Solution For Content Delivery Research Articles

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.

Indoor Content Delivery Solution for a Museum Based on BLE Beacons.

The digital transformation advancement enables multiple areas to provide modern services to their users. Culture is one of the areas that can benefit from these advances, more specifically museums, by presenting many benefits and the most emergent technologies to the visitors. This paper presents an indoor location system and content delivery solution, based on Bluetooth Low Energy Beacons, that enable visitors to walk freely inside the museum and receive augmented reality content based on the acquired position, which is done using the Received Signal Strength Indicator (RSSI). The solution presented in this paper was created for the Foz Côa Museum in Portugal and was tested in the real environment. A detailed study was carried out to analyze the RSSI under four different scenarios, and detection tests were carried out that allowed us to measure the accuracy of the room identification, which is needed for proper content delivery. Of the 89 positions tested in the four scenarios, 70% of the received signals were correctly received throughout the entire duration of the tests, 20% were received in an intermittent way, 4% were never detected and 6% of unwanted beacons were detected. The signal detection is fundamental for the correct room identification, which was performed with 96% accuracy. Thus, we verified that this technology is suitable for the proposed solution.

A Multi-User Cost-Efficient Crowd-Assisted VR Content Delivery Solution in 5G-and-Beyond Heterogeneous Networks

The latest evolution of wireless communications enables user access rich Virtual Reality (VR) services via the Internet, including while on the move. However, providing a premium immersive experience for massive number of concurrent users with various device configurations is a significant challenge due to the ultra-high data rate and ultra-low delay requirements of live VR services. This paper introduces an innovative multi-user cost-efficient crowd-assisted delivery and computing (MEC-DC) framework, which leverages mobile edge computing and end-user resources to support high performance VR content delivery over 5G-and-beyond heterogeneous networks (5G-HetNets). The proposed MEC-DC framework is based on three main solutions. First is a novel buffer-nadir-based multicast (BNM) mechanism for VR transmissions over 5G-HetNets. BNM ensures smooth and synchronized user viewing experience by maximizing the average playback buffer-nadir of all participants with stochastic optimization. Second and third are practical distributed algorithms: the cost-efficient multicast-aware transcoding offloading (MATO) and crowd-assisted delivery algorithm (CAD) which optimize jointly multicast delivery and video transcoding. The algorithms optimality and complexity were investigated. The proposed MATO-CAD solution was evaluated with real datasets, trace-driven numerical simulations, and prototype-based experiments. The trace-driven experimental results showed how the proposed solution provides 18% throughput improvement, lowest delay and best playback freeze ratio in comparison with three other state-of-the-art solutions.

Optimized video content delivery for mobile networks using the transformative computing model

It is a challenge for future mobile networks to cope with enormous video traffic due to bottlenecks of the backhaul capacity and spectrum shortages. To address this situation, we study a content delivery solution for video-on-demand (VoD) applications in orthogonal frequency division multiplexing (OFDM)-based mobile networks in this paper. As done in some transformative computing models, the proposed solution firstly collects the user and environment information, and then computes a global-optimized video delivery scheme based on the collected information. The video delivery scheme is orchestrated using a novel video delivery model that implements deep cooperation among video users and device-to-device (D2D) communications. Several orchestration algorithms are proposed to improve the performance of video delivery.

Efficient vehicular content delivery

Nowadays, most of the traffic in vehicular networks is relevant to content, so the content-to-requester method could be an ideal solution for vehicular content delivery. However, due to the features of vehicular networks such as high mobility, the content-to-requester paradigm might cause the frequent content delivery failures and increase the content delivery cost. Inspired by the idea that the address-based mechanism can support mobility and reduce content delivery costs, we are motivated to take advantage of the address-based mechanism to achieve the content-to-requester paradigm. Based on this motivation, we propose a vehicular content delivery scheme with mobility support (VCDM). In VCDM, the receiver and provider handovers are achieved so that a receiver can correctly receive the requested content from a provider via one successful content delivery process. Moreover, a location-based address is proposed so that a requester can acquire the content from the nearest provider in a unicast way. Finally, VCDM is analyzed and evaluated, and the data show that VCDM effectively improves the content delivery success rate and reduces the content delivery cost and latency.

Content Delivery Based on Vehicular Cloud

Nowadays, Vehicular Ad Hoc NETworks (VANETs) become actually the main force to disseminate and deliver position-related contents such as road-safety information, so it is significant to improve content delivery efficiency. Usually, users employ the address-centric mechanism to upload/download contents to/from servers located in backbone networks, which leads to considerable content delivery latency and costs. This paper proposes a Content Delivery solution based on Vehicular Cloud (CDVC) and aims to take advantage of the vehicular cloud and name-based mechanism to reduce the content delivery cost and latency. In CDVC, vehicular cloud members store and provide the content locally so that vehicles can rapidly retrieve the content from the nearest member. Moreover, the hierarchical name-based mechanism is proposed to achieve the request aggregation so that vehicles can share the content via one content delivery process. Finally, CDVC is evaluated, and the experimental data show that CDVC effectively reduces the content delivery cost and latency.

Muslin: A QoE‐aware CDN resources provisioning and advertising system for cost‐efficient multisource live streaming

SummaryDelivering video content with a high and fairly shared quality of experience is a challenging task in view of the drastic video traffic increase forecasts, as live video traffic will grow 15‐fold by 2022. Currently, content delivery networks provide numerous servers hosting replicas of the video content, and consuming clients are redirected to the closest server. Then, the video content is streamed using adaptive streaming solutions. However, servers and network links often become overloaded during major events, and users may experience a poor or unfairly distributed quality of experience, unless more servers are provisioned. In this paper, we propose Muslin, a streaming solution supporting a high, fairly shared end users' quality of experience for live streaming, while minimizing the required content delivery platform scale. Muslin leverages on MS‐Stream, a content delivery solution, which aggregates video content from multiple servers to offer a high quality of experience for its users. Muslin dynamically provisions servers and replicates content into servers and advertises servers to clients based on real‐time delivery conditions. We have used Muslin to replay a 1‐day video‐games event, with hundreds of clients and several test beds. Our results show that our approach outperforms traditional content delivery schemes by increasing the fairness and quality of experience at the user side with a smaller infrastructure scale.

Modeling and Analysis of a Shared Edge Caching System for Connected Cars and Industrial IoT-Based Applications

The next revolution of industrial applications, known as smart industry or Industry 4.0, will rely on Internet of Things (IoT) to automate the monitoring, inspection, and control of industrial equipment and processes. In Industry 4.0, efficient content delivery is one of the fundamental challenges to be addressed. Nowadays, the promising solution for content delivery in smart industrial applications is the use of hierarchical caching systems at the network edge (5G small cells). This approach reduces the delay for content delivery and helps improve the performance of smart industrial applications. However, the caching management is a challenging and complex task, especially in those scenarios of shared storage resources on edge devices to support multiple concurrent applications (e.g., industrial, mobile users, and connected cars applications). In this article, we study the performance of a shared edge caching system for content delivery in smart industry and connected cars applications. To do so, we propose a mathematical framework to model the performance of a hierarchical shared edge caching system. The proposed mathematical framework considers the distinct content catalogs of the different applications (e.g., industrial and connected cars applications) and content request characteristics from industrial IoT devices and vehicles. Numerical results show that the performance of the shared edge caching system is sensitive to vehicular mobility (i.e., vehicular speed).

Toward Dynamic Link Utilization for Efficient Vehicular Edge Content Distribution

With the significant advance of connected vehicles, future demand for vehicular infotainment services will be greatly increased. Traditional content distribution approaches based on typical cellular architecture suffer from long latency and unstable connections in high-dynamic vehicular environments and even may cause congestion on the backhaul network due to a large amount of requested data. In this paper, we propose a novel content delivery framework by leveraging the 5G edge networks, in which the content caching and data prefetching techniques are exploited accordingly. We investigate the comprehensive dynamic link utilization problem in 5G edge networks from the perspectives of vehicle users and network operator, respectively. For the vehicle users’ perspective, our aim is to maximize the vehicular content distribution throughput through optimal scheduling of vehicular access link slots, and also the utilization problem of backhaul link slots in edge networks is studied to reduce the data access delay of vehicles. For the network operator's perspective, the objective is to maximize the total profit of the network operator, and therefore, the auction model is utilized for the vehicular access link slot scheduling and the backhaul link utilization is analyzed in terms of compensations and costs. Finally, extensive simulations are conducted to demonstrate the efficiency of the proposed solutions for edge content delivery of connected vehicles.

A DASH-Based Adaptive Multiple Sensorial Content Delivery Solution for Improved User Quality of Experience

Increasing number of researchers are focusing on the emerging communication technologies which enrich user perceived quality of experience by involving vision, auditory, tactile, olfaction, gustatory, and other senses. However, there are multiple challenges related to using multiple sensorial media (i.e., mulsemedia), including synchronization with the traditional multimedia content and delivery over diverse network environments. This paper proposes MulseDASH, a novel multiple sensorial media content delivery solutions based on the Dynamic Adaptive Streaming over HTTP standard (DASH). MulseDASH is described and evaluated in a real test-bed in terms of the effectiveness of its adaptive streaming and synchronization mechanisms. The extensive testing involving both network emulation and subjective assessment experiments shows how MulseDASH performs an excellent real-time streaming adjustment to match network conditions and improves user quality of experience.

Case Note: Payments to Foreign Entity to Accelerate Access to Online Content Not Income under Income Tax Act or United States Treaty

This case note summarizes the recent ruling by the Authority for Advance Rulings in Akamai Technologies Inc. that payments received by a foreign company from its Indian subsidiary for a content delivery solution to accelerate online content and business processes under a services reseller agreement were not in the nature of fees for technical services or royalties under the Income-tax Act, 1961 or the India-United States Income Tax Treaty (1989), and that the arrangement did not create a permanent establishment of the foreign company in India.

Network-Coding Approach for Information-Centric Networking

The current internet architecture is inefficient in fulfilling the demands of newly emerging internet applications. To address this issue, several over-the-top application-level solutions have been employed, making the overall architecture very complex. Information-centric-networking (ICN) architecture has emerged as a promising alternative solution. The ICN architecture decouples the content from the host at the network level and supports the temporary storage of content in an in-network cache. Fundamentally, the ICN can be considered a multisource, multicast content-delivery solution. Because of the benefits of network coding in multicasting scenarios and proven benefits in distributed storage networks, the network coding is apt for the ICN architecture. In this study, we propose a solvable linear network-coding scheme for the ICN architecture. We also propose a practical implementation of the network-coding scheme for the ICN, particularly for the content-centric network (CCN) architecture, which is termed the coded CCN. The performance results show that the network-coding scheme improves the performance of the CCN and significantly reduces the network traffic and average download delay.

Mitigating Interference in Content Delivery Networks by Spatial Signal Alignment: The Approach of Shot-Noise Ratio

Multimedia content, especially videos, is expected to dominate data traffic in next-generation mobile networks. Caching popular content at the network edge, namely content helpers (base stations and access points), has emerged as a solution for low-latency content delivery. Compared with traditional wireless communication, content delivery has a key characteristic that many signals coexisting in the air carry identical popular content. However, they can interfere with each other at a receiver if their modulation-and-coding (MAC) schemes are adapted to individual channels following the classic approach. To address this issue, we present a novel idea of content adaptive MAC (CAMAC) where adapting MAC schemes to content ensures that all signals carrying identical content are encoded using an identical MAC scheme to achieve spatial MAC alignment. Consequently, interference can be harnessed as signals to improve the reliability of wireless delivery. In the remaining part of the paper, we focus on quantifying the gain that CAMAC can bring to a content-delivery network by using a stochastic-geometry model. Specifically, content helpers are distributed as a Poisson point process and each of them transmits a file from a content database based on a given popularity distribution. Given a fixed threshold on the signal-to-interference ratio for successful transmission, it is discovered that the successful content-delivery probability is closely related to the distribution of the ratio of two independent shot noise processes, named a shot-noise ratio . The distribution itself is an open mathematical problem that we tackle in this work. Using stable-distribution theory and tools from stochastic geometry, the distribution function is derived in closed form. Extending the result in the context of content-delivery networks with CAMAC yields the content-delivery probability in different closed forms. In addition, the gain in the probability due to CAMAC is shown to grow with the level of skewness in the content popularity distribution.

A novel self-adaptive content delivery protocol for vehicular networks

Content Delivery Network (CDN) has been successfully adapted to deliver content on the traditional Internet. CDNs help reduce the load on the origin server by transferring part of the responsibility to surrogate servers. Content delivery is even more challenging in vehicular networks given their particular characteristics, such as dynamic topology and large-scale scenarios. In order to overcome these challenges, we propose an effective mobile content delivery solution for vehicular networks. The main contribution to adaptation is the use of the dissemination protocol along with the concepts of CDN, in order to increase content availability without compromising network overhead, regardless of traffic conditions and road networks. Some simulations were performed through the NS3 simulator in which the proposed solution presented an excellent performance compared with other six baseline solutions, in both urban and highway road networks, in terms of content availability and network resource consumption through a high coverage about 80% in highways and 98% in urban environments with a low amount of packet loss (approximately 5% in highway scenarios and 15% in urban scenarios).

When Collaboration Hugs Intelligence: Content Delivery over Ultra-Dense Networks

With the increasing popularity of traffic-intensive video applications, UDNs are treated as one of the most promising technologies for massive video delivery. However, due to the drastic interference between neighboring cells, how to achieve high energy and spectrum efficiency is still an open and challenging problem. This work proposes a systematic solution for content delivery over UDNs by integrating collaboration with intelligence. In particular, we first design a hybrid video coding scheme that is flexible and robust to the dynamic wireless environment. Then an active and proactive video update strategy is designed by intelligently alleviating the impact of the interference. Finally, a collaborative video scheduling scheme is developed to maximize the video quality as well as the energy and spectrum efficiency. Importantly, we summarize three fundamental design guidelines, and believe that they are useful for improving the transmission capacity of UDNs.

A novel hybrid forwarding strategy for content delivery in wireless information-centric networks

Information-centric networking (ICN) is a promising solution for content delivery in multi-hop wireless networks. In these environments, the ICN forwarding strategies typically rely on broadcasting, which facilitates content distribution by taking advantage of the shared medium, but brings about undesirable side effects. To avoid the broadcast-related issues of packet redundancy and unreliability due its unacknowledged mode, a few recent proposals advocated unicasting as the communication mode to resort to, once the content provider has been discovered. However, unicasting may suffer from connectivity breakages due to node mobility and harsh propagation conditions, and, generally, limits the data sharing capability of the wireless medium.In this paper, we design a robust ICN-based forwarding strategy, called Ad Hoc Dynamic Unicast (ADU), that wisely harnesses unicast and broadcast primitives on top of IEEE 802.11-based wireless networks. ADU relies on unicasting for content dissemination after the provider discovery, and promptly falls back to broadcast to find a new content provider in case of a link failure notified by the Medium Access Control (MAC) layer. Extensive simulations in two different multi-hop wireless scenarios, i.e., mobile and vehicular ad hoc networks, under different load settings, assess the ADU performance against benchmark ICN forwarding schemes, representative of broadcast-based and unicast-based solutions. Results show that ADU outperforms them in all circumstances, proving its better responsiveness to link failures, which guarantees a shorter content retrieval delay and a lower message overhead and energy consumption.

Potential of Cost-Effective Mobile Learning in Resource and Bandwidth Constrained Environments

E-learning has received significant research attention over years in order to ensure reliability, availability and cost-effectiveness through Information and Communication Technologies (ICTs). The evolvement of mobile computing devices especially smartphones brings prospects in overcoming the inherent limitations of the Internet when accessing contents on web. Among the potential opportunity revealed includes the ability to work offline. Therefore, this study aims at analyzing the existing online and offline electronic-learning systems in order to explore the uniqueness, technical problems and opportunities in this field. Similarly, this study proposes synchronization and caching solution for cost-effective electronic-learning content delivery. The proposed approach synchronizes contents from the remote servers to local database in mobile computing devices for offline use. It therefore contributes to reliability, cost-effectiveness, timely and increase motivation in learning activities.

An Efficient Cache Strategy in Information Centric Networking Vehicle-to-Vehicle Scenario

Information centric networking (ICN) has been recently proposed as a prominent solution for content delivery in vehicular ad hoc networks. By caching the data packets in vehicular unused storage space, vehicles can obtain the replicate of contents from other vehicles instead of original content provider, which reduces the access pressure of content provider and increases the response speed of content request. In this paper, we propose a community similarity and population-based cache policy in an ICN vehicle-to-vehicle scenario. First, a dynamic probability caching scheme is designed by evaluating the community similarity and privacy rating of vehicles. Then, a caching vehicle selection method with hop numbers based on content popularity is proposed to reduce the cache redundancy. Moreover, to lower the cache replacement overhead, we put forward a popularity prediction-based cooperative cache replacement mechanism, which predicts and ranks popular content during a period of time. Simulation results show that the performance of our proposed mechanisms is greatly outstanding in reducing the average time delay and increasing the cache hit ratio and the cache hit distance.

The Collaboration for Content Delivery and Network Infrastructures: A Survey

With the explosive growth of Internet traffic and the rapid development of network technology, content delivery has become a significant service in the current Internet. However, the existing content delivery solutions, such as peer-to-peer and content delivery network, have many insufficient aspects. Meanwhile, the collaboration between content delivery and network infrastructures has been considered as a promising technique in network field. From the perspective of collaboration, content delivery systems can make full use of the network characteristics and the effective information provided by the network operators, so as to improve the efficiency of the content distribution and optimize the overall performance of the network. In this paper, we present a comprehensive survey on the collaboration for content delivery and network infrastructures. First, we provide some of the works, which have been done on collaboration solutions from two perspectives: evolutionary and revolutionary. And then, the advantages and disadvantages of these solutions are compared and analyzed from three aspects of technology, business, and standardization. Finally, we outline some challenges and research directions in the future.

Priority-Based Content Delivery in the Internet of Vehicles through Named Data Networking

Named Data Networking (NDN) has been recently proposed as a prominent solution for content delivery in the Internet of Vehicles (IoV), where cars equipped with a variety of wireless communication technologies exchange information aimed to support safety, traffic efficiency, monitoring and infotainment applications. The main NDN tenets, i.e., name-based communication and in-network caching, perfectly fit the demands of time- and spatially-relevant content requested by vehicles regardless of their provenance. However, existing vehicular NDN solutions have not been targeted to wisely ensure prioritized traffic treatment based on the specific needs of heterogeneous IoV content types. In this work, we propose a holistic NDN solution that, according to the demands of data traffic codified in NDN content names, dynamically shapes the NDN forwarding decisions to ensure the appropriate prioritization. Specifically, our proposal first selects the outgoing interface(s) (i.e., 802.11, LTE) for NDN packets and then properly tunes the timing of the actual transmissions. Simulation results show that the proposed enhancements succeed in achieving differentiated traffic treatment, while keeping traffic load under control.