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Analysis of the Impact and Interactions of Protocol and Environmental Parameters on Overall MANET Performance. Michael W. Totaro and Dmitri D. Perkins Center for Advanced Computer Studies University of Louisiana at Lafayette Presented by Michael W. Totaro. Topics.
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Analysis of the Impact and Interactions of Protocol and EnvironmentalParameters on Overall MANET Performance Michael W. Totaro and Dmitri D. Perkins Center for Advanced Computer Studies University of Louisiana at Lafayette Presented by Michael W. Totaro
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
Introduction and Motivation • Important design challenge of MANETs: maximize overall performance of protocols operating in a MANET • Impact that one or more factors have on MANET performance? • 2k factorial design—an important tool that may aid researchers in analyzing effect of factors on MANET performance
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
2k Factorial DesignProcess • Code each factor to a “+” and a “-” level • Design matrix: All possible combinations of factor levels • Example for k = 3 factors: Make the 8 simulation runs, and measure the effects of the factors!
2k Factorial DesignMain Effect of a Factor Main effect of a factor is the average difference in the response when this factor is at its “+” level as opposed to its “-” level:
2k Factorial DesignMain Effect of a Factor – cont’d The main effects measure the average change in the response due to a change in an individual factor, with this average being taken over all possible combinations of the other k-1 factors (numbering 2k-1).
2k Factorial DesignMain Effect of a Factor – cont’d We can rewrite the above as “Factor 1” column ● “Response” column / 2k-1 -R1 + R2 – R3 + R4 – R5 + R6 – R7 + R8 e1 = 4
2k Factorial DesignFactor Interaction • Two factors A and B are said to interact if the effect of one depends upon the level of the other • Conversely, these two factors, A and B, are said to be noninteracting if the performance of one is not affected by the level of the other • We shall look at examples of interacting factors and noninteracting factors
2k Factorial DesignExamples of Noninteracting and Interacting Factors Noninteracting Factors As the factor A is changed from level A1 to level A2, the performance increases by 2 regardless of the level of factor B Interacting Factors As the factor A is changed from level A1 to level A2, the performance increases either by 2 or 3 depending upon whether B is at level B1 or level B2, respectively
2k Factorial DesignExamples of Noninteracting and Interacting Factors – cont’d 8 8 Performance Performance B2 A2 6 6 B1 A1 2 2 A1 A2 B1 B2 (a) No Interaction 8 8 B2 Performance Performance A2 6 6 B1 A1 2 2 A1 A2 B1 B2 (b) Interaction Graphical representation of interacting and noninteracting factors.
2k Factorial DesignInteraction Effects 1 x 3 interaction effect: “Factor 1” ● “Factor 3” ● “Response” / 2k-1 • Addresses the question: “Does the effect of a factor depend on level of others?” R1 - R2 + R3 - R4 – R5 + R6 – R7 + R8 e13 = 4 • Sign of effect indicates direction of effect on response of moving that factor from its “-” to its “+” level
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
Related Work • Interest in cross-layer factor interaction in MANETs is not entirely new. • Performance metrics for assessing the behavior of MANETs are identified, discussed, and, most especially, partitioned into three classification levels [1] • Thread-task level metrics (algorithmic level) such as average power expended and task completion time • Diagnostic packet level metrics such as end-to-end throughput, end-to-end delay, link utilization, and packet loss, which characterize network behavior at the packet level • Scenario metrics that describe the network environment and define the scenario; these include: nodal movement/topology rate of change, number of network nodes, area size of network, density of nodes per unit area, offered load and traffic patterns, and number of unidirectional links
Related Work – cont’d • A comprehensive analysis of five factors—node speed, pause-time, network size, number of traffic sources, and type of routing (source vs. distributed)—was done using a factorial experimental design in an effort to identify and quantify the effects and two-way interactions of these factors on three performance responses: throughput, average routing overhead, and power consumption [2] • Potential benefits may be derived by information exchange between the lower layer, routing layer, and transport layer, which is useful in the design and standardization of an adaptive architecture that can exploit the interdependencies among link, medium access, network, and applications protocols [3] • The underlying premise in cross-layer interaction analyses is that, by learning more about factor and two-way interactions on the performance of MANETs, researchers may want to consider taking these effects into account in the design of future protocols
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
Methodology Effects of factors?
Methodology – cont’d Partial Design Grid (Coded)
Methodology – cont’d Partial Design Grid (Uncoded)
Methodology – cont’d • Simulation—QualNet • 26 factors = 64 experimental runs • Replications = 5 • Total running time = 320 seconds • LAR1 routing protocol • Free-space model • 2 Mbps • Packet size = 512 bytes • Pause time = 25 seconds • Transmission range = 250 meters • Terrain dimensions*: N = √ [ (MR2π / X) – 1 ] where X = average number of neighbors M = number of nodes R2 = transmission range *Using the formula for computing the average number of neighbors for a node, derived by Ihklas Ajbar.
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
Analysis, Results, and Models Scatterplot—Packet delivery ratio
Analysis, Results, and Models Scatterplot—End-to-end delay
Analysis, Results, and Models Scatterplot—Control packet overhead
Analysis, Results, and Models Main effects—Packet delivery ratio
Analysis, Results, and Models – cont’d Main effects—End-to-end delay
Analysis, Results, and Models – cont’d Main effects—Control packet overhead
Analysis, Results, and Models – cont’d Two-way factor interactions—Packet delivery ratio
Analysis, Results, and Models – cont’d Two-way factor interactions—Control packet overhead
Analysis, Results, and Models – cont’d Two-way factor interactions—End-to-end delay
Analysis, Results, and Models – cont’d Response-surface plots
Analysis, Results, and Models – cont’d Contour plots
Analysis, Results, and Models – cont’d Predictive effects—Packet delivery ratio
Analysis, Results, and Models – cont’d Predictive effects—End-to-end delay
Analysis, Results, and Models – cont’d Predictive effects—Control packet overhead
Analysis, Results, and Models – cont’d Prediction profile
Analysis, Results, and Models – cont’d Regression Models—Packet delay ratio
Analysis, Results, and Models – cont’d Regression Models—End-to-end delay
Analysis, Results, and Models – cont’d Regression Models—Control packet overhead
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
Future Work and Open Questions • Validation of prediction (regressions) models • Other factors (e.g., power consumption, etc.)? • Other empirical models (e.g., neural networks, time-series prediction)?
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
Questions • Thank you!
Topics • Introduction and Motivation • 2k Factorial Design (A Brief Tutorial) • Related Work • Methodology • Analysis, Results, and Models • Future Work and Open Questions • Questions • References
References • M. W. Subbarao, “Ad Hoc Networking Critical Features and Performance Metrics”. White paper, Wireless Communications Technology Group, National Institutes of Standards and Technology, September 15, 1999 • D. D. Perkins, H. D. Hughes, and C. B. Owen, “Factors Affecting the Performance of Ad Hoc Networks”. Proceedings of IEEE International Conference on Communications (ICC 2002), New York, April 2002 • J. Lee, S. Singh, and Y. Roh, “Interlayer Interactions and Performance in Wireless Ad Hoc Networks,” Internet – Draft, IRTF ANS Working Group; http://www.flarion.com/ans-research/Drafts/draft-irtf-ans-interlayer-performance-00.txt, accessed 1/29/2004