Optimización de la metodología utilizando los coeficientes

tation

This section presents the results of performance measurements of the Virtual Network Configuration algorithm. The Virtual Network Configuration algorithm has been im- plemented for Rapidly Deployable Radio Network. Measurements have been taken in the environment shown in Figure 5.1. As mentioned previously, Global Position- ing System (GPS) location is simulated such that Remote Nodes move in a linear path where the initial direction is chosen at random. The complete Network Control Proto- col (NCP) code is used in this emulation environment except for the simulated Global Positioning System receiver which replaces the actual Global Positioning System driver interface code. In addition the beam table creation and download time is replaced with a delay which can be changed to examine the effect of task execution time on Virtual Network Configuration performance. The beam steering code includes beam steering optimization [40] between the Edge Switch and Remote Node nodes. Thus, most of the Network Control Protocol code is exercised in this emulation.

The details of the Network Control Protocol operation have been discussed in Sec- tion 2.5. A position update message (USER POS) is sent by Remote Node nodes to Edge Switch nodes in order to update the Remote Node location. The first measurement is the time to process a position update message. This time begins from the receipt of an Remote Node position update message and ends when the Remote Node position update message has been processed. This may include the creation and download of a new beam table. When Virtual Network Configuration is disabled, the resulting beam creation times are shown in Figure 5.2. The y-axis in Figure 5.2 plots the time required

emulated real PC PR GPS PC PR GPS Ethernet KBOWTN _KBOWTC

ES

RN

to generate a beam table. The x-axis identifies a particular USER POS message. There is not a significant variation in the beamform delay.

0 2 4 6 8 10 0 5 10 15 20 25 30

Beamform Delay (Secs)

USER_POS Instance Beamform Time

KBOWTN Beamform Time (No VNC)

Figure 5.2: Edge Switch Beamforming Time without VNC.

The orderwire network load as a function of time as measured on the Edge Switch without Virtual Network Configuration is shown in Figure 5.3 and the orderwire load due to the Remote Node is shown in Figure 5.4. The load is normalized in terms of Data Encryption Standard encoded packets per second and is averaged over one second intervals. The traffic on the orderwire consists of the initial Edge Switch configuration followed by the Remote Node position update messages and handoff messages. The initial load shown in Figure 5.3 is caused by the Edge Switch configuration which quickly tapers off as Edge Switch configuration ends and HANDOFF messages may be transmitted.

The beam creation time is 3.5 times faster if the beam results have been cached, thus the speedup as determined from the analysis is shown in Figure 5.14. The ex-

0 0.05 0.1 0.15 0.2 0.25 0 100 200 300 400 500 600 700 800 900 1000 Load (Pkts/Sec) Time (Secs) Load

KBOWTN Orderwire Output Packets (No VNC)

Figure 5.3: Edge Switch Orderwire Load without VNC.

0 0.05 0.1 0.15 0.2 0.25 0 100 200 300 400 500 600 700 800 900 1000 Load (Pkts/Sec) Time (Secs) Load

KBOWTC Orderwire Output Packets (No VNC)

pected beam creation time without Virtual Network Configuration was 8.0 seconds. With perfect prediction, the expected beam creation time with Virtual Network Config- uration was 2.29 seconds for a speedup of 3.5 times. The measured results are plotted with Figure 5.14 in Figure 5.14. The Virtual Network Configuration algorithm using perfect position prediction generated the beamform delay shown in Figure 5.5. The beam creation time has been significantly reduced. Figure 5.6 shows the Virtual Net- work Configuration orderwire traffic load from the Edge Switch and Figure 5.7 shows the load from the Remote Node. The load is approximately double the load shown in Figure 5.3. 0 2 4 6 8 10 0 5 10 15 20 25 30

Beamform Delay (Secs)

USER_POS Instance Beamform Time

KBOWTN Beamform Time (Pr[Out of Tol.]=0.0)

Figure 5.5: ES Beam formation Time with VNC and No Prediction Error.

Figure 5.8 shows the Remote Node Local Virtual Time as a function of time. This figure shows the Local Virtual Time quickly reaching the 30 second lookahead and de- laying until the end of the lookahead window as expected. The prediction rate shown in Figure 5.8 is 1.23 virtual seconds per second as determined from the analysis in Section

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0 100 200 300 400 500 600 700 800 900 1000 Load (Pkts/Sec) Time (Secs) Load

KBOWTN Orderwire Output Packets (Pr[Out of Tol.]=0.0)

Figure 5.6: ES Orderwire Load with VNC and No Prediction Error.

0 0.05 0.1 0.15 0.2 0.25 0 100 200 300 400 500 600 700 800 900 Load (Pkts/Sec) Time (Secs) Load

KBOWTC Orderwire Output Packets (Pr[Out of Tol.]=0.0)

4.3.3 givenvm

= 0

:

03

virtual messages per millisecond,

vm

= 30

:

0

milliseconds, task

= 7

:

0

milliseconds,rb

= 1

:

0

milliseconds,

S

parallel

= 1

:

5

and

C

r

= 100

where

C

r

is the speedup gained from reading the cache over computing the result. These param- eters were chosen to accommodate the Edge Switch topology task which is currently the most time consuming Rapidly Deployable Radio Network operation and precludes the Edge Switch nodes from becoming mobile without Virtual Network Configuration. Figure 5.9 shows the Edge Switch Local Virtual Time as a function of time. The Edge Switch Local Virtual Time is driven by the Receive Time (TR) of messages entering its input queue from the Remote Node. Thus the Edge Switch Local Virtual Time is similar to the Remote Node Local Virtual Time.

0 100 200 300 400 500 600 700 800 900 0 100 200 300 400 500 600 700 800 900 LVT (Secs)

Real Time (Secs) Prediction Rate

KBOWTC LVT vs Real Time (Pr[Out of Tol.]=0.0)

Figure 5.8: Remote Node LVT with VNC and No Prediction Error.

The next set of results show the performance of the Virtual Network Configura- tion algorithm as the prediction algorithm becomes less perfect. The predicted values are degraded in the driving process by adding an exponentially distributed error to the

0 100 200 300 400 500 600 700 800 900 0 100 200 300 400 500 600 700 800 900 1000 LVT (Secs)

Real Time (Secs) Prediction Rate

KBOWTN LVT vs Real Time (Pr[Out of Tol.]=0.0)

Figure 5.9: ES LVT with VNC and No Prediction Error.

predicted values. As discussed in the analysis section, rollback will increase the load on the orderwire and increase the user position message processing time. Figure 5.10 shows the Edge Switch orderwire load under the presence of rollback and Figure 5.11 shows the Remote Node load.

Compare the Edge Switch load without Virtual Network Configuration Figure 5.3, the Edge Switch load with Virtual Network Configuration and no prediction error in Figure 5.6, and the Edge Switch load with Virtual Network Configuration and large prediction error 5.10. The first peak in all the Edge Switch figures is the initial MY-

CALL packet broadcast upon startup. The next peak is the initial HANDOFF packet

sent from the Edge Switch to the Remote Node. Notice that the handoff occurs earlier in Figure 5.6 than it does in Figure 5.3. This due to the speedup gained via Virtual Net- work Configuration. However, in Figure 5.10, a third peak occurs which is a HAND-

prediction was out of tolerance. Once the handoff location has been corrected by the

HANDOFF anti-message, no additional messages are sent from the Edge Switch.

0 0.1 0.2 0.3 0.4 0.5 0.6 0 100 200 300 400 500 600 700 800 900 1000 Load (Pkts/Sec) Time (Secs) Load

KBOWTN Orderwire Output Packets (Pr[Out of Tol.]=0.243)

Figure 5.10: ES Orderwire Load with VNC and Large Prediction Error.

Figure 5.13 shows the analytical and measured bandwidth overhead as the predic- tion error increases. The bandwidth overhead increases by a small amount above twice the non-Virtual Network Configuration bandwidth as expected in the analysis. Figure 5.14 shows the analytical and measured speedup in the processing of a USER POS packet as the prediction error increases. The measured results have a slightly lower speedup for low out-of-tolerance message probability and higher speedup than the ana- lytical results for higher out-of-tolerance message probabilities. There are several pos- sible explanations for the inaccuracy. First, the emulation was done on a shared proces- sor with many other unrelated processes with different processor scheduling priorities. It is possible that these other processes have influenced the real time results. Second, the beam table creation task measured in this experimental implementation uses the

0 0.05 0.1 0.15 0.2 0.25 0 100 200 300 400 500 600 700 800 900 Load (Pkts/Sec) Time (Secs) Load

KBOWTC Orderwire Output Packets (Pr[Out of Tol.]=0.243)

Figure 5.11: RN Orderwire Load with VNC and Large Prediction Error.

0 100 200 300 400 500 600 700 800 900 0 100 200 300 400 500 600 700 800 900 LVT (Secs)

Real Time (Secs) Prediction Rate

KBOWTN LVT vs Real Time (Pr[Out of Tol.]=0.243)

Virtual Network Configuration time warp mechanism across two different processors. The simplified speedup analysis for the contribution of time warp to Virtual Network Configuration speedup may not be precise enough. Finally, the analysis assumed an average time to perform the standard rollback (rb) operations such as restoring the

Logical Process state to a previously saved state from the State Queue (SQ) and mod- ifying the Local Virtual Time. The actual time to perform a rollback may be smaller than the value used in the analysis. Over estimatingrb would have little or no effect

when

Y

is small, but it would have a larger effect as

Y

increases which appears to be the case in Figure 5.14.

1.9 1.92 1.94 1.96 1.98 2 2.02 2.04 2.06 2.08 0 0.2 0.4 0.6 0.8 1 Bandwidth Overhead Probability of Rollback

VNC Bandwidth Overhead Experimental Validation

Analytical Measured

Figure 5.13: VNC Bandwidth Overhead.

0.5 1 1.5 2 2.5 3 3.5 0 0.2 0.4 0.6 0.8 1 VNC Speedup (S) Y

VNC Speedup Experimental Validation

Analytical Measured

Figure 5.14: ES Beam Creation Speedup.

In document Determinación de los coeficientes para las variables de decisión de una metodología de planificación energética a comunidades rurales aisladas en la provincia Granma-Cuba. Estudio de caso Las Peladas. (página 76-92)