ACM Workshop Research Articles

Introduction to the special issue of the 16th ACM workshop on Adaptive and Reflective Middleware (ARM)

Introduction to the special issue of the 16th ACM workshop on Adaptive and Reflective Middleware (ARM)

Introduction to the Best Papers of the ACM Multimedia Systems (MMSys) Conference 2018 and the ACM Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV) 2018 and the International Workshop on Mixed and Virtual Environment Systems (MMVE) 2018

Introduction to the Best Papers of the ACM Multimedia Systems (MMSys) Conference 2018 and the ACM Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV) 2018 and the International Workshop on Mixed and Virtual Environment Systems (MMVE) 2018

Smooth estimates of multiple quantiles in dynamically varying data streams

In this paper, we investigate the problem of estimating multiple quantiles when samples are received online (data stream). We assume a dynamical system, i.e., the distribution of the samples from the data stream changes with time. A major challenge of using incremental quantile estimators to track multiple quantiles is that we are not guaranteed that the monotone property of quantiles will be satisfied, i.e, an estimate of a lower quantile might erroneously overpass that of a higher quantile estimate. Surprisingly, we have only found two papers in the literature that attempt to counter these challenges, namely the works of Cao et al. (Proceedings of the first ACM workshop on mobile internet through cellular networks, ACM, 2009) and Hammer and Yazidi (Proceedings of the 30th international conference on industrial engineering and other applications of applied intelligent systems (IEA/AIE), France, Springer, 2017) where the latter is a preliminary version of the work in this paper. Furthermore, the state-of-the-art incremental quantile estimator called deterministic update-based multiplicative incremental quantile estimator (DUMIQE), due to Yazidi and Hammer (IEEE Trans Cybernet, 2017), fails to guarantee the monotone property when estimating multiple quantiles. A challenge with the solutions, in Cao et al. (2009) and Hammer and Yazidi (2017), is that even though the estimates satisfy the monotone property of quantiles, the estimates can be highly irregular relative to each other which usually is unrealistic from a practical point of view. In this paper, we suggest to generate the quantile estimates by inserting the quantile probabilities (e.g., $$0.1, 0.2, \ldots , 0.9$$) into a monotonically increasing and infinitely smooth function (can be differentiated infinitely many times). The function is incrementally updated from the data stream. The monotonicity and smoothness of the function ensure that both the monotone property and regularity requirement of the quantile estimates are satisfied. The experimental results show that the method performs very well and estimates multiple quantiles more precisely than the original DUMIQE (Yazidi and Hammer 2017), and the approaches reported in Hammer and Yazidi (2017) and Cao et al. (2009).

Best Papers of the ACM Multimedia Systems (MMSys) Conference 2017 and the ACM Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV) 2017

Best Papers of the ACM Multimedia Systems (MMSys) Conference 2017 and the ACM Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV) 2017

Editorial of the Special Issue on Quantified Self and Personal Informatics

In recent years, we witnessed the spreading of a plethora of wearable and mobile technologies allowing for a continuous and “transparent” gathering of personal data [...]

Best Papers of the 2016 ACM Multimedia Systems (MMSys) Conference and Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV) 2016

Best Papers of the 2016 ACM Multimedia Systems (MMSys) Conference and Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV) 2016

ICMR 2014

ICMR was initially started as a workshop on challenges in image retrieval (in Newcastle in 1998 ) and later transformed into the Conference on Image and Video Retrieval (CIVR) series. In 2011 the CIVR and the ACM Workshop on Multimedia Information Retrieval were combined into a single conference that now forms the ICMR series. The 4th ACM International Conference on Multimedia Retrieval took place in Glasgow, Scotland, from 1 – 4 April 2014. This was the largest edition of ICMR to date with approximately 170 attendees from 25 different countries. ICMR is one of the premier scientific conference for multimedia retrieval held worldwide, with the stated mission “to illuminate the state of the art in multimedia retrieval by bringing together researchers and practitioners in the field of multimedia retrieval .” According to the Chinese Computing Federation Conference Ranking (2013), ACM ICMR is the number one multimedia retrieval conference worldwide and the number four conference in the category of multimedia and graphics. Although ICMR is about multimedia retrieval, in a wider sense, it is also about automated multimedia understanding. Much of the work in that area involves the analysis of media on a pixel, voxel, and wavelet level, but it also involves innovative retrieval, visualisation and interaction paradigms utilising the nature of the multimedia — be it video, images, speech, or more abstract (sensor) data. The conference aims to promote intellectual exchanges and interactions among scientists, engineers, students, and multimedia researchers in academia as well as industry through various events, including a keynote talk, oral, special and poster sessions focused on re search challenges and solutions, technical and industrial demonstrations of prototypes, tutorials, research, and an industrial panel. In the remainder of this report we will summarise the events that took place at the 4th ACM ICMR conference.

Hoda Roodaki

With the growing demand for 3D video, efforts are underway to incorporate it in the next generation of broadcast and streaming applications and standards. Scalability is one possible solution to reduce the amount of data in multi-view/3D video in heterogeneous environments. But using Scalable Multi-view Video Coding (SMVC) for multi-view/3D video still has many unresolved challenges. In this thesis, we propose an adaptive framework to use SMVC in various 3D video applications effectively. For this issue, first, the proper scalable modality should be selected according to the application at hand, its related features and requirements. To the best of our knowledge, no work has systematically defined new and proper scalable modalities specifically for multi-view 3D video, so far. Hence, at the first step of the proposed framework, we will suggest a methodology to extract the proper scalable modalities for multi-view/3D video. In addition, while SMVC can help support heterogeneous receivers, the question becomes: how to scale the 3D video content in a given type of scalability and a specified application in order to achieve the highest performance and satisfy the receivers? constraint as much as possible? In other words, the proper mechanism to assign SMVC data to various layers should be clearly determined. This issue is considered as the second step of our proposed framework. This method uses the inter-layer and intralayer disparity concepts. Note that specific features of any given scalable modality should be used to define these concepts in that specific scalable modality. Simulation results indicate that the proposed method achieves relatively better compression rate for each layer, with much less overhead. At the next step of our proposed framework, we propose an analytical view-level rate model for multiview video coding. Our rate model takes into account both previous theoretical results as well as new results specifically obtained for multi-view video and confirmed by comprehensive practical experiments. Simulation results show that our model can predict the rate of each view with relatively high precision and a low estimation error of 12% on average for tested sequences. In addition, the evaluation of the overall visual quality of scalable multi-view video requires a new objective perceptual quality measure specifically designed for scalable multi-view/3D video. Although several subjective and objective quality assessment methods have been proposed for multi-view/3D sequences, no comparable attempt has been made for quality assessment of scalable multi-view/3D video so far. Hence, in this framework, we propose a new methodology to build suitable objective quality assessment metrics for different scalable modalities in multi-view/3D video. Our proposed methodology considers the importance of each layer and its content as a quality of experience factor in the overall quality. Furthermore, in addition to the quality of each layer, the concept of inter-layer and intra-layer disparity is considered as an effective feature to evaluate overall perceived quality more accurately. Our simulation results indicate that the correlation coefficient between our extracted objective quality evaluation metric and subjective quality assessment is 0.8 on average for tested video sequences. At the last step of our proposed framework, we present a novel method for rate-distortion optimization in scalable multi-view video that tries to minimize the perceptual distortion of decoded video under the conditions that the sum of bits generated from different views is constrained within a given bit budget. Since the constraint-based optimization problem is usually computational intensive, our proposed approach considers the concept of intra-layer and inter-layer disparity to reduce this computational complexity. Experimental results show that the proposed approach uses on average 24% and 42% less bitrate than the H.264/AVC rate-distortion optimization for base and base plus enhancement layers, respectively. Although the thesis is in Farsi (Persian), the following English papers capture most of its essence: H. Roodaki, M.R. Hashemi, and S. Shirmohammadi, ?A New Methodology to Derive Objective Quality Assessment Metrics for Scalable Multi-view 3D Video Coding?, ACM Transactions on Multimedia Computing, Communications, and Applications, Vol. 8, No. 3S, Article 44, September 2012, 25 pages. DOI: 10.1145/2348816.2348823 H. Roodaki, M.R. Hashemi, and S. Shirmohammadi, ?Rate-Distortion Optimization for Scalable Multi-View Video Coding?, Proc. IEEE International Conference on Multimedia and Expo, Chengdu, China, July 14-18 2014, 6 pages. DOI: 10.1109/ICME.2014.6890275 H. Roodaki, Z. Iravani, M.R. Hashemi, S. Shirmohammadi, and M. Gabbouj, ?A New Rate Distortion Model for Multi-View/3D Video Coding?, Proc. IEEE International Workshop on Hot Topics in 3D, in Proc. IEEE International Conference on Multimedia and Expo, July 15-19 2013, San Jose, USA, 6 pages. DOI: 10.1109/ICMEW.2013.6618338 H. Roodaki, M.R. Hashemi, and S. Shirmohammadi, ?New Scalable Modalities in Multi-view 3D Video?, Proc. ACM Workshop on Mobile Video, Oslo, Norway, February 27 2013, pp. 25-30. DOI: 10.1145/2457413.2457420

Reducing the arity in unbiased black-box complexity

We show that for all 1<k≤logn the k-ary unbiased black-box complexity of the n-dimensional OneMax function class is O(n/k). This indicates that the power of higher arity operators is much stronger than what the previous O(n/logk) bound by Doerr et al. [Benjamin Doerr, Daniel Johannsen, Timo Kötzing, Per Kristian Lehre, Markus Wagner, Carola Winzen, Faster black-box algorithms through higher arity operators, in Proc. of the 11th ACM Workshop on Foundations of Genetic Algorithms, FOGA’11, ACM, 2011, pp. 163–172] suggests. The key to this result is an encoding strategy, which might be of independent interest. It shows that, using k-ary unbiased variation operators only, we may simulate an unrestricted memory of O(2k) bits.

Hotnets 2012 highlights

This article captures some of the discussion and insights from this year's ACM Workshop on Hot Topics in Networks (HotNets-XI).

Report on the second ACM workshop on hot topics in software upgrades (HotSWUp'09)

The Second ACM SIGPLAN Workshop on Hot Topics in Software Upgrades (HotSWUp'09) was held on 25 October 2009 in Orlando, FL. The workshop was co-located with OOPSLA 2009 and was sponsored by ACM SIGPLAN. Twenty researchers and practitioners, from the programming languages, systems, software engineering and database communities, attended HotSWUp'09. The goal of HotSWUp is to identify, through interdisciplinary collaboration, cutting-edge research ideas for implementing software upgrades. The workshop combined presentations of peer-reviewed research papers with invited presentations from well-known experts and a keynote speech on the practical issues related to performing large-scale upgrades. The audience included researchers and practitioners from academia, the industry (Facebook, ABB, Oracle) and the open-source community (AppUpdater). In addition to the technical presentations, the program allowed ample time for discussions, which were driven by debate questions provided in advance by the presenters HotSWUp provides a premier forum for discussing problems that are often considered niche topics in the established research communities. For example, the technical discussions at HotSWUp'09 covered dynamic software updates, package management tools, database schema upgrades, upgrades of systems with real-time constraints, etc., and highlighted many synergies among these topics. Perhaps more interestingly, the industry presentations provided real-world examples of systems that a have strong requirement for online upgrades. These examples emphasized the magnitude of the software upgrade problems that the industry is facing today

Guest Editorial: “Special issue on selected papers from NOSSDAV 2009”

We are pleased to introduce this special issue featuring selected papers from the 19th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV 2009) held in Williamsburg, VA, USA. Based on the reviews of the NOSSDAV program committee, we invited authors of seven papers from the workshop to extend their papers for this special issue. We received five submissions, and, after a rigorous review process, three papers are accepted to appear in this special issue. The first paper, entitled ‘‘Frequent Layer Switching for Perceived Quality Improvements of Coarse-Grained Scalable Video’’, addresses the issue of adapting the video data rate to the available bandwidth. Existing coding-based approach for fine-grain adaptation often lead to high overhead. In this paper, Pengpeng Ni and her co-authors investigate an alternative method to achieve fine-grain scalability with low coding overhead. They propose a technique called frequent layer switching, where a coarsegrain scalable video is switched between different layers frequently to adapt to available bandwidth. A key question is how such frequent layer switches affect the perceptual quality of the video. The authors, through extensive user studies, show that frequent layer switching does not significantly affect the perceptual quality under certain scenario and switching patterns, making it a viable approach to achieve fine-grain video rate adaptation to available bandwidth. The second paper in this special issue considers the design of a large-scale VoD streaming system using peer-to-peer techniques. The paper, entitled, ‘‘InstantLeap: An Architecture for Fast Neighbor Discovery in Large-Scale P2P VoD Streaming,’’ tackles the challenge of fast neighbor discovery whenever a VCR command is issued. In this paper, Xuanjia Qiu and co-authors, propose a method to organize peers to facilitate smooth playback when a peer seeks to a new playback position in the video. The key idea is for each peer to maintain, in addition to neighbors that are viewing the video around the same playback point, a set of shortcut neighbors whose playback points are further away. The authors show that these shortcut neighbors allow constanttime lookup of neighbors at the new playback position. The last paper in this special issue, ‘‘Zebroid: Using IPTV Data to Support STB-Assisted VoD Content Delivery,’’ considers scaling up VoD services in the context of IPTV. In this paper, the authors, Yih-Farn Robin Chen et al., propose that popular content be prefetched into selected set top boxes during idle hours. During peak hours, a set top box requesting a popular content can receive the content from participating neighborhood set top boxes, reducing the load on the VoD server. VoD access patterns, properties of set top boxes, and load on network components are considered in deciding how to partition the content into stripes and which stripe to store into which set top boxes. The paper shows that storing a small amount of data into each set top box can reduce the load on the VoD server significantly during peak hours. The three selected papers cover many aspects of media streaming and distribution, from bandwidth adaptation, to reducing rebuffering time and improving scalability. We W. T. Ooi (&) Department of Computer Science, National University of Singapore, Singapore, Singapore e-mail: ooiwt@comp.nus.edu.sg

Special issue on “quality of service and security in wireless and mobile networks”

Special issue on “quality of service and security in wireless and mobile networks”

Report on the First MobiSys ACM workshop on mobile opportunistic networking (MobiOpp'07)

The aim of the MobiOpp workshop series is to bring together the (increasing) community of researchers working in the area of Mobile Opportunistic Networking. The first workshop in this series, MobiOpp'07, was held on June 11, 2007 in San Juan, Puerto Rico (USA) in conjunction with MobiSys 2007. MobiOpp'07 was sponsored by ACM SIGMOBILE and jointly organized by the IIT Institute of the Italian National Research Council (CNR) and by the UCLA Network Research Laboratory.

Report on the Sixth ACM Workshop on Privacy in the Electronic Society (WPES 2007)

The world is transforming into an electronic society where almost every aspect of our lives is increasingly computerized and interconnected. Such a transformation has profoundly changed the scope, the scale and the level of automation for information collection, storage, analysis and dissemination. It, on the one hand, has and continues to enable new and better services. On the other hand, it inevitably increases the degree of privacy concerns.

Report on ACM Workshop on Health Information and Knowledge Management (HIKM 2006)

Health information technology is receiving a tremendous amount of attention as a strategic area that will benefit the society in the 21st century. The continued advances in healthcare such as digitization of medical records, creation of central record systems, development of healthcare data warehouses increasingly pose new challenges to information and knowledge management. The high stakes and unique characteristics of healthcare data such as the long-term value of the data, varied data quality, the complexity of the data, the privacy constraints, as well as the availability requirements in emergent situations require a special treatment of traditional information management techniques.

Report on MobiDE 2003

The 3rd International ACM Workshop on Data Engineering for Wireless and Mobile Access (MobiDE 2003 for short) took place on September 19, 2003 at the Westin Horton Plaza Hotel in San Diego, California in conjunction with MobiCom 2003. The MobiDE workshops serve as a bridge between the data management and network research communities, and have a tradition of presenting innovations on mobile as well as wireless data engineering issues (such as those found in sensor networks). This workshop was the third in the MobiDE series, MobiDE 1999 having taken place in Seattle in conjunction with MobiCom 1999, and MobiDE 2001 having taken place in Santa Barbara in conjunction with SIGMOD 2001.

Preface: Volume 59, Issue 3

QAPL'01This volume contains the Post-Proceedings of the ACM Workshop on Quantitative Aspects of Programming Languages (QAPL'01). The workshop was held in Firenze, Italy on Friday 7th September 2001, as satellite event to Principles, Logics, and Implementations of high-level programming languages, PLI'01.The majority of approaches in program semantics and analysis are arguably concentrated on qualitative investigations of various computational properties. As a result, some aspects of computation are neglected, which are of a quantitative nature. Such aspects are nevertheless important and sometimes essential in determining the behaviour of systems. As an example, issues related to resource consumption (storage, time, bandwidth, etc.) cannot be ignored when systems of interacting, competing or cooperating processes are considered.The aim of this workshop was to discuss appropriate models of programming languages, which are able to capture quantitative aspects of computation. Such models are good candidates to provide the base of new approaches in semantics and program analysis. Their investigation will hopefully not just allow for a better understanding of program behaviour (e.g. how agents compete for a limited resource), but also help to establish better connections with related complexity theoretic questions.Probabilistic languages and real-time languages constitute two important prototypical examples of quantitative models. But we encouraged the contributions covering other and/or more general quantitative aspects in the design, analysis and implementation of programming languages, with particular emphasis on the functional and declarative paradigms.The papers presented at the workshop were selected by the program committee consisting of •Luca de Alfaro, University of California at Berkeley, USA•Frank de Boer, University of Utrecht, The Netherlands•Alessandra Di Pierro, University of Pisa, Italy•Maurizio Gabbrielli, University of Udine, Italy•Marta Z. Kwiatkowska, University of Birmingham, UK•Herbert Wiklicky, Imperial College, UK.At the workshop there was one invited talk by •David Sands: Asymptotic Reasoning Meets Programming Language Semanticsas well as eight contributed talks: •Keye Martin: Powerdomains and Zero Finding•Thom Frühwirth: As Time Goes By: Complexity Analysis of Simplification Rule•Antonio Brogi, Alessandra Di Pierro and Herbert Wiklicky: On Language Expressiveness and Dimension•David Clark, Sebastian Hunt and Pasquale Malacaria: Quantitative Analysis of the Leakage of Confidential Data•Marius C. Bujorianu and Manuela L. Bujorianu: On the Hilbert Machine Quantitative Computational Model•Frank S. de Boer, Maurizio Gabbrielli and Maria Chiara Meo: Proving Correctness of Timed Concurrent Constraint Programs•Nicos Angelopoulos and David R. Gilbert: A Statistical View of Probabilistic Finite Domains•Richard Kieburtz: Real-time Reactive Programming for Embedded ControllersThese Post-Proceedings contain the reviewed and revised versions of the first four of these presentations.October 2002 Alessandra di Pierro Herbert Wiklicky

The Lob–Pass Problem

We consider a new variant of the online learning model in which the goal of an agent is to choose his or her actions so as to maximize the number of successes, while learning about his or her reacting environment through those very actions. In particular, we consider a model of tennis play, in which the only actions that the player can take are a pass and a lob, and the opponent is modeled by two linear (probabilistic) functions fL(r)=a1r+b1 and fP(r)=a2r+b2, specifying the probability that a lob (and a pass, respectively) will win a point when the proportion of lobs played in the past trials is r. We measure the performance of a player in this model by his or her expected regret, namely how many fewer points the player expects to win as compared to the ideal player (one that knows the two probabilistic functions) as a function of t, the total number of trials, which is unknown to the player a priori. Assuming that the probabilistic functions satisfy the “matching shoulders condition,” i.e., fL(0)=fP(1), we obtain a variety of upper bounds for assumptions and restrictions of varying degrees, ranging from O(logt), O(t1/2), O(t3/5), O(t2/3) to O(t5/7) as well as a matching lower bound of order Ω(logt) for the first case. When the total number of trials t is given to the player in advance, the upper bounds can be improved significantly. An extended abstract describing part of this work has appeared in N. Abe and J. Takeuchi, 1993, in “Proceedings of the Sixth Annual ACM Workshop on Computational Learning Theory,” pp. 422–428.

Attribute-Efficient Learning in Query and Mistake-Bound Models

We consider the problem ofattribute-efficientlearning in query and mistake-bound models. Attribute-efficient algorithms make a number of queries or mistakes that is polynomial in the number of relevant variables in the target function, but only sublinear in the number of irrelevant variables. We consider a variant of the membership query model in which the learning algorithm is given as input the number of relevant variables of the target function. We show that in this model, any projection and embedding closed class of functions (including parity) that can be learned in polynomial time can be learned attribute-efficiently in polynomial time. We show that this does not hold in the randomized membership query model. In the mistake-bound model, we consider the problem of learning attribute-efficiently using hypotheses that are formulas of small depth. Our results extend the work of A. Blum, L. Hellerstein, and N. Littlestone (J. Comput. System Sci.50(1995), 32–40) and N. Bshouty, R. Cleve, S. Kannan, and C. Tamon (in “Proceedings, 7th Annu. ACM Workshop on Comput. Learning Theory,” pp. 130–139, ACM Press, New York, 1994).