Content Delivery Applications Research Articles

Special Issue on Informatics Education: Teaching Data Science through an Interactive, Hands-On Workshop with Clinically-Relevant Case Studies.

In this case report, we describe the development of an innovative workshop to bridge the gap in data science education for practicing clinicians (and particularly nurses). In the workshop, we emphasize the core concepts of machine learning and predictive modeling to increase understanding among clinicians. Addressing the limited exposure of healthcare providers to leverage and critique data science methods, this interactive workshop aims to provide clinicians with foundational knowledge in data science, enabling them to contribute effectively to teams focused on improving care quality. The workshop focuses on meaningful topics for clinicians, such as model performance evaluation and introduces machine learning through hands-on exercises using free, interactive python notebooks. Clinical case studies on sepsis recognition and opioid overdose death provide relatable contexts for applying data science concepts. Positive feedback from over 300 participants across various settings highlights the workshop's effectiveness in making complex topics accessible to clinicians. Our approach prioritizes engaging content delivery and practical application over extensive programming instruction, aligning with adult learning principles. This initiative underscores the importance of equipping clinicians with data science knowledge to navigate today's data-driven healthcare landscape, offering a template for integrating data science education into healthcare informatics programs or continuing professional development.

Optimized Dynamic Cache Instantiation and Accurate LRU Approximations Under Time-Varying Request Volume

Content-delivery applications can achieve scalability and reduce wide-area network traffic using geographically distributed caches. However, each deployed cache has an associated cost, and under time-varying request rates (e.g., a daily cycle) there may be long periods when the request rate from the local region is not high enough to justify this cost. Cloud computing offers a solution to problems of this kind, by supporting dynamic allocation and release of resources. In this paper, we analyze the potential benefits from dynamically instantiating caches using resources from cloud service providers. We develop novel analytic caching models that accommodate time-varying request rates, transient behavior as a cache fills following instantiation, and selective cache insertion policies. Within the context of a simple cost model, we then develop bounds and compare policies with optimized parameter selections to obtain insights into key cost/performance tradeoffs. We find that dynamic cache instantiation can provide substantial cost reductions, that potential reductions strongly dependent on the object popularity skew, and that selective cache insertion can be even more beneficial in this context than with conventional edge caches. Finally, our contributions also include accurate and easy-to-compute approximations that are shown applicable to LRU caches under time-varying workloads.

Dynamic popularity window and distance-based efficient caching for fast content delivery applications in CCN

Content-Centric Networking (CCN) is being established as an emerging Internet architecture that brings efficient data retrieval technology to access the contents with their names. In CCN, the in-network caching capability plays a critical role in the improvement of network performance by reducing the load of content server and increasing the content availability. Thus, the efficiency of the content caching strategy crucially affects the performance of the entire network. Towards this, a novel content caching scheme has been proposed in this article that efficiently utilizes the available caching capacity and improves Quality-of-Service (QoS) during content delivery. To perform optimized caching operations, the proposed scheme considers a dynamic threshold value and takes caching decisions based on two parameters, first is a novel dynamic size popularity window to determine content popularity, and secondly, the distance navigated by the Content message from the preceding on-path router that cached the content copy. For content caching decisions, the dynamic threshold value decreases with an increase in Content message distance from the preceding on-path router (that cached the content) and the content popularity. Using these heuristics, the scheme places the popular contents near the edges of the network. Through extensive simulations, the QoS delivered by the proposed scheme has been examined for different cache sizes on standard Abilene network topology. The results show that the proposed scheme outperforms the existing caching strategies for various performance parameters such as hit-ratio, average network delay, hop count, and average traffic generated in the network. This makes the proposed solution suitable for futuristic Internet architectures with 5G/6G and Industry 4.0 revolutions and their applications where faster content deliveries are required.

Ontology Modelling and Standardized Information Exchange with Content Delivery Applications in Technical Communication

Ontologies are a technology recently used in technical communication (TC) to model information into a multidimensional net. They expand the modelling by taxonomy of metadata in TC. Any kind of relation between multiple classes and instances can be established. These ontologies can appear in the form of semantic correlation rules (SCR), which represent the connection between the metadata of the objects. SCR are used in connection with component content management systems (CCMS), semantic modelling systems (SMS) and content delivery portals (CDP) to deliver the appropriate amount of content in a more precise manner to the end user. In general, Ontology tools, CCMS and CDP are not based on the same ecosystem and therefore, they do not always work together effortlessly. A solution to this problem are exchange formats like the intelligent information Request and Delivery Standard (iiRDS), which enable a standardized information exchange between supported systems. Another solution would be compound information systems (CIS) like ONTOLIS, which combine a CCMS, CDP and SMS all in one. This paper aims to investigate the effect of SCR in the CDP of a CIS like ONTOLIS and to evaluate the use of exchange formats like iiRDS.

A Capacitated House Allocation Game for the Energy Efficient Relays Selection in 5G Multicast Context.

The upcoming fifth generation (5G) wireless networks making use of higher-frequency spectrum bands suffer from serious propagation issues due to high path loss and beam directivity requirements. This promotes the device-to-device communications to boost the transmission reliability at the network edges, providing remarkable benefits in terms of the energy and spectrum efficiency, essential for a wide class of sensors networks and Internet-of-Things. More in general, applications where devices are usually constrained in computational and transmission range capabilities. In such a context, the selection of the proper number of devices arranged as a relay plays a crucial role. Towards this goal, this paper proposes an efficient relay selection scheme minimizing both the delivery transmission delay and the overall energy consumption, i.e., the overall number of relays to be used. By focusing on a multicast content delivery application scenario the problem of interest is formulated as a one-sided preferences matching game. In addition, the strategy designed takes into account specific information, named reputation coefficient, associated to each device jointly with link propagation conditions for allowing the selection of suitable relays for disseminating the content among the devices. The effectiveness of the proposed solution is underpinned by computer simulations, and the performance is evaluated in terms of power consumption, end-to-end delay, and number of selected relays. As confirmed by results, the proposed approach improves network performance compared to the greedy approach, the random algorithm, a scheme previously proposed in literature, and with two game theory-based strategies.

Challenges and Issues of Resource Allocation Techniques in Cloud Computing

In a cloud computing paradigm, allocation of various virtualized ICT resources is a complex problem due to the presence of heterogeneous application (MapReduce, content delivery and networks web applications) workloads having contentious allocation requirements in terms of ICT resource capacities (resource utilization, execution time, response time, etc.). This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. However, there is no published research available in this domain that clearly address this research problem and provides research taxonomy for classification of resource allocation techniques including strategic, target resources, optimization, scheduling and power. Hence, the main aim of this paper is to identify open challenges faced by the cloud service provider related to allocation of resource such as servers, storage and networks in cloud computing. More than 70 articles, between year 2007 and 2020, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and are reviewed under clearly defined objectives. Lastly, the evolution of research in resource allocation techniques has also been discussed along with salient future directions in this area.

Extending intelligent content delivery in technical communication by semantics: microdocuments and content services

We address and develop a new concept for the dynamic delivery of topic-based content created within the domain of technical communication. Corresponding content management environments introduced within the last decades, focused so far on semantically structured and mostly XML-based information models and, more recently, on semantic metadata using taxonomies leading together to concepts of so-called intelligent content. Latest developments attempt to extend these concepts with additional explicit semantic approaches modelled and implemented, for example, by using ontologies and related technologies. In this article, we propose how content users might benefit from these semantic concepts by the delivery of sets of logically connected topics, which can be described as microdocuments (“microDocs”). This generic approach of topic assemblies might also play a role in the provisioning of content by web-services being integrated into different types of content processing and content delivery applications.

Dynamic Network Formation Game With Social Awareness in D2D Communications

The benefit of having a complementary network such as device-to-device (D2D) communications underlaying cellular systems lies in alleviating the traffic overloading burdens at base stations (BSs). This is critical in modern-day scenarios, e.g., in offloading and caching of mobile data traffic, and delivery of popular Internet contents to users. In this paper, we are chiefly interested in the establishment of D2D networks and how such a network evolves dynamically over time as D2D links are continuously formed and broken. Another important yet challenging research opportunity, i.e., the leverage of human users’ social ties for D2D communications, will also be addressed in this paper. To investigate the D2D network formation problem, we look at a game-theoretic framework where the utility function is designed to balance the physical and social domains—where we systematically extract social tie strengths from a real-world data set. To study the evolution of such D2D networks through time in a dynamic stochastic context, we propose a dynamic potential game and show that its equilibrium behaviors can be achieved through some strategy and payoff learning mechanisms. Simulation results verify our analysis. Using a content delivery application to assess the performance of our proposed scheme, it can be shown that major improvements can be obtained in terms of network delay, content accessibility, and BS load reduction.

Enhancement of Compressed Image Transmission in WMSNs Using Modified <inline-formula> <tex-math notation="LaTeX">$\mu$ </tex-math> </inline-formula>-Nonlinear Transformation

Multimedia content delivery applications over wireless sensor networks have been progressively popular. The crucial obstacle to communicating compressed images over wireless multimedia sensor networks (WMSNs) has been the lack of suitable energy efficient processing architectures and strategies. In this letter, we propose a low-complexity energy efficient scheme to improve the transmission quality of images compressed by the embedded zerotrees of wavelet transforms and set partitioning in hierarchical trees algorithms in the WMSNs based on an orthogonal frequency-division multiplexing technique. The proposed scheme use a simple post-inverse discrete Fourier transform modified $\mu $ nonlinear transformation, called $\mu $ -MNLT. Simulation results show the effectiveness of the proposed approach, which gives an improvement of peak signal-to-noise ratio (SNR) of about 30 dB (at SNR = 8 dB) without any bit-error-ratio degradation.

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

Cloud computing with its three key facets (i.e., Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service) and its inherent advantages (e.g., elasticity and scalability) still faces several challenges. The distance between the cloud and the end devices might be an issue for latency-sensitive applications such as disaster management and content delivery applications. Service level agreements (SLAs) may also impose processing at locations where the cloud provider does not have data centers. Fog computing is a novel paradigm to address such issues. It enables provisioning resources and services outside the cloud, at the edge of the network, closer to end devices, or eventually, at locations stipulated by SLAs. Fog computing is not a substitute for cloud computing but a powerful complement. It enables processing at the edge while still offering the possibility to interact with the cloud. This paper presents a comprehensive survey on fog computing. It critically reviews the state of the art in the light of a concise set of evaluation criteria. We cover both the architectures and the algorithms that make fog systems. Challenges and research directions are also introduced. In addition, the lessons learned are reviewed and the prospects are discussed in terms of the key role fog is likely to play in emerging technologies such as tactile Internet.

Improving the transmission control efficiency in Content Centric Networks

The current Internet is facing a lot of challenges, including the transmission inefficiency due to the popularity of content-delivery applications. Content-Centric Networking (CCN) solves this problem by name-oriented routing and in-network caching. However, the existing transmission control approaches are not applicable in CCN.In this paper, we propose Flow-Aware Congestion Estimation (FACE) for congestion control in CCN. FACE predicts the future occupancy of the forwarding queue of the CCN router by historical flow information. Based on the current queue utilization, FACE estimates whether the congestion occurs more accurately. The Pending Interest Table (PIT), as a core component of the CCN router, is also crucial for the transmission control efficiency. Therefore, we then propose RTT-Aware PIT (RAPIT) for more precise transmission control. RAPIT measures the Round-Trip Time (RTT) between a CCN router and a content publisher, and sets PIT entry residence time dynamically based on the measured RTT. The evaluations show that FACE and RAPIT improve the PIT utilization and transmission control efficiency of CCN greatly.

Ephemeral Content Popularity at the Edge and Implications for On-Demand Caching

The ephemeral content popularity seen with many content delivery applications can make indiscriminate on-demand caching in edge networks highly inefficient, since many of the content items that are added to the cache will not be requested again from that network. In this paper, we address the problem of designing and evaluating more selective edge-network caching policies. The need for such policies is demonstrated through an analysis of a dataset recording YouTube video requests from users on an edge network over a 20-month period. We then develop a novel workload modelling approach for such applications and apply it to study the performance of alternative edge caching policies, including indiscriminate caching and cache on kth request for different k. The latter policies are found able to greatly reduce the fraction of the requested items that are inserted into the cache, at the cost of only modest increases in cache miss rate. Finally, we quantify and explore the potential room for improvement from use of other possible predictors of further requests. We find that although room for substantial improvement exists when comparing performance to that of a perfect “oracle” policy, such improvements are unlikely to be achievable in practice.

A smart routing scheme for named data networks

As the popularity of content-delivery applications (e.g., YouTube) grows, the inefficiency of transmission on the Internet has emerged, since in the TCP/IP networks, routers are unaware of the passing contents and the same content might be transmitted through the same path multiple times. To solve the problem as well as other problems, a lot of Information Centric Networking (ICN) architectures, including Named Data Networking (NDN), are proposed. These architectures enable the routers to identify and cache contents.In this paper, we design an efficient and feasible scheme of caching and routing for NDN, i.e., Selective cAching and Dynamic rOuting (SADO). First, we propose a selective caching method that balances caching load among routers and reduces the caching redundancy dramatically. Then, we provide a scalable method to maintain routing information for the in-router cached contents. After that, a probabilistic forwarding method for requests is proposed to minimize the expected cost of fetching contents. Finally, we evaluate the performance of SADO by comprehensive simulations. The simulation results show that SADO achieves a decrease of 34% in the cost of fetching a content and a decrease of 81% in the load carried by the source servers, and a cached content is utilized 0.8 times on average.

Exposure and Use of Mobile Media Devices by Young Children.

Research on children's use of mobile media devices lags behind its adoption. The objective of this study was to examine young children's exposure to and use of mobile media devices. Cross-sectional study of 350 children aged 6 months to 4 years seen October to November 2014 at a pediatric clinic in an urban, low-income, minority community. The survey was adapted from Common Sense Media's 2013 nationwide survey. Most households had television (97%), tablets (83%), and smartphones (77%). At age 4, half the children had their own television and three-fourths their own mobile device. Almost all children (96.6%) used mobile devices, and most started using before age 1. Parents gave children devices when doing house chores (70%), to keep them calm (65%), and at bedtime (29%). At age 2, most children used a device daily and spent comparable screen time on television and mobile devices. Most 3- and 4-year-olds used devices without help, and one-third engaged in media multitasking. Content delivery applications such as YouTube and Netflix were popular. Child ownership of device, age at first use, and daily use were not associated with ethnicity or parent education. Young children in an urban, low-income, minority community had almost universal exposure to mobile devices, and most had their own device by age 4. The patterns of use suggest early adoption, frequent and independent use, and media multitasking. Studies are urgently needed to update recommendations for families and providers on the use of mobile media by young children.

Subjective and objective quality assessment of videos in error-prone network environments

Compression and transmission are two fundamental stages involved in wireless video communications, each of which may cause degradation of the quality of experience (QoE) of end users by producing compression artifacts and packet loss artifacts, respectively. They have their own unique perceptual influences. To provide insight for designing QoE-aware content delivery applications, this paper studies subjective and objective quality of videos containing both types of artifacts. First, subjective quality assessment is conducted, from which interaction between the two types of artifacts during quality perception is investigated. Second, using the subjective data, the performance of the state-of-the-art objective quality metrics is evaluated, with the aim of examining suitability of the existing metrics for their use in error-prone video communication applications. Finally, the developed data set is made publicly available for the community.

Adaptive content caching simulation with visualization capabilities

Current Internet architecture is being challenged by the overwhelming multiplication of available content and the increasing requirements of the content delivery applications. Content Delivery Networks have been playing a catalytic role in content delivery solutions, replicating (caching) content at the edges of the network. In this paper, we have investigated the potential benefits offered by adaptability in overlay content replication, considering changing conditions such as the popularity and the size of the content objects and a system of collaborating content caches. Pursuing the understanding of the influence of these parameters we have designed and implemented a simulation framework, with enhanced visualization and parameterization capabilities, and performed a series of experiments, under varying conditions.

Unveiling the Incentives for Content Publishing in Popular BitTorrent Portals

BitTorrent is the most popular peer-to-peer (P2P) content delivery application where individual users share various types of content with tens of thousands of other users. The growing popularity of BitTorrent is primarily due to the availability of valuable content without any cost for the consumers. However, apart from the required resources, publishing valuable (and often copyrighted) content has serious legal implications for the users who publish the material. This raises the question that whether (at least major) content publishers behave in an altruistic fashion or have other motives such as financial incentives. In this paper, we identify the content publishers of more than 55 K torrents in two major BitTorrent portals and examine their characteristics. We discover that around 100 publishers are responsible for publishing 67% of the content, which corresponds to 75% of the downloads. Our investigation reveals several key insights about major publishers. First, antipiracy agencies and malicious users publish files to protect copyrighted content and spread malware, respectively. Second, excluding the fake publishers, content publishing in major BitTorrent portals appears to be largely driven by companies that try to attract consumers to their own Web sites for financial gain. Finally, we demonstrate that profit-driven publishers attract more loyal consumers than altruistic top publishers, whereas the latter have a larger fraction of loyal consumers with a higher degree of loyalty than the former.

Digital Hardware Design Teaching

This article presents the design and implementation of a complete review of undergraduate digital hardware design teaching in the School of Engineering at the University of Edinburgh. Four guiding principles have been used in this exercise: learning-outcome driven teaching, deep learning, affordability, and flexibility. This has identified discrete electronics as key components in the early stages of the curriculum and FPGAs as an economical platform for the teaching of various digital hardware design concepts and techniques in later stages of the curriculum. In particular, the article presents the detailed design and implementation of one digital hardware design laboratory, called Gateway, which introduces students to synchronous digital circuit development from high level functional specifications, uses Verilog for hardware description and FPGAs as an implementation platform. Biggs’ theory of constructive alignment was applied in the design of this lab’s learning outcomes, lab content, teaching and learning methods, and assessment methods. The lab makes extensive use of multimedia in both lab content delivery and demonstration applications developed by students. Student feedback following the deployment of this lab was overwhelmingly positive and an evaluation of the lab results compared to previous lab offerings’ shows the merit of the approach taken.

Peer-assisted content distribution on a budget

In this paper, we propose a general framework and present a prototype implementation of peer-assisted content delivery application. Our system – called Cyclops – dynamically adjusts the bandwidth consumed by content servers (which represents the bulk of content delivery costs) to feed a set of swarming clients, based on a feedback signal that gauges the real-time health of the swarm. Our extensive evaluation of Cyclops in a variety of settings – including controlled PlanetLab and live Internet experiments involving thousands of users – shows a significant reduction in content distribution costs when compared to existing swarming solutions, with a minor impact on the content delivery times.

Virtualised e-Learning on the IRMOS real-time Cloud

This paper presents the real-time virtualised Cloud infrastructure that was developed in the context of the IRMOS European Project. The paper shows how different concepts, such as real-time scheduling, QoS-aware network protocols, and methodologies for stochastic modelling and run-time provisioning were practically combined to provide strong performance guarantees to soft real-time interactive applications in a virtualised environment. The efficiency of the IRMOS Cloud is demonstrated by two real interactive e-Learning applications, an e-Learning mobile content delivery application and a Virtual World e-Learning application.