Cache replacement positions in information-centric network

Information dissemination as the sole functionality driving the current Internet trend has been of keen interest for its manageability. Information Centric Network (ICN) proposed as a new paradigm shift to mitigate the predicted traffic of the current Internet.However, caching as an advantageous building block of ICN is faced with the challenges of content placement, content replacement and eviction.The current practice of ICN caching has given birth to the problems of content redundancy, path redundancy and excessive wastage of bandwidth.This study analyzes the intelligence in cache content management to palliate the gross expenses incurred in the ICN practice.The use of the current factors in previous studies in recency and frequency in content usage play delicate roles in our study. Replacement strategies are agreed to influence the entire cache-hit, stretch and Network diversity

Content caching in ICN using Bee-Colony optimization algorithm

Information dissemination has recently been overtaken by the huge media-driven data shared across different platforms.Future Internet shall greatly be concerned about pervasion and ubiquity of data on all devices.Information-Centric Network seems the challenging paradigm that aims at guaranteeing the flexibility needed when the data explosion occurs.Caching is thus an option that provides the flexibility that manages data exchange practices. Different caching issues has raised concern about the content flooded all over the Internet.In line with the challenges, Bee-Colony Optimization Algorithm (B-COA) has been proposed in this paper to avail content on the Internet with less referral cost and heavy monopoly of data on hosts.It is believed that the advantages of the grouping and waggle phase could be used to place the contents faster in ICN

Cache-skip approach for information-centric network

Several ICN cache deployment and management techniques have since been using the Web management techniques to manage information sharing and better cache-hit ratio.Leave Copy Down, Leave Copy Everywhere and Probabilistic cache managements have gained more attention. However, with Leave Copy Everywhere being the initial design specification in ICN proposal, several research issues of content manageability have posed a threat of particularly content and path redundancy.This paper presents an extensive simulation analysis of the popular cache management techniques by subjecting the concepts into different network topologies to investigate the prospect of extending and proposing a new form of cache management in ICN known as Cache-skip. Cache-skip use the consciousness of time of request, network size and Time Since Birth (TSB) and Time Since Inception (TSI) to carefully dedicate the positions of caching to benefits hit rates and less network stress as a form to efficiently utilize the bandwidth and enhance hits

Controlling the Trade-Off between Resource Efficiency and User Satisfaction in NDNs Based on Naïve Bayes Data Classification and Lagrange Method

[EN] This paper addresses the fundamental problem of the trade-off between resource efficiency and user satisfaction in the limited environments of Named Data Networks (NDNs). The proposed strategy is named RADC (Resource Allocation based Data Classification), which aims at managing such trade-off by controlling the system's fairness index. To this end, a machine learning technique based on Multinomial Naive Bayes is used to classify the received contents. Then, an adaptive resource allocation strategy based on the Lagrange utility function is proposed. To cache the received content, an adequate content placement and a replacement mechanism are enforced. Simulation at the system level shows that this strategy could be a powerful tool for administrators to manage the trade-off between efficiency and user satisfaction.This work is derived from R&D project RTI2018-096384-B-I00, funded by MCIN/AEI/ 10.13039/501100011033 and "ERDF A way of making Europe".Herouala, AT.; Kerrache, CA.; Ziani, B.; Tavares De Araujo Cesariny Calafate, CM.; Lagraa, N.; Tahari, AEK. (2022). Controlling the Trade-Off between Resource Efficiency and User Satisfaction in NDNs Based on Naïve Bayes Data Classification and Lagrange Method. Future Internet. 14(2):1-14. https://doi.org/10.3390/fi1402004811414

Proxcache: A new cache deployment strategy in information-centric network for mitigating path and content redundancy

One of the promising paradigms for resource sharing with maintaining the basic Internet semantics is the Information-Centric Networking (ICN). ICN distinction with the current Internet is its ability to refer contents by names with partly dissociating the host-to-host practice of Internet Protocol addresses. Moreover, content caching in ICN is the major action of achieving content networking to reduce the amount of server access. The current caching practice in ICN using the Leave Copy Everywhere (LCE) progenerate problems of over deposition of contents known as content redundancy, path redundancy, lesser cache-hit rates in heterogeneous networks and lower content diversity. This study proposes a new cache deployment strategy referred to as ProXcache to acquire node relationships using hyperedge concept of hypergraph for cache positioning. The study formulates the relationships through the path and distance approximation to mitigate content and path redundancy. The study adopted the Design Research Methodology approach to achieve the slated research objectives. ProXcache was investigated using simulation on the Abilene, GEANT and the DTelekom network topologies for LCE and ProbCache caching strategies with the Zipf distribution to differ content categorization. The results show the overall content and path redundancy are minimized with lesser caching operation of six depositions per request as compared to nine and nineteen for ProbCache and LCE respectively. ProXcache yields better content diversity ratio of 80% against 20% and 49% for LCE and ProbCache respectively as the cache sizes varied. ProXcache also improves the cache-hit ratio through proxy positions. These thus, have significant influence in the development of the ICN for better management of contents towards subscribing to the Future Internet

Exploiting Information-centric Networking to Federate Spatial Databases

This paper explores the methodologies, challenges, and expected advantages related to the use of the information-centric network (ICN) technology for federating spatial databases. ICN services allow simplifying the design of federation procedures, improving their performance, and providing so-called data-centric security. In this work, we present an architecture that is able to federate spatial databases and evaluate its performance using a real data set coming from OpenStreetMap within a heterogeneous federation formed by MongoDB and CouchBase spatial database systems

Optimal broadcast strategy-based producer mobility support scheme for named data networking

Named Data Networking is a consumer-driven network that supports content consumer mobility due to the nature of in-network catching. The catching suppressed unnecessary Interest packets losses by providing an immediate copy of the data and consumer-driven nature influencedthe mobile consumer to resend unsatisfied Interest packet immediately after the handoff. Once the producer moves to a new location, the name prefix changed automatically after handoff to the new router or point of attachment. The entire network lacks the knowledge of producer movement unless if the producer announces its new prefix to update the FIBs of intermediate routers. Lack of producer’s movement knowledge causes an increase of handoff latency, signaling overhead cost, Interests packets losses, poor utilization of bandwidth and packets delivery. Therefore, there is needs to provide substantial producer mobility support to minimize the handoff latency, handoff signaling overhead cost, reduce the unnecessary Interest packets loss to improve data packets delivery once a content producer relocated. In this paper, broadcasting strategy is introduced to facilitate the handoff procedures and update the intermediate routers about the producer movement. Hence, analytical investigation result of this paper addresses the deficiency of Kite scheme by minimizing handoff signaling cost and provides data path optimization after the handoff

Energy-aware and adaptive fog storage mechanism with data replication ruled by spatio-temporal content popularity

Data traffic demand increases at a very fast pace in edge networking environments, with strict requisites on latency and throughput. To fulfil these requirements, among others, this paper proposes a fog storage system that incorporates mobile nodes as content providers. This fog storage system has a hybrid design because it does not only bring data closer to edge consumers but, as a novelty, it also incorporates in the system other relevant functional aspects. These novel aspects are the user data demand, the energy consumption, and the node distance. In this way, the decision whether to replicate data is based on an original edge service managed by an adaptive distance metric for node clustering. The adaptive distance is evaluated from several important system parameters like, distance from consumer to the data storage location, spatio-temporal data popularity, and the autonomy of each battery-powered node. Testbed results evidence that this flexible cluster-based proposal offers a more responsive data access to consumers, reduces core traffic, and depletes in a fair way the available battery energy of edge nodes.info:eu-repo/semantics/acceptedVersio

SVM-based Analysis for Predicting Success Rate of Interest Packets in Information Centric Networks

Copyright © 2022 The Author(s). A consumer in Information Centric Network (ICN) generates an Interest packet by specifying the name of the required content. As the network emphasizes on content retrieval without much bothering about who serves it (a cache location or actual producer), every Content Router (CR) either provides the requested content back to the requester (if exists in its cache) or forwards the Interest packet to the nearest CR. While forwarding an Interest packet, the ICN routing by default does not provide any mechanism to predict the probable location of the content searched. However, having a predictive model before forwarding may significantly improve content retrieval performance. In this paper, a machine learning (ML) algorithm, particularly a Support Vector Machine (SVM) is used to forecast the success of the Interest packet. A CR can then send an Interest packet in the outgoing interface which is forecasted successful. The objective is to maximize the success rate which in turn minimizes content search time and maximizes throughput. The dataset used in is generated from a simulation topology designed in ndnSim comprising 10 K data points having 10 features. The linear, RBF and the polynomial kernel (with degree 3) are used to analyze the dataset. The polynomial kernel shows the best behavior with 98% accuracy. A comparative retrieval time with and without ML demonstrates around 10% improvement with SVM enable forwarding compared to normal ICN forwarding