Adaptive Prioritized Probabilistic Caching Algorithm for Content Centric Networks
This paper presents an adaptive prioritized probabilistic caching algorithm (APP) for content centric networks (CCN). The objective of the new caching algorithm is to satisfy content requesters with both improving received data quality and maintaining overall network performance. APP allows CCN routers to cache data packets based on the caching probability which is prioritized and unequally handles incoming data packets according to data priorities. APP adjusts the caching probability based on cache events occurred at the CCN router, and the current caching probability is calculated from the previous caching probability. We evaluate APP performance via computer simulations and compare the performance of our caching algorithm with previous caching schemes. The performance evaluation metrics compose of the received data quality, cache-hit percentage, server load, and traffic load. The computer simulation results show that APP yields the better data quality to content requesters and nearly performs in-network caching as well as the previous probabilistic caching scheme.