In-network Caching Research Articles

QM-ARC: QoS-aware Multi-tier Adaptive Cache Replacement Strategy

Distributed data-centric systems, such as Named Data Networking, utilize in-network caching to reduce application latency by buffering relevant data in high-speed memory. However, the significant increase in data traffic makes expanding memory capacity prohibitively expensive. To address this challenge, integrating technologies like non-volatile memory and high-speed solid-state drives with dynamic random-access memory can form a cost-effective multi-tier cache system. Additionally, most existing caching policies focus on categorizing data based on recency and frequency, overlooking the varying Quality-of-Service (QoS) requirements of applications and customers—a concept supported by Service Level Agreements in various service delivery models, particularly in Cloud computing. One of the most prominent algorithms in caching policy literature is the Adaptive Replacement Cache (ARC), that uses recency and frequency lists but does not account for QoS. In this paper, we propose a QoS-aware Multi-tier Adaptive Replacement Cache (QM-ARC) policy. QM-ARC extends ARC by incorporating QoS-based priorities between data applications and customers using a penalty concept borrowed from service-level management practices. QM-ARC is generic, applicable to any number of cache tiers, and can accommodate various penalty functions. Furthermore, we introduce a complementary feature for QM-ARC that employs Q-learning to dynamically adjust the sizes of the two ARC lists. Our solution, evaluated using both synthetic and real-world traces, demonstrates significant improvements in QoS compared to state-of-the-art methods by better considering priority levels. Results show that QM-ARC reduces penalties by up to 45% and increases the hit rate for high priority data by up to 84%, without negatively impacting the overall hit rate, which also increases by up to 61%.

On the aggregation of FIBs at ICN routers using routing strategy

Utilizing in-network caching is essential for the current communication network. In the last decade, ICN (Information-Centric Networking) has been under the spotlight as a network that mainly focuses on transmitted and received data rather than on hosts that transmit and receive data. In ICNs, to appropriately forward request packets, a router maintains a routing table called FIB (Forwarding Information Base). However, it is unsuitable for us to assume that FIB can store entries of all contents within a network. This is mainly because the FIB memory is not large enough to store the prefix of all contents. Thus, for realizing global-scale ICNs, it is crucial to develop an effective technique to reduce the size of FIB. In this paper, to tackle the reduction in the FIB size with the aggregation, we propose a routing strategy called constrained shortest-path tree (CSPT) routing. The fundamental idea of our CSPT routing is to combine shortest-paths on the network and that on a shortest-path tree of the network, which is intended to enhance the effect of FIB aggregation. Furthermore, we extensively investigate the relationship, i.e., trade-off, between the FIB aggregation and the communication performance of ICN using CSPT routing. Consequently, we reveal that our CSPT routing can dramatically reduce the number of FIB entries while suppressing the increase in the number of hops required to deliver request packets.

Trailblazer: A proactive caching, blockchain, minimum content retrieval latency, and energy cost-aware resource and job orchestration scheme for publisher-subscriber based 6G ICN services

With the rise of information-centric networks (ICN), the user can access the caching content from nearby caching nodes rather than the remote content server through in-network caching facilities. The existing articles did not look into minimum caching content retrieval latency, user energy consumption, user financial cost, and maximum service provider profit-aware proper resource orchestration and job scheduling policies all at once, taking into account multiple publishers and subscriber-based caching jobs, blockchain, user-owned and service provider cache, pre-caching, neighbor collaboration, and available resources. To suppress these challenges, this article offers a proactive pre-caching, collaboration, blockchain, minimum latency-aware resource, and job scheduling policy for 6G ICN services that takes into account publishers’ and subscribers’ caching job requests, user-owned and service provider cache, available resources, and deadline. The experimental results visualized that at least 16% content retrieval delay, 66% energy, and 22% service provider profit gain are attained in the proposed scheme over the existing techniques.

A hybrid Bi-level management framework for caching and communication in Edge-AI enabled IoT

The proliferation of IoT devices has led to a surge in network traffic, resulting in higher energy usage and response delays. In-network caching has emerged as a viable solution to address this issue. However, caching IoT data faces two key challenges: the transient nature of IoT content and the unknown spatiotemporal content popularity. Additionally, the use of a global view on dynamic IoT networks is problematic due to the high communication overhead involved. To tackle these challenges, this paper presents an adaptive management approach that jointly optimizes caching and communication in IoT networks using a novel bi-level control method called BC3. The approach employs two types of controllers: a global ILP-based optimal controller for long-term timeslots and local learning-based controllers for short-term timeslots. The long-term controller periodically establishes a global cache policy for the network and sends specific cache rules to each edge server. The local controller at each edge server solves the joint problem of bandwidth allocation and cache adaptation using deep reinforcement learning (DRL) technique. The main objective is to minimize energy consumption and system response time with utilizing the global and local observations. Experimental results demonstrate that the proposed approach increases cache hit rate by approximately 12% and uses 11% less energy compared to the other methods. Increasing the cache hit rate can lead to a reduction in about 17% in response time for user requests. Our bi-level control approach offers a promising solution for leveraging the network's global visibility while balancing communication overhead (as energy consumption) against system performance. Additionally, the proposed method has the lowest cache eviction, around 19% lower than the lowest eviction of the other comparison methods. The eviction metric is a metric to evaluate the effectiveness of adaptive caching approach designed for transient data.

Learning automata based routing and content delivery for vehicular named data networking

In Vehicular Named Data Networking (VNDN), vehicle mobility leads to frequent reverse-path interruptions and stale forwarding information, which further results in content delivery failures and disenables aggregation. Taking into account these limitations, we propose a learning automata based routing and content delivery solution for VNDN. The novelties of the solution are threefold: (1) Learning automata is leveraged to make forwarding decisions and deliver vehicular contents; (2) Various metrics including connection durations, unsatisfied requests and data response delays are utilized to compute the selection probability of each vehicle in order to select the best vehicle for content delivery; and (3) Aggregation and in-network caching are achieved through stable reverse paths. The typical application of the proposal is that vehicles rapidly access nearby road conditions to maneuver safe driving. The proposal is evaluated quantitatively. Compared with the existing solutions, the proposal reduces the content delivery latency and overheads by nearly 32.54% and 38.3%, respectively.

RMBCC: A Replica Migration-Based Cooperative Caching Scheme for Information-Centric Networks

How to maximize the advantages of in-network caching under limited cache space has always been a key issue in information-centric networking (ICN). Replica placement strategies aim to fully utilize cache resources by optimizing the location and quantity distribution of replicas in the network, thereby improving the performance of the cache system. However, existing research primarily focuses on optimizing the placement of replicas along the content delivery path, which cannot avoid the inherent drawback of not being able to leverage off-path cache resources. The proposals for off-path caching cannot effectively solve this problem as they introduce excessive complexity and cooperation costs. In this paper, we address the trade-off between cache resource utilization and cooperation costs by introducing a mechanism complementary to replica placement. Instead of redesigning a new caching strategy from scratch, we propose a proactive cooperative caching mechanism (called RMBCC) that involves an independent replica migration process, through which we proactively relocate replicas evicted from the local cache to neighboring nodes with sufficient cache resources. The cooperation costs are effectively controlled through migration replica filtering, migration distance limitation, as well as hop-by-hop migration request propagation. Extensive simulation experiments show that RMBCC can be efficiently integrated with different on-path caching strategies. Compared with representative caching schemes, RMBCC achieves significant improvements in evaluation metrics such as cache hit ratio and content retrieval time, while only introducing negligible cooperation overhead.

Distance-based dynamic caching and replacement strategy in NDN-IoT networks

The amount of data on the Internet has risen noticeably due to the exponential increase in the number of Internet of Things (IoT) devices. Recently, Information-Centric Networking (ICN) is acknowledged as a suitable framework for creating IoT network protocols. One notable feature of ICN is in-network caching, which stores the data packets on intermediate routers/nodes that can be accessed by the subscribers when required. This work proposes a novel Distance-based dynamic caching and replacement strategy (DBDCRS) which involves a light weight calculation that utilizes the request aggregation to find the request weight of the requests stored in Pending interest table (PIT) and node weight of a node based on the distance from the subscriber and IoT publisher to accomplish the caching decision. To eliminate the data redundancy, the scheme caches a particular content on a single node along the specific interest-data path. Additionally, a custom cache replacement policy is introduced which retains the essential contents in cache. Simulation results show that our proposed DBDCRS scheme outperform other in-network cache placement schemes in terms of cache hit ratio, server hit reduction ratio, average response latency, and energy consumption.

Review of Congestion Control Methods in Named Data Network

In recent years, with the development of new networking technologies, the demand for networks has shifted from simple resource sharing to large-scale content distribution. This change has led to the gradual inadequacy of the traditional TCP/IP architecture in meeting the current needs of production and daily life. In this context, Named Data Networking (NDN) has emerged. NDN networks, with their content-centric nature and features such as in-network caching, multi-source forwarding, and routing control, have attracted significant attention from researchers both domestically and internationally. However, the novel architecture of the network also presents new challenges for congestion control research in NDN. This paper conducts thorough research on the related work of congestion control in NDN, provides a detailed overview of existing research efforts in NDN congestion control, and describes potential future research directions in NDN congestion control. The aim is to provide valuable references for future research on congestion control in NDN.

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.

A survey of classification cache replacement techniques in the contentcentric networking domain

Content-Centric Networking (CCN) is an innovative approach that emphasizes content. A key strategy in CCN for spreading data across the network is in-network caching. Effective caching methods, including content placement and removal tactics, enhance the use of network resources. Cache replacement, also known as content eviction policies, is essential for maximizing CCN's efficiency. When cache storage is full, some content must be removed to make room for new items due to limited storage space. Recently, several advanced replacement strategies have been developed to determine the most suitable content for eviction. This study categorizes the latest cache replacement strategies into various groups such as static, space scarcity, content update, centralized, energy-efficient, weighted, adaptive, and based on dynamic popularity. These categories are based on the approaches suggested in previous research. Additionally, this paper provides a critical analysis of existing methods and suggests future research directions. To the best of our knowledge, this is the most up-to-date and comprehensive review available on this topic.

CTJIF-ICN: A Coadjuvant Trust Joint Interest Forwarding Mechanism in Information Centric Networks

The Information centric networks (ICN) transforms the focal point of current Internet paradigm to data centric approach from host centric approach by allowing content driven forwarding and in-network caching mechanisms. Though NDN (Named data networking) paradigm of ICN assures a secure content communication, it is vulnerable to different attacks by the malicious nodes. To minimize the hazards from compromised nodes and to improve the network security, the remaining nodes should transparently receive information about such nodes. This will restrict the forwarding strategy to exploit these malicious nodes for forwarding interest and content as well. Our protocol introduces a dynamic model for prediction of trust in order to evaluate the node trust. Proposed approach observes the historical behaviors of node and uses extended fuzzy logic rules for the prediction of future behaviors to evaluate the node’s trust value. This prediction model is incorporated within the trust based forwarding mechanism that aims to forward interest through secure and shortest path. The extensive simulation study has been carried out to analyze the protocol performance in ns-3 driven ndnSIM-2.0 simulator for performance metrics such as data discovery latency, packet delivery ratio, network overhead, detection ratio and cache hit ratio. When we integrate our trust joint forwarding strategy to state-of-the-art protocols, their performance is significantly improved up to approximately 10-35% against stated performance measures for realistic network topology.

Controller-driven vector autoregression model for predicting content popularity in programmable named data networking devices.

Named Data Networking (NDN) has emerged as a promising network architecture for content delivery in edge infrastructures, primarily due to its name-based routing and integrated in-network caching. Despite these advantages, sub-optimal performance often results from the decentralized decision-making processes of caching devices. This article introduces a paradigm shift by implementing a Software Defined Networking (SDN) controller to optimize the placement of highly popular content in NDN nodes. The optimization process considers critical networking factors, including network congestion, security, topology modification, and flowrules alterations, which are essential for shaping content caching strategies. The article presents a novel content caching framework, Popularity-aware Caching in Popular Programmable NDN nodes (PaCPn). Employing a multi-variant vector autoregression (VAR) model driven by an SDN controller, PaCPn periodically updates content popularity based on time-series data, including 'request rates' and 'past popularity'. It also introduces a controller-driven heuristic algorithm that evaluates the proximity of caching points to consumers, considering factors such as 'distance cost,' 'delivery time,' and the specific 'status of the requested content'. PaCPn utilizes customized DATA named packets to ensure the source stores content with a valid residual freshness period while preventing intermediate nodes from caching it. The experimental results demonstrate significant improvements achieved by the proposed technique PaCPn compared to existing schemes. Specifically, the technique enhances cache hit rates by 20% across various metrics, including cache size, Zipf parameter, and exchanged traffic within edge infrastructure. Moreover, it reduces content retrieval delays by 28%, considering metrics such as cache capacity, the number of consumers, and network throughput. This research advances NDN content caching and offers potential optimizations for edge infrastructures.

Cache-MCDM: A hybrid caching scheme in Mobile Named Data Networks based on multi-criteria decision making

Robust and reliable content retrieval in a Mobile Ad Hoc Network (MANET) is challenged by its intermittent connectivity and mobility characteristics. In-network caching and name-based content retrieval attributes of Named Data Networks (NDN) can counterattack the stated challenges of MANETs. The distance- or hop-based caching schemes, proposed mainly for infrastructure NDN, admit contents either close to the content source, client, or midway, which are trivial to realize since content mainly travels from the network core (content sources) to the edge (clients). In NDN-based MANETs, the mobility attribute causes source and consumer nodes to change their locations frequently. Therefore, the content can travel from the network core to the edge and vice-versa. Under such circumstances, the traditional hop-based schemes that cache at particular points, for instance, either near the source, client, or halfway, may vandalize the efficient content retrieval in MANETs. Thus, proposing a new strategy capable of caching at any of the stated caching points considering varying network contexts, for instance, location change of source and consumer, is inevitable. Such a strategy can scale well in terms of network resource usage and significantly improve PDR and content retrieval latency performances in NDN-based MANET. In this direction, we propose an AHP-based hybrid caching scheme, namely Cache-MCDM, that equips each router with a set of different hop-based caching options and employs AHP-TOPSIS method to pick the most suitable caching option. The proposed method models the suitable option selection as a Multi-Criteria Decision Making (MCDM) problem. Simulation reveals that Cache-MCDM is more effective and efficient than hop-based probabilistic caching (HPC), opportunistic caching (OppProb), probabilistic in-network caching (ProbCache), and SourceCacheProb (SCP), in terms of (i) PDR by approximately 3%, 15%, 10%, and 11%, respectively, (ii) latency by approximately 25%, 145%, 75%, and 77%, respectively, (iii) retransmission ratio by approximately 7%, 30%, 25%, and 25%, respectively, and (iv) cache replacement rate by approximately 8%, 100%, 80%, and 25%, respectively.

A practical and UC-secure decentralized key management and authentication scheme based on blockchain for VNDN

In Vehicular Named Data Networking (VNDN), most of the existing key management mechanisms still rely on the hierarchical key trust model or the Public Key Infrastructure (PKI), in which the centralized certificate authority is used as a Trusted Third Party (TTP) to provide a signature for the user?s public key. Thus, the TTP becomes vulnerable to attacks and maybe there exists a singlepoint failure problem. In addition, the in-network caching in the VNDN may incur a threat to the system and make it is vulnerable to the DoS attack caused by Interest flooding aimed at the Content-Store. To tackle these security issues, we firstly propose an efficient decentralized key management solution based on blockchain for VNDN. Secondly, based on the proposed key management scheme, a lightweight mutual authentication scheme and a key agreement protocol for V2X are respectively proposed in this paper. Finally, we analyze the security attributes of our solutions in the Universally Composable (UC) framework. Our analysis results show that our novel schemes can meet the security requirements of our solutions. In addition, our experimental results show our new schemes have highly efficient, lower computation and communication costs than other related schemes.

On Learning Suitable Caching Policies for In-Network Caching

On Learning Suitable Caching Policies for In-Network Caching

MsDD: A novel NDN producer mobility support scheme based on multi-satellite data depot.

The Named Data Networking (NDN) is currently an important future network framework, and the mobility issue of producers within NDN is a primary challenge. However, in environments characterized by frequent producers mobility, traditional producer mobility support schemes still encounter issues such as excessive consumer delays and interest packet loss. With the development of The 6th generation communication technology (6G), integrating ground networks with satellites has emerged as a potential solution to address the aforementioned problems. In this paper, we propose an NDN producer mobility support scheme based on multi-satellite data depot, named MsDD. The proposed scheme proactively caches producer data into a data depot built on a low-earth orbit satellite constellation to minimize the impact of NDN producer mobility on network performance. We design data depot construction strategy, in-network caching strategy, and routing strategy based on forwarding hint to facilitate effective communication in satellite networks. Experimental results using ndnSIM demonstrate that compared with other existing schemes, MsDD can effectively shield the impact of producer mobility on consumer delay, delivery ratio, and signaling overhead, and MsDD has a clear advantage in terms of consumer delay and delivery ratio.

Enabling In-Network Caching in Traditional IP Networks: Selective Router Upgrades and Cooperative Cache Strategies

Enabling In-Network Caching in Traditional IP Networks: Selective Router Upgrades and Cooperative Cache Strategies

An efficient content replacement policy to retain essential content in information-centric networking based internet of things network

In the current scenario, TCP/IP is widely used in the Internet of Things (IoT) for disseminating data, addressing, and controlling traffic. However, the exponential growth of IoT devices has incurred the TCP/IP-based network from mismanagement due to heavy traffic, address space scarcity, and low efficiency. In the last few years, Information-centric networking (ICN) has emerged as an excellent choice to address the above issues. One of the important characteristics of ICN is In-network Caching, in which contents are cached at the intermediate nodes. Most in-network caching strategies use traditional replacement policies such as First in first out, least recently used, and least frequently used, ignoring the essential content properties, eventually evicting the vital contents. This work introduces a novel content replacement scheme that proactively records the number of requests and access time of the content in the Pending interest table (PIT) and considers essential content attributes, e.g., number of requests, remaining lifetime, and upcoming request waiting time, before replacement to retain vital contents in the cache. The simulations are performed on the ndnSIM framework of NS-3 to evaluate the performance of our proposed replacement scheme with other widely used benchmark replacement schemes and tested under six different caching strategies. The experimental finding indicates that, on average, the proposed replacement scheme shows 28.94% and 27.49% increase in cache hit ratio and server hit reduction ratio while 22.30% and 30.64% reduction in response delay and energy consumption compared to NDN-FIFO, NDN-LRU, and NDN-LRFU.

ICN-Based Enhanced Content Delivery for CDN

With the rapid growth of internet traffic, the traditional host-to-host TCP/IP architecture is subject to many service limitations faced with content-oriented applications. Various novel network architectures have been proposed to solve these limitations, among which Information-Centric Networking (ICN) is one of the most prominent. ICN features the decoupling of content (service) from the physical devices storing (providing) it through location-independent naming, and offers inherent enhancement to network performance, such as multicast and in-network caching. ICN in-network caching has been extensively studied, and we believe that it may also be the main incentive for ISPs to deploy ICN. A CDN (content delivery network) is a typical content-oriented network paradigm that aims to provide the fast delivery of content. In this paper, we leverage the advantages of the in-network caching of ICN to enhance the content delivery efficiency of CDN by integrating ICN as a service. First, we present our design of a content delivery network enhanced with ICN, called IECDN. Additionally, we formulate a mathematical model to optimize the performance of our proposed design and conduct a series of evaluations. The results indicate that our proposed design provides significant performance gains while reducing bandwidth consumption and shows better resilience to traffic surge.

Low delay fragment forwarding in LEO satellite networks based on named data networking

The LEO satellite network with cache and computing capabilities has become an important evolution of the next generation (6G) mobile communication network. The satellite networks employing Named Data Networking (NDN) can achieve swift content access through in-network caches and data multicast. The data packet is the basic unit of transmission in NDN. In order to adapt to the limited MTU of links, large data packets must be transmitted in fragments. However, due to the issues such as large transmission delay, redundant reassembly, and infeasible fragment reuse, the existing fragmentation methods in NDN cannot be applied to satellite communication. In this paper, we propose a low delay fragment forwarding method in NDN: Direct Forwarding and Reuse of Fragments (DFRF). Specifically, the content in the large data packet will be split and packaged into fragments that conform to NDN semantics. Once the fragment is received by the satellite router, it can be forwarded directly without reassembly, thus saving the forwarding delay. In addition, we design a new fragment format and the list-based cache, so that all fragments generated from the same data packet can be cached intact in a list, and each fragment can be reused as a complete packet in the content store (CS). The proposed approach has been further evaluated and the simulation results show that compared with the NDN Link Protocol (NDNLP), using the DFRF method, the end-to-end transmission delay of large content is reduced by up to 51%, and the content acquisition delay is reduced by up to 60% through fragment reuse.