Add BeladyOnline

[JasonGuo98]

I have implemented Belady's MIN algorithm as follows:

for obj in trace:
    if(max(occ_array[obj.last_access_vtime, current_vtime]) + obj.size <= cache_size):
        # The object should be inserted into the cache at its last_access_vtime
        occ_array[obj.last_access_vtime, current_vtime] += obj.size
        # cache hit
    else:
        # cache miss

This implementation allows us to evaluate the performance of the Belady algorithm on raw traces. For example, we can run the following command:

./bin/cachesim ../data/cloudPhysicsIO.vscsi vscsi beladyOnline 0.001,0.002,0.005,0.01,0.02,0.05,0.1,0.2

Notes:

• The complexity of this implementation is $O(n*log(n))$, and the space overhead is $O(n)$, where $n$ is the number of requests in the trace.
• Compared to the existing offline Belady, MIN does not guarantee that requests will always be inserted into the cache, so the miss rate will have slight differences from the current offline implementation.
• Since each BeladyOnline instance requires $O(n)$ memory, running multiple instances will consume a significant amount of memory. For the twitter_cluster45.oracleGeneral.sample10 case, testing the following 8 sizes will consume approximately 20GB of memory in total.

Test Results

I tested the efficiency of BeladyOnline in constructing Request-MRC and Byte-MRC for cache size 0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, and 0.2, using multiple workloads, and compared it with Belady.

Workload	#req	Belady Time(s)	BeladyOnline Time(s)	Average MAE
cloudPhysicsIO.oracleGeneral.bin	113872	2.3	2.3	0.03%
twitter_cluster45.oracleGeneral.sample10	22288116	14.3	29.9	0.004%

[sonarqubecloud]

Quality Gate passed

Issues
58 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
2.5% Duplication on New Code

See analysis details on SonarQube Cloud