PB-NCC: A Popularity-Based Caching Strategy with Number-of-Copies Control in Information-Centric Networks

The Information-Centric Network (ICN), designed for efficient content acquisition and distribution, is a promising candidate architecture for the future Internet. In-network caching in ICN makes it possible to reuse contents and the Name Resolution System (NRS) makes cached contents better serve users. In this paper, we focused on the ICN caching scenario equipped with an NRS, which records the positions of contents cached in ICN. We propose a Popularity-based caching strategy with Number-of-Copies Control (PB-NCC) in this paper. PB-NCC is proposed to solve the problems of unreasonable content distribution and frequent cache replacement in traditional caching strategies in ICN. We examine PB-NCC with a large number of experiments in different topologies and workloads. The simulation results reveal that PB-NCC can improve the cache hit ratio by at least 8.85% and reduce the server load by at least 11.34% compared with other on-path caching strategies, meanwhile maintaining a low network latency.

IMU: A Content Replacement Policy for CCN, Based on Immature Content Selection

In-network caching is the essential part of Content-Centric Networking (CCN). The main aim of a CCN caching module is data distribution within the network. Each CCN node can cache content according to its placement policy. Therefore, it is fully equipped to meet the requirements of future networks demands. The placement strategy decides to cache the content at the optimized location and minimize content redundancy within the network. When cache capacity is full, the content eviction policy decides which content should stay in the cache and which content should be evicted. Hence, network performance and cache hit ratio almost equally depend on the content placement and replacement policies. Content eviction policies have diverse requirements due to limited cache capacity, higher request rates, and the rapid change of cache states. Many replacement policies follow the concept of low or high popularity and data freshness for content eviction. However, when content loses its popularity after becoming very popular in a certain period, it remains in the cache space. Moreover, content is evicted from the cache space before it becomes popular. To handle the above-mentioned issue, we introduced the concept of maturity/immaturity of the content. The proposed policy, named Immature Used (IMU), finds the content maturity index by using the content arrival time and its frequency within a specific time frame. Also, it determines the maturity level through a maturity classifier. In the case of a full cache, the least immature content is evicted from the cache space. We performed extensive simulations in the simulator (Icarus) to evaluate the performance (cache hit ratio, path stretch, latency, and link load) of the proposed policy with different well-known cache replacement policies in CCN. The obtained results, with varying popularity and cache sizes, indicate that our proposed policy can achieve up to 14.31% more cache hits, 5.91% reduced latency, 3.82% improved path stretch, and 9.53% decreased link load, compared to the recently proposed technique. Moreover, the proposed policy performed significantly better compared to other baseline approaches.

An Intelligent Caching and Replacement Strategy Based on Cache Profit Model for Space-Ground Integrated Network

Compared with the stable states of the ground networks, the space-ground integrated networks (SGIN) have limited resources, high transmission delay, and vulnerable topology, which make traditional caching strategies unable to adapt to the complex space network environment. An intelligent and efficient caching strategy is required to improve the edge service capabilities of satellites. Therefore, we investigate these problems in this paper and make the following contributions. First, the content value evaluation model based on classification and regression tree is proposed to solve the problem of “what to cache” by describing the cache value of content, which considers the multidimensional content characteristics. Second, we propose a cache decision strategy based on the node caching cost model to answer “where to cache.” This strategy modified the genetic algorithm to adapt the 0-1 knapsack problem under SDN architecture, which greatly improved the cache hit rate and the network service quality. Finally, we propose a cache replacement strategy by establishing an effective service time model between the satellite and ground transmission link, which solves the problem of “when to replace.” Numerical results demonstrate that the proposed strategy in SGIN can improve the nodes’ cache hit rate and reduce the network transmission delay and transmission hops.

Mobility Markov Chain & Matrix based Location-Aware Cache Replacement Policy in Mobile Environment

In the location aware services, past mobile device cache invalidation-replacement practises used are ineffective if the client travel route varies rapidly. In addition, in terms of storage expense, previous cache invalidation-replacement policies indicate high storage overhead. These limitations of past policies are inspiration for this research work. The paper describes the models to solve the aforementioned challenges using two different approaches separately for predicting the future path for the user movement. In the first approach, the most prevalent Sequential Pattern Mining & Clustering (SPMC) technique is used to pre-process the user's movement trajectory and find out the pattern that appears frequently. In the second approach, frequent patterns are forwarded into the Mobility Markov Chain & Matrix-(MMCM) algorithm leading to a reduction in the size of candidate sets and, therefore, efficiency enhancement of mining sequence patterns. Analytical results show significant caching performance improvement compared to previous caching policies.

A New Efficient Cache Replacement Strategy for Named Data Networking

The Information-Centric Network (ICN) is a future internet architecture with efficient content retrieval and distribution. Named Data Networking (NDN) is one of the proposed architectures for ICN. NDN’s innetwork caching improves data availability, reduce retrieval delays, network load, alleviate producer load, and limit data traffic. Despite the existence of several caching decision algorithms, the fetching and distribution of contents with minimum resource utilization remains a great challenge. In this paper, we introduce a new cache replacement strategy called Enhanced Time and Frequency Cache Replacement strategy (ETFCR) where both cache hit frequency and cache retrieval time are used to select evicted data chunks. ETFCR adds time cycles between the last two requests to adjust data chunk’s popularity and cache hits. We conducted extensive simulations using the ccnSim simulator to evaluate the performance of ETFCR and compare it to that of some well-known cache replacement strategies. Simulations results show that ETFCR outperforms the other cache replacement strategies in terms of cache hit ratio, and lower content retrieval delay.

Information-Centric Networking Cache Placement Method Based on Cache Node Status and Location

Information-Centric Networking with caching is a very promising future network architecture. The research on its cache deployment strategy is divided into three categories, namely, noncooperative cache, explicit collaboration cache, and implicit collaboration cache. Noncooperative caching can cause problems such as high content repetition rate in the web cache space. Explicit collaboration caching generally reflects the best caching effect but requires a lot of communication to satisfy the exchange of cache node information and depends on the controller to perform the calculation. On this basis, implicit cooperative caching can reduce the information exchange and calculation between cache nodes while maintaining a good caching effect. Therefore, this paper proposes an on-path implicit cooperative cache deployment method based on the dynamic LRU-K cache replacement strategy. This method evaluates the cache nodes based on their network location and state and selects the node with the best state value on the transmission path for caching. Each request will only select one or two nodes for caching on the request path to reduce the redundancy of the data. Simulation experiments show that the cache deployment method based on the state and location of the cache node can improve the hit rate and reduce the average request length.