A popularity based caching strategy for the future Internet

Information-Centric Networking (ICN) is an attractive network model receiving increasing consideration by the research community because of its inspiring features. To better manage the Internet usage move from host-centric communication to receiver-driven content retrieval, revolutionary ICN architectures have been proposed. A distinguished characteristic of these innovative architectures is to provide ubiquitous and transparent in-network caching to enhance network resource utilization and accelerate content dissemination. With the exponential increase of Internet traffic, the issue of content storage is a growing concern in ICN. In this paper, we present a caching strategy that considerably increases cache hit rate and reduces stretch ratio, which are the most important metrics in the evaluation of ICN caching. Through extensive simulations, it is shown that our proposed work is a favorable and realistic contribution for the standardization exercise of data caching for achieving accurate and valid network performance in the future Internet

Cache Management Strategy for CCN based on Content Popularity

Part 2: Ph.D. Workshop — Monitoring and ModelingInternational audienceContent Centric Networking is a promising architecture for the Future Internet to deliver content at large-scale. It relies on named data and caching features which consists of storing content across the delivery path to serve forthcoming requests. As some content is more likely to be requested than other, caching only popular content may help to manage the cache of CCN nodes. In this paper, we present our new caching strategy adapted to CCN and based on the popularity of content. We show through simulation experiments that our strategy is able to cache less content while it still achieves a higher Cache Hit and outperforms existing default caching strategy in CCN

Flexpop: A popularity-based caching strategy for multimedia applications in information-centric networking

Information-Centric Networking (ICN) is the dominant architecture for the future Internet. In ICN, the content items are stored temporarily in network nodes such as routers. When the memory of routers becomes full and there is no room for a new arriving content, the stored contents are evicted to cope with the limited cache size of the routers. Therefore, it is crucial to develop an effective caching strategy for keeping popular contents for a longer period of time. This study proposes a new caching strategy, named Flexible Popularity-based Caching (FlexPop) for storing popular contents. The FlexPop comprises two mechanisms, i.e., Content Placement Mechanism (CPM), which is responsible for content caching, and Content Eviction Mechanism (CEM) that deals with content eviction when the router cache is full and there is no space for the new incoming content. Both mechanisms are validated using Fuzzy Set Theory, following the Design Research Methodology (DRM) to manifest that the research is rigorous and repeatable under comparable conditions. The performance of FlexPop is evaluated through simulations and the results are compared with those of the Leave Copy Everywhere (LCE), ProbCache, and Most Popular Content (MPC) strategies. The results show that the FlexPop strategy outperforms LCE, ProbCache, and MPC with respect to cache hit rate, redundancy, content retrieval delay, memory utilization, and stretch ratio, which are regarded as extremely important metrics (in various studies) for the evaluation of ICN caching. The outcomes exhibited in this study are noteworthy in terms of making FlexPop acceptable to users as they can verify the performance of ICN before selecting the right caching strategy. Thus FlexPop has potential in the use of ICN for the future Internet such as in deployment of the IoT technology

Compound popular content caching strategy to enhance the cache management performance in named data networking

Named Data Networking (NDN) is a leading research paradigm for the future Internet architecture. The NDN offers in-network cache which is the most beneficial feature to reduce the difficulties of the location-based Internet paradigm. The objective of cache is to achieve a scalable, effective, and consistent distribution of information. However, the main issue which NDN facing is the selection of appropriate router during the content’s transmission that can disrupt the overall network performance. The reason is that how each router takes a decision to the cache which content needs to cache at what location that can enhance the complete caching performance. Therefore, several cache management strategies have been developed. Still, it is not clear which caching strategy is the most ideal for each situation. This study proposes a new cache management strategy named as Compound Popular Content Caching Strategy (CPCCS) to minimize cache redundancy with enhanced diversity ratio and improving the accessibility of cached content by providing short stretch paths. The CPCCS was developed by combining two mechanisms named as Compound Popular Content Selection (CPCS) and Compound Popular Content Caching (CPCC) to differentiate the contents regarding their Interest frequencies using dynamic threshold and to find the best possible caching positions respectively. CPCCS is compared with other NDN-based caching strategies, such as Max-Gain In-network Caching, WAVE popularity-based caching strategy, Hop-based Probabilistic Caching, Leaf Popular Down, Most Popular Cache, and Cache Capacity Aware Caching in a simulation environment. The results show that the CPCCS performs better in which the diversity and cache hit ratio are increased by 34% and 14% respectively. In addition, the redundancy and path stretch are decreased by 44% and 46% respectively. The outcomes showed that the CPCCS have achieved enhanced caching performance with respect to different cache size (1GB to 10GB) and simulation parameters than other caching strategies. Thus, CPCCS can be applicable in future for the NDN-based emerging technologies such as Internet of Things, fog and edge computing

Cooperative announcement-based caching for video-on-demand streaming

Recently, video-on-demand (VoD) streaming services like Netflix and Hulu have gained a lot of popularity. This has led to a strong increase in bandwidth capacity requirements in the network. To reduce this network load, the design of appropriate caching strategies is of utmost importance. Based on the fact that, typically, a video stream is temporally segmented into smaller chunks that can be accessed and decoded independently, cache replacement strategies have been developed that take advantage of this temporal structure in the video. In this paper, two caching strategies are proposed that additionally take advantage of the phenomenon of binge watching, where users stream multiple consecutive episodes of the same series, reported by recent user behavior studies to become the everyday behavior. Taking into account this information allows us to predict future segment requests, even before the video playout has started. Two strategies are proposed, both with a different level of coordination between the caches in the network. Using a VoD request trace based on binge watching user characteristics, the presented algorithms have been thoroughly evaluated in multiple network topologies with different characteristics, showing their general applicability. It was shown that in a realistic scenario, the proposed election-based caching strategy can outperform the state-of-the-art by 20% in terms of cache hit ratio while using 4% less network bandwidth

Content Delivery Latency of Caching Strategies for Information-Centric IoT

In-network caching is a central aspect of Information-Centric Networking (ICN). It enables the rapid distribution of content across the network, alleviating strain on content producers and reducing content delivery latencies. ICN has emerged as a promising candidate for use in the Internet of Things (IoT). However, IoT devices operate under severe constraints, most notably limited memory. This means that nodes cannot indiscriminately cache all content; instead, there is a need for a caching strategy that decides what content to cache. Furthermore, many applications in the IoT space are timesensitive; therefore, finding a caching strategy that minimises the latency between content request and delivery is desirable. In this paper, we evaluate a number of ICN caching strategies in regards to latency and hop count reduction using IoT devices in a physical testbed. We find that the topology of the network, and thus the routing algorithm used to generate forwarding information, has a significant impact on the performance of a given caching strategy. To the best of our knowledge, this is the first study that focuses on latency effects in ICN-IoT caching while using real IoT hardware, and the first to explicitly discuss the link between routing algorithm, network topology, and caching effects.Comment: 10 pages, 9 figures, journal pape