A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone

Rapid advancement of technology and their increasing affordability have transformed mobile devices from a means of communication to tools for socialization, entertainment, work and learning. However, advancement of battery technology and capacity is slow compared to energy need. Viewing content with high quality of experience will consume high power. In limited available energy, normal content adaptation system will decrease the content quality, hence reducing quality of experience. However, there is a need for optimizing content quality of experience (QoE) in a limited available energy. With modification and improvement, content adaptation may solve this issue. The key objective of this research is to propose a framework for energy-aware video content adaptation system to enable video delivery over the Internet. To optimise the QoE while viewing streaming video on a limited available smartphone energy, an algorithm for energy-aware video content adaptation decision-taking engine named EnVADE is proposed. The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. Thus, QoE can be improved. To evaluate EnVADE algorithm in term of energy efficiency, an experimental evaluation has been done. Subjective evaluation by selected respondents are also has been made using Absolute Category Rating method as recommended by ITU to evaluate EnVADE algorithm in term of QoE. In both evaluation, comparison with other methods has been made. The results show that the proposed solution is able to increase the viewing time of about 14% compared to MPEG-DASH which is an official international standard and widely used streaming method. In term of QoE subjective test, EnVADE algorithm score surpasses the score of other video streaming method. Therefore, EnVADE framework and algorithm has proven its capability as an alternative technique to stream video content with higher QoE and lower energy consumption

XML-driven exploitation of combined scalability in scalable H.264/AVC bitstreams

The heterogeneity in the contemporary multimedia environments requires a format-agnostic adaptation framework for the consumption of digital video content. Scalable bitstreams can be used in order to satisfy as many circumstances as possible. In this paper, the scalable extension on the H.264/AVC specification is used to obtain the parent bitstreams. The adaptation along the combined scalability axis of the bitstreams is done in a format-independent manner. Therefore, an abstraction layer of the bitstream is needed. In this paper, XML descriptions are used representing the high-level structure of the bitstreams by relying on the MPEG-21 Bitstream Syntax Description Language standard. The exploitation of the combined scalability is executed in the XML domain by implementing the adaptation process in a Streaming Transformation for XML (STX) stylesheet. The algorithm used in the transformation of the XML description is discussed in detail in this paper. From the performance measurements, one can conclude that the STX transformation in the XML domain and the generation of the corresponding adapted bitstream can be realized in real time

Investigation of dielectric constant variations for Malaysians soil species towards its natural background dose

The correlation of natural background gamma radiation and real part of the complex relative permittivity (dielectric constant) for various species Malaysian soils was investigated in this research. The sampling sites were chosen randomly according to soils groups that consist of sedentary, alluvial and miscellaneous soil which covered the area of Batu Pahat, Kluang and Johor Bahru, Johor state of Malaysia. There are 11 types of Malaysian soil species that have been studied; namely Peat, Linau-Sedu, Selangor-Kangkong, Kranji, Telemong�Akob-Local Alluvium, Holyrood-Lunas, Batu Anam-Melaka- Tavy, Harimau Tampoi, Kulai�Yong Peng, Rengam-Jerangau, and Steepland soils. In-situ exposure rates of each soil species were measured by using portable gamma survey meter and ex-situ analysis of real part of relative permittivity was performed by using DAK (Dielectric Assessment Kit assist by network analyser). Results revealed that the highest and the lowest background dose rate were 94 ±26.28 μR hr-1 and 7 ±0.67 μR hr-1 contributed by Rengam Jerangau and Peat soil species respectively. Meanwhile, dielectric constant measurement, it was performed in the range of frequency between 100 MHz to 3 GHz. The measurements of each soils species dielectric constant are in the range of 1 to 3. At the lower frequencies in the range of 100 MHz to 600 MHz, it was observed that the dielectric constant for each soil species fluctuated and inconsistent. But it remained consistent in plateau form of signal at higher frequency at range above 600 MHz. From the comparison of dielectric properties of each soil at above 600 MHz of frequency, it was found that Rengam-Jerangau soil species give the highest reading and followed by Selangor-Kangkong species. The average dielectric measurement for both Selangor-Kangkong and Rengam-Jerangau soil species are 2.34 and 2.35 respectively. Meanwhile, peat soil species exhibits the lowest dielectric measurement of 1.83. It can be clearly seen that the pattern of dielectric measurement for every soil at the frequency above 600 MHz demonstrated a specific distribution which can be classified into two main regions which are higher and lower between the ranges of 1.83 to 2.35. Pearson correlation analysis between the frequency of 100 MHz and 2.6 GHz with respect to exposure rate for every soil species was r = 0.38 and r = 0.51, respectively. This indicates that there was no strong correlation between both parameter, natural background dose and soils dielectric for each soils sample. This factor could be contributed by major and minor elements contained in each soils sample species, especially Ferum, Fe and Silica, Si

Dynamic and distributed adaptation of scalable multimedia content in a context-aware environment

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Effect of oil palm empty fruit bunches (OPEFB) fibers to the compressive strength and water absorption of concrete

Growing popularity based on environmentally-friendly, low cost and lightweight building materials in the construction industry has led to a need to examine how these characteristics can be achieved and at the same time giving the benefit to the environment and maintain the material requirements based on the standards required. Recycling of waste generated from industrial and agricultural activities as measures of building materials is not only a viable solution to the problem of pollution but also to produce an economic design of building

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

Semantischer Schutz und Personalisierung von Videoinhalten. PIAF: MPEG-kompatibles Multimedia-Adaptierungs-Framework zur Bewahrung der vom Nutzer wahrgenommenen Qualität.

UME is the notion that a user should receive informative adapted content anytime and anywhere. Personalization of videos, which adapts their content according to user preferences, is a vital aspect of achieving the UME vision. User preferences can be translated into several types of constraints that must be considered by the adaptation process, including semantic constraints directly related to the content of the video. To deal with these semantic constraints, a fine-grained adaptation, which can go down to the level of video objects, is necessary. The overall goal of this adaptation process is to provide users with adapted content that maximizes their Quality of Experience (QoE). This QoE depends at the same time on the level of the user's satisfaction in perceiving the adapted content, the amount of knowledge assimilated by the user, and the adaptation execution time. In video adaptation frameworks, the Adaptation Decision Taking Engine (ADTE), which can be considered as the "brain" of the adaptation engine, is responsible for achieving this goal. The task of the ADTE is challenging as many adaptation operations can satisfy the same semantic constraint, and thus arising in several feasible adaptation plans. Indeed, for each entity undergoing the adaptation process, the ADTE must decide on the adequate adaptation operator that satisfies the user's preferences while maximizing his/her quality of experience. The first challenge to achieve in this is to objectively measure the quality of the adapted video, taking into consideration the multiple aspects of the QoE. The second challenge is to assess beforehand this quality in order to choose the most appropriate adaptation plan among all possible plans. The third challenge is to resolve conflicting or overlapping semantic constraints, in particular conflicts arising from constraints expressed by owner's intellectual property rights about the modification of the content. In this thesis, we tackled the aforementioned challenges by proposing a Utility Function (UF), which integrates semantic concerns with user's perceptual considerations. This UF models the relationships among adaptation operations, user preferences, and the quality of the video content. We integrated this UF into an ADTE. This ADTE performs a multi-level piecewise reasoning to choose the adaptation plan that maximizes the user-perceived quality. Furthermore, we included intellectual property rights in the adaptation process. Thereby, we modeled content owner constraints. We dealt with the problem of conflicting user and owner constraints by mapping it to a known optimization problem. Moreover, we developed the SVCAT, which produces structural and high-level semantic annotation according to an original object-based video content model. We modeled as well the user's preferences proposing extensions to MPEG-7 and MPEG-21. All the developed contributions were carried out as part of a coherent framework called PIAF. PIAF is a complete modular MPEG standard compliant framework that covers the whole process of semantic video adaptation. We validated this research with qualitative and quantitative evaluations, which assess the performance and the efficiency of the proposed adaptation decision-taking engine within PIAF. The experimental results show that the proposed UF has a high correlation with subjective video quality evaluation.Der Begriff "Universal Multimedia Experience" (UME) beschreibt die Vision, dass ein Nutzer nach seinen individuellen Vorlieben zugeschnittene Videoinhalte konsumieren kann. In dieser Dissertation werden im UME nun auch semantische Constraints berücksichtigt, welche direkt mit der Konsumierung der Videoinhalte verbunden sind. Dabei soll die Qualität der Videoerfahrung für den Nutzer maximiert werden. Diese Qualität ist in der Dissertation durch die Benutzerzufriedenheit bei der Wahrnehmung der Veränderung der Videos repräsentiert. Die Veränderung der Videos wird durch eine Videoadaptierung erzeugt, z.B. durch die Löschung oder Veränderung von Szenen, Objekten, welche einem semantischen Constraints nicht entsprechen. Kern der Videoadaptierung ist die "Adaptation Decision Taking Engine" (ADTE). Sie bestimmt die Operatoren, welche die semantischen Constraints auflösen, und berechnet dann mögliche Adaptierungspläne, die auf dem Video angewandt werden sollen. Weiterhin muss die ADTE für jeden Adaptierungsschritt anhand der Operatoren bestimmen, wie die Vorlieben des Nutzers berücksichtigt werden können. Die zweite Herausforderung ist die Beurteilung und Maximierung der Qualität eines adaptierten Videos. Die dritte Herausforderung ist die Berücksichtigung sich widersprechender semantischer Constraints. Dies betrifft insbesondere solche, die mit Urheberrechten in Verbindung stehen. In dieser Dissertation werden die oben genannten Herausforderungen mit Hilfe eines "Personalized video Adaptation Framework" (PIAF) gelöst, welche auf den "Moving Picture Expert Group" (MPEG)-Standard MPEG-7 und MPEG-21 basieren. PIAF ist ein Framework, welches den gesamten Prozess der Videoadaptierung umfasst. Es modelliert den Zusammenhang zwischen den Adaptierungsoperatoren, den Vorlieben der Nutzer und der Qualität der Videos. Weiterhin wird das Problem der optimalen Auswahl eines Adaptierungsplans für die maximale Qualität der Videos untersucht. Dafür wird eine Utility Funktion (UF) definiert und in der ADTE eingesetzt, welche die semantischen Constraints mit den vom Nutzer ausgedrückten Vorlieben vereint. Weiterhin ist das "Semantic Video Content Annotation Tool" (SVCAT) entwickelt worden, um strukturelle und semantische Annotationen durchzuführen. Ebenso sind die Vorlieben der Nutzer mit MPEG-7 und MPEG-21 Deskriptoren berücksichtigt worden. Die Entwicklung dieser Software-Werkzeuge und Algorithmen ist notwendig, um ein vollständiges und modulares Framework zu erhalten. Dadurch deckt PIAF den kompletten Bereich der semantischen Videoadaptierung ab. Das ADTE ist in qualitativen und quantitativen Evaluationen validiert worden. Die Ergebnisse der Evaluation zeigen unter anderem, dass die UF im Bereich Qualität eine hohe Korrelation mit der subjektiven Wahrnehmung von ausgewählten Nutzern aufweist

Video Streaming Energy Consumption Analysis for Content Adaption Decision-Taking

Over recent years, rapid growth of smartphone technology and capabilities makes it an important tool in our daily activities. Despite increasing processing power and capabilities as well as decreasing price, these consumer smartphones are still limited in term of batteries capacity. The heterogeneity properties of these devices, subscribed network as well as its users also lead to mismatch problem. Usage in power-hungry multimedia applications such as streaming video players and 3D games, the limited battery capacity motivates smartphone energy aware content adaptation research to address these problems. This paper present experiments of energy consumption of video streaming in various video encoding properties as well as different network scenarios. The result of the experiments shows that energy savings up to 40% can be achieved by using different encoding property

A Framework for Personalized Utility-Aware IP-Based Multimedia Consumption

Providing transparent and augmented use of multimedia con-tent across a wide range of networks and devices is still a challenging task within the multimedia research community. Multimedia adaptation was figured out as a core concept to overcome this issue. Most multimedia adaptation engines for providing Universal Multimedia Access (UMA) scale the content under consideration of terminal capabilities and re-source constraints but do not really consider individual user preferences. This paper introduces an adaptive multimedia framework which offers the user a personalized content vari-ation for satisfying his/her individual utility preferences. 1

Employing H.264 Coarse and Medium Grain Scalable Video to Optimize Video Playback over Passive Optical Networks

In this work, we propose the use of Coarse Grain Scalable (CGS) and Medium Grain Scalable (MGS) H.264/AVC video to optimize video playback on passive optical networks (PONs) by investigating network performance metrics such as data delay, video delay, and video delay jitter. Video playback is improved by sequentially dropping layers of scalable video. Dropping just a single CGS enhancement layer results in improvements of up to 57% for both data and video delay. However, video delay jitter benefits the most with an improvement ranging from 47% to 87%. Surprisingly, dropping subsequent CGS enhancement layers does not significantly improve the PONs performance. In order to remedy this effect, our focus switched to employing the H.264/AVC MGS video standard. Though video traffic delay is the primary object of optimization in this work, the proposed algorithm’s impacts on other network performance metrics such as data traffic delay and video traffic delay variance (jitter) are analyzed as well. Video playback is improved by employing an adaptive scalable video layer dropping algorithm which drops a progressively larger number of scalable video layers as network utilization increases as measured by the moving average of the video packet delay. The influence of the algorithm\u27s three parameters on its performance is investigated in detail, and the results of the optimized adaptive dropping algorithm are compared to baseline static dropping algorithm