A Simulation of Cache Replacement Strategy on Named Data Network

NDN (Named Data Networking, NDN) which is one of the next generation network architectures based on named-data, uses in-network caching. Cache has limited capacity, so the cache replacement policy determines which content is evicted when the cache space is full. This paper analyzes some cache replacement strategies in NDN, and puts forword a cache replacement strategy based on hierarchical popularity, then compares the effect of different cache replacement strategies to the cache performance through simulation experiments. Cache performance is evaluated in provision of cache hit ratio.

This article describes how the named data networking (NDN) has recently received a lot of attention as a potential information-centric networking (ICN) architecture for the future Internet. The NDN paradigm has a great potential to efficiently address and solve the current seminal IP-based IoT architecture issues and requirements. NDN can be used with different sets of caching algorithms and caching replacement policies. The authors investigate the most suitable combination of these two features to be implemented in an IoT environment. For this purpose, the authors first reviewed the current research and development progress in ICN, then they conduct a qualitative comparative study of the relevant ICN proposals and discuss the suitability of the NDN as a promising architecture for IoT. Finally, they evaluate the performance of NDN in an IoT environment with different caching algorithms and replacement policies. The obtained results show that the consumer-cache caching algorithm used with the Random Replacement (RR) policy significantly improve NDN content validity in an IoT environment.

Using Interests (requests that elicit content) and maintaining per-Interest forwarding state in Pending Interest Tables (PIT) are integral to the design of the Named Data Networking (NDN) and Content-Centric Networking (CCNx) architectures. However, using PITs makes the network vulnerable to Interest-flooding attacks, and PITs can become very large. It is shown that in-network caching eliminates the need for Interest aggregation and obviates the use of PITs. A new approach to content-centric networking (CCN-GRAM) is introduced that provides all the benefits of NDN and CCNx, eliminates the use of PITs by means of anonymous datagrams, and is immune to Interest-flooding attacks. Routers maintain routes to the anonymous origins of Interests using an on-demand routing approach in the data plane that can also be used to provide native support for multicasting in the dat a plane. Simulation experiments show that the number of forwarding entries required in CCN-GRAM is orders of magnitude smaller than the number of PIT entries.

Content-Centric Networking (CCN) is a communication paradigm that emphasizes content distribution. Named-Data Networking (NDN) is an instantiation of CCN, a candidate Future Internet Architecture. NDN supports human-readable content naming and router-based content caching which lends itself to efficient, secure, and scalable content distribution. Because of NDN's fundamental requirement that each content object must be signed by its producer, fragmentation has been considered incompatible with NDN since it precludes authentication of individual content fragments by routers. The alternative is to perform hop-by-hop reassembly, which incurs prohibitive delays. In this paper, we show that secure and efficient content fragmentation is both possible and even advantageous in NDN and similar content-centric network architectures that involve signed content. We design a concrete technique that facilitates efficient and secure content fragmentation in NDN, discuss its security guarantees and assess performance. We also describe a prototype implementation and compare performance of cut-through with hop-by-hop fragmentation and reassembly.

Named Data Networking (NDN), an emerging communication model in the content centric networks, has recently presented a solid framework for the future Internet. The NDN exploits content name instead of host name (IP address) and content caching. These features make NDN particularly efficient in networks with intermittent connectivity and dynamic topologies such as mobile ad hoc networks (MANETs). Due to the structure of NDN nodes, design of forwarding strategies has a vital impact on the network performance. In this paper, we propose a new forwarding strategy: redundancy elimination forwarding (REF). In REF, the NDN node structure and the operation of the data structures are modified. These modifications improve network performance in terms of throughput, overhead and resource requirements. REF strategy is simulated in different scenarios based on ndnSIM and the results demonstrate that it provides robust performance for various environments.

Content Centric Networking (CCN) [1] is a new network paradigm designed to satisfy user needs considering the growth of data demand. Named Data Networking (NDN) [2] is a research project that is developing the future Internet architecture using the principles behind CCN. In this novel architecture, the contents are addressed by their name and not by their location. Thus, the attention is shifted from user to content, resulting in a caching network that is more efficient and flexible than an IP network for content distribution and management with beneficial effects on timely delivery. In NDN, the content objects are divided into chunks, each digitally signed by its producer, and most papers assume that verification is made only by the content consumer. In order to perform signature verification, a node needs the signer’s key, which can be easily retrieved by issuing a standard interest message. Although content verification at the end node prevents disruptive attacks in which false data is delivered to applications, the verification of key validity is also necessary. Otherwise, false data would be cached and forwarded instead of correct data resulting in a denial of service and paving the way for more sophisticated attacks.

Radient: Scalable, memory efficient name lookup algorithm for named data networking

ABSTRACTSoftware‐defined networking (SDN), a cornerstone of future‐generation networks, is adopted in Named Data Networks (NDN) for large‐scale deployment. The forwarding strategies proposed for SDN‐based NDN primarily use the centralized controller to optimize Interest forwarding and Data delivery. The nodes direct the Interests to the controller to discover the content source(s) and suppress the suboptimal responses. To support such content discovery and delivery, the controller experiences frequent path calculation and trades excessive control messages to install the paths in the nodes due to rapid cache admission and replacement. Besides, the typical NDN forwarding solutions are not viable to realize or need considerable modifications in SDN‐based NDN. To that end, the proposed strategy optimizes Interest forwarding and Data delivery using a Single‐State Q‐learning‐based technique, namely, SDN‐Q. In SDN‐Q, each content source learns to suppress the suboptimal responses, with the learning task offloaded to the controller. The controller communicates the learning decision to the nodes. Each node only retains the action (decision) to entertain an incoming Interest. Once an Interest hits, the source either replies with the Data or remains silent and sends the Interest's information (meta‐data) to the controller for the learning task. Thus, SDN‐Q enables the NDN nodes to remain light‐loaded. Each node can instantly answer an Interest request without redirecting it to the controller. Additionally, we optimize Interest forwarding using a hop‐based scoped‐flooding approach. The proof‐of‐concept implementation in software (simulation) reveals that the proposed system outperforms the competing strategies by reducing the traffic load, latency, and control messages in SDN‐based NDN (at most by 40%, 7%, and four (4) times respectively), without negotiating packet delivery ratio.

The current Internet infrastructure, initially conceived to provide closed group connectivity to a limited user-base, is now facing the challenges of catering to over three billion users with dynamically changing data, transport, and access requirements. Content-Centric Networking (CCN) is being explored as a possible future Internet architecture. Named-Data Networking (NDN) exemplifies CCN and with the ever-changing security landscape, it is imperative to build it with intrinsic resilience based on the security by design narrative. In this extended abstract, we explore the fake interest fiooding by adversaries to launch a Distributed Denial of Service (DDoS) attack in NDN. We propose Kiram as an intelligent anomaly recognition and alert generation mechanism serving as a collaborative countermeasure to a DDoS attack. The alert generated by Kiram is named Warding Off Evil (WOE). This poster presents results establishing the effectiveness of Kiram based on substantial simulations over a fairly realistic topology.

In-network caching is one of the key aspects of content-centric networks (CCN), while the cache replacement algorithm of LRU does not consider the relation between the contents of the cache and its neighbor nodes in the cache replacement process, which bring worthless cache block in the cache and reduce the efficiency of the cache. An enhanced LRU cache replacement strategy has been proposed, which can replace the cache block in time that is not requested from other nodes and improve the rate of effective utilization of the cache space. Simulation results show that the A-LRU strategy increases cache hit rate, shortens the data request delay and improves overall network performance, verifies the validity of the A-LRU strategies in CCN.

Information-Centric Networking (ICN) is a prominent topic in current networking research. ICN design significantly considers the increased demand of scalable and efficient content distribution for Future Internet. However, intermittently connected mobile environments or disruptive networks present a significant challenge to ICN deployment. In this context, delay tolerant networking (DTN) architecture is an initiative that effectively deals with network disruptions. Among all ICN proposals, Content Centric Networking (CCN) is gaining more and more interest for its architectural design, but still has the limitation in highly disruptive environment. In this paper, we design a protocol stack referred as CCNDTN which integrates DTN architecture in the native CCN to deal with network disruption. We also present the implementation details of the proposed CCNDTN. We extend CCN routing strategies by integrating Bundle protocol of DTN architecture. The integration of CCN and DTN enriches the connectivity options of CCN architecture in fragmented networks. Furthermore, CCNDTN can be beneficial through the simultaneous use of all available connectivities and opportunistic networking of DTN for the dissemination of larger data items. This paper also highlights the potential use cases of CCNDTN architecture and crucial questions about integrating CCN and DTN.

Internet of Things (IoT) and named data network (NDN) are innovative technologies to meet up the future Internet requirements. NDN is considered as an enabling approach to improving data dissemination in IoT scenarios. NDN delivers in-network caching, which is the most prominent feature to provide fast data dissemination as compared to Internet protocol (IP)-based communication. The proper integration of caching placement strategies and replacement policies is the most suitable approach to support IoT networks. It can improve multicast communication which minimizes the delay in responding to IoT-based environments. Besides, these approaches are playing a most significant role in increasing the overall performance of NDN-based IoT networks. To this end, in this article, the challenges of NDN-IoT caching are identified with the aim to develop a new hybrid strategy for efficient data delivery. The proposed strategy is comparatively and extensively studied with NDN-IoT caching strategies through an extensive simulation in terms of average latency, cache hit ratio, and average stretch ratio. From the simulation findings, it is observed that the proposed hybrid strategy outperformed to achieve a higher caching performance of NDN-based IoT scenarios.

Achieving high system execution performance is challenging due to the variety of application features, the erratic nature of memory resources, and the erratic use of the cache application programming interface (API).Ineffective cache replacement procedures can lead to a variety of performance issues, including lengthy application execution times, low memory use, frequent replacements, and even program execution failures owing to memory outages.Spark is presently using the least recently used (LRU) cache refilling technique.Despite being a popular classical strategy, LRU ignores environmental conditions and workloads.It cannot therefore function well in a variety of situations.The model in this paper introduces a new cache replacement technique called least partition weight (LPW).LPW considers several parameters, such as the partition size, computational cost, and reference count, in evaluating the performance of a system.Once the LPW algorithm was integrated into Spark, it was evaluated against the LRU and other cutting-edge methods.The cache replacement model's functionality is substantially improved by the recommended model with the application of auto data division and weighted tree technique.Therefore, the focus of this review paper is on examining previous research to comprehend the cache replacement process and present an improved version of the catch replacement using LPW in conjunction with parallel computation, which will be described in the paper's next edition.

Optimal chunk caching in network coding-based qualitative communication

Boosting named data networking for data dissemination in urban VANET scenarios