Content Delivery Networks Research Articles

Competitive Analysis of Online Elastic Caching of Transient Data in Multi-Tiered Content Delivery Network

Competitive Analysis of Online Elastic Caching of Transient Data in Multi-Tiered Content Delivery Network

Content delivery network solutions for the CMS experiment: The evolution towards HL-LHC

The Large Hadron Collider at CERN in Geneva is poised for a transformative upgrade, preparing to enhance both its accelerator and particle detectors. This strategic initiative is driven by the tenfold increase in proton-proton collisions anticipated for the forthcoming high-luminosity phase scheduled to start by 2029. The vital role played by the underlying computational infrastructure, the World-Wide LHC Computing Grid, in processing the data generated during these collisions underlines the need for its expansion and adaptation to meet the demands of the new accelerator phase. The provision of these computational resources by the worldwide community remains essential, all within a constant budgetary framework. While technological advancements offer some relief for the expected increase, numerous research and development projects are underway. Their aim is to bring future resources to manageable levels and provide cost-effective solutions to effectively handle the expanding volume of generated data. In the quest for optimized data access and resource utilization, the LHC community is actively investigating Content Delivery Network (CDN) techniques. These techniques serve as a mechanism for the cost-effective deployment of lightweight storage systems that support both, traditional and opportunistic compute resources. Furthermore, they aim to enhance the performance of executing tasks by facilitating the efficient reading of input data via caching content near the end user. A comprehensive study is presented to assess the benefits of implementing data cache solutions for the Compact Muon Solenoid (CMS) experiment. This in-depth examination serves as a use-case study specifically conducted for the Spanish compute facilities, playing a crucial role in supporting CMS activities. Data access patterns and popularity studies suggest that user analysis tasks benefit the most from CDN techniques. Consequently, a data cache has been introduced in the region to acquire a deeper understanding of these effects. In this paper, the details of the implementation of a data cache system in the PIC Tier-1 compute facility are presented. It includes insights into the developed monitoring tools and discusses the positive impact on CPU usage for analysis tasks executed in the region. The study is augmented by simulations of data caches, with the objective of discerning the most optimal requirements in both size and network connectivity for a data cache serving the Spanish region. Additionally, the study delves into the cost benefits associated with deploying such a solution in a production environment. Furthermore, it investigates the potential impact of incorporating this solution into other regions of the CMS computing infrastructure.

A secured channel for transmitting multimedia contents in peer-assisted networks

The Internet's explosive growth has raised demand for effective online video streaming services and cast doubt on the viability of peer-to-peer (P2P) networks and conventional content distribution networks (CDN). To facilitate efficient video streaming, Peer-Assisted Networks (PA-CDNs) integrate the best aspects of P2P networks and CDNs. Transferring data content across a protected channel platform is crucial since the PA-CDNs strategy uses both servers and peers, optimizing both delivery methods to offer the best possible user experience. However, it is vulnerable to assaults. By guaranteeing secure access management and addressing security concerns, this study offers a strong security model to strengthen and improve security in PA-CDN network environments. The outcome of the experiment indicates that the strategy works. Strong security model to strengthen and improve security in PA-CDN network environments. The outcome of the experiment indicates that the strategy works.

Beyond Belady to Attain a Seemingly Unattainable Byte Miss Ratio for Content Delivery Networks

Beyond Belady to Attain a Seemingly Unattainable Byte Miss Ratio for Content Delivery Networks

Improving the efficiency of resource allocation in educational content delivery networks using the 1C:ESB integration bus

Learning Management Systems (LMS) play a key role in the educational process by providing students with various educational content and instructors with tools to monitor student knowledge and assess progress. However, as the number of students increases, the load on data transmission channels increases, which can lead to a decrease in the quality of learning. To solve this problem, Content Delivery Networks (CDN) are used to speed up the loading of websites and reduce the load on servers. CDN ensure the availability and security of websites and improve their scalability (resistance to smooth load growth) by distributing content across a network of servers around the world, allowing users to access content faster and more efficiently.Integration data exchange bus (Enterprise Service Bus, ESB) can be an effective tool for optimizing CDN content distribution algorithm. It allows integration of different systems and applications, enabling data exchange between them. This is particularly useful in the context of distance learning, which requires fast and reliable delivery of educational content, feedback, learning analytics, etc. Implementing an integration bus of data exchange with LMS-based distance learning system can be a key factor in ensuring an efficient and quality educational process. The article considers the properties and characteristics of the integration bus and justifies the use of the integration bus to optimize the algorithm of CDN content distribution, in particular in LMS.

ENHANCING THE RESILIENCE OF IOT NETWORKS: STRATEGIES AND MEASURES FOR MITIGATING DDOS ATTACKS

The Internet of Things (IoTs) are emerging and become a vital need in our daily routine. The privacy protection and insecurity of these IoT-based devices face many challenges. Distributed denial of service (DDoS) attacks in IoT networks become a significant growing challenge that is addressed in this research. The resilience and strategy for IoT devices due to distributed denial of service (DDoS) attacks assess current security measures by proposing modern procedures to upgrade the strength of IoT frameworks. This article proposes a mechanism that mitigiates the effects of DDoS attacks in IoTs, that cause significant destruction to existing systems. Utilizing secondary data from Kaggle, the machine is trained and tested. Our proposed approach incorporates descriptive statistics, correlations, t-tests, chi-square tests, and regression analyses to supply a systematic understanding of IoT security by critically analyzing the existing variants of numerous DDoS attacks, Security issues in IoTs, and creation of them in Botnets or zombies. Our findings show that the proposed security techniques are viable and detection rates correlate with security viability. The proposed model asses various network threat and cybersecurity arrangements for mitigating DDoS attacks in IoT’s and outperforms the previously implemented Web Application Firewall (WAF), Bot Mitigation, Resource Prioritisation, and Content Delivery Networks (CDNs)based DDoS mitigation techniques by 80.5%, 88%, 86% in terms of effectiveness, T-test, chi test, and correlation.

A cost-efficient content distribution optimization model for fog-based content delivery networks

The massive data demand requires content distribution networks (CDNs) to use evolving techniques for efficient content distribution with guaranteed quality of service (QoS). The distributed fog-based CDN model, with optimal fog node placements, is a suggested aproach by researchers to meet this demand. While many studies have focused on improving QoS by optimizing fog node placement, they have rarely considered the impact on content distribution, affected by placement, usage changes, and delivery rates. Therefore, the practical approach to fog node placement for CDN services must examine its impact on content distribution. Further, current research on fog-based CDN lacks formal methods to address key challenges: R1) strategic placement of fog nodes to process end-user requests; R2) construction of a content distribution path with guaranteed QoS; R3) cost minimization of building a fog-based CDN model. We construct this as a joint optimization problem by considering four parameters: geographical regions, open public Wi-Fi access points (OPWAPs) locations, QoS, and cost to achieve research objectives R1–R3. As a solution, we propose a dual-step framework. First, a heuristic for optimal fog node placement based on geographic regions and OPWAP locations is proposed. Second, we propose two algorithms, Greedy Performance-based Node Selection (GPDS) and Greedy Fog Node Selection algorithm (GFNSA), for selecting fog nodes, minimizing the cost of building a fog-based CDN while achieving optimal content distribution paths. The results demonstrate that the proposed methods outperform the baseline techniques and provide near-optimal solutions to the problem.

Generalized hierarchical coded caching

Optimizing data traffic is a key concern in content distribution networks to reduce the bandwidth needed to serve the requested content to the final users. In this context, hierarchical coded caching has been proposed as an effective method for reducing traffic. The typical two-level scenario consists in a tree-like structure: on the first layer, a set of intermediate nodes or helpers with local caches store and serve content to a subset of users at the second layer, who also have their local caches. A central server partially stores its content between the first- and second-layer caches, in uncoded form, and subsequently transmits coded messages to satisfy the files demanded by the users. This topology has been thoroughly analyzed in the literature over the past years; however, little attention has been put in arbitrary topologies, where users might be connected to multiple helper nodes, which is especially interesting for scenarios such as wireless networks. Thus, in this paper we study a hierarchical two-level coded caching system with an arbitrary topology and propose a novel content distribution method for this generalized model that leverages the multiple connections between users and helpers to improve the performance of the distribution process. We give achievability results for this system and compare its performance with other classical single-layer and two-layer coded caching systems. Our results show that further gains are possible by using two levels of caching in different operating regimes.

Framework for content server placement using integrated learning in content delivery network

<p>Content placement is a significant concern in content delivery networks (CDN), irrespective of various evolving studies. Existing methodologies showcase various significant unaddressed issues concerning content placement approaches' complexities. Therefore, the proposed study presents a novel computational framework towards dynamic content placement strategy using a novel integrated machine learning approach. Simplified mathematical modelling is used to formulate and solve the content placement problem. At the same time, reinforcement learning and the sequential attentional neural network have been utilized to optimize the decision-making towards placement of content servers. Designed and assessed over a Python environment, the proposed scheme is witnessed to exhibit 35% reduced bandwidth utilization, 20% reduced delay, 23% reduced computational resource utilization, and 28% reduced algorithm processing time in contrast to existing predictive content placement schemes.</p>

Capture Beyond the Platforms: The Material and Infrastructural Conditions for Digital Journalism

News organisations are growing increasingly dependent on digital infrastructures for the distribution of news, AI implementation, and management of data. In this article, we argue that this dependency goes beyond the level of platforms, reaching into the internet backbone infrastructures that transmit, peer, deliver and host data on which journalism relies. Using Norway as a case, we map the actors involved in the subsea cable sectors, internet exchange points, content delivery networks and the data centres and cloud services that traffic, store and process digital journalism. Given the private, foreign nature of most of the actors involved in these infrastructures, we ask how these backbone infrastructures create interdependencies for the news industries in terms of data sovereignty, distribution control and regulatory jurisdiction. We discuss journalism’s dependency on each of these infrastructural sectors using sociotechnical theory, the contribution to which is to extend the range at which platform capture is considered in journalism scholarship.

Optimization of UAV base station placement for D2D content delivery network

Optimization of UAV base station placement for D2D content delivery network

XRL-SHAP-Cache: an explainable reinforcement learning approach for intelligent edge service caching in content delivery networks

XRL-SHAP-Cache: an explainable reinforcement learning approach for intelligent edge service caching in content delivery networks

An Effective Investigation for Quality of Service Enhancement of Content Delivery Network for HTTP Live Streaming Using H.265

In the contemporary era, the prevailing trend among individuals is the widespread utilization of streaming technology to indulge in audio or video content emanating from a server. This innovative approach negates the necessity for downloading the content beforehand, allowing users to seamlessly revel in the material through the streaming mechanism. However, this cutting-edge technology mandates a substantial bandwidth to uphold its Quality of Service (QoS) at an optimal level. Challenges may arise, such as packet loss, attributed to the restricted bandwidth provided by the network service provider, thereby compromising the delivered content’s quality. To address this issue, one viable solution is the integration of CDN (Content Delivery Network), a technology proven to enhance the quality of content delivered through streaming services. This research endeavors to elevate the quality of live video streaming by leveraging CDN. The HTTP Live Streaming (HLS) format for content streaming, the study empirically demonstrates that CDN significantly improves the Quality of Service. As a result, the proposed method Content Delivery Network (CDN) using H.265 plays vital role in live video streaming. The result shows that live video streaming with CDN outperforms without CDN. Specifically, the live video streaming experience with CDN showcases a remarkable throughput average of 5899.7 kbps, coupled with a minimal packet loss ratio average of 0.05%. This stands in stark contrast to the version without CDN, which exhibits a comparatively diminished throughput average of 5287.3 kbps and a higher packet loss ratio average of 0.22%. These empirical findings strongly emphasize the effectiveness of CDN in elevating the Quality of Service for live video streaming. The tangible enhancements in throughput and the reduction of packet loss achieved through CDN implementationcontribute significantly to an enriched user experience. The evidence supports the notion that integrating CDN technology not only optimizes the technical performance of live video streaming but also plays a pivotal role in enhancing the overall satisfaction and engagement of users with the content delivery system.

Server Saturation in Skewed Networks

We use bipartite graphs to model compatibility constraints that arise between tasks and servers in data centers, cloud computing systems and content delivery networks. We prove that servers with skewed graph neighborhoods saturate with tasks in a limiting regime. The neighborhood of a server is skewed if it contains a diverging number of dispatchers with uniformly bounded degrees.

Proof of Work and Secure Element in CDN-assisted online voting

Electronic voting consistently fails to supplant conventional paper ballot due to a plethora of security shortcomings. Not only are traditional voting methods mediocre in terms of transparency, audit, and costs, but they also encompass a principal-agent problem, where acting governments have real capability for tampering. Here I propose Proof of Work by user devices to fortify integrity of votes as cast and seed-isolated time-based one-time passwords to force observable polling stations. Coupled with end-2-end verifiability the measures pro-posed are intended to improve on the issues mentioned. A state would only issue single-use authorizations to vote, while an untrusted publisher would collect and publish two unrelatable lists: votes and voters. Eventually, anyone could tabulate results. Content distribution networks are shown to be instrumental security providers. Weaknesses of proposed architecture are discussed.

Server Saturation in Skewed Networks

We consider a model inspired by compatibility constraints that arise between tasks and servers in data centers, cloud computing systems and content delivery networks. The constraints are represented by a bipartite graph or network that interconnects dispatchers with compatible servers. Each dispatcher receives tasks over time and sends every task to a compatible server with the least number of tasks, or to a server with the least number of tasks among \mathrmd compatible servers selected uniformly at random. We focus on networks where the neighborhood of at least one server is skewed in a limiting regime. This means that a diverging number of dispatchers are in the neighborhood which are each compatible with a uniformly bounded number of servers; thus, the degree of the central server approaches infinity while the degrees of many neighboring dispatchers remain bounded. We prove that each server with a skewed neighborhood saturates, in the sense that the mean number of tasks queueing in front of it in steady state approaches infinity. Paradoxically, this pathological behavior can even arise in random networks where nearly all the servers have at most one task in the limit.

SLAP: Segmented Reuse-Time-Label Based Admission Policy for Content Delivery Network Caching

‘‘Learned” admission policies have shown promise in improving Content Delivery Network (CDN) cache performance and lowering operational costs. Unfortunately, existing learned policies are optimized with a few fixed cache sizes while in reality, cache sizes often vary over time in an unpredictable manner. As a result, existing solutions cannot provide consistent benefits in production settings. We present SLAP , a learned CDN cache admission approach based on segmented object reuse time prediction. SLAP predicts an object’s reuse time range using the Long-Short-Term-Memory model and admits objects that will be reused (before eviction) given the current cache size. SLAP decouples model training from cache size, allowing it to adapt to arbitrary sizes. The key to our solution is a novel segmented labeling scheme that makes SLAP without requiring precise prediction on object reuse time. To further make SLAP a practical and efficient solution, we propose aggressive reusing of computation and training on sampled traces to optimize model training, and a specialized predictor architecture that overlaps prediction computation with miss object fetching to optimize model inference. Our experiments using production CDN traces show that SLAP achieves significantly lower write traffic (38%-59%), longer SSDs lifetime (104%-178%), a consistently higher hit rate (3.2%-11.7%), and requires no effort to adapt to changing cache sizes, outperforming existing policies.

Delivering content: Modular broadcasting technology and the role of content delivery networks

Television distribution has changed profoundly over the past 10–15 years. Now increasingly geared towards streaming, broadcasting's value chain hinges on content delivery networks (CDNs) to reach audiences. CDNs are important for content quality, as they constitute the part of the chain that stores and transmits data from broadcasters to the end-user. In this article, we investigate what this value chain shift means for television distribution in Norway, a country where global actors like Akamai and Amazon's CloudFront dominate the CDN market. Based on seven whiteboard-based, co-creation sessions with 15 industry experts representing broadcasters, telecoms, regulators and interest organisations, a value chain analysis reveals that the distribution part of the chain is outsourced and modular. As the technology of television distribution becomes increasingly outsourced, we ask what this means for television's autonomy as a universal service provider.

Enabling seamless migration of optical metro-urban networks to the multi-band: unveiling a cutting-edge 6D planning tool for the 6G era

The relentless demand for high-bandwidth services and applications in the beyond-5G/6G era necessitates optical networks to provide ample spectral resources to accommodate the increasing traffic loads. This requirement is especially pronounced in metro and regional segments, where a projected traffic compound annual growth rate (CAGR) of over 40%, driven by content delivery network (CDN) traffic concentrated near the end users, threatens to push the fiber capacity to its limits on a number of heavily utilized links in the short to medium term. This limitation cannot be circumvented despite the utilization of spectrally efficient modulation formats designed for short-distance transmission. Thus, it is imperative to explore migration strategies to solutions that allow the expansion of spectral resources beyond the current usage of the extended C-band (4.8 THz). In this article, we present a comprehensive evaluation of multi-homed edge-to-core routing, modulation-level selection, and spectrum assignment simulations conducted over reference metropolitan area networks (MANs) by leveraging on a novel network planner called 6D-MAN, which we have developed to adapt to heterogeneous multi-layer networks based on multi-band and multi-fiber transmission. Our simulations consider coherent transmission with flexible modulation format transponders operating at capacities ranging from 100 to 400 Gbps on the 50 GHz grid and explore link-by-link migration strategies restricted to the C+L-band, ensuring optimal performance in terms of the generalized signal-to-noise ratio (GSNR). The obtained results demonstrate that deploying L-band equipment on a selected number of links effectively extends the lifespan of existing networks, enabling congestion-free operation with minimal intervention. In their entirety, our findings underscore the importance of contemplating alternative spectral resources beyond the conventional C-band. They unequivocally accentuate the potential of L-band equipment strategic deployment to tackle capacity constraints in MANs, resulting in a 60% reduction in fiber length and a remarkable 45% decrease in new fiber-pair link deployment needs. The profound implications of efficient fiber capacity utilization manifest themselves in substantial OPEX and optical total cost of ownership savings, amounting to approximately 71% and 17%–27%, respectively, over a 10-year period. This research provides valuable insights for MAN operators seeking sustainable strategies to support the growing demands of future beyond-5G/6G services.

Selective encryption of video frames using the one-time random key algorithm and permutation techniques for secure transmission over the content delivery network

Selective encryption of video frames using the one-time random key algorithm and permutation techniques for secure transmission over the content delivery network