Class No 03 & 09Review:The validation of large-scale network models and simulation of wireless and mobile networks inthe r...
Class No 03 & 09network is thus correct if the underlying simulation is correct, and if no unwanted artifacts areintroduce...
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Validation of Wireless and Mobile Network Models and Simulation Paper Review

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Review of the paper titled as Validation of Wireless and Mobile Network Models and Simulation

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Validation of Wireless and Mobile Network Models and Simulation Paper Review

  1. 1. Class No 03 & 09Review:The validation of large-scale network models and simulation of wireless and mobile networks inthe real world is not easily or accurately repeatable, due to the complications and subtleties ofphysical movement and wireless propagation, making the system highly variable and extensivelyincreasing the complex interactions between the system parts and the surrounding environment,thus reducing the use of such experiments for validation.In particular, the position and movement of nodes in the network and the position and possiblemovement of other objects in the environment around the nodes themselves, such as buildings,mountains, and trees, or vehicles, people, and rain, can significantly affect the behavior andperformance of the system being modeled. Furthermore, to accurately control an entireexperiment in the real world, all of these positions and movements would need to be controlled.Models and real experiments, to some degree, can only be approximations as having completecontrol over all of the factors is simply not fully achievable in any real system.In this paper, few validation approaches are suggested that can be used to compare different runsusing simulation, emulation, or measurements from the real world. These approaches seem to beappropriate at least for small- or medium-scale networks, and should be able to be applied tolarge-scale networks given suitable choices by the modeler.In simulation work, a system is created for emulating an ad hoc network on a stationary, wirednetwork. Network emulation allows a stationary, wired network to be made to behave in thesame way as a wireless network by altering the one network’s behavior, as seen by packets onthe network, to perform like the other’s. Ad hoc network emulation for simple wireless networksis demonstrated by creating two alternate approaches in the trace modulation.In the “trace emulation” approach, a trace of the desired network’s behavior is generated usingsimulation, and then uses this trace to drive the standard trace modulation system in the operatingsystem kernel of the real machines on the real network; each packet is then delayed or droppedunder control of trace modulation. In the “direct emulation” approach instead, each packet from areal machine is sent to a centralized machine on which a simulation of the desired network isrunning, if the packet is not dropped within the simulation, it is then resent on the real network atthe appropriate time to its real destination. In either approach, the behavior of the emulated
  2. 2. Class No 03 & 09network is thus correct if the underlying simulation is correct, and if no unwanted artifacts areintroduced in the emulation process.Initial approaches to the validation of simulation work, were to check the operation of the systemaccording to a number of logical consistency checks. Although initial validation checks giveconsiderable confidence in results, they do not actually fully validate the simulator resultsmatching to the real world. By substantial logging information provided by ad hoc networktestbed implementation, the identical movement and communication scenarios can be simulatedthat are experienced in these real implementation experiments and only then will be able toassess the degree to which the results from the simulator match those from the real world.One approach to comparing the results from simulations and real measurements (or emulations)that was considered is a comparison based on the progression of some performance metric as afunction of time. For example, rather than simply comparing results at the end of the simulationrun and at the end of the measurements from the real world, it become possible to compare thesimulated and measured systems using graphs over each instant of time. Such graphs, known astime-sequence number plots, show not only the total results, but also show the changes overtime. Similar graphs could be produced for other performance metrics of interest.An example presented shows three time-sequence number plots for the TCP connection betweenthe two nodes in a 16-node ad hoc network. The top curve shows the connection’s behavior in acompletely simulated ad hoc network using simulator, while the other two curves show the sameconnection’s behavior when run on an emulated ad hoc network, using the two differenttechniques for emulation that was developed. Due to the experimental setup, the network emulation curve are shifted from simulator results,The shape of the direct emulation curve tracks the simulation curve more tightly than the traceemulation curve, although the absolute RMS error is significantly greater.An alternative approach to validation could be to record a trace of all significant events (e.g., allpackets sent, received, or forwarded) during the experiment in the real network, and to create asimilar trace during a corresponding simulation run. The two trace files could then be compared.However, such a comparison seems to be extremely difficult to perform, since each tracerepresents the intertwined events caused by many different nodes and traffic streams in thenetwork. Each of these events possibly influences other events in the trace and may also beindependent of yet other events. Many events in the trace may even be able to be ignored, but itseems hard to identify which without risking too much abstraction and introducing inaccuracy.So currently research is running to find the possible methods for turning this general tracecomparison approach into a more concrete algorithm.Hence we can say that the validation approaches suggested in this paper can be used to comparedifferent runs using simulation, emulation, or measurements from the real world. They seem tobe appropriate at least for small- or medium-scale networks, and should be able to be applied tolarge-scale networks provided that suitable choices given by the modeler.

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