Abstract:
Web proxy caching is one of the effective solutions to avoid web
service bottleneck, reduce traffic over the Internet and improve scalability
of the web service. The core of a caching system is the caching
replacement policies. This study describes the use of intelligent agent
model to improve the performance of the proxy cache. A multi-agent
system has been developed to control the cache cleanup task on the
hierarchy caches.
Fuzzy logic is used to combine LFU, LRU and Size caching
replacement policies on the parent cache side. LFU and LRU policies are
used on the child caches side. Cache cleaner Agents use fuzzy logic to
make an intelligent decision and remove the web object proactively when
it has high clean up priority. Reactive Coordination has been applied
between the parent and child cleaner agents to achieve the cleanup task in
efficient way, they have a common goal to increase hit ratio and byte hit
ratio.
Coordination agent applied the coordination rules when the web
object with medium priority is found in parent and children caches. Q-
learning algorithm has been implemented by the cleaner agent to avoid
difficult calculation when it reached a similar state and take a suitable
action.
A reward value has been associated to each action, when Cleaner
agent takes its optimal action that leads to the goal, it has an instant high
reward. Other actions have low reward. States and actions had been
represented on a graph each node represented a "state", agent's movement
from one node to another represented the "action".
The model has been tested using five samples of workload
generated using Webtraff simulator, these samples represented the users
requests and used cache sizes. The standard performance metrics Hit
Ratio and byte hit ratio are used to evaluate the cache performance.
Simulation results show that when the cache size increase the new
approach PCCIA performs better than LRU,LFU and Size replacement
polices in terms of hit rate and byte hit rate.
