Performance of probabilistic caching and cache replacement policies for Content-Centric Networks

Abstract

The Content-Centric Networking (CCN) architecture exploits a universal caching strategy whose inefficiency has been confirmed by research communities. Various caching schemes have been proposed to overcome some drawbacks of the universal caching strategy but they come with additional complexity and overheads. Besides those sophisticated caching schemes, there is a probabilistic caching scheme that is more efficient than the universal caching strategy and adds a modest complexity to a network. The probabilistic caching scheme was treated as a benchmark and the insights into its behavior have never been studied despite its promising performance and feasibility in practical use. In this paper we study the probabilistic caching scheme by means of computer simulation to explore the behavior of the probabilistic caching scheme when it works with various cache replacement policies. The simulation results show the different behavioral characteristics of the probabilistic caching scheme as a function of the cache replacement policy.

On the Performance of Caching and Forwarding in Information-Centric Networking for the IoT

“…In particular, probabilistic caching coupled with LRU gives the highest performance in terms of hit ratio and, consequently, in terms of retrieval delay and Interest retransmissions. This result is due to the fact that the always strategy generates high redundancy in the network, a condition already pinpointed in general literature about ICN caching [17]. In presence of small CSs, the negative effects of the always strategy are even exacerbated.…”

“…This simple strategy, however, has been shown inefficient because it generates high redundancy without maximizing the data diversity in the network [9]. Therefore, other solutions are usually used in the literature as benchmark, including probabilistic caching [17], where the node randomly caches incoming Data with a certain probability p.…”

Adaptive Prioritized Probabilistic Caching Algorithm for Content Centric Networks

“…The proposed caching algorithm is used for calculating the caching probability according to the occurred events in the networks. Furthermore, we use Least-Recently Used (LRU) as a cache replacement policy in the caching system because LRU is the best cache replacement policy when it is deployed with probabilistic caching scheme [16]. When there is no room for the new incoming data packet, CS will evict the least-recently used data packet.…”

“…We evaluate the proposed caching algorithm using the computer simulation tool called ndnSIM [15,16]. ndnSIM is an open source NS-3 based NDN simulator and composes of CCN architecture and CCN basic components.…”

Caching in Named Data Networking for the wireless Internet of Things

“…However, many papers have already pointed out the inefficiency of the universal caching strategy, e.g., [11], due to the high level of content redundancy and the inefficient utilization of available cache resources. This is why other solutions are usually used in the literature, including probabilistic caching [12]. The key idea behind the probabilistic strategy is that a NDN node randomly caches incoming Data with a certain probability p, where 0 < p < 1.…”