive growth of the Internet users, researchers had addressed how to make well clusters of many web servers in past. In this paper, we propose a hierarchical clustering method of web servers to cover limits of single-level web server with high scalability and availability. Underlying structures of the hierarchical web server clustering are load balancers and real servers at the bottom level. The load balancer is attached on the top level basically and it can be extendable to n-levels of structure. The proposed algorithm dealing with dynamic weights based on agents at the bottom level shows faster response time compared to the existing round-robin and least connection algorithms. It is also possible to apply different algorithms for each level, and we evaluate that the proposed algorithm could reduce the workload imbalance among the real servers.

A Tracking System Supporting Large-Scale Users Based on GPS and G-Sensor

As the need for tracking objects in our daily life is increasing, how to take advantage of widely used technologies and devices to meet everyone's need is becoming a burning issue. To achieve this aim, a tracking system supporting large-scale users based on GPS and G-sensors (TSSLSU) is designed to track items by obtaining various pieces information of the item's states and analyzing various conditions. In this system, a microprocessor with Global Positioning System (GPS) modules embedded in target sends data in real-time through General Packet Radio Service (GPRS) and Global System for Mobile Communication (GSM), and an inner G-sensor can fetch real-time state information, such as acceleration and vibration signals. The system designed a message protocol to encapsulate and send these data to servers and also adopted distributed architecture, including backend server cluster, cache queue cluster, database cluster, and web server cluster. This specific architecture provides a better performance when large-scale users visit concurrently. In particular, there are alarm mechanisms to inform the user of any illegal cases through smart phone application and power-saving mechanism for embedded terminal by changing the frequency of sending messages. At any time, user can locate it and query the carrier's previous path by web page or phone application.