Leave Copy Everywhere Research Articles

Caching Policy in Low Earth Orbit Satellite Mega-Constellation Information-Centric Networking for Internet of Things.

Information-Centric Networking (ICN) is the emerging next-generation internet paradigm. The Low Earth Orbit (LEO) satellite mega-constellation based on ICN can achieve seamless global coverage and provide excellent support for Internet of Things (IoT) services. Additionally, in-network caching, typically characteristic of ICN, plays a paramount role in network performance. Therefore, the in-network caching policy is one of the hotspot problems. Especially, compared to caching traditional internet content, in-networking caching IoT content is more challenging, since the IoT content lifetime is small and transient. In this paper, firstly, the framework of the LEO satellite mega-constellation Information-Centric Networking for IoT (LEO-SMC-ICN-IoT) is proposed. Then, introducing the concept of "viscosity", the proposed Caching Algorithm based on the Random Forest (CARF) policy of satellite nodes combines both content popularity prediction and satellite nodes location prediction, for achieving good cache matching between the satellite nodes and content. And using the matching rule, the Random Forest (RF) algorithm is adopted to predict the matching relationship among satellite nodes and content for guiding the deployment of caches. Especially, the content is cached in advance at the future satellite to maintain communication with the current ground segment at the time of satellite switchover. Additionally, the policy considers both the IoT content lifetime and the freshness. Finally, a simulation platform with LEO satellite mega-constellation based on ICN is developed in Network Simulator 3 (NS-3). The simulation results show that the proposed caching policy compared with the Leave Copy Everywhere (LCE), the opportunistic (OPP), the Leave Copy down (LCD), and the probabilistic algorithm which caches each content with probability 0.5 (prob 0.5) yield a significant performance improvement, such as the average number of hops, i.e., delay, cache hit rate, and throughput.

An Intelligent Caching Strategy Considering Time-Space Characteristics in Vehicular Named Data Networks

In the Internet of Vehicles (IoV), the classic TCP/IP still plays an important role for data transmission, traffic control and address assignment. However, with increasing requirements on content retrieve efficiency in IoV, the drawbacks of traditional TCP/IP stacks, such as weak scalability in large networks, low efficiency in dense environment and unreliable addressing in high mobility circumstance, have incurred significant performance degradations in vehicular environments. Fortunately, the emerging Named Data Network (NDN) technology provides a good choice to address above issues in vehicular environment by proving content caching capability with introduced content store module, and boosts the research activity of Vehicular Named Data Network (VNDN) in the last few years. In this paper, to improve the service performance, e.g., reducing the delay of data acquisition, a data caching scheme is proposed by taking the spatial-temporal characteristics of data into account. At first, we divided the data in a VNDN into emergency safety message, traffic efficiency message and service message, according to the application requirements. Then, we analyze the spatial-temporal characteristics of these three message categories and design the caching strategy according to these characteristics. Experimental results from NDNSim platform show that our designed scheme has an approximately 50% performance enhancement compared with Leave Copy Everywhere (LCE), Pro(0.7), and Pro(0.2) data caching protocols in terms of average hit rate, average hop count and average cache replacement times, which verifies the reliability and effectiveness of our proposed data caching scheme.

Caching scheme for information‐centric networks with balanced content distribution

SummaryInformation‐centric network (ICN) emphasizes on content retrieval without much bothering about the location of its actual producer. This novel networking paradigm makes content retrieval faster and less expensive by shifting data provisioning into content holder rather than content owner. Caching is the feature of ICN that makes content serving possible from any intermediate device. An efficient caching is one of the primary requirements for effective deployment of ICN. In this paper, a caching approach with balanced content distribution among network devices is proposed. The selection of contents to be cached is determined through universal and computed using Zipf's law. The dynamic change in popularity of contents is also considered to take make caching decisions. For balancing the cached content across the network, every router keeps track of its neighbor's cache status. Three parameters, the proportionate distance of the router from the client (pd), the router congestion (rc), and the cache status (cs), are contemplated to select a router for caching contents. The new caching approach is evaluated in the simulated environment using ndnSIM‐2.0. Three state‐of‐the‐art approaches, Leave Copy Everywhere (LCE), centrality measures‐based algorithm (CMBA), and a probability‐based caching (probCache), are considered for comparison. The proposed method of caching shows the better performance compared to the other three protocols used in the comparison.

COCP: Coupling Parameters Content Placement Strategy for In-Network Caching-Based Content-Centric Networking

On-path caching is the prominent module in Content-Centric Networking (CCN), equipped with the capability to handle the demands of future networks such as the Internet of Things (IoT) and vehicular networks. The main focus of the CCN caching module is data dissemination within the network. Most of the existing strategies of in-network caching in CCN store the content at the maximum number of routers along the downloading path. Consequently, content redundancy in the network increases significantly, whereas the cache hit ratio and network performance decrease due to the unnecessary utilization of limited cache storage. Moreover, content redundancy adversely affects the cache resources, hit ratio, latency, bandwidth utilization, and server load. We proposed an in-network caching placement strategy named Coupling Parameters to Optimize Content Placement (COCP) to address the content redundancy and associated problems. The novelty of the technique lies in its capability to minimize content redundancy by creating a balanced cache space along the routing path by considering request rate, distance, and available cache space. The proposed approach minimizes the content redundancy and content dissemination within the network by using appropriate locations while increasing the cache hit ratio and network performance. The COCP is implemented in the simulator (Icarus) to evaluate its performance in terms of the cache hit ratio, path stretch, latency, and link load. Extensive experiments have been conducted to evaluate the proposed COCP strategy. The proposed COCP technique has been compared with the existing state-of-the-art techniques, namely, Leave Copy Everywhere (LCE), Leave Copy Down (LCD), ProbCache, Cache Less for More (CL4M), and opt-Cache. The results obtained with different cache sizes and popularities show that our proposed caching strategy can achieve up to 91.46% more cache hits, 19.71% reduced latency, 35.43% improved path stretch and 38.14% decreased link load. These results confirm that the proposed COCP strategy has the potential capability to handle the demands of future networks such as the Internet of Things (IoT) and vehicular networks.

Content Management Based on Content Popularity Ranking in Information-Centric Networks

Users can access the Internet anywhere they go at any time due to the advancement of communications and networking technologies. The number of users and connected devices are rapidly increasing, and various forms of content are becoming increasingly available on the Internet. Consequently, several research ideas have emerged regarding the storage policy for the enormous amount of content, and procedures to remove existing content due to the lack of storage space have also been discussed. Many of the proposals related to content caching offer to identify the popularity of certain content and hold the popular content in a repository as long as possible. Although the host-based Internet has been serving its users for a long time, managing network resources efficiently during high traffic load is problematic for the host-based Internet because locating the host with their IP address is one of the primary mechanisms behind this architecture. A more strategical networking paradigm to resolve this issue is Content-Centric Networking (CCN), a branch of the networking paradigm Information-Centric Networking (ICN) that is focused on the name of the content, and therefore can deliver the requested content efficiently, securely, and faster. However, this paradigm has relatively simple content caching and content removal mechanisms, as it caches all the relevant content at all the nodes and removes the content based on the access time only when there is a lack of space. In this paper, we propose content popularity ranking (CPR) mechanism, content caching scheme, and content removal scheme. The proposed schemes are compared to existing caching schemes such as Leave Copy Everywhere (LCE) and Leave Copy Down (LCD) in terms of the Average Hop Count, content removal schemes such as Least Recently Used (LRU) and Least Frequently Used (LFU) in terms of the Cache Hit Ratio, and finally, the CCN paradigm incorporating the LCE and the LRU schemes and the host-based Internet architecture in terms of Content Delivery Time. Graphical presentations of performance results utilizing the proposed schemes show that the proposed CPR-based schemes for content caching and content removal provide better performance than the host-based Internet and the original CCN utilizing LCE and LRU schemes.

Deep learning inspired routing in ICN using Monte Carlo Tree Search algorithm

Information Centric Networking (ICN) provides caching strategies to improve network performance based on consumer demands from the intermediate routers. It reduces the load on content server, network traffic, and improves end-to-end delay. The content requesters use an Interest packet containing the name of data to express their needs. If such Interest packets are routed efficiently, the end to end delay and throughput of the network could be improved further. This paper describes an efficient method of forwarding Interest packets to retrieve the requested content at the earliest possible time. Here the data source is found and considered as a single player game with content requester as its start state and location of the desired content as final or goal state. The Monte Carlo Tree Search (MCTS) algorithm is used for constructing the path from content requester to concerned data source. For performance evaluation, the proposed scheme is integrated with Leave Copy Down (LCD) and Leave Copy Everywhere (LCE), Cache Less for More (CL4M), and Probability based caching (ProbCache) In ns-3 simulation environment (ndnSim), all these are evaluated in terms of content search latency, server hit ratio, network load, overhead and throughput. Simulation observation reveals that the integration of MCTS significantly improves performance in regard to experimental parameters.

Popularity‐Aware In‐Network Caching for Edge Named Data Network

The traditional centralized network architecture can lead to a bandwidth bottleneck in the core network. In contrast, in the information‐centric network, decentralized in‐network caching can alleviate the traffic flow pressure from the network center to the edge. In this paper, a popularity‐aware in‐network caching policy, namely, Pop, is proposed to achieve an optimal caching of network contents in the resource‐constrained edge networks. Specifically, Pop senses content popularity and distributes content caching without adding additional hardware and traffic overhead. We conduct extensive performance evaluation experiments by using ndnSIM. The experiments showed that the Pop policy achieves 54.39% cloud service hit reduction ratio and 22.76% user request average hop reduction ratio and outperforms other policies including Leave Copy Everywhere, Leave Copy Down, Probabilistic Caching, and Random choice caching. In addition, we proposed an ideal caching policy (Ideal) as a baseline whose popularity is known in advance; the gap of Pop and Ideal in cloud service hit reduction ratio is 4.36%, and the gap in user request average hop reduction ratio is only 1.47%. More simulation results further show the accuracy of Pop in perceiving popularity of contents, and Pop has good robustness in different request scenarios.

A collaborative caching strategy for content-centric enabled wireless sensor networks

The Content-Centric Networking (CCN) is an efficient traffic handling technology by accessing content with its name instead of its physical location and achieving in-network caching. Indeed, CCN caching ensures high content availability, network traffic reduction, and low retrieval latency which reduces congestion and improves end-to-end delay. Moreover, it could greatly improve the efficiency of content delivery in Wireless Sensor Networks (WSNs). In this article, we propose to exploit this feature to enable CCN in WSN environments. The CCN architecture enables the content caching on each sensor-node in WSN and several research studies have been devoted to the caching management issue in such a context. However, caching the content on all the nodes is not a good strategy in terms of resource utilization. It is, therefore, necessary to determine where to cache and how to handle it in order to optimize the resources while realizing a high-interest satisfaction rate. Thus, our objective is to study existing caching strategies and propose a novel one that takes into account the node centrality and its distance from the source of the content. Through extensive simulations, we examine the performance of our scheme under different configurations and demonstrate how it outperforms the traditional caching strategies such as LCE (Leave Copy Everywhere) and LCD (Leave Copy Down).

Cache-Filter: A Cache Permission Policy for Information-Centric Networking

Information Centric Networking (ICN) has recently attracted great attention. It names the content decoupling from the location and introduces network caching, making the content to be cached anywhere within the network. The benefits of such design are obvious, however, many challenges still need to be solved. Among them, the local caching policy is widely discussed and it can be further divided into two parts, namely the cache permission policy and the cache replacement policy. The former is used to decide whether an incoming content should be cached while the latter is used to evict a cached content if required. The Internet is a user-oriented network and popular contents always have much more requests than unpopular ones. Caching such popular contents closer to the user’s location can improve the network performance, and consequently, the local caching policy is required to identify popular contents. However, considering the line speed requirement of ICN routers, the local caching policy whose complexity is larger than O(1) cannot be applied. In terms of the replacement policy, Least Recently Used (LRU) is selected as the default one for ICN because of its low complexity, although its ability to identify the popular content is poor. Hence, the identification of popular contents should be completed by the cache permission policy. In this paper, a cache permission policy called Cache-Filter, whose complexity is O(1), is proposed, aiming to store popular contents closer to users. Cache-Filter takes the content popularity into account and achieves the goal through the collaboration of on-path nodes. Extensive simulations are conducted to evaluate the performance of Cache-Filter. Leave Copy Down (LCD), Move Copy Down (MCD), Betw, ProbCache, ProbCache+, Prob(p) and Probabilistic Caching with Secondary List (PCSL) are also implemented for comparison. The results show that Cache-Filter performs well. For example, in terms of the distance to access to contents, compared with Leave Copy Everywhere (LCE) used by Named Data Networking (NDN) as the permission policy, Cache-Filter saves over 17% number of hops.

Hierarchical Cache Performance Analysis Under TTL-Based Consistency

This paper introduces an analytical model for characterizing the instantaneous hit ratio and instantaneous average hit distance of a traditional least recently used (LRU) cache hierarchy. The analysis accounts for the use of two variants of the Time-to-Live (TTL) weak consistency mechanism. The first is the typical TTL scheme (TTL-T) used in the HTTP/1.1 protocol where expired objects are refreshed using conditional GET requests. The second is TTL immediate ejection (TTL-IE) where objects are ejected as soon as they expire. The analysis also accounts for two sharing protocols: Leave Copy Everywhere (LCE) and Promote Cached Objects (PCO). PCO is a new sharing protocol introduced in this paper that decreases the user's perceived latency and is robust under nonstationary access patterns.