Webcachesim v2 is available, with many improvements. Please it check out HERE.
Simulate a variety of existing caching policies by replaying request traces, and use this framework as a basis to experiment with new ones.
The webcachesim simulator was built for the AdaptSize project, see References for more information.
We replay production traffic from a CDN server operated by the Wikimedia Foundation, and consider various modern caching policies.
You will need a compiler that supports C++11, e.g., GCC 4.8.1 upwards (with -std=c++11). Older compilers that partially support C++11, e.g., GCC 4.4, can compile (with -std=c++0x).
Then, get started with
make
The basic interface is
./webcachesim traceFile cacheType cacheSize [cacheParams]
where
- traceFile: a request trace (see below)
- cacheType: one of the caching policies (see below)
- cacheSize: the cache capacity in bytes
- cacheParams: optional cache parameters, can be used to tune cache policies (see below)
Request traces must be given in a space-separated format with three colums
- time should be a long long int, but can be arbitrary (for future TTL feature, not currently in use)
- id should be a long long int, used to uniquely identify objects
- size should be a long long int, this is object's size in bytes
| time | id | size |
|---|---|---|
| 1 | 1 | 120 |
| 2 | 2 | 64 |
| 3 | 1 | 120 |
| 4 | 3 | 14 |
| 4 | 1 | 120 |
Example trace in file "test.tr".
There are currently ten caching policies. This section describes each one, in turn, its parameters, and how to run it on the "test.tr" example trace with cache size 1000 Bytes.
does: least-recently used eviction
params: none
example usage:
./webcachesim test.tr LRU 1000
does: first-in first-out eviction
params: none
example usage:
./webcachesim test.tr FIFO 1000
does: greedy dual size eviction
params: none
example usage:
./webcachesim test.tr GDS 1000
does: greedy dual-size frequency eviction
params: none
example usage:
./webcachesim test.tr GDSF 1000
does: least-frequently used eviction with dynamic aging
params: none
example usage:
./webcachesim test.tr LFUDA 1000
does: LRU eviction + admit only after N requests
params: n - admit after n requests)
example usage (admit after 10 requests):
./webcachesim test.tr Filter 1000 n=10
does: LRU eviction + admit only after N requests
params: t - the size threshold in log form (base 2)
example usage (admit only objects smaller than 512KB):
./webcachesim test.tr ThLRU 1000 t=19
does: LRU eviction + admit with probability exponentially decreasing with object size
params: c - the size which has a 50% chance of being admitted (used to determine the exponential family)
example usage (admit objects with size 256KB with about 50% probability):
./webcachesim test.tr ExpLRU 1000 c=18
does: evict object which has oldest K-th reference in the past
params: k - eviction based on k-th reference in the past
example usage (each segment gets half the capacity)
./webcachesim test.tr LRUK 1000 k=4
does: uses adaptive ExpLRU (ExpProb-LRU) policy that adapts with request traffic, adapted from the official implementation
params: t - reconfiguration interval (default 500K), i - numeric iteration (precision, default 15)
example usage
./webcachesim test.tr AdaptSize 1000 t=1000000 i=5
One example is a Pareto (Zipf-like) popularity distribution and Bounded-Pareto object size distribution. The "basic_trace" tool takes the following parameters:
- how many unique objects
- how many requests to generate for most popular object (total request length will be a multiple of that)
- Pareto shape
- min object size
- max object size
- output name for trace
Here's an example that recreates the "test.tr" trace for the examples above. This uses the "basic_trace" generator with 1000 objects, about 10000 requests overall, Pareto shape 1.8 and object sizes between 1 and 10000 bytes.
g++ tracegenerator/basic_trace.cc -std=c++11 -o basic_trace
./basic_trace 1000 1000 1.8 1 10000 test.tr
make
./webcachesim test.tr 0 LRU 1000
Example: download a public 1999 request trace (trace description), rewrite it into our format, and run the simulator.
wget http://www.cs.bu.edu/techreports/1999-011-usertrace-98.gz
gunzip 1999-011-usertrace-98.gz
g++ -o rewrite -std=c++11 ../traceparser/rewrite_trace_http.cc
./rewrite 1999-011-usertrace-98 test.tr
make
./webcachesim test.tr 0 LRU 1073741824
All cache implementations inherit from "Cache" (in policies/cache.h) which defines common features such as the cache capacity, statistics gathering, and the request interface. Defining a new policy needs little overhead
class YourPolicy: public Cache {
public:
// interface to set arbitrary parameters request
virtual void setPar(string parName, string parValue) {
if(parName=="myPar") {
myPar = stof(parValue);
}
}
// requests call this function with their id and size
bool request (const long cur_req, const long long size) {
// your policy goes here
}
protected:
double myPar;
};
// register your policy with the framework
static Factory<YourPolicy> factoryYP("YourPolicy");
This allows the user interface side to conveniently configure and use your new policy.
// create new cache
unique_ptr<Cache> webcache = move(Cache::create_unique("YourPolicy"));
// set cache capacity
webcache->setSize(1000);
// set an arbitrary param (parser implement by yourPolicy)
webcache->setPar("myPar", "0.94");
Want to contribute? Great! We follow the Github contribution work flow. This means that submissions should fork and use a Github pull requests to get merged into this code base.
There are a couple ways to help out.
Tell us how you use webcachesim or how you'd want to use webcachesim and what you're missing to implement your use case. Feel free to create an issue for this purpose.
If you come across a bug in webcachesim, please file a bug report by creating a new issue. This is an early-stage project, which depends on your input!
This project has not be thoroughly tested, any test cases are likely to get a speedy merge.
If you want to add a new caching policy, please augment your code with a reference, a test case, and an example. Use pull requests as usual.
We ask academic works, which built on this code, to reference the AdaptSize paper:
AdaptSize: Orchestrating the Hot Object Memory Cache in a CDN
Daniel S. Berger, Ramesh K. Sitaraman, Mor Harchol-Balter
To appear in USENIX NSDI in March 2017.
You can find more information on USENIX NSDI 2017 here.