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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 proposed are intended to completely decentralize the voting process. 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. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One of the vital components of an organization's prosperity is data. Through true sites that are explicitly intended for showcasing, data might be spread. The created site should satisfy speed and security measures. Cloudflare is an organization that offers content conveyance network administrations, cloud online protection, DDoS relief, and ICANN-licensed space enrollment administrations. Cloudflare typically facilitates the transport of data from website pages so it ends up being faster with splendid execution. Cloudflare confines bots and blocks dangers. Cloudflare fundamentally diminishes spam and dangers while additionally improving quality paces by up to 95%. Cloudflare's savvy framework reserving saves transmission capacity, and that implies less work for the server and less cash. Cloudflare cuts down bandwidth by a typical 60%. Cloudflare decreases open time by half on each site page, bringing about speeding up. [ABSTRACT FROM AUTHOR]

With the advent of 5G+ services, it has become increasingly convenient for mobile users to enjoy high-quality multimedia content from CDN driven streaming and catch-up TV services (Netflix, iPlayer) in the (post-) COVID over-the-top (OTT) content rush. To relieve ISP owned fixed-line networks from CDN streamed multimedia traffic, system ideas (e.g., Wi-Stitch in [45]) have been proposed to (a) leverage 5G services and enable consumers to share cached multimedia content at the edge, and (b) consequently, and more importantly, reduce IP traffic at the core network. Unfortunately, given that contemporary multimedia content might be a monetized asset, these ideas do not take this important fact into account for shared content. We present EdgeMart--a content provider (CP) federated, and computationally sustainable networked (graphical) market economy for paid-sharing of cached licensed (OTT) content with autonomous users of a wireless edge network (WEN). EdgeMart is a unique oligopoly multimedia market (economy) that comprises competing networked sub-markets of non-cooperative content sellers/buyers--each sub-market consisting of a single buyer connected (networked) to only a subset of sellers. We prove that for any WEN-supported supply-demand topology, a pure strategy EdgeMart equilibrium exists that is (a) nearly efficient (in a microeconomic sense) indicating economy sustainability, (b) robust to edge user entry/exit, and (c) can be reached in poly-time (indicating computational sustainability). In addition, we experimentally show that for physical WENs of varying densities, a rationally selfish EdgeMart economy induces similar orders of multimedia IP traffic savings when compared to the ideal (relatively less practical), altruistic, and non-monetized "economy" implemented atop the recently introduced Wi-Stitch WEN-based content trading architecture. Moreover, the EdgeMart concept helps envision a regulated edge economy of opportunistic (pay per licensed file) client services for commercial OTT platforms. [ABSTRACT FROM AUTHOR]

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

Introduction: Moving away can be motivated by a multitude of factors, just as the reasons for not moving away might be different. The individual’s social situation greatly determines the chance of turning their life situation around through moving away. Aims: We investigated the factors that affected the representatives of the three Roma groups researched here (Romungro, Vlach, Boyash) in their moving in the past and in their intentions to move in the future. Methods: A SEM model was developed (N = 570) to analyze the differences between previous movers and non-movers in well-being, socioeconomic status, and social network. We also investigated the effect of the above variables on the intention to move. Data were collected via the “snowball method”. Results: Out of the Vlachs, those who had moved in the past have significantly fewer confidant relatives (p = .021) and also know significantly fewer people pursuing high-prestige vocations (p = .003), moreover, the fewer people pursuing moderate-prestige vocations they know, the more they would like to move away from their present residence (p = .031). Regarding the Boyash, the more favorable their socio-economic situation, the more they would like to move away (p = .007); while regarding the Romungro, the low level of their mental wellbeing (p = .019) and the relatively high number of their confidant relatives constitutes (p = .017) the incentive to change their residence. Conclusions: The spatially mobile Roma who had moved before possess fewer confidant relatives and weak ties. The individual factors connect to the different Roma groups’ moving intentions to various extents.

Content Delivery Networks (CDNs) play a vital role in today's Internet ecosystem. To reduce the latency of loading a website's content, CDNs deploy edge servers in different geographic locations. CDN providers also offer important security features including protection against Denial of Service (DoS) attacks, Web Application Firewalls (WAFs), and recently, issuing and managing certificates for their customers. Many popular websites use CDNs to benefit from both the security and the performance advantages. For HTTPS websites, Transport Layer Security (TLS) security choices may differ in the connections between end-users and a CDN (front-end or user-to-CDN), and between the CDN and the origin server (back-end or CDN-to-Origin). Modern browsers can stop/warn users if weak or insecure TLS/HTTPS options are used in the front-end connections. However, such problems in the back-end connections are not visible to browsers or end-users, and lead to serious security issues (e.g., not validating the certificate can lead to MitM attacks). In this article, we primarily analyze TLS/HTTPS security issues in the back-end communication; such issues include inadequate certificate validation and support for vulnerable TLS configurations. We develop a test framework and investigate the back-end connection of 14 leading CDNs (including Cloudflare, Microsoft Azure, Amazon, and Fastly), where we could create an account. Surprisingly, for all the 14 CDNs, we found that the back-end TLS connections are vulnerable to security issues prevented/warned by modern browsers; examples include failing to validate the origin server's certificate, and using insecure cipher suites such as RC4, MD5, SHA-1, and even allowing plain HTTP connections to the origin. We also identified 168,795 websites in the Alexa top 1 million that are potentially vulnerable to Man-in-the-Middle (MitM) attacks in their back-end connections regardless of the origin/CDN configurations chosen by the origin owner. [ABSTRACT FROM AUTHOR]

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

Introduction: Moving away can be motivated by a multitude of factors, just as the reasons for not moving away might be different. The individual’s social situation greatly determines the chance of turning their life situation around through moving away. Aims: We investigated the factors that affected the representatives of the three Roma groups researched here (Romungro, Vlach, Boyash) in their moving in the past and in their intentions to move in the future. Methods: A SEM model was developed (N = 570) to analyze the differences between previous movers and non-movers in well-being, socioeconomic status, and social network. We also investigated the effect of the above variables on the intention to move. Data were collected via the “snowball method”. Results: Out of the Vlachs, those who had moved in the past have significantly fewer confidant relatives (p = .021) and also know significantly fewer people pursuing high-prestige vocations (p = .003), moreover, the fewer people pursuing moderate-prestige vocations they know, the more they would like to move away from their present residence (p = .031). Regarding the Boyash, the more favorable their socio-economic situation, the more they would like to move away (p = .007); while regarding the Romungro, the low level of their mental wellbeing (p = .019) and the relatively high number of their confidant relatives constitutes (p = .017) the incentive to change their residence. Conclusions: The spatially mobile Roma who had moved before possess fewer confidant relatives and weak ties. The individual factors connect to the different Roma groups’ moving intentions to various extents. [ABSTRACT FROM AUTHOR]

In recent years, image and video super-resolution have gained attention outside the computer vision community due to the outstanding results produced by applying deep-learning models to solve the super-resolution problem. These models have been used to improve the quality of videos and images. In the last decade, video-streaming applications have also become popular. Consequently, they have generated traffic with an increasing quantity of data in network infrastructures, which continues to grow, e.g., global video traffic is forecast to increase from 75% in 2017 to 82% in 2022. In this paper, we leverage the power of deep-learning-based super-resolution methods and implement a model for video super-resolution, which we call VSRGAN+. We train our model with a dataset proposed to teach systems for high-level visual comprehension tasks. We also test it on a large-scale JND-based coded video quality dataset containing 220 video clips with four different resolutions. Additionally, we propose a cloud video-delivery framework that uses video super-resolution. According to our findings, the VSRGAN+ model can reconstruct videos without perceptual distinction of the ground truth. Using this model with added compression can decrease the quantity of data delivered to surrogate servers in a cloud video-delivery framework. The traffic decrease reaches 98.42% in total. [ABSTRACT FROM AUTHOR]

Copyright of German International Journal of Modern Science / Deutsche Internationale Zeitschrift für Zeitgenössische Wissenschaft is the property of Artmedia24 and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modern key-value stores, object stores, Internet proxy caches, and Content Delivery Networks (CDN) often manage objects of diverse sizes, e.g., blobs, video files of different lengths, images with varying resolutions, and small documents. In such workloads, size-aware cache policies outperform size-oblivious algorithms. Unfortunately, existing size-aware algorithms tend to be overly complicated and computationally expensive. Our work follows a more approachable pattern; we extend the prevalent (size-oblivious) TinyLFU cache admission policy to handle variable-sized items. Implementing our approach inside two popular caching libraries only requires minor changes. We show that our algorithms yield competitive or better hit-ratios and byte hit-ratios compared to the state-of-the-art size-aware algorithms such as AdaptSize, LHD, LRB, and GDSF. Further, a runtime comparison indicates that our implementation is faster by up to 3× compared to the best alternative, i.e., it imposes a much lower CPU overhead. [ABSTRACT FROM AUTHOR]

Latency is one of the key parameters of Internet services. However, it is difficult to correctly assess a service by its latency. Many latency measurements are blocked en route by routers and firewalls. For this reason, the service latency is not fully known. This work proposes a method to assess Internet services including the blocked latency measurements. Survival theory is applied to process latency values. The results show that the omission of blocked latencies from statistical processing severely underestimates the service latency. Two Internet service providers were compared as an example. Their latency difference was 9 ms using the traditional approach. The survival latency resulted in a difference of 17 ms. The method of survival latency can be used to increase revenues in e-commerce and to improve the experience of online gaming.

The transmission bandwidth of a vehicle–ground connection is low when an EMU (electric multiple unit) is running in a high-speed scenario. To this end, this paper focuses on the need to solve the problem of the poor bandwidth of the vehicle–ground integration information network, and proposes a vehicle–ground integration information network scheme for EMUs based on small base stations. Based on the existing wi-fi system of the EMU, in order to realize the coverage of the 5G signal in the carriage, this paper—through the deployment of the technical characteristics of 5G—sinks the customized UPF (user plane function) and MEC (mobile edge computing) to the train carriage, and expands the internet channels of the train carriage. Relying on the technologies of MEC and CDN (content delivery network) for high-speed railways, network extension service products can satisfy passengers' needs around network rate and delay. On the one hand, this can relieve the pressure of the network backhaul and save the bandwidth resources of the vehicle–ground integration information network. On the other hand, it can help operators to reduce the investment of network construction, operation, and maintenance. As a result, the proposed scheme can inspire the products that match the extended service needs of the passenger, realize the technical and innovation value of the 5G mobile network, and achieve business model innovation in high-speed mobile scenarios. [ABSTRACT FROM AUTHOR]

Aiming at the problem of how edge computing and Content Delivery Network (CDN) edge nodes implementing the resource coordination, the technology and method of CDN cache software adapting to virtual machines and containers are proposed. By comparing and analyzing the performance test data of CDN in three deployment modes of physical machine, container and virtual machine, the performance loss caused by CDN virtualization is evaluated. The performance loss of the container mode is small, and its performance is comparable to the physical machine. The performance loss of the virtual machine mode is large, and its performance is equivalent to about 75%of the physical machine. According to the nominal value of performance, the virtualized CDN edge node can release most of the central processing unit, memory and disk resources, and achieve resource sharing with edge computing.

Kubernetes is one of the platforms which provides different features that help in the deployment of applications. This platform provides different ways to enhance the application’s capability. With the better exploration of these ways, we can provide the best Content Delivery Network (CDN) services. Some of the important Kubernetes features that are useful in the deployment of CDN application is highlighted in this paper. The aim of this paper is the analysis of the CDN application deployment and the demonstration of high)speed data delivery from the CDN application. We deployed a single-node Kubernetes edge cluster on the physical machine using Intel’s Open NESS software toolkit. We installed the NGINX-based CDN applications on the Kuberenetes cluster. To achieve higher speed, the Single Root I/O Virtualization (SR-IOV) interface is used between the edge node and the CDN client machine. The performance measurements of the CDN application show higher data delivery speed. [ABSTRACT FROM AUTHOR]

Large content providers and content distribution network operators usually connect with large Internet service providers (eyeball networks) through dedicated private peering. The capacity of these private network interconnects is provisioned to match the volume of the real content demand by the users. Unfortunately, in cases in which there is a surge in traffic demand, (e.g., due to trending content or massive software updates) the capacity of the private interconnect may deplete, requiring the content provider/distributor to reroute the excess traffic through transit providers. Although such overflow events are rare, they negatively impact content providers, Internet service providers, and end-users. Such impact includes unexpected delays and disruptions that reduce the quality of the user experience, as well as direct costs paid by the Internet service provider to the transit providers. In this article, we examine the problem of predicting an overflow event in order to enable content and Internet service providers to handle the excess traffic in a timely manner. We propose an ensemble of deep learning models trained to predict overflow events over a short-term horizon of 2–4 hours and predict the specific interconnections through which the excess traffic will enter the Internet service provider. Evaluated with 2.5 years (2017-2019) of traffic measurement data from a large European Internet service provider, the models were shown to successfully recall 65% of the events with precision of 51% on average. While the lockdowns imposed by the COVID-19 pandemic reduced the overflow prediction accuracy, the pandemic’s impact on the accuracy was temporary. Although the lockdown continued on and off, the performance of models trained before the pandemic regained their performance during April-May 2020. [ABSTRACT FROM AUTHOR]

In recent years, image and video super-resolution have gained attention outside the computer vision community due to the outstanding results produced by applying deep-learning models to solve the super-resolution problem. These models have been used to improve the quality of videos and images. In the last decade, video-streaming applications have also become popular. Consequently, they have generated traffic with an increasing quantity of data in network infrastructures, which continues to grow, e.g., global video traffic is forecast to increase from 75% in 2017 to 82% in 2022. In this paper, we leverage the power of deep-learning-based super-resolution methods and implement a model for video super-resolution, which we call VSRGAN+. We train our model with a dataset proposed to teach systems for high-level visual comprehension tasks. We also test it on a large-scale JND-based coded video quality dataset containing 220 video clips with four different resolutions. Additionally, we propose a cloud video-delivery framework that uses video super-resolution. According to our findings, the VSRGAN+ model can reconstruct videos without perceptual distinction of the ground truth. Using this model with added compression can decrease the quantity of data delivered to surrogate servers in a cloud video-delivery framework. The traffic decrease reaches 98.42% in total.

The rapid development of blockchain technology has provided new ideas for network security research. Blockchain-based network security enhancement solutions are attracting widespread attention. This paper proposes an Internet domain name verification method based on blockchain. The authenticity of DNS (Domain Name System) resolution results is crucial for ensuring the accessibility of Internet services. Due to the lack of adequate security mechanisms, it has always been a challenge to verify the authenticity of Internet domain name resolution results. Although the solution represented by DNSSEC (Domain Name System Security Extensions) can theoretically solve the domain name verification problem, it has not been widely deployed on a global scale due to political, economic, and technical constraints. We argue that the root cause of this problem lies in the significant centralization of the DNS system. This centralized feature not only reduces the efficiency of domain name verification but also has the hidden risks of single point of failure and unilateral control. Internet users may disappear from the Internet due to the results of fake, subverted, or misconfigured domain name resolution. This paper presents a decentralized DNS cache verification method, which uses the consortium blockchain to replace the root domain name server to verify the authenticity of the domain name. Compared with DNSSEC's domain name verification process, the verification efficiency of this method has increased by 30%, and there is no single point of failure or unilateral control risk. In addition, this solution is incrementally deployable, and even if it is deployed on a small number of content delivery network servers, satisfactory results can be obtained. [ABSTRACT FROM AUTHOR]

In the era of social media, the political speech of undergraduates blots out the sky and covers up the earth, which perhaps generates the negative effect. To enhance the management ability of government departments, it is considerably necessary to pay more attention to the public opinion. However, the current researches on the public opinion mainly focus on mathematical modeling or data mining irrespective of public opinion analysis. Consider that Convolutional Neural Network (CNN) has the strong data analysis ability, this paper uses CNN to realize the special application, that is, politics public opinion analysis of undergraduates, which has two functions. On one hand, greatly help the government departments eliminate the crisis timely; On the other hand, correctly guide the political education of undergraduates. Besides, this paper also presents a case study based on Content Delivery Network (CDN) deployment, in which a monitor system of public opinion analysis is implemented to analyze the undergraduates' political speech. Finally, with three public opinion dissemination modes consideration, the experiments are made. The results show that CNN has better training ability and the whole deployment is more significant compared to the state‐of‐the‐art schemes. [ABSTRACT FROM AUTHOR]

Copyright of Study on Optical Communications / Guangtongxin Yanjiu is the property of Study on Optical Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to accelerate the industrialization and commercialization of 5G and promote the integration and innovation development of 5G with various industries,the operators launched the demonstration project of 5G business application.The typical business scenarios under 5G network was firstly analyzed,the architecture of system was described,then hardware scheme was given including 4K collector,cloud platform and broadcast terminal.Then software solutions were proposed including management platform,cloud fast encoding system,4K transcoding platform，CDN and network slicing.

The delivery of multimedia contents through a Content Delivery Network (CDN) is typically handled by a specific third party, separated from the content provider. However, in some specific cases, the content provider may be interested in carrying out this function using a private CDN, possibly using a off-sourced network infrastructure.The differences between this scenario and the typical content delivery one can be summarized as follows. First, we have a different workload as the content consumer are typically part of the same organization that is the content provider. Second, the off-sourced nature of the network infrastructure has a major impact on the available choices for CDN design. In this paper we discuss the optimization model for the design of such CDN infrastructure and we validate the results through a real case study.

In Software Defined-Content Delivery Networks (SD-CDN), the policies of tenants such as Youtube, Netflix, Office 365, etc. are not the same due to having different 5G traffic requirements for such contents as enhanced Mobile Broadband (eMBB), ultra-reliable low-latency (URLLC) and massive machine-type communication (mMTC). This leads SD-CDN multi-tenant slicing to provide different services with limited network resources, where each tenant can functionally manage their own virtual slice of a physical component according to service level agreements (SLAs). However, they are not permitted to dynamically configure their own components. Therefore, the physical end-to-end configuration of all edge devices causes extra hardware and bandwidth costs. Although software as a service (SaaS) is more preferred to handle cost-efficiency on a switch configuration that increases forwarding throughput (Mbps) with a less number of physical components in SD-CDN, the edge devices can be only served as infrastructure as a service (IaaS) currently. This motivation leads us to serve the switch as a service that includes both IaaS and SaaS characteristics. Therefore, we propose an OpenFlow as a service (OFaaS) design where each tenant has flow management and switch configuration permissions on their own virtual slice. In flow management, we define a novel Service Oriented Architecture (SOA) to orchestrate OFaaS driven topology by isolating each tenant from physical complexity. Here, each tenant can dynamically alter QoS on a flow and load balance between a sub-set of contents via OpenFlow protocol. In switch configuration; a novel OFaaS Management Algorithm for a multi-tenant slicing increases the number of tenants served per OpenFlow switch thanks to OFaaS design. It enables an end-to-end configuration via the NETCONF protocol with a novel YANG model of OFaaS. According to performance evaluation; OFaaS has the same forwarding throughput as conventional IaaS based OpenFlow switch for a homogenous content, whereas it has 71% more forwarding throughput (Mbps) and it has 40% more cost-efficient than conventional one for a heterogeneous content with $17 savings per tenant. [ABSTRACT FROM AUTHOR]

Caching popular content at storage enabled routers or small-cell base stations (SBSs) is a key technology for future communication systems. Primarily limited to wired backbone systems, content-caching techniques are useful to offload mobile data traffic too. Several protocols have been developed towards realization of content-caching, namely, information-centric networking (ICN), content-centric networking, and named data networking. Studies have revealed that incorporating ICN caching schemes at SBSs could significantly enhance the user level performance, i.e., the lesser download delay and the higher throughput. However, smaller coverage area of a SBS would make the communication prone to high handover probability. Therefore, the implementation of ICN caching schemes at SBS requires extremely low processing delay, i.e., delay to search if the requested content is available at the cache, and accordingly make decision to serve the content request or forward it to the content server. In this article, a configurable hardware add-on has been developed to incorporate content caching features in a traditional SBS that can serve the user with extremely low processing delay while optimizing a combination of various network and hardware metrics. Using extensive results being generated from simulations, the usefulness of content caching has been demonstrated, and the effect of several hardware parameters over the latency performance has been studied too. In addition, the caching hardware accelerator has the ability to adapt dynamically to the optimal caching policy required by the prevailing network conditions as well as hardware requirements. An improvement upto 53% in network delay and 15% in handover probability due to the support of hardware-based caching is observed that incurs a negligible 0.07 mm 2 and up to only 11.1 mW energy overhead while operating in the range of 690–910 MHz. [ABSTRACT FROM AUTHOR]

This paper proposes a Fuzzy-logic Threat Classification (FTC) model as the basis of a method to auto-detect three different confidentiality levels for videos streamed from heterogeneous, mobile devices via web edge servers, possibly part of a Content Distribution Network (CDN). The FTC consists of three parallel Fuzzy Inference Systems (FIS) corresponding to device, network, and type of video application, for the real-time, intelligent selection of an appropriate confidentiality level for a specific end-user. After selection of the level, an encryption module implements the corresponding form of encryption. In tests to demonstrate the concept, there were three increasing confidentiality levels, namely (1) low-level with no encryption, (2) Medium level with an in-house cipher [variant of eXclusive OR (XOR)], named P-XOR (XOR with additional rounds of permutation) applied to Selective Encryption (SE) and (3) high level with the Advanced Encryption Standard again for SE of compressed video syntax components. Results were obtained by considering realistic specifications of multiple digital devices, networks, and differing real-time streaming applications. Visual analysis of encrypted test video clips established that the FTC outputs an appropriate privacy level by reason of the implemented FISs. Absolute encryption times across the privacy levels were distinguished by their real-time response level, which is proportionate to the required degree of confidentiality. [ABSTRACT FROM AUTHOR]

The problem of resource provisioning and content placement in cloud-based content delivery networks is studied, and a two-stage resource provisioning and cloud assignment is proposed based on dynamic large and small-scale fluctuations of user demand rates as well as considering a constrained minimum lease time for resources. In the first stage, we perform resource provisioning while costs of resources, quality of service (QoS) violation, and cloud-based root server redirection are included in the optimization, and constraints of QoS and limited resource of cloud sites are taken into account. In the second stage, cloud site assignment is conducted where for fixed allocated resources, QoS violation and cloud-based root server redirection costs are minimized or reduced using three different proposed schemes. We further show that reassignment of cloud sites during rising demand rates within a lease time period improves revenue, while reassignment is not very effective for falling demand rates.

Cyclic dinucleotides (CDNs) have emerged as ubiquitous signaling molecules in all domains of life. In eukaryotes, CDN signaling systems are evolutionarily ancient and have developed to sense and respond to pathogen infection. On the other hand, dysregulation of these pathways has been implicated in the pathogenesis of autoimmune diseases. Thus, CDNs have garnered major interest over recent years for their ability to elicit potent immune responses in the eukaryotic host. Similarly, ancestral CDN-based signaling systems also appear to confer immunological protection against infection in prokaryotes. Therefore, a better understanding of the host processes regulated by CDNs will be of tremendous value in many areas of research. Here, we aim to review the latest discoveries and recent trends in CDN research with a particular focus on the molecular mechanisms by which these small molecules mediate innate immunity. [ABSTRACT FROM AUTHOR]

Using citric acid (CA) and ethylenediamine (EDA) as precursors, stable nitrogen-doped carbon dots (CD) nanosols were prepared by microwave procedure and characterized in detail. It was found that CDNs catalyze ethanol (Et)-HAuCl4 to generate gold nanoparticles (AuNPs), which have strong surface plasmon resonance, Rayleigh scattering, (RRS) and a surface plasmon resonance (SPR) absorption (Abs) effect at 370 nm and 575 nm, respectively. Compled the new catalytic amplification indicator reaction with the specific As3+ aptamer reaction, a new RRS/Abs dual-mode aptamer sensor for the assay of trace As3+ was developed, based on the RRS/Abs signals increasing linearly with As3+ increasing in the ranges of 5–250 nmol/L and 50−250 nmol/L, whose detection limits were 0.8 nmol/L and 3.4 nmol/L As3+, respectively. This analytical method has the advantages of high selectivity, simplicity, and rapidity, and it has been successfully applied to the detection of practical samples.

Cyclic di-nucleotides (CDN) are potent stimulators of innate and adaptive immune responses. Cyclic di-AMP (CDA) is a promising adjuvant that generates humoral and cellular immunity. The strong STING-dependent stimulation of type I IFN represents a key feature of CDA. However, recent studies suggested that this is dispensable for adjuvanticity. Here we demonstrate that stimulation of IFN-γ-secreting CD8+ cytotoxic T lymphocytes (CTL) is significantly decreased after vaccination in the absence of type I IFN signaling. The biological significance of this CTL response was confirmed by the stimulation of MHC class I-restricted protection against influenza virus challenge. We show here that type I IFN (and not TNF-α) is essential for CDA-mediated cross-presentation by a cathepsin independent, TAP and proteosome dependent cytosolic antigen processing pathway, which promotes effective cross-priming and further CTL induction. Our data clearly demonstrate that type I IFN signaling is critical for CDN-mediated cross-presentation.

In a state of law, a citizen must live under the protection of their fundamental rights. Therefore, when authorities makes an intervention in a family nucleus and separates children from their parents for alleged protection purposes, it should be noted that if the decision was misguided, during the time that the separation remains, fundamental rights of the whole family are being infringed, especially for children, as stated in Article 9 of the CRC. With these premises, this article reveals that the reasons of risk and abandonment of a child should be typified in order to ensure the full success of the decisions of family separation. In addition, following a declaration of abandonment of a child, a lawsuit should be arise, whose procedural aspects would ensure fully adequate protection of the fundamental rights of the child in question, regardless of their parents' litigator ability.

Stimulator of interferon genes (STING) binds cyclic dinucleotides (CDNs), which induce a large conformational change of the protein. The structural basis of activation of STING by CDNs is rather well understood. Unliganded STING forms an open dimer that undergoes a large conformational change (∼10 Å) to a closed conformation upon the binding of a CDN molecule. This event activates downstream effectors of STING and subsequently leads to activation of the type 1 interferon response. However, a previously solved structure of STING with 3′,3′‐c‐di‐GMP shows Mg atoms mediating the interaction of STING with this CDN. Here, it is shown that no Mg atoms are needed for this interaction; in fact, magnesium can in some cases obstruct the binding of a CDN to STING. [ABSTRACT FROM AUTHOR]

It is a significant trend that the Internet Content Providers (ICPs) improve the quality of service and reduce the cost of content distribution by the Content Delivery Networks (CDNs). In order to spend the less money to get better services, ICPs need to find a lot of information about CDNs, such as server deployment, performance, price and so on, to determine whether CDN services satisfy their requirements. Unfortunately, these information can't be obtained by third party due to business secret. ICPs still choose CDNs on the basis of one-sided viewpoint. For this reason, we have proposed a data-driven and the deep learning based CDN recommendation framework for ICPs. The contributions lie in: 1) A three-tier CDN recommendation framework is presented to achieve data-driven and the deep learning based recommendation service. 2) A CDN recommendation model is built based on the deep neural network, which improves the efficiency of the recommendation service and satisfies the personalized demand. 3) A prototype system is developed and deployed on the real-world large-scale Internet in China. Experimental results demonstrate that the correctness of the recommendation results is up to 91%, and degree of satisfaction reached 80%. [ABSTRACT FROM AUTHOR]

In this paper, we propose a digital programmable OTA-based multi-standard receiver for analog baseband chain. It consists of a switchable-order low-pass filter and two programmable gain amplifiers (PGAs). The low-pass filter has a cutoff frequency that can be digitally tuned from 1 MHz to 10.2 MHz. Thus, it covers Bluetooth, UMTS, DVB-H and IEEE 802.11a/g standards. The gain of each PGA can be varied from 0 dB to 35 dB with a gain step of 5 dB. The proposed multi-standard receiver is designed and simulated in 90 nm CMOS technology under ± 0.6 V supply voltage. The overall simulation results show a variable gain from 0 dB to 70 dB, switchable-order (2nd/4th/6th) frequency response, in-band IIP3 of 21.9 dBm, and input referred noise of 102.6 nV/ Hz at 1 MHz with total power consumption of 11.77 mW. [ABSTRACT FROM AUTHOR]

In recent years, deep learning methods, especially deep convolutional neural network, have been successfully applied to the single‐image super‐resolution (SISR) task. In this Letter, the authors propose an accurate SISR method by introducing cascading dense connections in a very deep network. In detail, they construct the cascading dense network (CDN) to fully make use of the hierarchical features from all the convolutional layers, which implements a cascading mechanism upon the dense connected convolutional layers. The cascading dense connection in the CDN enables short and long paths to be built directly from the output to each layer, alleviating the vanishing‐gradient problem of very deep networks. Extensive experiments show that CDN achieves state‐of‐the‐art performance on traditional metrics (PSNR and SSIM). Also, they introduce object recognition as the additional evaluation metric for SISR, which further demonstrates the effectiveness of the authors' method. [ABSTRACT FROM AUTHOR]

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A content delivery network (CDN) is able to handle high traffic and offer reliable services by geographically bringing the content data to the edge network, where replica servers are installed closer to the end users. The traditional CDN architecture lacks a global view of the whole network and, thus, cannot dynamically and optimally perform the server selection task. In this letter, we propose to integrate a software-defined network (SDN) into the CDN architecture. Our intuitive motivation is to decouple the control plane from the forwarding plane in order to offer flexibility and programmability by using the centralized controller. This letter also develops a novel server selection algorithm that is based on the so-called multi-armed bandit problem. Such an algorithm is proved to optimize the server selection function and provide a good experimental result in terms of both average response time and reward score. [ABSTRACT FROM AUTHOR]

In content delivery networks (CDNs), caches are resources that must be allocated. For that purpose, videos' popularity knowledge helps to make efficient decisions about which videos should be cached. Thus, we must be able to anticipate future needs in terms of requested videos. To do this, we rely on the requests history. This paper focuses on predicting the videos' popularity: the daily number of requests. For that purpose, we propose a two-level prediction approach. At the first level, the experts compute the videos' popularity, each expert using its own prediction method with its own parameters. At the second level, the forecasters select the best experts and build a prediction based on the predictions provided by these experts. The prediction accuracy is evaluated by a loss function as the discrepancy between the prediction value and the real number of requests. We use real traces extracted from YouTube to compare different prediction methods and determine the best parameter tuning for experts and forecasters. The goal is to find the best trade-off between complexity and accuracy of the prediction methods used. Finally, we apply these prediction methods to caching. Prediction methods are compared in terms of cache hit ratio and update ratio. The gain brought by this two-level prediction approach is compared with that obtained by a single prediction level. The results show that the choice of a two-level prediction approach is justified. [ABSTRACT FROM AUTHOR]

Researchers and entertainment companies have given lots of attention to virtual reality over the past decade. 3D multi-view is a technology that provides interactions that are similar to those in the real world. However, 3D video streaming has a high data transfer rate because we must transmit multimedia data at a rate several times higher than that used for regular streaming. Besides, network throughput is unstable due to the inherent limitations of network infrastructure, which degrades video streaming quality. Additionally, network failure can occur frequently, causing stalling in multimedia playback. Hence, a network system is required to have more than one backup route in order to successfully guarantee the reliability of a network at all times. Furthermore, in the field of multi-view transmission, not much research has been published that has been conducted in a network virtualization environment. Therefore, we present a study on adaptive-based, high-efficiency video coding with three-dimensional, multi-view streaming over a peer-to-peer network. First, we study adaptive bitrate streaming methods based on high-efficiency video coding. Then we research transmitting multi-view data over a multi-path system. In the experiment, we first record a video from different views using five cameras. Next we merge recorded videos from the five cameras into a file and encode it before transmitting it over the peer-to-peer network. Moreover, we build a virtualized system using Docker virtualization technology and network function virtualization. The results of the experiment show that transmitting high-volume data over a multi-path network channel increases the streaming buffer level, which is about 20% higher than an adaptive streaming 3D method. It also makes the video quality 4% higher than in an HEVC-based adaptive streaming method. [ABSTRACT FROM AUTHOR]

The prohibitive cost of deploying a sophisticated DNS-based CDN makes anycast-based CDN an attractive alternative for new or small CDN operators. In anycast-based CDNs, user requests are naturally routed to the “closest” server determined by Internet routing. For the operators, however, this comes at a cost—loss of control—how the traffic is routed is entirely at the mercy of BGP routing. The “closest” server may be overloaded, or simply not the best choice. This “loss of control” undermines the scalability of anycast-based CDN architectures. To have control over how traffic is routed, existing work either requires adding a large amount of complexity to the system (high Capex/Opex) or is unable to achieve precise and fine-grained control. This paper proposes T-SAC, a scalable anycast-based CDN architecture that capitalizes on the programmability and flexibility of SDN/NFV, enabling fine-grained traffic redirection among CDN servers. T-SAC achieves precise control by leveraging a load-based redirection algorithm and a single 1-bit no-redirect flag. We implement T-SAC in the real system and evaluate its performance from various aspects using DASH and web applications. The results show that T-SAC is capable of redirecting the right amount of traffic at the right time to the right servers, making the system highly scalable. [ABSTRACT FROM AUTHOR]

The delivery of multimedia contents through a Content Delivery Network (CDN) is typically handled by a specific third party, separated from the content provider. However, in some specific cases, the content provider may be interested in carrying out this function using a Private CDN, possibly using an off-sourced network infrastructure. This scenario poses new challenges and limitations with respect to the typical case of content delivery. First, the systems has to face a different workload as the content consumer are typically part of the same organization that is the content provider. Second, the offsourced nature of the network infrastructure has a major impact on the available choices for CDN design. In this paper we develop an exact mathematical model for the design of a Private CDN addressing the issues and the constraints typical of such scenario. Furthermore, we analyze different heuristics to solve the optimization problem. We apply the proposed model to a real case study and validate the results by means of simulation. [ABSTRACT FROM AUTHOR]

Summary: A high throughput does not necessarily translate to a good Quality of Experience, especially in a satellite context. The round trip time, for instance, also has a tremendous impact on the reactivity of applications and thus on the Quality of Experience. Content delivery networks are massively used for over‐the‐top services in terrestrial network: They reduce the load of network and the delay as they draw the content closer to the end user. In a satellite system, the content delivery network presents a good opportunity for enhancing the end users' Quality of Experience and can change the conventional use of performance‐enhancing proxies. This paper investigates the satellite as access link for home networks or a backhaul link for small cells for a 5G perspective. We analysed the impact of caching on both gateway side and satellite terminal side for 2 on‐trend services: web browsing and adaptive video streaming (dynamic adaptive streaming over HTTP). The main contribution is an evaluation of transparent caching through a satellite platform. The caching policy is out of the scope of this paper. One large part of the testbed is based on an open‐source platform, OpenSAND that emulates the satellite system. To confirm the results, some real experiments have been conducted on a commercial satellite link. As expected, the transparent caching at the satellite terminal side can increase the Quality of Experience to its upper border as long as the content is available in the cache. For the satellite gateway cache, the performances exceed the expectations. Although the application experiences the satellite delay in this case, the traversal time of different Internet service provider networks also delays the delivery of content. Then it may have a greater impact on reactivity than the satellite itself. Through careful analysis of the different results, we noticed some issues. Transparent caching is unable to cache encrypted or dynamic content. Moreover, a misuse of caching can provoke bad behaviour of dynamic adaptive streaming over HTTP mechanisms and severely decrease the Quality of Experience. We designed a solution that in addition to solving the issue, alleviates the storage space of satellite terminal caches. In this paper, we propose to use Content Delivery Network in a satellite network in order to enhance the Quality of Experience of end‐user. The major contribution of this study is to evaluate the impact of the placement of the caches for multiples applications (Web browsing and Adaptive video streaming). The experiences were made on an emulation tool and on a real satellite network. [ABSTRACT FROM AUTHOR]

This paper proposes a novel highly linear digitally programmable fully differential operational transconductance amplifier (DPOTA) circuit. Two versions of the proposed DPOTA structure are designed. The first version is optimized for high-frequency operation with current division networks designated to 3-bit control code words. On the other hand, the second version is optimized for low-frequency operation with 4-bit control code words. The third-order harmonic distortion (HD3) of the first DPOTA version remains below − 66 dB up to 0.4 V differential input voltage at 10 MHz frequency. The second DPOTA version achieved HD3 of − 70 dB with an amplitude of 20 mVp-p and at 100 Hz frequency. The proposed circuits are designed and simulated in 90 nm CMOS model, BSIM4 (level 54) under a balanced 1.2 V supply voltage. [ABSTRACT FROM AUTHOR]

This paper introduces OCLDN, an agile, programmable, and scalable optical cloud distribution network, which exploits content distribution networks to deliver killer cloud and tactile services to end users at very high speeds, ultra-low latency, and low cost. With OCLDN, a software-defined-networking-based mini-cloud data center is installed at the central office of a next-generation passive optical network, which includes a cloud-based tactile steering server, and supports all types of cloud applications. These applications have stringent quality-of-service (QoS) requirements and, thus, require a fast, adaptive, and effective bandwidth allocation mechanism. Therefore, in this paper, we introduce a new dynamic wavelength and bandwidth allocation (DWBA) scheme that meets the QoS requirements of tactile services via dedicating it upstream wavelength(s), and also enables inter-channel statistical multiplexing so as to maximize the network throughput without impairing the QoS requirements for all types of services. Extensive simulations demonstrate the ability of the proposed DWBA to outperform existing schemes, and highlight its effectiveness in meeting the QoS demands for tactile and non-tactile services. [ABSTRACT FROM AUTHOR]

This paper describes an approach that improves the functionality of LH*RS -high-availability scalable distributed data structure. The core concept behind this approach is the particular implementation of LB* schema that allows efficient imagery data storage for content delivery networks (CDN) to be created. We propose the novel wavelet-based method of buckets composition and distribution among storage nodes to improve the basic characteristics of schema. This method is less redundant than image pyramid structure (MIP maps). Also we propose some ideas for multilevel encoding algorithms and multilevel privacy protection in this storage schema.

Con estas notas, recordamos a Judith Ennew, quien falleció prematuramente y de manera imprevista en octubre de 2013. Judith fue una persona maravillosa, que combinó de manera impresionante el compromiso práctico con los niños y sus derechos con un ethos convincente como investigadora de las vidas de los niños. Como activista e investigadora, trabajó y visitó varias partes del mundo, primero en Jamaica, luego en América Latina, en África y en el sudeste de Asia, así como en varios países europeos. Ella centró su interés particularmente en los niños que sufren desigualdad social, pobreza, violencia, explotación y discriminación.

In order to apply the cyber-physical system (CPS) co-simulation method based on state cache to a complex distribution network (CDN), a physical model corresponding to multiple operating states should be proposed. As the different spatial resolution of the physical model leads to different performances of the cyber-physical models, a multi-resolution model based on time-state-machine is presented for CDN here. First, the operation process of CDN is divided into five operating states by using time-state-machine method, and the boundary conditions between states are qualitatively discussed. Second, three different spatial resolution physical models of CDN are built, and their simulation performances under different operating states are quantitatively analysed to form a multi-resolution physical model of CDN. Finally, the multi-resolution model of CDN is validated by use of a cyber-physical co-simulation example. Simulation results show that the multi-resolution model is capable to automatically transmission from anyone operating state to another.

With the development of 4G networks,telecom operators are urgent to find the service that can use the high speed broadband.Video streaming service became the first choice.But providing video streaming service on the 4G network,operators faced many technical problems like network architecture changing,1arge flow concurrency,multicast solution,content distribution,UE's ability and so on.And the key resource requirement and technology suggestion of providing video streaming service on 4G networks were studied and proposed,based on the analysis of current network status.At the same time,the feasibility analysis of the service deployment was also given,and then some references were provided to operators.