Content Delivery System Research Articles

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.

Beyond Echo Chambers: Unraveling the Impact of Social Media Algorithms on Consumer Behavior and Exploring Pathways to a Diverse Digital Discourse

Purpose: This study delves into the intricate dynamics of how social media algorithms cultivate echo chambers, with a focus on their profound influence on consumer behavior. Methodology: Through an exhaustive review of existing literature and detailed case studies, we explore the mechanisms by which personalized content delivery systems on social media platforms not only reinforce users' pre-existing beliefs and preferences but also significantly impact their consumption patterns, decision-making processes, and overall perception of reality. Findings: Our analysis reveals that while these algorithms are designed to enhance user engagement and satisfaction, they inadvertently foster digital polarization, diminish exposure to diverse viewpoints, and contribute to the spread of misinformation. The paper further investigates the broader societal implications of these echo chambers, including decreased public trust in traditional information sources and the erosion of democratic discourse. To counteract these effects, we propose a multifaceted approach encompassing increased algorithmic transparency, user empowerment through digital literacy education, and policy interventions aimed at encouraging content diversity. Unique Contribution to Theory, Policy and Practice: Our recommendations are designed to mitigate the echo chamber effect and foster a more inclusive and well-informed online public sphere. By addressing these challenges, we underscore the need for a concerted effort among stakeholders—including policymakers, educators, and technology developers—to navigate the complexities of the digital landscape and ensure a more diverse and resilient digital environment.

고령자 웰다잉을 위한 법제 개선 방안 (4)

This paper deals with the topic of so-called education about death or preparation for death. This paper, as part of the studies from a legal perspective on the well-dying of the elderly, aims to analyze the current status of legislation and operation related to death (preparation) education and seek improvement points. The Elderly experience so-called ‘death anxiety’, where they feel fear and stress about their own death through the death of family members and relatives. The purpose of death education is to alleviate and resolve this ‘death anxiety’ through understanding the process and nature of death, to rediscover the value and meaning of life, and to have a positive attitude toward the remaining life and the future. Through death education, it becomes possible to exercise the correct ‘right to self-determination’ to independently decide how to end one’s life. This paper reviews the legal and institutional status of death education. The death education for the elderly is carried out as part of elderly education or leisure activities at leisure welfare facilities for the elderly (for example, welfare center for senior citizens, center for senior citizens, educational courses for senior citizens, etc.) under the Welfare of Senior Citizens Act. In addition, Jeju Island is the first and currently only local government in Korea to enact and implement an ordinance on death education. This paper proposes the following as a legal and institutional improvement plan for death education. First, it is necessary to systematically legislate various matters related to death education for the elderly. Next is to improve the death education contents delivery system for the elderly. Lastly, it is required to classify the subjects of death education by age and provide education contents appropriate for each age group, thereby promoting death education for the elderly and institutionalizing death education for youth.

Critical Analysis of OTT Platforms in the light of Censorship Laws in India

The goal of the study paper is to perform a thorough and critical analysis of Over-The-Top (OTT) platforms in India with a particular focus on their content and the difficulties presented by the changing censorship landscape. Concerns about content control have increased due to the explosive expansion of OTT platform usage and the consumption of digital media. The study starts out by giving a general overview of the OTT market in India, charting its development, and analyzing its effects on traditional media. The paper discusses the development of streaming services, content delivery systems, and the elements influencing their enduring appeal to a wide range of audiences. The research then examines the censoring laws and rules that currently apply to India's conventional media, movies, and broadcasting. It examines the issues given by the decentralized and international nature of OTT material as well as how these rules, developed before to the OTT era, relate to the digital medium.Analysis of OTT content's impact on the younger generation and prospective implications on social norm formation receives special focus.Finally, the research provides a critical assessment of the status quo and recommendations for policy makers, content creators and OTT platforms to balance creative freedom with responsible content curation.

REVIEW OF AI IN EDUCATION: TRANSFORMING LEARNING ENVIRONMENTS IN AFRICA

This study analyses artificial intelligence (AI's) impact on education in Africa, focusing on personalized learning, technology integration, and challenges in educational development. This review explores the transformative role of Artificial Intelligence (AI) in reshaping educational landscapes across Africa. As the continent strives for inclusive and quality education, AI emerges as a potent tool with the potential to address educational challenges, enhance learning outcomes, and bridge existing gaps. The review delves into various applications of AI in education, ranging from personalized learning experiences to adaptive assessment methodologies, and examines their impact on diverse learning environments. It gives an overview of the current state of education in Africa, the review highlights the disparities in access, quality, and infrastructure. It also investigates the innovative ways in which AI technologies are being integrated into educational systems. AI-powered adaptive learning platforms, virtual tutors, and intelligent content delivery systems are analyzed for their effectiveness in catering to the diverse needs of students across the continent. The review also addresses the potential of AI in overcoming language barriers, promoting literacy, and fostering digital skills development. Moreover, it explores the role of AI in facilitating teacher support, professional development, and administrative tasks, thereby contributing to the overall improvement of the education ecosystem. Ethical considerations, privacy concerns, and the digital divide are critically examined to ensure that the integration of AI in education aligns with ethical standards and promotes equitable access. Case studies and pilot projects from various African countries are presented to illustrate successful implementations, challenges faced, and lessons learned. Furthermore, the review discusses the importance of collaborative efforts involving governments, educational institutions, technology developers, and the private sector. Policy recommendations and strategic initiatives are explored to guide the responsible and sustainable integration of AI in education across the diverse socio-economic and cultural contexts prevalent in Africa. In conclusion, the review synthesizes the current state of AI in education in Africa, offering insights into its potential to revolutionize learning environments. The transformative power of AI in addressing educational challenges and fostering a culture of continuous improvement is underscored, paving the way for a more inclusive, accessible, and innovative education landscape in the African context.
 Keywords: Artificial Intelligence, Education, Transform Learning, Environments, Africa.

Unveiling the power of knowledge graph embedding in knowledge aware deep recommender systems for e-commerce: A comparative study

Recommendation systems address content delivery system information overload. Recent recommender systems include knowledge-aware deep recommender models. These models train user and item embeddings using Graph Neural Networks and operate on collaborative knowledge graphs that combine user-item interactions with item-entity relationships to deliver more item information. Certain models employ a two-step learning procedure wherein the primary objective is to generate recommendations while simultaneously training knowledge graph embeddings. By co-learning, the models are able to comprehend the structural connections that exist between entities and relations, while also improving user embeddings through the use of previous encounters. The objective of this research endeavour is to assess the efficacy of cutting-edge models through the integration of knowledge graph embedding co-learning and the manipulation of embedding techniques. Co-learning boosts quicker learning and enhances the precision of recommendations, according to empirical findings. When a KG embedding layer was incorporated into KGCN, the recall metric outperformed the initial model by as much as 37%. Compared to translational embedding techniques, RotatE decreased training duration by 18% and demonstrated a noteworthy 15% improvement in the recall metric. The study’s outcome offer valuable guidance for enhancing recommendation accuracy and reducing training time for models incorporating Knowledge Graph (KG) embeddings. Furthermore, the study introduces a new application for complex-valued KG embeddings.

Tobacco Imagery in Indian Over-the-Top (OTT) Media and Its Compliance With Existing Tobacco Laws: A Content Analysis.

Over-the-top (OTT) media are internet-based content delivery systems offering media services to the viewers bypassing the traditional broadcasting platforms. The OTT media, with limited regulatory oversight, can serve as a source of exposure to tobacco-promoting content. This study analyzed the depiction of tobacco imagery in Indian OTT programs and assessed their compliance with existing Indian tobacco control policies. We conducted a content analysis of 28 purposively sampled OTT exclusive programs (14 movies and 14 web series) in India. Breathe California method was used to code the OTT content for tobacco imagery. We assessed the prevalence of tobacco imagery, its duration per episode or program, product placements, and brand appearances. We also evaluated OTT programs adherence to existing tobacco control policies in India. Tobacco imagery was identified in all of the web series and most OTT-exclusive movies. On average the web series depicted seven incidents of tobacco imagery per episode, whereas there were close to 19 incidents of tobacco imagery per movie. Ten minutes of OTT programming (including movies and web series) had on average 8.40 s of tobacco imagery. None of the OTT programs studied fully complied with Indian tobacco control policies. Depiction of tobacco imagery in OTT exclusive programs is common in India. Streaming platforms need to comply with existing tobacco control policies. Furthermore, there is a need to strengthen these policies and strictly enforce them to ensure tobacco-free mass media. India has more than 267 million tobacco users and accounts for the largest share of smokeless tobacco use globally. OTT platforms are largely unregulated and are considered drivers for global tobacco use. This is one of the few studies examining tobacco imagery in Indian OTT content, reporting the gaps in tobacco control policies in India. This study documents the product placement of smokeless tobacco, duration of exposure to tobacco imagery, and empirically report the compliance of OTT platforms with Indian tobacco control policies. The study findings can aid in strengthening tobacco control policies in India.

A systematic review of methodology for the creation of virtual 3D models for use in dental education and a narrative review.

Virtual Reality (VR) technologies can be used as a content-delivery system for the purposes of both entertainment and education. Remote and digital education has become ever so important in a world where global disruptive events such as pandemics and natural disasters can define access to a face-to-face learning environment. An important aspect of VR technologies for dentistry is the creation of digital 3D models. The primary of this review was to answer the focused research question, "What software techniques are used in the creation of digital 3D models for use in dental education." This study systematically evaluates current software and techniques used for creating digital 3D models in dental education using the Preferred Reporting Items for Systematic Reviews (PRIMSA). The search strategies did not find any studies specific to the creation of dental-related 3D models. Therefore, this study for the first time provided an overview of common techniques of 3D model fabrication is discussed. Further some examples of methods of creating 3D models relevant to dentistry such armamentarium and anatomical oral structures have been discussed in considerable detail. The creation of 3D modelling is a rapidly evolving field with software updates and new programs being continually released. This work highlights fundamental lack of published work in the creation of 3D dental models for educational applications.

The Relationship between Course Evaluation and Academic Achievement of University Students Using Latent Profile Analysis

This study was conducted with the purpose of deriving a heterogeneous potential profile through the results of university lecture evaluation, which is students' perception of class and the product of professor-student interaction in the classroom, and identified the factors that affect it. In addition, the degree of learning flow for each potential profile was investigated and the difference was verified. For the analysis, 83,069 cases were used because of the university A course evaluation organized in the second semester of 2020, and a total of 12,919 subjects were studied. As a result of analyzing the aspects of course evaluation through class plan, content delivery, communication, response, and evaluation system, that were the sub-factors of course evaluation, the miscellaneous material profiles were classified in four. It was named as the upper group. As factors determining the latent profile using physiological data analysis. It was discovered that significant differences existed between student features (grade, major field), professor features (position), and lecture variables (category of accomplishment, lecture size). Students with lesser grades have a greater chance of succeeding quickly in the top group than do those in the humanities and social sciences, science, or engineering professions. The likelihood of being in the upper group in a course assessment as well as the likelihood of being in the upper group with higher course evaluation outcomes for general education lectures as opposed to major lectures and smaller lecture sizes increases with decreasing professor status. The level of academic obligation was then examined by potential profile based on the course evaluation outline, and the results revealed that the greater the course evaluation result, the greater the level of educational obligation. This is a significant study because it examines the variables that affect the outcomes of the university's course evaluations, which are done at the end of every semester, as well as the relationship between the outcomes of the course evaluations and academic commitment. This study established a scientific basis for colleges to prepare measures to improve the quality of education through lecture evaluation and emphasized the importance of preparing concrete measures to improve students' learning outcomes in college education.

Metaverse Learning Experience Platform (MLXP) for Immersive Design Thinking to Enhance Digital Intelligence Quotient and Virtual Game Developer Skills

A Metaverse Learning Experience Platform (MLXP) is needed to enhance undergraduate students' creative innovation and professional advancement in multimedia technology and gaming business. This learning aid utilizes immersive design thinking methodology, transforming classroom teaching, connecting teachers and students, and enhancing learning outcomes. This study aims to develop a MLXP for immersive design thinking to enhance the digital intelligence quotient and virtual game developer skills. The research methodology involved three phases: developing the MLXP, developing the immersive design thinking process, and evaluating the skills. The sample group consisted of 36 undergraduate students from the Faculty of Science and Technology at Rajamangala University of Technology Suvarnabhumi, who were enrolled in a game design and game development course from academic year 2022. The research instruments consisted of MLXP, immersive design thinking lesson plan, Digital Intelligence Quotient (DQ) and virtual game developer skills assessment form. The MLXP consisted of 14 components, including a Metaverse Learning management system, metaverse content management system, metaverse content delivery system, metaverse personalized learning tools, analytics and reporting tools, assessment and evaluation tools, immersive collaboration tools, immersive virtual learning space, online self-paced learning space, immersive virtual meeting space, immersive virtual co-working space, immersive virtual presentation space, immersive virtual exhibition space, and immersive virtual portfolio space. The immersive design thinking process on the MLXP involved six steps: empathize, define, ideate, prototype, test, and share. The MLXP and learning process were found to be appropriate at an excellent level, and undergraduate students studying using the MLXP demonstrated excellent digital intelligence quotient and game developer skills.

Network Coding Datagram Protocol for TCP/IP Networks

In this article, a new multicast protocol is introduced at the session layer, which is based on network coding and is called the Network Coding Datagram Protocol (NCDP). The NCDP protocol is specifically designed for content delivery systems that utilize multicast data transmission from multiple sources. The development of the NCDP packet and its operational logic takes into consideration the variability of the protocols used in conjunction with it, as well as the packet header processing algorithms for routing nodes-coders. Additionally, a virtual laboratory bench is proposed to facilitate research on the operation of the protocol. The article also includes the results of testing the NCDP protocol in networks with butterfly and diamond topologies, with a comparison between simple sequential multicast transmission and network coding transmission.

Examining the Use of Mobile Technology to Deliver Tailored Sexual Assault Prevention in a Classroom Environment in the Military: Development and Usability Study.

Advances in mobile technology over the last 10 years have expanded its use in scientific research. However, there are challenges in creating a reliable system for intervention content delivery and data collection in an environment with limited internet connectivity and limited staffing capacity. The Sexual Communication and Consent (SCC) study used tablets to provide individualized Sexual Assault Prevention and Response training in a classroom environment that was both technologically and support staff limited. We developed the SCC Basic Military Training app and a separate Sexual Assault Response Coordinator app to support individualized training within the new SCC program. This paper presents the functionality, protocols, challenges, and feasibility of deploying mobile technology in an educational environment in the military with limited resources. We developed both mobile apps targeting the Apple iOS ecosystem. The Basic Military Training app provided a screening instrument that routed the trainee into 1 of 5 specific intervention programs. Over 2 days of basic military training set 2 weeks apart, trainees received a combined 6 hours of program-specific tablet training, combined with universal, interactive classroom training, led by qualified instructors. The Sexual Assault Response Coordinator app, used to deliver supplemental content to a subgroup of trainees, was made available for voluntary and private use at the Sexual Assault Response Coordinator's office on base. All anonymous data were manually transferred onto laptops, where the data were aggregated into files and securely transferred to the project staff for analysis. The study was conducted at the Lackland Air Force Base, Joint Base San Antonio, with 9196 trainees providing the data. A total of 7742 trainees completed both the sessions of the SCC program and a series of evaluative assessments. Some trainees did not receive day 2 training, and only received day 1 training because the COVID-19 pandemic shortened the study period. Of the 190 SCC classes taught, only one class was unable to complete tablet training because of Apple licensing-related technology failure. The 360 study tablets were distributed across 3 classrooms (120 per classroom) and were handled at least 16,938 times with no reports of breakage or requiring replacement. Wi-Fi access limitations exacerbated the complexity of Apple licensing revalidation and the secure transfer of data from the classroom to project personnel. The instructor staff's limited technical knowledge to perform certain technical tasks was challenging. The results demonstrated the feasibility of deploying a mobile app for tablet-based training in a military educational environment. Although successful, the study was not without technical challenges. This paper gives examples of technical lessons learned and recommendations for conducting the study differently, with the aim that the knowledge gained may be helpful to other researchers encountering similar requirements.

Approach to Software Integration of Heterogeneous Sources of Medical Data Based on Microservice Architecture

The task of processing medical information is currently being solved in our country and abroad by means of heterogeneous medical information systems, mainly at the local and regional levels. The ever-increasing volume and complexity of the accumulated information, along with the need to ensure transparency and continuity in the processing of medical data (in particular, for bronchopulmonary diseases) in various organizations, requires the development of a new approach to integrating their heterogeneous sources. At the same time, an important requirement for solving the problem is the possibility of web-oriented implementation, which will make the corresponding applications available to a wide range of users without high requirements for their hardware and software capabilities. The paper considers an approach to the integration of heterogeneous sources of medical information, which is based on the principles of building microservice web architectures. Each data processing module can be used independently of other program modules, providing a universal entry point and the resulting data set in accordance with the accepted data schema. Sequential execution of processing steps implies the transfer of control to the corresponding program modules in the background according to the Cron principle. The schema declares two types of data schemas - local (from medical information systems) and global (for a single storage system), between which the corresponding display parameters are provided according to the principle of constructing XSLT tables. An important distinguishing feature of the proposed approach is the modernization of the medical information storage system, which consists in creating mirror copies of the main server with periodic replication of the relevant information. At the same time, the interaction between clients and data storage servers is carried out according to the type of content delivery systems with the creation of a connection session between end points based on the principle of the nearest distance between them, calculated using the haversine formula. The computational experiments carried out on test data on bronchopulmonary diseases showed the effectiveness of the proposed approach both for loading data and for obtaining them by individual users and software systems. Overall, the reactivity score of the corresponding web-based applications was improved by 40% on a stable connection.

Reformed QoE-Based Approach in Bitrate-Adaptation for Dynamic Adaptive Streaming Systems

With the COVID-19 pandemic, the demand for popular streaming applications is expected to soar. Ensuring high user-perceived quality correlates with higher profits for content providers and delivery systems. Dynamic adaptive streaming over HTTP (DASH) is a widely adopted video streaming standard, utilized by service providers to provide competitive quality of experience (QoE). DASH is capable of providing seamless streaming even during uncertain network conditions by switching across different video qualities and their corresponding segment bitrates. This paper introduces a non-complex algorithm that allows smooth step-like transition in the streamed video quality. The proposed approach deploys an optimization model to manage key elements that affect the user-perceived experience such as video quality, re-buffering and quality switching events. The objective is to optimize the QoE metric, which is constrained by the network throughput, segment size and buffer occupancy to continuously select the optimum bitrate levels with low complexity.

Media: The Case of Spain and New Spain

This article develops the new concept of environing media against the case of Mexico’s complex history over the past five centuries. To do this, it stakes out a theoretical development consisting in a shift in understanding from media as content-delivery systems to data processors, combining it with a processual understanding of environment as an ongoing and historical process of environing. In addition, the article discusses examples of indigenous media, an area that has so far received very little attention. The Aztec empire was as dependent on media forms as the Spanish colonizers who replaced it, and there are numerous cases of knowledges and practices surviving in hybrid forms, for example as part of maps. For much of its history, the field of media studies has been biased toward questions of (1) ideological or attitudinal influence caused by (2) modern or emergent technologies. This article goes in another direction by thinking about media as (1) environing and (2) residual. Media are agencies of civilizational and environmental order. The rise of digital media in recent decades has reinforced the fundamental logistical role of media as agencies that arrange, catalog, organize, network, and index people, places, and things. Our understanding of media as fundamental constituents of organization joins the recent interest in infrastructures. Calendars, clocks, towers, names, addresses, maps, registers, arms, and money are all infrastructural media. Such media become second nature, morphing biorhythms and altering ecosystems. Today’s planetary digital infrastructure builds upon the long legacy of resource management via databases. We argue for a longer genealogy of the nature shaping logistical role of media that is so evident today. In this article, we refine and exemplify these claims via a case study of some environing media in Mexico, a country with a deep and rich media history.

Deep Neural Network–based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions

Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual apps spanning from on-demand movies and 360° videos to video-conferencing and live streaming. However, robustly delivering visual content under fluctuating networking conditions on devices of diverse capabilities remains an open problem. In recent years, advances in the field of deep learning on tasks such as super-resolution and image enhancement have led to unprecedented performance in generating high-quality images from low-quality ones, a process we refer to as neural enhancement. In this article, we survey state-of-the-art content delivery systems that employ neural enhancement as a key component in achieving both fast response time and high visual quality. We first present the components and architecture of existing content delivery systems, highlighting their challenges and motivating the use of neural enhancement models as a countermeasure. We then cover the deployment challenges of these models and analyze existing systems and their design decisions in efficiently overcoming these technical challenges. Additionally, we underline the key trends and common approaches across systems that target diverse use-cases. Finally, we present promising future directions based on the latest insights from deep learning research to further boost the quality of experience of content delivery systems.

You May Also Like... Privacy: Recommendation Systems Meet PIR

AbstractWe describe the design, analysis, implementation, and evaluation of Pirsona, a digital content delivery system that realizes collaborative-filtering recommendations atop private information retrieval (PIR). This combination of seemingly antithetical primitives makes possible—for the first time—the construction of practically efficient e-commerce and digital media delivery systems that can provide personalized content recommendations based on their users’ historical consumption patterns while simultaneously keeping said consumption patterns private. In designing Pirsona, we have opted for the most performant primitives available (at the expense of rather strong non-collusion assumptions); namely, we use the recent computationally 1-private PIR protocol of Hafiz and Henry (PETS 2019.4) together with a carefully optimized 4PC Boolean matrix factorization.

A real-time large-volume content delivery system using globally distributed storage

A real-time large-volume content delivery system using globally distributed storage

Learning Ecosystem using New Normal Active Administrative Innovation in Thai Society

: Learning ecosystem has been using in educational context in different areas to enhance the development of leaning ability in current situation. The purpose of this article was to propose learning ecosystem using new normal active administrative innovation in Thai society. Documentary study and qualitative research synthesis were used for the study. Results showed that 1) there are four aspects to consider of setting learning ecosystem that consisted of learning differently, supportive collaborative learning, self-directed learning, and thinking utilization. 2) New normal active administrative innovation is an active administration applying constructivism concept that consisted of knowledge, persuasion, decision, implementation, and confirmation. The nature of innovation should have relative advantage, compatibility, less complexity, divisibility, and visibility. 3) e-Learning Ecosystem will be applied in new normal active administrative innovation with 3 aspects consisted of (1) content providers offer content for learning solutions that is linked to competency development and personal development, (2) consultants which are strategy consultant, compensation consultant, information technology consultants, and implementation consultants, and (3) Infrastructure which are learning content management system, content delivery system and tools. Learning ecosystem is not started from how teacher design the lesson, but it will start from acceptance the difference of learners, teachers, parents, and community by performing roles of giving and taking knowledge from learners on supportive collaborative learning

The concept of multicast protocol based on network coding

Research subject. The paper presents the concept of a multicast session protocol based on the net-work coding method. Method. Development of a data transfer protocol based on the analysis of existing principles and models of network coding. Core results. The proposed NCDP multicast protocol is de-signed to work over a datagram transport protocol. The basic structure of the NCDP packet header has been developed, taking into account the variability of the protocols used in conjunction with NCDP. Prac-tical relevance. The proposed protocol is intended for use in content delivery systems based on mul-ticast data transmission from several sources.