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Paper Accepted @ Journal of Ambient Intelligence and Humanized Computing

Title: MCred: Multi-Modal Message Credibility for Fake News Detection using BERT and CNN

Journal: Journal of Ambient Intelligence and Humanized Computing

Authors: Pawan Kumar Verma, Prateek Agrawal, Vishu Madaan, Radu Prodan

Abstract:

Online social media enables low cost, easy access, rapid propagation, and easy communication of information, including spreading low-quality fake news. Fake news has become a huge threat to every sector in society, and resulting in decrements in the trust quotient for media and leading the audience into bewilderment. In this paper, we proposed a new framework called Message Credibility (MCred) for fake news detection that utilizes the benefits of local and global text semantics. This framework is the fusion of Bidirectional Encoder Representations from Transformers (BERT) using the relationship between words in sentences for global text semantics and Convolutional Neural Networks (CNN) using N-gram features for local text semantics. We demonstrate through experimental results a popular Kaggle dataset that MCred improves the accuracy over a state-of-the-art model by 1.10%, thanks to its combination of local and global text semantics.

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A Webbing Journey @ Level Up 2022

On Friday and Saturday (July 1 and July 2, 2022), Sebastian Uitz presented his game “A Webbing Journey” with his partner Manuel Santner at the Level Up event in the Messezentrum Salzburg. This was the biggest event they presented their game at, with a 300m² area for indie games and over 20.000m² in total. Over 6.500 people visited the event, and 2 PCs were provided for their game. In the end, 6 PCs were running “A Webbing Journey” due to some game developers not making it or leaving the event early. All the PCs were in constant use, and all players had so much fun playing the game, especially kids. This event and the last two provided so much feedback in the form of player tests, which have helped progress the game. The next goal is to implement all the feedback and releasing the new demo version on Steam.

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Paper accepted at IEEE Cluster 2022 Matching-based Scheduling of Asynchronous Data Processing Workflows on the Computing Continuum

Title: Matching-based Scheduling of Asynchronous Data Processing Workflows on the Computing Continuum

Heidelberg, Germany | September 6-9, 2022

https://clustercomp.org/2022/

Authors: Narges Mehran, Zahra Najafabadi Samani, Dragi Kimovski, Radu Prodan

Abstract: Today’s distributed computing infrastructures encompass complex workflows for real-time data gathering, transferring, storage, and processing, quickly overwhelming centralized cloud centers. Recently, the computing continuum that federates the Cloud services with emerging Fog and Edge devices represents a relevant alternative for supporting the next-generation data processing workflows. However, eminent challenges in automating data processing across the computing continuum still exist, such as scheduling heterogeneous devices across the Cloud, Fog, and Edge layers. We propose a new scheduling algorithm called C3-MATCH, based on matching theory principles, involving two sets of players negotiating different utility functions: 1) workflow microservices that prefer computing devices with lower data processing and queuing times; 2) computing continuum devices that prefer microservices with corresponding resource requirements and less data transmission time. We evaluate C3-MATCH using real-world road sign inspection and sentiment analysis workflows on a federated computing continuum across four Cloud, Fog, and Edge providers. Our combined simulation and real execution results reveal that C3-MATCH achieves up to 67% lower completion time compared to three state-of-the-art methods.

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Paper accepted: Low Latency Live Streaming Implementation in DASH and HLS

Low Latency Live Streaming Implementation in DASH and HLS

ACM Multimedia Conference – OSS Track

Lisbon, Portugal | 10-14 October 2022

Abdelhak Bentaleb (National University of Singapore), Zhengdao Zhan (National University of Singapore), Farzad Tashtarian (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), May Lim (National University of Singapore), Saad Harous (University of Sharjah), Christian Timmerer (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Hermann Hellwagner (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), and Roger Zimmermann (National University of Singapore)

Low latency live streaming over HTTP using Dynamic Adaptive Streaming over HTTP (LL-DASH) and HTTP Live Streaming} (LL-HLS) has emerged as a new way to deliver live content with respectable video quality and short end-to-end latency. Satisfying these requirements while maintaining viewer experience in practice is challenging, and adopting conventional adaptive bitrate (ABR) schemes directly to do so will not work. Therefore, recent solutions including LoL$^+$, L2A, Stallion, and Llama re-think conventional ABR schemes to support low-latency scenarios. These solutions have been integrated with dash.js  that support LL-DASH. However, their performance in LL-HLS remains in question. To bridge this gap, we implement and integrate existing LL-DASH ABR schemes in the hls.js video player which supports LL-HLS.
Moreover, a series of real-world trace-driven experiments have been conducted to check their efficiency under various network conditions including a comparison with results achieved for LL-DASH in dash.js.

Hermann Hellwagner in a BITMOVIN Webinar featuring ATHENA

Video streaming is not for online video providers alone. Telco providers are equal players in the game of adaptive video streaming, but to stand out, there is a constant demand for innovations at the edge.

Join us for an interview session between Bitmovin Solution Architect, Adrian Britton, and Alpen Adria University Professor, Dr. Hermann Hellwagner, as they discuss some of the latest research around Edge Computing solutions that will improve functionality for mobile network and CDN providers.

Find here the “Latest Edge Computing Innovations for Video Streaming (ft. ATHENA)”  Webinar Recording    of 14th June 2022.

 

A Webbing Journey @ Button Festival 2022

On Friday and Saturday (June 24 and June 25, 2022), Sebastian Uitz presented his game “A Webbing Journey” together with his partner Michael Steinkellner at the Button Festival in the Stadthalle Graz. This time 3 PCs have been prepared so more people could play the game. The feedback from last week’s event was implemented, and the results were fantastic. Everybody loved the game, especially the kids. Some of them came back several times to play the game over and over.

 

Paper accepted: LiDeR: Lightweight Dense Residual Network for Video Super-Resolution on Mobile Devices

IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP 2022)

June 26-29, 2022 | Nafplio, Greece

Conference Website

[Video]

Ekrem Çetinkaya (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), Minh Nguyen (Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität Klagenfurt), and Christian Timmerer (Christian Doppler LaboratoryATHENA, Alpen-Adria-Universität Klagenfurt)

 

Abstract: Video is now an essential part of the Internet. The increasing popularity of video streaming on mobile devices and the improvement in mobile displays brought together challenges to meet user expectations. Advancements in deep neural networks have seen successful applications on several computer vision tasks such as super-resolution (SR). Although DNN-based SR methods significantly improve over traditional methods, their computational complexity makes them challenging to apply on devices with limited power, such as smartphones. However, with the improvement in mobile hardware, especially GPUs, it is now possible to use DNN based solutions, though existing DNN based SR solutions are still too complex. This paper proposes LiDeR, a lightweight video SR network specifically tailored toward mobile devices. Experimental results show that LiDeR can achieve competitive SR performance with state-of-the-art networks while improving the execution speed significantly, i.e., 267 % for X4 upscaling and 353 % for X2 upscaling compared to ESPCN.

Keywords: Super-resolution, Mobile machine learning, Video super-resolution.

 

Paper Accepted @ The Journal of Supercomputing

Title: An Elastic and Traffic-Aware Scheduler for Distributed Data Stream Processing in Heterogeneous Clusters

Authors: Hamid Hadian, Mohammadreza Farrokh, Mohsen Sharifi, and Ali Jafari

Abstract:

Existing Data Stream Processing (DSP) systems perform poorly while encountering heavy workloads, particularly on clustered set of (heterogeneous) computers. Elasticity and changing application parallelism degree can limit the performance degradation in the face of varying workloads that negatively impact the overall application response time. Elasticity can be achieved by operator scaling, i.e., by replication and relocation of operators at runtime. However, scaling decisions at runtime is challenging, since it first increases the overall communication overhead between operators and secondly changes any initial scheduling that could lead to a non-optimal scheduling plan. In this paper, we investigate the problem of elasticity and scaling decisions and propose a DSP system called ER-Storm. To curb communication overhead, we propose a new 3-step mechanism for replication and relocation of operators upon detecting a bottleneck operator that overutilizes a worker node. The other challenge is to select the proper worker nodes to host relocated operators. By discretizing the input workload, we model the relocation of operators between worker nodes at runtime through a scalable Markov Decision Process (MDP) and use a model-free notion of reinforcement learning (Q-Learning) to find optimal solutions. We have implemented our propositions on the Apache Storm version 2.1.0. Our experimental results show that ER-Storm reduces the average topology response time by 20 to 60 percent based on the rate of input workload (low or high) compared to the R-Storm scheduler and the Online-Scheduler of Storm.

Paper accepted: Detection and Localization of Video Transcoding From AVC to HEVC Based on Deep Representations of Decoded Frames and PU Maps

Detection and Localization of Video Transcoding From AVC to HEVC Based on Deep Representations of Decoded Frames and PU Maps

IEEE Transactions on Multimedia

Haichao Yao (Beijing Jiaotong University), Rongrong Ni (Beijing Jiaotong University), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Christian Timmerer (Alpen-Adria-Universität Klagenfurt), Yao Zhao (Beijing Jiaotong University).

Hadi
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Hadi Amirpour to give a talk at Fraunhofer FOKUS MWS

Video Encoding Optimizations for Live Video Streaming

FOKUS Media Web Symposium

20th – 24th June 2022 | Berlin, Germany

 

Abstract: Live video streaming is expected to become mainstream in the fifth-generation (5G) mobile networks. Optimizing video encoding for live video streaming is challenging due to the latency introduced by any optimization method. In this talk, we introduce low-latency video optimization methods that are utilized to improve the quality of video encodings by predicting optimized encoding parameters.

Hadi Amirpour is a postdoc research fellow at ATHENA  directed by Prof. Christian Timmerer. He received his B.Sc. degrees in Electrical and Biomedical Engineering, and he pursued his M.Sc. in Electrical Engineering. He got his Ph.D. in computer science from the University of Klagenfurt in 2022. He was appointed co-chair of Task Force 7 (TF7) Immersive Media Experience (IMEx) at the 15th Qualinet meeting. He was involved in the project EmergIMG, a Portuguese consortium on emerging imaging technologies, funded by the Portuguese funding agency and H2020. Currently, he is working on the ATHENA project in cooperation with its industry partner Bitmovin. His research interests are image processing and compression, video processing and compression, quality of experience, emerging 3D imaging technology, and medical image analysis.