IT Business Proposal Part 2 - Mapping the New Network to Business Requirements
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IT Business Proposal Part 2 - Mapping the New Network to Business Requirements

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IT Business Proposal for upgrading existing network infrastructure to meet the growing business needs of a small to medium-sized company. Proposal is supported by actual OPNET simulation data. Part 2 ...

IT Business Proposal for upgrading existing network infrastructure to meet the growing business needs of a small to medium-sized company. Proposal is supported by actual OPNET simulation data. Part 2 discusses exactly how the new network infrastructure will successfully accommodate current and future business needs.

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IT Business Proposal Part 2 - Mapping the New Network to Business Requirements IT Business Proposal Part 2 - Mapping the New Network to Business Requirements Document Transcript

  • IT BUSINESS PROPOSAL UPGRADING EXISTING NETWORK TO MEET FUTURE NEEDS OF YOUR BUSINESS Part 2 Mapping the New Technology Infrastructure to Business RequirementsRevision Created On2.0 November 28, 2004Project Lead Project Lead Dr. Lynn DeNoia__________________________________ Phil Wu _______________________________________________________________________ ____________________________________
  • Page 2 PART 2 Suitability of Existing Network to Videoconferencing ServicesFurther consultation with the TEC liaison revealed the following:• TEC still prefers to dedicate one server to each application.• TEC’s IT group performed an application analysis on the TEC network and discovered differencesfrom the previously predicted application parameters (highlighted in the MP2 problem description).• The Director of Engineering wants to install a videoconference service for use within TEC and the CEOis very interested in exploring the potential for such videoconferencing services.This addendum is basically an analysis of the following: 1.) Feasibility of videoconferencing services over existing 10BaseT buliding LANS. 2.) Feasibility of videoconferencing services through TECs backbone network.Baseline Model 2 - new application parametersAdjustments were made to the previous baseline model to reflect differences from previously predictedapplication parameters (highlighted in the MP2 problem description). This model was used as a newbaseline model. All constraints and assumptions from the previous model still apply (they are highlightedagain below for completeness in the same table containing new assumptions (Table ????).Detailed model descriptions and their attributes can be found in the Appendix. Baseline Model 2 - Network Traffic and Usage Characteristics and AssumptionsModel characteristic (input parameters) Assumptions/Reason/Usage Patterns50% of the database (light) traffic being It was assumed that Sales and Marketing personnel willgenerated from the Administration access order information to help them assess sales numbersDepartment for Sales and Marketing is and develop better marketing strategies (half the time). Itdirected towards the Order Provisioning is likely that they will also need to look at someServer while the other 50% is directed corresponding customer information associated with eachtowards the Customer Information Server. order (half the time).50% of the web (light) traffic being generated It was assumed that Computing Center employees willfrom the Computing Center towards the Web spend half their time managing the network and requireand Email Server while other 50% is directed access to web based network management tools.towards the Network Management Server.20% of database (light) traffic being It was assumed that Garage personnel will be spendinggenerated by the Garage is directed towards 20% of their database time servicing Trouble Tickets andthe Customer Information Server where require Trouble Ticket information from the database. TheTrouble Ticket information resides, 80% 80% of their database time will be spentdirected towards Order Provisioning Server.An Exponential Distribution to model a For modeling purposes, it was sufficient to model allPoisson Distribution for all inter-arrival times network traffic using a Poisson Distribution. It was assumed that the Poisson Distribution was adequate for modeling the "overall" network traffic that would be observed in a real enterprise setting. It was assumed that most kinds of network traffic would be bursty and fairly randomized (number of videoconferences in any given unit of time, number of customer service events in any given unit of time..etc...). It was noted that certain kinds of network traffic can be characterized by certain types of probability distributions. certain types of network traffic produced by certain
  • Page 3 applications were modeled using specific probability distributions. However, this report is not a study on how well certain probability distributions reflect certain kinds of network traffic patterns. Table ???? Baseline Model 2 - Application Characteristics and AssumptionsApplication Profile Configuration Assumptions in relation to application characteristics and network usageHeavy FTP • Inter-request times between • It was assumed that file transfers occur more heavy file transfers = frequently during heavy file transfer usage than exponential distribution, 60 initially predicted and can be adequately modeled with seconds 60 second inter-request times. (modeled with an exponential distribution with the assumption that most requests are serviced under 60 seconds). • File sizes = normal • It was assumed that most of the file transfers will distribution, 20000 bytes with a involve files containing maps and detailed cabling variance of 5000 bytes diagrams, most of which are roughly 20000 bytes in size (but can be as high as 25000 bytes depending on the images)Light DB • Inter-request times between • It was assumed that database requests occur more light database transacations = frequently during light database usage than initially exponential distribution, 20 predicted and can be adequately modeled with 20 seconds second inter-request times. (this was modeled with an exponential distribution with the assumption that most requests are serviced under 20 seconds). • File sizes = normal • It was assumed that most light database queries will distribution, 100 bytes with a return relatively brief recordsets contain customer variance of 50 bytes information, order information, and inventory information, most of which should be ~100 bytes.Heavy DB • Inter-request times between • It was assumed that database requests occur more heavy database transactions = frequently during heavy database usage than initially exponential distribution, 10 predicted and can be adequately modeled with 10 seconds second inter-request times. (this was modeled with an exponential distribution with the assumption that most requests are serviced under 10 seconds). • File sizes = normal • It was assumed that most light database queries will distribution, 1000 bytes with a return detailed recordsets containing extensive variance of 200 bytes customer information, order information, inventory information, trouble ticket information, most of which shouldnt be more than ~1000 bytes.Light FTP • Inter-request times between • It was assumed that light file transfers occur more light file transfers = frequently during light file transfer usage than initially exponential distribution, 120 predicted and can be adequately modeled with 120 seconds second inter-request times. (modeled with an exponential distribution with the assumption that most requests are serviced under 120 seconds). • File sizes = normal • It was assumed that most of the file transfers will distribution, 20000 bytes with a involve files containing maps and detailed cabling variance of 5000 bytes diagrams, most of which are roughly 20000 bytes in size (but can be as high as 25000 bytes depending on the images)Light Email • Time between emails • It was assumed that this is the time used in SMTP by
  • Page 4 received/transmitted = 180 default for time between receiving and transmitting seconds emails. • Send queue = 1 emails • It was assumed that most employees will receive • Receive queue = 5 emails more emails than they send. • Email size = normal • It was assumed that most emails that are sent are distribution, 10000 bytes with roughly ~10000 bytes but can vary greatly (modeled by variance of 5000 byte variance of 5000 bytes) depending on attachments.Light Web • Inter-request times between • It was assumed that 30 seconds is an appropriate page requests = exponential estimate for the time between selecting pages. distribution, 30 seconds • Web objects size = • It is assumed that all web objects consistently fall Uniform_int Distribution with a within the range of 700-1000 bytes range of 700-1000 bytes Table ????Model V - added server based videoconferencing servicesBaseline Model 2 was modified to include server-based videoconferencing services with the followingadditions: • Added new server configured to support the videoconferencing application to the central server farm. • Configured the Engineering LAN object (40 workstations) to generate videoconferencing traffic and direct that traffic to the videoconferencing server. • An additional test workstation external to the LAN object used to analyze the feasibility of videoconferencing services over existing 10BaseT building LANS. In particular, the link capacity of the link between this test workstation and the LAN object was measured to assess how well existing 10BaseT links handle videoconferencing traffic. • Changed the number workstations in the Eng LAN object to 39 to account for the external workstation.This model was used to analyze the impact of deploying and supporting videoconferencing services withinthe existing TEC network. Model V - Network Traffic and Usage Characteristics and Assumptions• Same as Baseline Model 2 from above. Baseline Model 2 - Application Characteristics and Assumptions• Same as Baseline Model 2 from above with the following additions:Application Profile Configuration Assumptions pertaining to application characteristics and type of trafficVideo • Exponential distribution • It was assumed that video traffic is burstyConferencing to model Poisson • It was assumed that multiple independent full duplex(light) distribution video streams are occurring simultaneously with random inter-arrival times (video conferencing sessions are random) • "light" was chosen because video quality is heavily dependent upon compression schemes/techniques and algorithms and not so much on network capacity (therefore, "light" is more than adequate for our modeling purposes)
  • Page 5 Table ????• Identify any potential single points of failure. Describe measures you would take to reduce risksassociated with your findings.• Your assessment of the suitability of the existing technologies to handle growth in use ofexisting applications as well as the videoconferencing.• Your high-level recommendations for what TEC should do next.• Selected simulation results to support your assessment and recommendations.Baseline 2 Model Simulation ResultsBaseline 2 Backbone Switch PerformanceThe performance of the backbone switch to which all servers and LANs are connected was analyzed. Thesimulation results are summarized below.Baseline 2 Backbone Switch Performance (refer to , Appendix B)Packets dropped 0 Table ?? - Baseline 2 Backbone Switch Performance Data• The switch appears to have no problems be handling the current volume of traffic from all the LANS andservers as no packets were dropped over the duration of the simulation for all models.Baseline 2 Server Load and UtilizationThe simulation results for the load and utilization of each server for each model above are summarizedbelow. Geographic Order Customer Web Network Info Server Provisioning; Database; and Mgt Facilities and billing; email Server Equipment accounting; Server Inventory Server trouble tickets ServerAvg. CPU Utilization ~1.41 ~0.026 ~0.127 ~3.01 ~0.129(%) for Each Server(refer to Figure ????,Appendix B)Peak Server CPU ~3.35 ~0.034 ~0.173 ~13.5 ~0.233Utilization (%) (refer toFigure ????, AppendixB)Avg. Server Load ~0.720 ~2.56 ~1.430 ~14.42 ~4.51(requests/sec) (refer toFigure ????, AppendixB)Peak Server Load ~1.79 ~3.30 ~2.07 ~26.57 ~7.62(requests/sec) (refer toFigure ????, AppendixB) Table ?? - Baseline 2 Server Load and Utilization Data
  • Page 6• CPU utilization and load across all servers were well within acceptable tolerances.• All observed peaks were well within tolerances and were not areas of concern.Baseline 2 Network Capacity and Utilization(Refer to Figure ????, Figure ????, Figure ????, Appendix B)Avg. Link Utilization - very low: avg. << 1.0 % across all linksAll Links (%)Peak Link Utilization - very low: 1.24 max link utilization from web server to backbone switch, maxAll Links (%) << 1.0 for all other links Table ?? - Baseline 2 Network Capacity and Utilization Data• All links were being lightly utilized.• All observed peaks were well within tolerances and were not areas of concern.Model V Simulation ResultsModel V Backbone Switch PerformanceThe performance of the backbone switch to which all servers and LANs are connected was analyzed. Thesimulation results are summarized below.Model V Backbone Switch Performance (refer to , Appendix B)Packets dropped 0 Table ?? - Model V Backbone Switch Performance Data• The addition of server based videoconferencing seems to have little effect on the performance of thebackbone switch.• The switch appears to have no problems be handling the current volume of traffic from all the LANS andservers as no packets were dropped over the duration of the simulation for all models.Model V Server Load and UtilizationThe simulation results for the load and utilization of each server for each model above are summarizedbelow. Geographic Order Customer Web Network Videoconf Info Server Prov; Database; and Mgt Server Facilities billing; email Server and accounting; Server Equipment trouble Inventory tickets Server ServerAvg. CPU Utilization ~1.43 ~0.026 ~0.126 ~3.02 ~0.120 0.0(%) for Each Server(refer to Figure ????,Appendix B)Peak Server CPU ~5.10 ~0.049 ~0.200 ~20.3 ~0.320 0.0Utilization (%) (referto Figure ????,Appendix B)Avg. Server Load ~0.728 ~2.52 ~1.38 ~13.9 ~4.18 0.0
  • Page 7(requests/sec) (refer toFigure ????, AppendixB)Peak Server Load ~2.67 ~4.83 ~2.28 ~40.8 ~10.7 0.0(requests/sec) (referto Figure ????,Appendix B) Table ?? - Model V Server Load and Utilization Data• No observed peaks were areas of concern.• It is worth noting, however, the addition of videoconferencing appears to slightly increase the overallload and CPU utilization across all servers, most notably the web and email server. Potential problemswith server load as a result of future expansion will likely occur first with the web and email server.• It was noted the videoconferencing server had practically no load and zero CPU utilization which seemsto be consistent with the idea that the server essentially acts as a facilitator that allows videoconferencing totake place between workstations. In essense, it can be thought of as a pass thru that directs video trafficfrom one workstation to another and differentiates between multiple sessions of videoconferencing thatcould be taking place at any given time. Therefore, the amount of server CPU utilization and load will beminimal. Of course, it reality, the server would need some minimum CPU time and utilization toaccomplish this task. Other videoconferencing tasks such video processing and compression takes place onthe client workstations.Model V Network Capacity and Utilization(Refer to Figure ????, Figure ????, Figure ????, Appendix B) Avg. Link Utilization (%)Eng LAN to/from backbone switch ~54.0%Backbone switch to/from videoconf server ~54.0%test workstation to/from Eng LAN (10BaseT link) ~13.4%all other links avg. << 1.0% Peak Link Utilization - (%)Eng LAN to/from backbone switch ~58.0Backbone switch to/from videoconf server ~57.0test workstation to/from Eng LAN (10BaseT link) ~14.5%all other links avg. << 1.0% Table ?? - Model V Network Capacity and Utilization Data• Link utilization on the 10BaseT link between two workstations during videoconferencing sessions arewell within acceptable tolerances.• It is assumed that there are multiple videoconferencing sessions in progress so that link utilization fromthe Eng LAN object and the backbone switch should reflect the aggregate traffic that is directed from 40workstations to the videoconferencing server. Likewise, the link between the backbone switch and thevideoconferencing server should be the same (traffic on the first link continues on to through the bridge tothe link to the videoconferencing server).
  • Page 8Recommended actions to be taken by TEC and concluding remarksAppendix A: Model Descriptions
  • Page 9Appendix B: Supporting Simulation Results and Statistics SIMULATION RESULTS - Baseline Model 2 Figure A1 Baseline 2 Backbone Switch Packets Dropped Figure A2 Baseline 2 CPU Utilization (%) of Each Server Figure A3
  • Page 10 Baseline 2 Load (requests/sec) on Each Server Figure A4Baseline 2 Server Load (request/sec) by Application - Database (heavy, light) Figure A5 Baseline 2 Server Load by Application - Email (light) Figure A6 Baseline 2 Server Load by Application - FTP (light, heavy) Figure A7 Baseline 2 Server Load by Application - HTTP (light)
  • Page 11 Figure A8 Baseline 2 Link Utilization - point to point (%) Across all Links Figure A9Baseline 2 Link Utilization - point to point (%) Across All Links 2
  • Page 12 SIMULATION RESULTS - Model V Figure B1 Model V Backbone Switch Packets Dropped Figure B2 Model V CPU Utilization (%) of Each Server Figure B3 Model V Load (requests/sec) on Each Server Figure B4Model V Server Load (request/sec) by Application - Database (heavy, light)
  • Page 13 Figure B5 Model V Server Load by Application - Email (light) Figure B6 Model V Server Load by Application - FTP (light, heavy) Figure B7 Model V Server Load by Application - HTTP (light) Figure B8Model V Link Utilization - point to point (%) Across all Links
  • Page 14 Figure B9 Model V Link Utilization - point to point (%) Across All Links 2 Model V - Modified with 1000BaseX (Gigabit Ethernet) Links Figure C1Model V - Modified Link Utilization (%) - point to point across all links
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