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188 are summarised, before potential extended functionality is presented in Section 4.3. Control Generator Analyser System under test Figure 4.1 The ATM 100 measurement system with multiple STGs in a bulk load configuration Model database Software Hardware Pattern editor Source-type editor Profile editor Figure 4.2 STG system block diagram Scenario editor 4.1 Design 4.1.1 The measurement system The work on the STG was started during the RACE project PARASOL (R 1083). X-windows MMI Manual load control STG module handler VME/VXI Interface STG Kernel Run time control PARASOL was established to define measurement and validation methods for ATM systems and to develop prototype equipment. At the end of the project, beginning of 1993, a complete modular measurement system was available. For a more detailed presentation of PARASOL see [32] and [33]. After the conclusion of the PARASOL project, its prime contractor Wandel und Golterman (D) started work on turning the prototype into an industrial pilot series named ATM 100. This effort included a complete redesign and redevelopment of the measurement control system. <strong>Telenor</strong> Research and DELAB have carried out this work related to the STG as a part of an agreement between NTR and W&G. This enhanced system is now running in a number of sites. An overview of this system is given in Figure 4.1. It consists of three parts. The generator which produces load, including test cells, towards the system under test (SUT), the analyser which analyses the test cells from the SUT and the control workstation which is used for setting up the instrument, control during measurements and for presentation of the results. These three parts may reside in the same physical cabinet, or they can be distributed over a wide area, e.g. to measure the traffic flow through a network. In addition, the X-window based MMI allows remote operation of the control system. The measurement system is based on modules with different functionality, as indicated in the figure. Each module performs a specific task. For instance, important modules of the analyser are - the module which traces a subset of the connections or a complete cell-stream, and - the module which performs a real time analysis of properties of the cell stream and presents them on the MMI. This modularity makes ATM 100 a flexible tool, which is easily reconfigured to perform a wide range of measurements, like bulk load generation as in Figure 4.1, and real time analysis of live traffic 2 . In the following it will be concentrated on the STG. 2 For further information about the ATM 100 measurement system, we refer to Wandel und Golterman.
4.1.2 The STG overview The purpose of the STG is to generate traffic with properties similar to a multiplex of independent sources where each source has a behaviour close to real source. The software and hardware elements that constitute the STG sub-system are shown in Figure 4.2. The software runs on a SUN SPARC under SOLARIS 2.3. It includes an Open Windows based man machine interface (MMI), several graphical editors, the STG Module Handler performing the necessary checking and compilation of source types and scenarios and the STG specific drivers. The system also contains the STG database which includes various set-ups, scenarios, source-type definitions, etc. 4.1.3 The STG hardware The hardware is made as a two slot Csize VXI module. It consists of 12 FPGAs (field programmable gate arrays), each in the range 10,000–20,000 gates and 10 Mbit of RAM. One of the slots serves as the VME/VXI interface, which handles the communication with the rest of the instrument. The other slot is the STG kernel and handles the composite source model. The functionality is arranged as shown in Figure 4.3. In the block to the left, the next time and old/new state are found for the next state change, cf. (3) and (4) of Table 2.1. These are transferred to the next block, and the block is ready for the next operation. The FIND SOURCE block finds the source for the state change, cf. (5) and (6), and finds the pattern associated with the new state. These data are sent down to the UPDATE PATTERN block together with the time when the pattern should be updated. The FIND SOURCE block also handles the activations/deactivations sent by the software, and the long patterns. Long patterns are handled as a set of normal patterns resulting in a “state change” for each new part of the long pattern. The UPDATE PATTERN block updates up to 8 state changes in parallel, at the time requested. The old patterns are removed from the PCTP (periodic cell transmission pattern) and the new ones added, see Figure 2.13. Every 2.7 microsecond a source_id is read out from the PCTP and sent to the ASSEMBLE CELL block. This block uses the source_id from the PCTP as a pointer to a cell with header and payload, Find: next time old state new state Next time Old state New state Activation Deactivation Find: source Handle: Activation deactivation Long Pattern Figure 4.3 The STG hardware block diagram and sends this cell out to the next module in the test tool. A cell may be transformed into a test cell (foreground traffic) before it ends up in the output module (OM). The two blocks to the left in Figure 4.3, which handle the stochastic parts of the model, use four Tausworthe pseudo-random generators with primitive trinomials between 25 and 34 bit [34, 35]. The sequence lengths of each random generator are mutually prime. To ensure no correlation between the numbers, the generators are clocked as many time as their length between each time a number is used. The activation and deactivation are used to emulate the connection level. The software sends activation and deactivation messages to the hardware at the time these should take place according to the load profiles. There will be one profile for each pair of source type and destination in the network, see Table 2.2 for an example. In a profile the number of sources for this pair will vary according to the graph. When the level changes, the software selects which sources to activate/deactivate. Since the properties of all the source of the same type toward the same destination are identical, an arbitrary selection of these may be chosen. The software handles simultaneously all profiles for all source types toward all destinations, cf. Figure 2.14. When a profile changes, the activation/deactivation which corresponds to the change will be sent to the hardware. The changes are effectuated in the hardware as soon as possible, which is maximum eight activations or deactivations per 0.1 ms and, on the average, seven at nominal load. Next time Next source Next pattern ATM-cell Update pattern Assemble cell Update Cell pointer Periodic cell transmission pattern 4.1.4 The STG software The software is written in C. The volume of the executable is about 12.5 Mbytes and on-line help, database, etc. occupy a similar volume. An outline of the various software elements is presented in Figure 4.2. The Scenario editor is in many ways the core of the STG software. For each measurement, a scenario is defined. In this editor the number of sources, source types, destinations, cell headers/payloads and load profiles are put together, see Table 2.2. It also checks the parameters and calculates values, like average and maximum load, average rate of state and pattern changes. Graphs like the expected load as a function of time and type/destination are also calculated and presented to the user, see Figure 2.14. Load profiles for activation – deactivation, i.e. handling the connection level, are defined in the Profile editor as a graph of how many sources that are active at any measurement instant. The graphs are similar to those indicated in Table 2.2. The hardware is initialised and controlled through the STG module handler. When a measurement shall be carried out it calculates the necessary parameters to set the STG in a steady state for the actual load scenario, transforms the scenario definition to the format required by the STG and downloads the data to the hardware. The Source type editor allows an efficient definition of state diagrams with a “bubble” for each state containing name, sojourn time and a pattern_id, arrows between the states hold the next state probabilities, i.e. similar to what is indi- 189
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Page 162 and 163: 160 Throughput [Mbit/s] Throughput
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Page 168 and 169: 166 Throughput [Mbit/s] Throughput
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Page 232 and 233: 230 Terminals/ Terminal Adapters
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