[ndnSIM] Fwd: Memory and Time Consumption - ndnSIM(v1) Simulations

[Andriana Ioannou]

Dear all,

I have recently been running a number of experiments to support my
research. However, I have found myself facing some issues with regard to
both memory and time consumption. My experiments' setup may be summarised
as follows:

Catalog Size:                                      1000000 & 100000000
objects
Network Topologies:                           Tiscali AS-3257 & Excodus
AS-3967 (75 & 97 routers / 56 & 58 gateways, respectively)
Object Size:                                        1000 chunks on average
Chunk Size:                                        10KB (10240 virtual
payload)
Cache Size:                                        100000 chunks, 1000000
chunks, 10000000 chunks
Number of Producers:                        1
Number of Consumers:                      150 on average installed at each
gateway
Popularity Distribution:                        Weibull Distribution
Interests Window:                               1
ΔΤ between subsequent Interests:     0ms

Based on the aforementioned setup, I am only able to run experiments when
my cache size is equal to 100000 chunks (the smallest). The memory
consumption for this scenario is about 10GBs - for as long as I have
recorded. The time consumption may vary depending on how many cores I am
using to run the experiments and how fast my CPU is, from 8 hours to 10
hours or so. At this point I should state that these numbers refer to code
using MPIs.

Consulting the documentation on ndnSIM simulator, these numbers look
reasonable to me since eg a single CS entry in ndnSIM v1 may take about
0.75KBs, while taking into account the memory consumption of the rest
architectural components. I do find that the time consumption is related to
the fact that a large number of Interests is generated while no time
interval has been applied between them.

So, my first question is, does this look reasonable to you too? Is this
something that is indeed to be expected?

And my second question is if so, is there a way to avoid this and run
larger experiments?

Kind regards,
Andriana.
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