PERFORMANCE EVALUATION OF E-COMMERCE SERVERS USING THE TPC-W BENCHMARK
|
|
- Marylou McDowell
- 7 years ago
- Views:
Transcription
1 PERFORMANCE EVALUATION OF E-COMMERCE SERVERS USING THE TPC-W BENCHMARK D.F. García, J. García, C. López, I. Canga, D. González University of Oviedo Department of Informatics Gijón, Spain ABSTRACT The performance of servers is currently a major factor in the success of electronic commerce services. These services and applications integrate two well-known technologies into the server: web servers operate as an interface with the clients, and database servers provide the information required in the transactions. There are well-established benchmarking technologies for both kinds of servers, but there is as yet little research into the combination of the two to provide particular services, such as electronic commerce services. The main contribution of this paper is a discussion of the issues involved in the characterization, implementation and utilization of a benchmark for performance evaluation of e-commerce servers. KEYWORDS Performance benchmark, E-Commerce server performance, Web server performance. 1. INTRODUCTION The most important aspects of the performance evaluation of e-commerce servers using benchmarking techniques are the workload characterization, the selection of appropriate metrics and the sensitivity analysis of the metrics to changes in workload or system parameters. The first aspect considered is the characterization of the workload with which to carry out the evaluation. Currently there are several models for e-commerce services. Some models are similar, there are significant differences between others. As the workload is one of the most important elements of the models, a single synthetic workload cannot represent all the current models of e-commerce services properly. To reach an appropriate level of representativeness of the synthetic workload, only one model of e-commerce is characterized: one that fits the majority of businesses. The second aspect is to select the best metric to express the performance level a server is capable of providing. The most common performance metric is the maximum sustained throughput provided by the server under several restrictions in the response time for the transactions. Finally, the way in which the selected metric reflects the influence of possible changes on the workload parameters and on the computer system parameters must be analyzed. Obtaining information about metric behavior when the user profiles change serves to establish the applicability and validity of a benchmark for wider or narrower e-commerce scenarios. Gaining insight into metric behavior when the system parameters change is essential to assess the applicability and utility of a benchmark in order to support decisions on dimensioning and scaling [Menasce2000] of e-commerce servers. This research shows how a benchmark achieves generalized usefulness and applicability for the evaluation of e-commerce server performance. There is no intention to develop a new e-commerce benchmark, but to use existing ones. Some benchmarks have been developed for research purposes, such as WebTP [Jutla1999a] a web-based order management system, or WebEC [Jutla1999b][Bodorik2000] a generic e-broker site. Other benchmarks have been developed by the IT industry following two different approaches. In the first approach, specific e-commerce applications were customized to be used for benchmarking purposes, such as on-line financial management services [NSTL1999], e-commerce solutions 284
2 PERFORMANCE EVALUATION OF E-COMMERCE SERVERS USING THE TPC-W BENCHMARK for Internet bankers [FISERV2000], or an on-line bookstore application [Pendleton2000]. In the second approach, general-purpose e-commerce benchmarks were developed, such as the e-commerce suite included as a part of WebBench [WebBench2001] or TPC-W [TPC-W2000] [García2003], which also represents an on-line bookstore application. Because the TPC-W commercial benchmark is an excellent representation of the most common type of e-commerce applications currently being developed by the IT industry, the work on performance evaluation of e-commerce servers presented in this paper is based on this benchmark following this structure. In section two, a brief analysis of the characteristics, components and the e-commerce model supported by TPC-W is presented. In section three, the approach taken for the design of a specific implementation of the TPC-W benchmark is outlined. The experimental results obtained are presented in section four, and finally, the conclusions are briefly commented. 2. ANALYSIS OF THE TPC-W BENCHMARK In this section the main features of an e-commerce benchmark are briefly described, including the architecture of the tested system, the workload or e-commerce model supported, and the reporting metrics. 2.1 Architecture of the tested system All e-commerce benchmarks, including TPC-W, have a client-server architecture. The server computer includes all the components that constitute the e-commerce server. The client computers work as emulators to generate the same workload that real customers would generate and they are called RBEs (Remote Browser Emulators). The PGE (Payment Gateway Emulator) emulates the entity which authenticates the users and authorizes the payments. The server and clients communicate through a dedicated network. Figure 1 represents the architecture of the tested system. Emulated Browsers RBE-1 Remote Browser Emulator... Remote Browser Emulator RBE-N Payment Gateway Emulator PGE Network Web-Object Storage HTTP Server Application Server CGI ISAPI E-Commerce Server Application Data-Base Application transactions Figure 1. Architecture for benchmarking an e-commerce server with TPC-W 2.2 Workload model A general benchmark of widespread applicability should not represent the activity of a particular e-commerce segment, but that of any company which markets and sells products or services though Internet. TPC-W follows this approach. Next, the main e-commerce models currently used are analyzed to evaluate how they are represented by the TPC-W benchmark. 285
3 International Conference WWW/Internet 2003 E-commerce models are broadly categorized into three classes: cybermediary, manufacturer and auction models [Jutla1999c]. The cybermediary model represents a company that operates as an intermediary between suppliers of products or services and final customers. The TPC-W benchmark represents this model well, but in a simplified manner, as TPC-W considers all the products offered by the cybermediary in its internal databases, without consulting the supplier databases on-line. Furthermore, TPC-W does not consider the information interchanged with delivery companies or with other cybermediaries. The manufacturer model represents a company that markets and distributes its own products directly to the final customer through Internet. In this model, the company only requires access to external databases for payment management. TPC-W also fits the manufacturer model very well, covering all the main aspects addressed in the model. The auction model represents a company that manages a stock auction market, where both sellers (providing a list of goods to the company), and buyers (submitting bids for the goods), are final customers of the company. The TPC-W benchmark does not represent this model well due to the specific set of interactions and internal processes involved which are not considered in the TPC-W benchmark. Of all the different e-commerce models, the most typical workload supported by an e-commerce server consists of shopping sessions. Each session is composed of a sequence of interactions of different types, such as search and browse products, add products to the shopping cart, and buy products. The sequences of interactions can be represented by a state transition graph, called the Customer Behavior Model Graph (CBMG) in [Menasce1999], or simply a Web Interaction Diagram in TPC-W. Figure 2 represents the Interaction Diagram for the benchmark TPC-W. Start User Session Key: <name> Button name Web interaction transition via button Web interaction transition via HREF link Admin Confirm <Submit> Admin Request Best Seller Search Result <Submit query> Home New Product <Shopping Cart> <Confirm Updates> Shopping Cart Customer Registration (CURL) Product Detail <Checkout> <Admin> <Add to cart> <Shopping Cart> <Continue Buy> <Continue Buy> Returning customer Non-Returning customer Buy Request <Shopping Cart> Search Request Buy Confirm <Confirm Buy> <Order Status> Order Inquiry <Display Last Order> Order Display Figure 2. Modeling the customer behavior in TPC-W benchmark using an interaction diagram 286
4 PERFORMANCE EVALUATION OF E-COMMERCE SERVERS USING THE TPC-W BENCHMARK Most benchmarks dealing with user modeling in e-commerce environments differentiate between two typical user profiles. The first models customers that principally use the e-commerce service to find information about available products and usually leave the service without ordering. The second models customers with a higher probability of ordering a product before leaving the service. These customer profiles are called Browse and Order, respectively in the TPC-W benchmark. In [Menasce2000] they are called Occasional and Heavy Buyers. Both profiles share the same Interaction Diagram. The TPC-W benchmark defines a new profile, called Shopping, which merges of the two basic profiles. The difference between the profiles arises from the use of different transition probabilities in the interaction diagram. Therefore, the load generated with each profile will contain a different mix of the basic interactions, as illustrated in Table 1. Table 1. Expected percentage of each interaction for each customer profile Web interaction Browsing profile Shopping profile Ordering profile Browse group 95% 80% 50% Home 29.00% 16.00% 9.12% New products 11.00% 5.00% 0.46% Best sellers 11.00% 5.00% 0.46% Product detail 21.00% 17.00% 12.35% Search request 12.00% 20.00% 14.54% Search results 11.00% 17.00% 13.08% Order group 5% 20% 50% Shopping cart 2.00% 11.60% 13.53% Customer registration 0.82% 3.00% 12.86% Buy request 0.75% 2.60% 12.73% Buy confirm 0.69% 1.20% 10.18% Order inquiry 0.30% 0.75% 0.25% Order display 0.25% 0.66% 0.22% Admin request 0.10% 0.10% 0.12% Admin confirm 0.09% 0.09% 0.11% Each browser waits for a period, called think time, between two successive web interactions. In the TPC-W the think time must follow an exponential distribution with a mean between 7 and 8 seconds. The population of the database scales with the expected throughput of the server. This is a common characteristic of web and database benchmarks. In TPC-W the initial number of rows in each table of the database depends on two parameters: The number of emulated browsers (increasing one by one) The number of items to sell (5 discrete values: 10 3, 10 4, 10 5, 10 6, 10 7 ) In summary, the workload has only two independent parameters: the type of client and the number of items to be sold. The number of Emulated Browsers (EBs) is determined by the Web Interactions Per Second (WIPS) supported by the server, and cannot be selected freely. 2.3 Performance metrics for an e-commerce server The most common metric for measuring the performance of a server is the throughput under response time constraints. The performance metric in TPC-W is the number of Web Interactions Per Second (WIPS) measured in the average shopping scenario. The WIPS is computed as the total number of web interactions requested and completed successfully within a measurement interval divided by the length of that measurement interval in seconds. To provide additional insight into the performance of an e-commerce server working under scenarios of browsing or ordering customer profiles, two additional throughput metrics are defined, WIPSb (for browsing profile) and WIPSo (for ordering profile). 3. ISSUES OF AN IMPLEMENTATION OF THE TPC-W BENCHMARK The implementation of the TPC-W benchmark involves managing a wide spectrum of software and communication technologies to develop its main components, which are presented in next subsections. 287
5 International Conference WWW/Internet The electronic bookshop application The e-commerce application, an e-bookshop, was developed using PHP technology, implementing each web interaction as a page of PHP code. This technology allows portability between multiple platforms with an expected performance better than other highly portable technologies, such as Java. The e-bookshop has been organized in a small directory tree. Its main directory, /ebookshop/, must be installed in the root publication directory of the http server. Six directories of /ebookshop/ contain all the files of the application. Non-secure pages, served with http, are placed in the directory /pag. Secure pages, served with https over ssl, are placed in the directory /pags. The directory /inc contains styles (.css) and inclusion scripts (.inc) for the pages of the application. The GIF images of navigation items, such as buttons and logos, are placed in the directory /img_nav, while the JPEG images of the books are contained in the directory /images. The directory /pge contains the program developed to connect the bookshop application with the payment gateway emulator, PGE. This additional program is necessary because the PHP version used does not support connections based on SSL. 3.2 Data generation utilities The benchmark software includes two utilities developed to facilitate the generation of data: the data base population utility and an image generator. The data base population utility receives the number of items to be sold (10 3, 10 4, etc.), as well as the number of emulated browsers, and produces a program in PL/SQL which is used directly to eliminate, create and fill in all the tables required by the benchmark. The image generator for each item stored in the database creates two JPEG images, one thumbnail and one detailed. All thumbnail images have a fixed size of 5K, while the detailed images can have any of five pre-defined sizes. 3.3 The remote browser emulator Two general approaches are currently used to generate a sequence, or traffic, of web interactions to load an e-commerce server: user emulation [Bardford1998] and aggregate traffic generation [Kant2001]. This implementation of the benchmark follows the user emulation approach because it allows fine control over the behavioral aspects of the user, as required by the TPC-W benchmark. In this implementation, the RBE is designed as a multithreaded program, in which a single thread emulates each browser. All the threads are created just before the emulation begins and they are not destroyed until the emulation has finished. The emulation of browsing sessions consumes very little computational resources in a client-machine in relation to the load injected in the server-machine under test. Therefore, a single client-machine can efficiently emulate a large enough number of browsers to saturate relatively powerful servers. 3.4 The payment gateway emulator This module is implemented as a multithreaded server in which a dynamic pool of threads generates authorization for payments. Because a minimum delay of 2 seconds is required to generate the authorizations, and because of the low percentage of payments in relation to the total number of interactions, the design and implementation of the PGE does not present special performance challenges. Therefore, it was implemented in Java using the API for Secure Socket Extension. 3.5 Data analysis programs Two programs have been developed to generate the data to build two graphs required by the reporting procedures of the TPC-W benchmark. One program calculates the 90-percentile and the histogram of the response time for each web interaction following the TPC-W rules. The other calculates WIPS against elapsed time, counting the interactions within a sliding time window. The user can select two characteristics of the window: the size (always less than 30 seconds) and the displacement step. 288
6 PERFORMANCE EVALUATION OF E-COMMERCE SERVERS USING THE TPC-W BENCHMARK 4. EXPERIMENTAL RESULTS USING THE TPC-W IMPLEMENTATION This section presents a set of experimental results that help to explain the most relevant aspects of the TPC-W benchmark and its output metric. The experimental work was mainly developed using an Intel Pentium-III tetra-processor running the Linux operating system. Some experiments were carried out with an Alpha tetra-processor running the Dec-Unix operating system. In both servers, the database used was ORACLE and the HTTP server was Apache, both connected by PHP scripts. 4.1 Interpretation of the WIPS metric The primary interest here is to determine if WIPS is a throughput metric that always corresponds to a point of the same part of the throughput curve (linear, knee or saturation) of the server, or if on the contrary, the WIPS metric could fall on any part of the throughput curve in function of the characteristics of the server. Figure 3 shows two typical load experiments in which WIPS appears as a metric of the sustainable throughput of an e-commerce server within the linear part of the complete throughput curve. In general, WIPS could be interpreted or used as a throughput metric for e-commerce servers operating in the linear part of their throughput curve, always before the saturation knee. 7 6 CPU: Pentium EB / CPU: Alpha EB / 7 WIPS WIPS EB / 14 WIPS WIPS EB / EB Emulated Browsers (EBs) EB Emulated Browsers (EBs) Figure 3. WIPS metric on the throughput curve of two servers 4.2 Granularity of the WIPS metric In the TPC-W benchmark, the minimal variation of the throughput is obtained by adding or eliminating a single EB. Theoretically, with infinitely fast interactions (WIRT=0), the minimum increment of WIPS is 1/7 (0.1428) for each additional EB (curve EB/7 of figure 3). Also, to prevent over-scaling the server, the rules of TPC-W do not allow the throughput to fall under 50% of the maximum possible increments, that is, WIPS increments by 1/14 (0.0714) for each additional EB (curve EB/14 of figure 3). The slope of the throughput curve, obtained from the benchmarking experiments shown in figure 3 reveals an experimentally measured granularity of nearly 1/7, matching the theoretical expected behavior. 4.3 Influence of load factors on the WIPS metric The influence of load factors on WIPS is analyzed through experimental measurements. Although the reported WIPS depends on three load factors, only the client profile and the number of items in the database can be freely established in each load experiment. The number of emulated browsers cannot be selected in the experiments. It must be incremented just until the first response time restriction is violated. Figure 4 shows the relationship between the WIPS metric and the three load factors obtained from the experiments. Each point is the average of the three replications carried out for each experiment. Figure 4 289
7 International Conference WWW/Internet 2003 shows how WIPS clearly decreases with the increment of the number of items in the database. However, the influence of the type of client in WIPS does not show a clearly defined tendency. 4,5 4 3, ITEMS ITEMS 29 EB(sh) 27 EB(or) 26 EB(sh) 26 EB(br) 25 EB(or) 25 EB(br) WIPS 2,5 2 EB / 7 1,5 1 0, ITEMS 8 EB(br) 7 EB(sh) 10 EB(or) Emulated Browsers (EBs) Figure 4. Influence of load factors on the WIPS metric 4.4 Influence of system factors on the WIPS metric The system factors can be classified in two broad groups: software factors and hardware factors. The software factors are usually unordered qualitative factors, mainly associated to the version or release of each software component of the system or regarding their configuration parameters. The hardware factors are mainly ordered quantitative factors, whose levels are expressed numerically in increasing order: the number of CPUs and the amount of RAM. To evaluate the influence of system factors on WIPS, the load factors are fixed at their mean levels, that is, a client of shopping type and 10 5 items in the database. The evaluation of the influence of software system factors involves many configuration parameters of the system software. However, the default installation values for these parameters generally provide nearly optimum performance, except for the data base queries. To optimize the queries the database is indexed following this rule: when a field of a table is referenced in one or more SQL clauses, a single index is created using the field. We have checked that the addition of compound indexes does not improve the results obtained with single indexing. Figure 5 allows the comparison of the WIPS obtained without indexing (circles on dotted line) with the WIPS obtained with indexing (circles on continuous line). Single indexing of tables allows an increment of WIPS of up to 300%. To evaluate the influence of hardware system factors on WIPS, the load factors and software system factors remain fixed, while the most important hardware system factors are varied. There are many factors in a multiprocessor server that could affect the WIPS metric. However, the key factor to evaluate is the influence of the number of processors used on WIPS, which is the main factor to scale an e-commerce server. In addition, the influence of the amount of memory installed in the server must be evaluated for each configuration, because the processors will only provide their full computational power if they do not suffer memory starvation problems. Figure 5 shows the results of the experiments carried out varying these factors. When the minimum amount of memory installed in order to allow the database to operate, 128Mb (squares on continuous line), the number of processors used has no influence on WIPS. In other words, under 290
8 PERFORMANCE EVALUATION OF E-COMMERCE SERVERS USING THE TPC-W BENCHMARK the maximum memory starvation conditions, the e-commerce server is not scalable. With more memory installed, 256Mb (triangles on continuous line), the addition of a second processor increases the WIPS very slightly, but the addition of further processors is useless. By further increasing the memory installed, 512Mb (rhombs on continuous line), the addition of a second processor increases the WIPS noticeably, but the addition of the third processor only allows a small increment of the WIPS and a fourth processor is useless. Finally, under the absence of memory starvation problems, 1536Mb (circles on continuous line), the addition of processors always generates appreciable increments in WIPS. WIPS Experimental factors 1536Mb NO-PGE Indexed 1536Mb PGE Indexed 512Mb PGE Indexed Number of CPUs 256Mb PGE Indexed 1536Mb PGE NO-Indexed 128Mb PGE Indexed Figure 5. Influence of system factors on the WIPS metric 4.5 Influence of authentication on the WIPS metric A set of experiments was carried out to show the influence of the authentication service on the WIPS metric. This service is provided by the Payment Gateway Emulator (PGE). The TPC-W benchmark requires the response time of the PGE between the reception of a message and its response to be no less than 2 seconds. To evaluate if the PGE represents a brake in performance, Figure 5 shows the WIPS measured with PGE (circles on continuous line) and without PGE (crosses on thick continuous line). When the authentication services, provided by the PGE, are not considered, the WIPS increases, as the two upper curves of figure 5 show. Considering that the e-commerce server will be fully optimized before its operation, the authentication services will produce a reduction of 10% in the WIPS. 5. CONCLUSION The evaluation work presented in this paper shows that in general, the TPC-W e-commerce synthetic workload and its associated benchmarking rules are a very useful tool to generate a standard metric of the transactional capacity of servers working in e-commerce environments. The specific results of the evaluation work are summarized in the following paragraphs. The WIPS metric typically represents the sustainable throughput of an e-commerce server working between the middle and the end of the linear part of the whole throughput curve. The granularity of the WIPS metric is the inverse of the think time used by the emulated browsers between their successive interactions, showing a typical value of 1/7, and high repeatability. 291
9 International Conference WWW/Internet 2003 The TPC-W synthetic workload represents the manufacturer e-commerce model very well and the cybermediary e-commerce model only in a simplified manner. For other classic e-commerce models, such as the auction model, the TPC-W workload lacks representativeness. Users can select different values for the two factors of the TPC-W workload: the number of items in the database (10 3, 10 4, 10 5, 10 6, 10 7 ), and the navigation profile of the users (browsing, shopping, ordering). The number of items has a very strong influence on the WIPS metric, while the influence of the profile on WIPS is practically irrelevant. On symmetric multiprocessing platforms (SMPs), the TPC-W synthetic workload shows moderate scalability, measured as the WIPS speedup. With the maximum memory restrictions (128 Mbytes) scalability is null, that is, the workload cannot exploit additional processors added to the SMP platform. When the number of processors increases from 1 to 4 and without memory restrictions (>512 Mbytes), the workload shows a scalability of 2 without database indexing and 2.6 with database indexing. Finally, the authentication services provided by PGE reduce the maximum performance of the e-commerce server by 10% when the server software is fully optimized. ACKNOWLEDGEMENT The Spanish Research, Development and Innovation Program supported this work under the project TIC C REFERENCES Bardford, P. and Crovella, M., Generating Representative Web Workloads for Network and Server Performance Evaluation. In Performance Evaluation Review, Vol.26, No.1, pp Bodorik, P. et al, 2000, A Step Towards a Benchmark Repository for E-Commerce. Proceedings of 1 st International Conference on Electronic Commerce and Web Technologies. Greenwhich, UK. FISERV, The PremierEcom Scaling Tests Scalable E-Commerce Solutions for Internet Bankers. WhitePaper of Fiserv Inc. Brookfield, WI, USA. García, D.F. and García, J., TPC-W E-Commerce Benchamark Evaluation. In IEEE Computer, Vol.36, No.2, pp Jutla, D. et al, 1999a. WebTP: A Benchmark for Web-based Order Management Systems. Proceedings of 32 nd Hawaii International Conference on System Sciences. Maui, Hawaii, USA. Jutla, d., Bodorik, P. and Wang, Y., 1999b. Developing Internet E-Commerce Benchmarks. In Information Systems, Vol.4, No.6, pp Jutla, D. et al, 1999c. Making Bussines Sense of Electronic Commerce. In IEEE Computer, Vol.32, No.3, pp.67-75, March. Kant, K., Tewary, V. and Iyer, R., GEIST: A Generator for E-Commerce & Internet Server Traffic. Proceedings of the IEEE Int. Symp. on Performance Analysis of Systems and Software. Tucson, Arizona, USA. Menascé, D.A. et al, 1999a. A Methodology for Workload Characterization for E-commerce Sites. Proceedings of 1 st ACM Conference in Electronic Commerce. Denver, Colorado, USA. Menascé, D.A. and Almeida, V.F., Scaling for E-Bussiness: Technologies, Models, Performance, and Capacity Planning. Prentice-Hall, New Jersey, USA. NSTL, Scalability and Performance Testing of a DNA Application. Technical Report of National Software Testing Labs Inc. Philadelphia, Pennsylvania, USA. Pendleton, M., and Desai, G., Test Report: Performance and Scalability of Windows Technical Report of Doculabs. Chicago, USA. TPC, TPC Benchmark W (Web Commerce) Specification. Technical Specification of Transaction Processing Performance Council. San Francisco, California, USA. WebBench, WebBench Benchmark. Technical Specification of VeriTest. Los Angeles, California, USA
Ranking Configuration Parameters in Multi-Tiered E-Commerce Sites
Ranking Configuration Parameters in Multi-Tiered E-Commerce Sites Monchai Sopitkamol 1 Abstract E-commerce systems are composed of many components with several configurable parameters that, if properly
More informationTPC-W * : Benchmarking An Ecommerce Solution By Wayne D. Smith, Intel Corporation Revision 1.2
TPC-W * : Benchmarking An Ecommerce Solution By Wayne D. Smith, Intel Corporation Revision 1.2 1 INTRODUCTION How does one determine server performance and price/performance for an Internet commerce, Ecommerce,
More informationSpecification and Implementation of Dynamic Web Site Benchmarks. Sameh Elnikety Department of Computer Science Rice University
Specification and Implementation of Dynamic Web Site Benchmarks Sameh Elnikety Department of Computer Science Rice University 1 Dynamic Content Is Common 1 2 3 2 Generating Dynamic Content http Web Server
More informationMicrosoft Windows Server 2003 with Internet Information Services (IIS) 6.0 vs. Linux Competitive Web Server Performance Comparison
April 23 11 Aviation Parkway, Suite 4 Morrisville, NC 2756 919-38-28 Fax 919-38-2899 32 B Lakeside Drive Foster City, CA 9444 65-513-8 Fax 65-513-899 www.veritest.com info@veritest.com Microsoft Windows
More informationProviding TPC-W with web user dynamic behavior
Providing TPC-W with web user dynamic behavior Raúl Peña-Ortiz, José A. Gil, Julio Sahuquillo, Ana Pont Departament d Informàtica de Sistemes i Computadors (DISCA) Universitat Politècnica de València Valencia,
More informationExperimental Evaluation of Horizontal and Vertical Scalability of Cluster-Based Application Servers for Transactional Workloads
8th WSEAS International Conference on APPLIED INFORMATICS AND MUNICATIONS (AIC 8) Rhodes, Greece, August 2-22, 28 Experimental Evaluation of Horizontal and Vertical Scalability of Cluster-Based Application
More informationA Layered Architecture based on Java for Internet and Intranet Information Systems
A Layered Architecture based on Java for Internet and Intranet Information Systems Fidel CACHEDA, Alberto PAN, Lucía ARDAO, Ángel VIÑA Departamento de Electrónica y Sistemas Facultad de Informática, Universidad
More informationA Comparison of Software Architectures for E-Business Applications
A Comparison of Software Architectures for E-Business Applications Emmanuel Cecchet, Anupam Chanda, Sameh Elnikety, Juli Marguerite and Willy Zwaenepoel Rice University Department of Computer Science Dynamic
More informationA Statistically Customisable Web Benchmarking Tool
Electronic Notes in Theoretical Computer Science 232 (29) 89 99 www.elsevier.com/locate/entcs A Statistically Customisable Web Benchmarking Tool Katja Gilly a,, Carlos Quesada-Granja a,2, Salvador Alcaraz
More informationEvaluating and Comparing the Impact of Software Faults on Web Servers
Evaluating and Comparing the Impact of Software Faults on Web Servers April 2010, João Durães, Henrique Madeira CISUC, Department of Informatics Engineering University of Coimbra {naaliel, jduraes, henrique}@dei.uc.pt
More informationPerformance Evaluation for Software Migration
Performance Evaluation for Software Migration Issam Al-Azzoni INRIA, France Issam.Al-Azzoni@imag.fr ABSTRACT Advances in technology and economical pressure have forced many organizations to consider the
More informationPARALLELS CLOUD SERVER
PARALLELS CLOUD SERVER Performance and Scalability 1 Table of Contents Executive Summary... Error! Bookmark not defined. LAMP Stack Performance Evaluation... Error! Bookmark not defined. Background...
More informationPERFORMANCE ANALYSIS OF WEB SERVERS Apache and Microsoft IIS
PERFORMANCE ANALYSIS OF WEB SERVERS Apache and Microsoft IIS Andrew J. Kornecki, Nick Brixius Embry Riddle Aeronautical University, Daytona Beach, FL 32114 Email: kornecka@erau.edu, brixiusn@erau.edu Ozeas
More informationTESTING E-COMMERCE SITE SCALABILITY WITH TPC-W
TESTIG E-COMMERCE SITE SCALABILITY WITH TPC-W Ronald C Dodge JR Daniel A. Menascé Daniel Barbará United States Army Dept. of Computer Science Dept. of Information and Software Engineering Fort Leavenworth,
More informationCapacity Planning: an Essential Tool for Managing Web Services
Capacity Planning: an Essential Tool for Managing Web Services Virgílio Almeida i and Daniel Menascé ii Speed, around-the-clock availability, and security are the most common indicators of quality of service
More informationA STUDY OF WORKLOAD CHARACTERIZATION IN WEB BENCHMARKING TOOLS FOR WEB SERVER CLUSTERS
382 A STUDY OF WORKLOAD CHARACTERIZATION IN WEB BENCHMARKING TOOLS FOR WEB SERVER CLUSTERS Syed Mutahar Aaqib 1, Lalitsen Sharma 2 1 Research Scholar, 2 Associate Professor University of Jammu, India Abstract:
More informationThe Association of System Performance Professionals
The Association of System Performance Professionals The Computer Measurement Group, commonly called CMG, is a not for profit, worldwide organization of data processing professionals committed to the measurement
More informationPerformance Testing Process A Whitepaper
Process A Whitepaper Copyright 2006. Technologies Pvt. Ltd. All Rights Reserved. is a registered trademark of, Inc. All other trademarks are owned by the respective owners. Proprietary Table of Contents
More informationVirtuoso and Database Scalability
Virtuoso and Database Scalability By Orri Erling Table of Contents Abstract Metrics Results Transaction Throughput Initializing 40 warehouses Serial Read Test Conditions Analysis Working Set Effect of
More informationPredicting the QoS of an Electronic Commerce Server: Those Mean Percentiles
Predicting the QoS of an Electronic Commerce Server: Those Mean Percentiles Diwakar Krishnamurthy and Jerome Rolia Systems and Computer Engineering, Carleton University, Ottawa, Canada, K1S 5B6 {diwa,jar}@sce.carleton.ca
More informationUSING VIRTUAL MACHINE REPLICATION FOR DYNAMIC CONFIGURATION OF MULTI-TIER INTERNET SERVICES
USING VIRTUAL MACHINE REPLICATION FOR DYNAMIC CONFIGURATION OF MULTI-TIER INTERNET SERVICES Carlos Oliveira, Vinicius Petrucci, Orlando Loques Universidade Federal Fluminense Niterói, Brazil ABSTRACT In
More informationA Step towards a Benchmark Repository for E-commerce. Abstract
A Step towards a Benchmark Repository for E-commerce Peter Bodorik 1, Dawn Jutla 2, Lihong Cao 1 and Yie Wang 1 1 Faculty of Computer Science, Daltech, Dalhousie University 2 Faculty of Commerce, Saint
More informationPerformance Workload Design
Performance Workload Design The goal of this paper is to show the basic principles involved in designing a workload for performance and scalability testing. We will understand how to achieve these principles
More informationCentOS Linux 5.2 and Apache 2.2 vs. Microsoft Windows Web Server 2008 and IIS 7.0 when Serving Static and PHP Content
Advances in Networks, Computing and Communications 6 92 CentOS Linux 5.2 and Apache 2.2 vs. Microsoft Windows Web Server 2008 and IIS 7.0 when Serving Static and PHP Content Abstract D.J.Moore and P.S.Dowland
More informationImproving the Performance of Online Auctions Through Server-side Activity-Based Caching
Improving the Performance of Online Auctions Through Server-side Activity-Based Caching Daniel A. Menascé 1 and Vasudeva Akula 2 1 Department of Computer Science, George Mason University Fairfax, VA 22030,
More informationNETWRIX EVENT LOG MANAGER
NETWRIX EVENT LOG MANAGER QUICK-START GUIDE FOR THE ENTERPRISE EDITION Product Version: 4.0 July/2012. Legal Notice The information in this publication is furnished for information use only, and does not
More informationTPCC-UVa: An Open-Source TPC-C Implementation for Parallel and Distributed Systems
TPCC-UVa: An Open-Source TPC-C Implementation for Parallel and Distributed Systems Diego R. Llanos and Belén Palop Universidad de Valladolid Departamento de Informática Valladolid, Spain {diego,b.palop}@infor.uva.es
More informationSYSTEM DEVELOPMENT AND IMPLEMENTATION
CHAPTER 6 SYSTEM DEVELOPMENT AND IMPLEMENTATION 6.0 Introduction This chapter discusses about the development and implementation process of EPUM web-based system. The process is based on the system design
More informationSOLUTION BRIEF: SLCM R12.7 PERFORMANCE TEST RESULTS JANUARY, 2012. Load Test Results for Submit and Approval Phases of Request Life Cycle
SOLUTION BRIEF: SLCM R12.7 PERFORMANCE TEST RESULTS JANUARY, 2012 Load Test Results for Submit and Approval Phases of Request Life Cycle Table of Contents Executive Summary 3 Test Environment 4 Server
More informationThe Importance of Load Testing For Web Sites
of Web Sites Daniel A. Menascé George Mason University menasce@cs.gmu.edu Developers typically measure a Web application s quality of service in terms of response time, throughput, and availability. Poor
More informationRun your own Oracle Database Benchmarks with Hammerora
Run your own Oracle Database Benchmarks with Hammerora Steve Shaw Intel Corporation UK Keywords: Database, Benchmark Performance, TPC-C, TPC-H, Hammerora Introduction The pace of change in database infrastructure
More informationA Hybrid Web Server Architecture for e-commerce Applications
A Hybrid Web Server Architecture for e-commerce Applications David Carrera, Vicenç Beltran, Jordi Torres and Eduard Ayguadé {dcarrera, vbeltran, torres, eduard}@ac.upc.es European Center for Parallelism
More informationImpact of technology trends on the performance of current and future Web-based systems
1 Impact of technology trends on the performance of current and future Web-based systems Mauro Andreolini 1, Michele Colajanni 1 and Riccardo Lancellotti 1 1 University of Modena and Reggio Emilia, Department
More informationOracle Applications Release 10.7 NCA Network Performance for the Enterprise. An Oracle White Paper January 1998
Oracle Applications Release 10.7 NCA Network Performance for the Enterprise An Oracle White Paper January 1998 INTRODUCTION Oracle has quickly integrated web technologies into business applications, becoming
More informationECOMMERCE SITE LIKE- GRAINGER.COM
12/19/2012 ITFLEXSOLUTIONS ECOMMERCE SITE LIKE- GRAINGER.COM Developed by : IT Flex Solutions www.itflexsolutions.com *Please note that this is not a final proposal only an estimate of the time and type
More informationPerformance Issues of a Web Database
Performance Issues of a Web Database Yi Li, Kevin Lü School of Computing, Information Systems and Mathematics South Bank University 103 Borough Road, London SE1 0AA {liy, lukj}@sbu.ac.uk Abstract. Web
More informationMAGENTO HOSTING Progressive Server Performance Improvements
MAGENTO HOSTING Progressive Server Performance Improvements Simple Helix, LLC 4092 Memorial Parkway Ste 202 Huntsville, AL 35802 sales@simplehelix.com 1.866.963.0424 www.simplehelix.com 2 Table of Contents
More informationThe HPS3 service: reduction of cost and transfer time for storing data on clouds
The HPS3 service: reduction of cost and transfer time for storing data on clouds Jorge Veiga, Guillermo L. Taboada, Xoán C. Pardo, and Juan Touriño Computer Architecture Group University of A Coruña Campus
More informationAn Oracle White Paper July 2011. Oracle Primavera Contract Management, Business Intelligence Publisher Edition-Sizing Guide
Oracle Primavera Contract Management, Business Intelligence Publisher Edition-Sizing Guide An Oracle White Paper July 2011 1 Disclaimer The following is intended to outline our general product direction.
More informationIBM RATIONAL PERFORMANCE TESTER
IBM RATIONAL PERFORMANCE TESTER Today, a major portion of newly developed enterprise applications is based on Internet connectivity of a geographically distributed work force that all need on-line access
More informationhttp://docs.trendmicro.com
Trend Micro Incorporated reserves the right to make changes to this document and to the products described herein without notice. Before installing and using the product, please review the readme files,
More informationPRODUCT BRIEF 3E PERFORMANCE BENCHMARKS LOAD AND SCALABILITY TESTING
PRODUCT BRIEF 3E PERFORMANCE BENCHMARKS LOAD AND SCALABILITY TESTING THE FOUNDATION Thomson Reuters Elite completed a series of performance load tests with the 3E application to verify that it could scale
More informationRed Hat Network Satellite Management and automation of your Red Hat Enterprise Linux environment
Red Hat Network Satellite Management and automation of your Red Hat Enterprise Linux environment WHAT IS IT? Red Hat Network (RHN) Satellite server is an easy-to-use, advanced systems management platform
More informationRed Hat Satellite Management and automation of your Red Hat Enterprise Linux environment
Red Hat Satellite Management and automation of your Red Hat Enterprise Linux environment WHAT IS IT? Red Hat Satellite server is an easy-to-use, advanced systems management platform for your Linux infrastructure.
More informationPerformance Evaluation of Shared Hosting Security Methods
Performance Evaluation of Shared Hosting Security Methods Seyed Ali Mirheidari, Sajjad Arshad, Saeidreza Khoshkdahan Computer Engineering Department, Sharif University of Technology, International Campus,
More informationInformatica Data Director Performance
Informatica Data Director Performance 2011 Informatica Abstract A variety of performance and stress tests are run on the Informatica Data Director to ensure performance and scalability for a wide variety
More informationDeploying the BIG-IP LTM with the Cacti Open Source Network Monitoring System
DEPLOYMENT GUIDE Deploying the BIG-IP LTM with the Cacti Open Source Network Monitoring System Version 1.0 Deploying F5 with Cacti Open Source Network Monitoring System Welcome to the F5 and Cacti deployment
More informationWeb Application s Performance Testing
Web Application s Performance Testing B. Election Reddy (07305054) Guided by N. L. Sarda April 13, 2008 1 Contents 1 Introduction 4 2 Objectives 4 3 Performance Indicators 5 4 Types of Performance Testing
More informationChapter 12 Testing Your Implementation
Version 1.5 Chapter 12 Testing Your Implementation Prescriptive Architecture Guide Abstract This chapter outlines the steps necessary to verify that a deployment of a base Microsoft Systems Architecture
More informationBest Practices for Deploying SSDs in a Microsoft SQL Server 2008 OLTP Environment with Dell EqualLogic PS-Series Arrays
Best Practices for Deploying SSDs in a Microsoft SQL Server 2008 OLTP Environment with Dell EqualLogic PS-Series Arrays Database Solutions Engineering By Murali Krishnan.K Dell Product Group October 2009
More informationCA Nimsoft Monitor. Probe Guide for CPU, Disk and Memory. cdm v4.7 series
CA Nimsoft Monitor Probe Guide for CPU, Disk and Memory cdm v4.7 series Legal Notices Copyright 2013, CA. All rights reserved. Warranty The material contained in this document is provided "as is," and
More informationHow To Test For Performance And Scalability On A Server With A Multi-Core Computer (For A Large Server)
Scalability Results Select the right hardware configuration for your organization to optimize performance Table of Contents Introduction... 1 Scalability... 2 Definition... 2 CPU and Memory Usage... 2
More informationCloud Computing: Meet the Players. Performance Analysis of Cloud Providers
BASEL UNIVERSITY COMPUTER SCIENCE DEPARTMENT Cloud Computing: Meet the Players. Performance Analysis of Cloud Providers Distributed Information Systems (CS341/HS2010) Report based on D.Kassman, T.Kraska,
More informationBottleneck Characterization of Dynamic Web Site Benchmarks
Bottleneck Characterization of Dynamic Web Site Benchmarks Cristiana Amza, Emmanuel Cecchet, Anupam Chanda, Alan Cox, Sameh Elnikety, Romer Gil, Julie Marguerite, Karthick Rajamani, Willy Zwaenepoel Department
More informationAn Oracle White Paper May 2012. Oracle Database Cloud Service
An Oracle White Paper May 2012 Oracle Database Cloud Service Executive Overview The Oracle Database Cloud Service provides a unique combination of the simplicity and ease of use promised by Cloud computing
More informationhttp://docs.trendmicro.com
Trend Micro Incorporated reserves the right to make changes to this document and to the products described herein without notice. Before installing and using the product, please review the readme files,
More informationPerformance evaluation of Web Information Retrieval Systems and its application to e-business
Performance evaluation of Web Information Retrieval Systems and its application to e-business Fidel Cacheda, Angel Viña Departament of Information and Comunications Technologies Facultad de Informática,
More informationMySQL databases as part of the Online Business, using a platform based on Linux
Database Systems Journal vol. II, no. 3/2011 3 MySQL databases as part of the Online Business, using a platform based on Linux Ion-Sorin STROE Romanian Academy of Economic Studies Romana Sq, no 6, 1 st
More informationParallels Plesk Automation
Parallels Plesk Automation Contents Get Started 3 Infrastructure Configuration... 4 Network Configuration... 6 Installing Parallels Plesk Automation 7 Deploying Infrastructure 9 Installing License Keys
More informationPerformance Evaluation Approach for Multi-Tier Cloud Applications
Journal of Software Engineering and Applications, 2013, 6, 74-83 http://dx.doi.org/10.4236/jsea.2013.62012 Published Online February 2013 (http://www.scirp.org/journal/jsea) Performance Evaluation Approach
More informationDEPLOYMENT GUIDE Version 1.2. Deploying F5 with Oracle E-Business Suite 12
DEPLOYMENT GUIDE Version 1.2 Deploying F5 with Oracle E-Business Suite 12 Table of Contents Table of Contents Introducing the BIG-IP LTM Oracle E-Business Suite 12 configuration Prerequisites and configuration
More informationScalability Factors of JMeter In Performance Testing Projects
Scalability Factors of JMeter In Performance Testing Projects Title Scalability Factors for JMeter In Performance Testing Projects Conference STEP-IN Conference Performance Testing 2008, PUNE Author(s)
More informationAutonomic resource management for the Xen Hypervisor
Autonomic resource management for the Xen Hypervisor Íñigo Goiri and Jordi Guitart Universitat Politécnica de Catalunya Barcelona, Spain {igoiri,jguitart}@ac.upc.es Abstract Servers workload varies during
More informationCompaq Archive for R/3
Compaq Archive for R/3 Managing your data explosion Compaq Archive for R/3 is easy, flexible, fast, and certified by SAP. Its new, distributed architecture offers: à High-availability No single point of
More informationBusiness Application Services Testing
Business Application Services Testing Curriculum Structure Course name Duration(days) Express 2 Testing Concept and methodologies 3 Introduction to Performance Testing 3 Web Testing 2 QTP 5 SQL 5 Load
More informationCHAPTER 1 - JAVA EE OVERVIEW FOR ADMINISTRATORS
CHAPTER 1 - JAVA EE OVERVIEW FOR ADMINISTRATORS Java EE Components Java EE Vendor Specifications Containers Java EE Blueprint Services JDBC Data Sources Java Naming and Directory Interface Java Message
More informationPerformance Testing. Slow data transfer rate may be inherent in hardware but can also result from software-related problems, such as:
Performance Testing Definition: Performance Testing Performance testing is the process of determining the speed or effectiveness of a computer, network, software program or device. This process can involve
More informationSQL Anywhere 12 New Features Summary
SQL Anywhere 12 WHITE PAPER www.sybase.com/sqlanywhere Contents: Introduction... 2 Out of Box Performance... 3 Automatic Tuning of Server Threads... 3 Column Statistics Management... 3 Improved Remote
More information<Insert Picture Here> Michael Hichwa VP Database Development Tools michael.hichwa@oracle.com Stuttgart September 18, 2007 Hamburg September 20, 2007
Michael Hichwa VP Database Development Tools michael.hichwa@oracle.com Stuttgart September 18, 2007 Hamburg September 20, 2007 Oracle Application Express Introduction Architecture
More informationA Comparison of Software Architectures for E-business Applications
A Comparison of Software Architectures for E-business Applications Emmanuel Cecchet, Anupam Chanda, Sameh Elnikety, Julie Marguerite and Willy Zwaenepoel Department of Computer Science Rice University
More informationOracle Enterprise Manager
Oracle Enterprise Manager System Monitoring Plug-in Installation Guide for Apache Tomcat Release 12.1.0.1.0 E28545-04 February 2014 This document provides installation instructions and configuration information
More informationVarious Load Testing Tools
Various Load Testing Tools Animesh Das May 23, 2014 Animesh Das () Various Load Testing Tools May 23, 2014 1 / 39 Outline 3 Open Source Tools 1 Load Testing 2 Tools available for Load Testing 4 Proprietary
More informationServing 4 million page requests an hour with Magento Enterprise
1 Serving 4 million page requests an hour with Magento Enterprise Introduction In order to better understand Magento Enterprise s capacity to serve the needs of some of our larger clients, Session Digital
More informationhttp://alice.teaparty.wonderland.com:23054/dormouse/bio.htm
Client/Server paradigm As we know, the World Wide Web is accessed thru the use of a Web Browser, more technically known as a Web Client. 1 A Web Client makes requests of a Web Server 2, which is software
More informationSitecore E-Commerce Cookbook
Sitecore E-Commerce Cookbook Rev: 2013-07-23 Sitecore E-Commerce Services 2.1 on CMS 7.0 Sitecore E-Commerce Cookbook A marketer's guide to Sitecore E-Commerce Services Sitecore E-Commerce Cookbook Table
More informationLiferay Portal Performance. Benchmark Study of Liferay Portal Enterprise Edition
Liferay Portal Performance Benchmark Study of Liferay Portal Enterprise Edition Table of Contents Executive Summary... 3 Test Scenarios... 4 Benchmark Configuration and Methodology... 5 Environment Configuration...
More informationLast Updated: July 2011. STATISTICA Enterprise Server Security
Last Updated: July 2011 STATISTICA Enterprise Server Security STATISTICA Enterprise Server Security Page 2 of 10 Table of Contents Executive Summary... 3 Introduction to STATISTICA Enterprise Server...
More informationUnderstanding the Benefits of IBM SPSS Statistics Server
IBM SPSS Statistics Server Understanding the Benefits of IBM SPSS Statistics Server Contents: 1 Introduction 2 Performance 101: Understanding the drivers of better performance 3 Why performance is faster
More informationApache Web Server Execution Tracing Using Third Eye
Apache Web Server Execution Tracing Using Third Eye Raimondas Lencevicius Alexander Ran Rahav Yairi Nokia Research Center, 5 Wayside Road, Burlington, MA 01803, USA Raimondas.Lencevicius@nokia.com Alexander.Ran@nokia.com
More informationCentralized Systems. A Centralized Computer System. Chapter 18: Database System Architectures
Chapter 18: Database System Architectures Centralized Systems! Centralized Systems! Client--Server Systems! Parallel Systems! Distributed Systems! Network Types! Run on a single computer system and do
More informationEnterprise Edition Scalability. ecommerce Framework Built to Scale Reading Time: 10 minutes
Enterprise Edition Scalability ecommerce Framework Built to Scale Reading Time: 10 minutes Broadleaf Commerce Scalability About the Broadleaf Commerce Framework Test Methodology Test Results Test 1: High
More informationSPAMfighter Mail Gateway
SPAMfighter Mail Gateway User Manual Copyright (c) 2009 SPAMfighter ApS Revised 2009-05-19 1 Table of contents 1. Introduction...3 2. Basic idea...4 2.1 Detect-and-remove...4 2.2 Power-through-simplicity...4
More informationAdvantage Database Server
whitepaper Advantage Database Server Scalability Technical Brief A whitepaper from Sybase ianywhere TABLE OF CONTENTS 1 Introduction 2 Specifications 2 Tables 2 Server Machine 2 Client Machine 2 Development
More informationGlassfish Architecture.
Glassfish Architecture. First part Introduction. Over time, GlassFish has evolved into a server platform that is much more than the reference implementation of the Java EE specifcations. It is now a highly
More informationWeb Server Software Architectures
Web Server Software Architectures Author: Daniel A. Menascé Presenter: Noshaba Bakht Web Site performance and scalability 1.workload characteristics. 2.security mechanisms. 3. Web cluster architectures.
More informationHPSA Agent Characterization
HPSA Agent Characterization Product HP Server Automation (SA) Functional Area Managed Server Agent Release 9.0 Page 1 HPSA Agent Characterization Quick Links High-Level Agent Characterization Summary...
More informationAsta Powerproject Enterprise
Asta Powerproject Enterprise Overview and System Requirements Guide Asta Development plc Kingston House Goodsons Mews Wellington Street Thame Oxfordshire OX9 3BX United Kingdom Tel: +44 (0)1844 261700
More informationOpenProdoc. Benchmarking the ECM OpenProdoc v 0.8. Managing more than 200.000 documents/hour in a SOHO installation. February 2013
OpenProdoc Benchmarking the ECM OpenProdoc v 0.8. Managing more than 200.000 documents/hour in a SOHO installation. February 2013 1 Index Introduction Objectives Description of OpenProdoc Test Criteria
More informationApple Share IP and the Mac OS X Model
FAQ Q. What is? A. is Apple s next-generation server platform, combining the strengths of AppleShare IP with the power and innovation of Mac OS X. It simplifies network administration by integrating services
More informationNetwrix Auditor for SQL Server
Netwrix Auditor for SQL Server Quick-Start Guide Version: 7.1 10/26/2015 Legal Notice The information in this publication is furnished for information use only, and does not constitute a commitment from
More informationInformation and Communications Technology Courses at a Glance
Information and Communications Technology Courses at a Glance Level 1 Courses ICT121 Introduction to Computer Systems Architecture This is an introductory course on the architecture of modern computer
More informationA Scalability Study for WebSphere Application Server and DB2 Universal Database
A Scalability Study for WebSphere Application and DB2 Universal Database By Yongli An, Tsz Kin Tony Lau, and Peter Shum DB2 Universal Database Performance & Advanced Technology IBM Toronto Lab, IBM Canada
More informationIBM Rational Asset Manager
Providing business intelligence for your software assets IBM Rational Asset Manager Highlights A collaborative software development asset management solution, IBM Enabling effective asset management Rational
More informationComparison of Request Admission Based Performance Isolation Approaches in Multi-tenant SaaS Applications
Comparison of Request Admission Based Performance Isolation Approaches in Multi-tenant SaaS Applications Rouven Kreb 1 and Manuel Loesch 2 1 SAP AG, Walldorf, Germany 2 FZI Research Center for Information
More informationStarting and Operating An Online Business:
Starting and Operating An Online Business: Facts, Tips and Knowledge to help you become successful. 1 Dear Business Owner- We hope this handout will help guide you to become one of the successful online
More informationIFS-8000 V2.0 INFORMATION FUSION SYSTEM
IFS-8000 V2.0 INFORMATION FUSION SYSTEM IFS-8000 V2.0 Overview IFS-8000 v2.0 is a flexible, scalable and modular IT system to support the processes of aggregation of information from intercepts to intelligence
More informationRich Media & HD Video Streaming Integration with Brightcove
Rich Media & HD Video Streaming Integration with Brightcove IBM Digital Experience Version 8.5 Web Content Management IBM Ecosystem Development 2014 IBM Corporation Please Note IBM s statements regarding
More informationWHITE PAPER. Domo Advanced Architecture
WHITE PAPER Domo Advanced Architecture Overview There are several questions that any architect or technology advisor may ask about a new system during the evaluation process: How will it fit into our organization
More informationA Tool for Evaluation and Optimization of Web Application Performance
A Tool for Evaluation and Optimization of Web Application Performance Tomáš Černý 1 cernyto3@fel.cvut.cz Michael J. Donahoo 2 jeff_donahoo@baylor.edu Abstract: One of the main goals of web application
More information