for Journals by Title or ISSN
for Articles by Keywords
help
  Subjects -> COMPUTER SCIENCE (Total: 2002 journals)
    - ANIMATION AND SIMULATION (29 journals)
    - ARTIFICIAL INTELLIGENCE (99 journals)
    - AUTOMATION AND ROBOTICS (100 journals)
    - CLOUD COMPUTING AND NETWORKS (63 journals)
    - COMPUTER ARCHITECTURE (9 journals)
    - COMPUTER ENGINEERING (9 journals)
    - COMPUTER GAMES (16 journals)
    - COMPUTER PROGRAMMING (24 journals)
    - COMPUTER SCIENCE (1160 journals)
    - COMPUTER SECURITY (46 journals)
    - DATA BASE MANAGEMENT (13 journals)
    - DATA MINING (32 journals)
    - E-BUSINESS (22 journals)
    - E-LEARNING (29 journals)
    - ELECTRONIC DATA PROCESSING (21 journals)
    - IMAGE AND VIDEO PROCESSING (40 journals)
    - INFORMATION SYSTEMS (107 journals)
    - INTERNET (91 journals)
    - SOCIAL WEB (50 journals)
    - SOFTWARE (34 journals)
    - THEORY OF COMPUTING (8 journals)

COMPUTER SCIENCE (1160 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 13)
Abakós     Open Access   (Followers: 3)
Academy of Information and Management Sciences Journal     Full-text available via subscription   (Followers: 73)
ACM Computing Surveys     Hybrid Journal   (Followers: 22)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 9)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 13)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 16)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 6)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 11)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 4)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 13)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 4)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 1)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 20)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 11)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 22)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 26)
Advanced Science Letters     Full-text available via subscription   (Followers: 7)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 16)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 15)
Advances in Computer Science : an International Journal     Open Access   (Followers: 13)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Advances in Engineering Software     Hybrid Journal   (Followers: 25)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 10)
Advances in Human-Computer Interaction     Open Access   (Followers: 20)
Advances in Materials Sciences     Open Access   (Followers: 16)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 37)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 2)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 7)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
Air, Soil & Water Research     Open Access   (Followers: 8)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 4)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 7)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 9)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 6)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 12)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 2)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 14)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Clinical Informatics     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Computer Systems     Open Access   (Followers: 1)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 11)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 128)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 6)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access  
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 3)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 9)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Bioinformatics     Hybrid Journal   (Followers: 301)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 17)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 32)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 44)
British Journal of Educational Technology     Hybrid Journal   (Followers: 126)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 2)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal  
Cell Communication and Signaling     Open Access   (Followers: 1)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access  
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 15)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 12)
Circuits and Systems     Open Access   (Followers: 16)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
Communication Methods and Measures     Hybrid Journal   (Followers: 11)
Communication Theory     Hybrid Journal   (Followers: 20)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 53)
Communications of the Association for Information Systems     Open Access   (Followers: 18)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access  
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 9)
Computación y Sistemas     Open Access  
Computation     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 14)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 4)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 13)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 31)
Computer     Full-text available via subscription   (Followers: 85)
Computer Aided Surgery     Hybrid Journal   (Followers: 3)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Communications     Hybrid Journal   (Followers: 10)
Computer Engineering and Applications Journal     Open Access   (Followers: 5)
Computer Journal     Hybrid Journal   (Followers: 7)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 22)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 10)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 1)
Computer Music Journal     Hybrid Journal   (Followers: 16)
Computer Physics Communications     Hybrid Journal   (Followers: 6)
Computer Science - Research and Development     Hybrid Journal   (Followers: 7)
Computer Science and Engineering     Open Access   (Followers: 17)
Computer Science and Information Technology     Open Access   (Followers: 11)
Computer Science Education     Hybrid Journal   (Followers: 12)
Computer Science Journal     Open Access   (Followers: 20)
Computer Science Master Research     Open Access   (Followers: 10)
Computer Science Review     Hybrid Journal   (Followers: 10)

        1 2 3 4 5 6 | Last

Journal Cover ACM Computing Surveys
  [SJR: 3.405]   [H-I: 106]   [22 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0360-0300 - ISSN (Online) 1557-7341
   Published by ACM Homepage  [45 journals]
  • Automated Vehicle Detection and Classification: Models, Methods, and
           Techniques
    • Abstract: Azzedine Boukerche, Abdul Jabbar Siddiqui, Abdelhamid Mammeri

      Automated Vehicle Classification (AVC) based on vision sensors has received active attention from researchers, due to heightened security concerns in Intelligent Transportation Systems. In this work, we propose a categorization of AVC studies based on the granularity of classification, namely Vehicle Type Recognition, Vehicle Make Recognition, and Vehicle Make and Model Recognition. For each category of AVC systems, we present a comprehensive review and comparison of features extraction, global representation, and classification techniques. We also present the accuracy and speed-related performance metrics and discuss how they can be used to compare and evaluate different AVC works. The various datasets proposed over the years for AVC are also compared in light of the real-world challenges they represent, and those they do not.
      PubDate: Thu, 05 Oct 2017 00:00:00 GMT
       
  • A Survey of Active Object Languages
    • Abstract: Frank De Boer, Vlad Serbanescu, Reiner Hähnle, Ludovic Henrio, Justine Rochas, Crystal Chang Din, Einar Broch Johnsen, Marjan Sirjani, Ehsan Khamespanah, Kiko Fernandez-Reyes, Albert Mingkun Yang

      To program parallel systems efficiently and easily, a wide range of programming models have been proposed, each with different choices concerning synchronization and communication between parallel entities. Among them, the actor model is based on loosely coupled parallel entities that communicate by means of asynchronous messages and mailboxes. Some actor languages provide a strong integration with object-oriented concepts; these are often called active object languages. This article reviews four major actor and active object languages and compares them according to carefully chosen dimensions that cover central aspects of the programming paradigms and their implementation.
      PubDate: Thu, 05 Oct 2017 00:00:00 GMT
       
  • Interoperability and Portability Approaches in Inter-Connected Clouds: A
           Review
    • Abstract: Kiranbir Kaur, DR. Sandeep Sharma, DR. Karanjeet Singh Kahlon

      Inter-connected cloud computing is an inherent evolution of Cloud Computing. Numerous benefits provided by connecting clouds have garnered attraction from the academic as well as the industry sector. Just as every new evolution faces challenges, inter-connected clouds have their own set of challenges such as security, monitoring, authorization and identity management, vendor lock-in, and so forth. This article considers the vendor lock-in problem, which is a direct consequence of the lack of interoperability and portability. An extensive literature review by surveying more than 120 papers has been done to analyze and categorize various solutions suggested in literature for solving the interoperability and portability issues of inter-connected clouds.
      PubDate: Wed, 04 Oct 2017 00:00:00 GMT
       
  • Classification of Resilience Techniques Against Functional Errors at
           Higher Abstraction Layers of Digital Systems
    • Abstract: Georgia Psychou, Dimitrios Rodopoulos, Mohamed M. Sabry, Tobias Gemmeke, David Atienza, Tobias G. Noll, Francky Catthoor

      Nanoscale technology nodes bring reliability concerns back to the center stage of digital system design. A systematic classification of approaches that increase system resilience in the presence of functional hardware (HW)-induced errors is presented, dealing with higher system abstractions, such as the (micro)architecture, the mapping, and platform software (SW). The field is surveyed in a systematic way based on nonoverlapping categories, which add insight into the ongoing work by exposing similarities and differences. HW and SW solutions are discussed in a similar fashion so that interrelationships become apparent. The presented categories are illustrated by representative literature examples to illustrate their properties.
      PubDate: Wed, 04 Oct 2017 00:00:00 GMT
       
  • ACM Computing Surveys (CSUR) Volume 50 Issue 5, September 2017
           (Issue-in-Progress)
    • PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • Systems Applications of Social Networks
    • Abstract: Changtao Zhong, Nishanth Sastry

      The aim of this article is to provide an understanding of social networks as a useful addition to the standard toolbox of techniques used by system designers. To this end, we give examples of how data about social links have been collected and used in different application contexts. We develop a broad taxonomy-based overview of common properties of social networks, review how they might be used in different applications, and point out potential pitfalls where appropriate. We propose a framework, distinguishing between two main types of social network-based user selection—personalised user selection, which identifies target users who may be relevant for a given source node, using the social network around the source as a context, and generic user selection or group delimitation, which filters for a set of users who satisfy a set of application requirements based on their social properties.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • Structural XML Query Processing
    • Abstract: Radim Bača, Michal Krátký, Irena Holubová, Martin Nečaský, Tomáš Skopal, Martin Svoboda, Sherif Sakr

      Since the boom in new proposals on techniques for efficient querying of XML data is now over and the research world has shifted its attention toward new types of data formats, we believe that it is crucial to review what has been done in the area to help users choose an appropriate strategy and scientists exploit the contributions in new areas of data processing. The aim of this work is to provide a comprehensive study of the state-of-the-art of approaches for the structural querying of XML data. In particular, we start with a description of labeling schemas to capture the structure of the data and the respective storage strategies.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • Mobile Agents System Security: A Systematic Survey
    • Abstract: Pallavi Bagga, Rahul Hans

      A pivotal cause for the boom of Mobile Agent paradigm relies on the competence to ward off security attacks. This article surveys the prevalent attacks on the mobile agents and the agent platforms; the existing countermeasures and their curbs, catering threefold benefaction: First, to acquaint the researchers with numerous security requirements and the objectives. Second, to analyze the different detection and prevention mechanisms mitigating the security bottlenecks in Mobile Agents System. Third, to address the future security challenges. In a nutshell, this survey hands over a key to researchers who primarily target the security concerns of the mobile agent-based applications.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • A Survey of Dynamic Analysis and Test Generation for JavaScript
    • Abstract: Esben Andreasen, Liang Gong, Anders Møller, Michael Pradel, Marija Selakovic, Koushik Sen, Cristian-Alexandru Staicu

      JavaScript has become one of the most prevalent programming languages. Unfortunately, some of the unique properties that contribute to this popularity also make JavaScript programs prone to errors and difficult for program analyses to reason about. These properties include the highly dynamic nature of the language, a set of unusual language features, a lack of encapsulation mechanisms, and the “no crash” philosophy. This article surveys dynamic program analysis and test generation techniques for JavaScript targeted at improving the correctness, reliability, performance, security, and privacy of JavaScript-based software.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • A Tutorial for Olfaction-Based Multisensorial Media Application Design and
           Evaluation
    • Abstract: Niall Murray, Oluwakemi A. Ademoye, Gheorghita Ghinea, Gabriel-Miro Muntean

      Recently, multimedia researchers have added several so-called new media to the traditional multimedia components (e.g., olfaction, haptic, and gustation). Evaluating multimedia user-perceived Quality of Experience (QoE) is already non-trivial and the addition of multisensorial media components increases this challenge. No standardized methodology exists to conduct subjective quality assessments of multisensorial media applications. To date, researchers have employed different aspects of audiovisual standards to assess user QoE of multisensorial media applications and thus, a fragmented approach exists. In this article, the authors highlight issues researchers face from numerous perspectives including applicability (or lack of) existing audiovisual standards to evaluate user QoE and lack of result comparability due to varying approaches, specific requirements of olfactory-based multisensorial media applications, and novelty associated with these applications.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • Foundations of Modern Query Languages for Graph Databases
    • Abstract: Renzo Angles, Marcelo Arenas, Pablo Barceló, Aidan Hogan, Juan Reutter, Domagoj Vrgoč

      We survey foundational features underlying modern graph query languages. We first discuss two popular graph data models: edge-labelled graphs, where nodes are connected by directed, labelled edges, and property graphs, where nodes and edges can further have attributes. Next we discuss the two most fundamental graph querying functionalities: graph patterns and navigational expressions. We start with graph patterns, in which a graph-structured query is matched against the data. Thereafter, we discuss navigational expressions, in which patterns can be matched recursively against the graph to navigate paths of arbitrary length; we give an overview of what kinds of expressions have been proposed and how they can be combined with graph patterns.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • A Functional Taxonomy of Music Generation Systems
    • Abstract: Dorien Herremans, Ching-Hua Chuan, Elaine Chew

      Digital advances have transformed the face of automatic music generation since its beginnings at the dawn of computing. Despite the many breakthroughs, issues such as the musical tasks targeted by different machines and the degree to which they succeed remain open questions. We present a functional taxonomy for music generation systems with reference to existing systems. The taxonomy organizes systems according to the purposes for which they were designed. It also reveals the inter-relatedness amongst the systems. This design-centered approach contrasts with predominant methods-based surveys and facilitates the identification of grand challenges to set the stage for new breakthroughs.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • A Survey of Naturalistic Programming Technologies
    • Abstract: Oscar Pulido-Prieto, Ulises Juárez-Martínez

      Mainly focused on solving abstraction problems, programming paradigms limit language expressiveness, thus leaving unexplored natural language descriptions that are implicitly expressive. Several authors have developed tools for programming with a natural language subset limited to specific domains to deal with the ambiguity occurring with artificial intelligence technique use. This article presents a review of tools and languages with naturalistic features and highlights the problems that authors have resolved and those they have not addressed, going on to discuss the fact that a “naturalistic” language based on a well-defined model is not reported.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • Probabilistic Complex Event Recognition: A Survey
    • Abstract: Elias Alevizos, Anastasios Skarlatidis, Alexander Artikis, Georgios Paliouras

      Complex event recognition (CER) applications exhibit various types of uncertainty, ranging from incomplete and erroneous data streams to imperfect complex event patterns. We review CER techniques that handle, to some extent, uncertainty. We examine techniques based on automata, probabilistic graphical models, and first-order logic, which are the most common ones, and approaches based on Petri nets and grammars, which are less frequently used. Several limitations are identified with respect to the employed languages, their probabilistic models, and their performance, as compared to the purely deterministic cases. Based on those limitations, we highlight promising directions for future work.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • Modeling, Evaluation, and Scale on Artificial Pedestrians: A Literature
           Review
    • Abstract: Francisco Martinez-Gil, Miguel Lozano, Ignacio García-Fernández, Fernando Fernández

      Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim of this article is to provide a bibliographic outlook so that the reader may have quick access to the most relevant works related to this problem. We have used three main axes to organize the article’s contents: pedestrian models, validation techniques, and multiscale approaches. The backbone of this work is the classification of existing pedestrian models; we have organized the works in the literature under five categories, according to the techniques used for implementing the operational level in each pedestrian model.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • Automatic Sarcasm Detection: A Survey
    • Abstract: Aditya Joshi, Pushpak Bhattacharyya, Mark J. Carman

      Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing text. Beginning with an approach that used speech-based features, automatic sarcasm detection has witnessed great interest from the sentiment analysis community. This article is a compilation of past work in automatic sarcasm detection. We observe three milestones in the research so far: semi-supervised pattern extraction to identify implicit sentiment, use of hashtag-based supervision, and incorporation of context beyond target text. In this article, we describe datasets, approaches, trends, and issues in sarcasm detection. We also discuss representative performance values, describe shared tasks, and provide pointers to future work, as given in prior works.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • A Review on Quantification Learning
    • Abstract: Pablo González, Alberto Castaño, Nitesh V. Chawla, Juan José Del Coz

      The task of quantification consists in providing an aggregate estimation (e.g., the class distribution in a classification problem) for unseen test sets, applying a model that is trained using a training set with a different data distribution. Several real-world applications demand this kind of method that does not require predictions for individual examples and just focuses on obtaining accurate estimates at an aggregate level. During the past few years, several quantification methods have been proposed from different perspectives and with different goals.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • Secure Smart Homes: Opportunities and Challenges
    • Abstract: Jordi Mongay Batalla, Athanasios Vasilakos, Mariusz Gajewski

      The Smart Home concept integrates smart applications in the daily human life. In recent years, Smart Homes have increased security and management challenges due to the low capacity of small sensors, multiple connectivity to the Internet for efficient applications (use of big data and cloud computing), and heterogeneity of home systems, which require inexpert users to configure devices and micro-systems. This article presents current security and management approaches in Smart Homes and shows the good practices imposed on the market for developing secure systems in houses. At last, we propose future solutions for efficiently and securely managing the Smart Homes.
      PubDate: Tue, 26 Sep 2017 00:00:00 GMT
       
  • ACM Computing Surveys (CSUR) Volume 50 Issue 4, August 2017
           (Issue-in-Progress)
    • PubDate: Wed, 30 Aug 2017 00:00:00 GMT
       
  • The Need for Affective Trust Applied to Trust and Reputation Models
    • Abstract: Jones Granatyr, Nardine Osman, João Dias, Maria Augusta Silveira Netto Nunes, Judith Masthoff, Fabrício Enembreck, Otto Robert Lessing, Carles Sierra, Ana Maria Paiva, Edson Emílio Scalabrin

      Trust allows the behavior evaluation of individuals by setting confidence values, which are used in decisions about whether or not to interact. They have been used in several fields, and many trust and reputation models were developed recently. We perceived that most of them were built upon the numeric and cognitive paradigms, which do not use affective aspects to build trust or help in decision making. Studies in psychology argued that personality, emotions, and mood are important in decision making and can change the behaviors of individuals. Based on that, we present links between trust and affective computing, showing relations of trust dimensions found in trust models with affective aspects, and presenting why affective computing approaches fit trust issues often addressed by research in this field.
      PubDate: Wed, 30 Aug 2017 00:00:00 GMT
       
  • A Classification of Locality in Network Research
    • Abstract: Michael Stein, Mathias Fischer, Immanuel Schweizer, Max Mühlhäuser

      Limiting the knowledge of individual nodes is a major concern for the design of distributed algorithms. With the LOCAL model, theoretical research already established a common model of locality that has gained little practical relevance. As a result, practical research de facto lacks any common locality model. The only common denominator among practitioners is that a local algorithm is distributed with a restricted scope of interaction. This article closes the gap by introducing four practically motivated classes of locality that successively weaken the strict requirements of the LOCAL model. These classes are applied to categorize and survey 36 local algorithms from 12 different application domains.
      PubDate: Wed, 30 Aug 2017 00:00:00 GMT
       
  • Metrics for Community Analysis: A Survey
    • Abstract: Tanmoy Chakraborty, Ayushi Dalmia, Animesh Mukherjee, Niloy Ganguly

      Detecting and analyzing dense groups or communities from social and information networks has attracted immense attention over the last decade due to its enormous applicability in different domains. Community detection is an ill-defined problem, as the nature of the communities is not known in advance. The problem has turned even more complicated due to the fact that communities emerge in the network in various forms such as disjoint, overlapping, and hierarchical. Various heuristics have been proposed to address these challenges, depending on the application in hand. All these heuristics have been materialized in the form of new metrics, which in most cases are used as optimization functions for detecting the community structure, or provide an indication of the goodness of detected communities during evaluation.
      PubDate: Wed, 30 Aug 2017 00:00:00 GMT
       
  • Non-GPS Positioning Systems: A Survey
    • Abstract: Zain Bin Tariq, Dost Muhammad Cheema, Muhammad Zahir Kamran, Ijaz Haider Naqvi

      An enormous amount of research has been conducted in the area of positioning systems and thus it calls for a detailed literature review of recent localization systems. This article focuses on recent developments of non-Global Positioning System (GPS) localization/positioning systems. We have presented a new hierarchical method to classify various positioning systems. A comprehensive performance comparison of the techniques and technologies against multiple performance metrics along with the limitations is presented. A few indoor positioning systems have emerged as more successful in particular application environments than others, which are presented at the end.
      PubDate: Wed, 30 Aug 2017 00:00:00 GMT
       
  • Toward Real-Time Ray Tracing: A Survey on Hardware Acceleration and
           Microarchitecture Techniques
    • Abstract: Yangdong Deng, Yufei Ni, Zonghui Li, Shuai Mu, Wenjun Zhang

      Ray tracing has long been considered as the next-generation technology for graphics rendering. Recently, there has been strong momentum to adopt ray tracing--based rendering techniques on consumer-level platforms due to the inability of further enhancing user experience by increasing display resolution. On the other hand, the computing workload of ray tracing is still overwhelming. A 10-fold performance gap has to be narrowed for real-time applications, even on the latest graphics processing units (GPUs). As a result, hardware acceleration techniques are critical to delivering a satisfying level performance while at the same time meeting an acceptable power budget. A large body of research on ray-tracing hardware has been proposed over the past decade.
      PubDate: Wed, 30 Aug 2017 00:00:00 GMT
       
  • A Survey of Algorithmic Debugging
    • Abstract: Rafael Caballero, Adri´n Riesco, Josep Silva

      Algorithmic debugging is a technique proposed in 1982 by E. Y. Shapiro in the context of logic programming. This survey shows how the initial ideas have been developed to become a widespread debugging schema fitting many different programming paradigms and with applications out of the program debugging field. We describe the general framework and the main issues related to the implementations in different programming paradigms and discuss several proposed improvements and optimizations. We also review the main algorithmic debugger tools that have been implemented so far and compare their features.
      PubDate: Wed, 30 Aug 2017 00:00:00 GMT
       
  • Bridging the Chasm: A Survey of Software Engineering Practice in
           Scientific Programming
    • Abstract: Tim Storer

      The use of software is pervasive in all fields of science. Associated software development efforts may be very large, long lived, and complex, requiring the commitment of significant resources. However, several authors have argued that the “gap” or “chasm” between software engineering and scientific programming is a serious risk to the production of reliable scientific results, as demonstrated in a number of case studies. This article reviews the research that addresses the gap, exploring how both software engineering and research practice may need to evolve to accommodate the use of software in science.
      PubDate: Fri, 25 Aug 2017 00:00:00 GMT
       
  • On the Collaboration Support in Information Retrieval
    • Abstract: Laure Soulier, Lynda Tamine

      Collaborative Information Retrieval (CIR) is a well-known setting in which explicit collaboration occurs among a group of users working together to solve a shared information need. This type of collaboration has been deemed as beneficial for complex or exploratory search tasks. With the multiplicity of factors impacting on the search effectiveness (e.g., collaborators’ interactions or the individual perception of the shared information need), CIR gives rise to several challenges in terms of collaboration support through algorithmic approaches. More particularly, CIR should allow us to satisfy the shared information need by optimizing the collaboration within the search session over all collaborators, while ensuring that both mutually beneficial goals are reached and that the cognitive cost of the collaboration does not impact the search effectiveness.
      PubDate: Fri, 25 Aug 2017 00:00:00 GMT
       
  • Similarity of Business Process Models—A State-of-the-Art Analysis
    • Abstract: Andreas Schoknecht, Tom Thaler, Peter Fettke, Andreas Oberweis, Ralf Laue

      Business process models play an important role in today’s enterprises, hence, model repositories may contain hundreds of models. These models are, for example, reused during process modeling activities or utilized to check the conformance of processes with legal regulations. With respect to the amount of models, such applications benefit from or even require detailed insights into the correspondences between process models or between process models’ nodes. Therefore, various process similarity and matching measures have been proposed during the past few years. This article provides an overview of the state-of-the-art regarding business process model similarity measures and aims at analyzing which similarity measures exist, how they are characterized, and what kind of calculations are typically applied to determine similarity values.
      PubDate: Fri, 25 Aug 2017 00:00:00 GMT
       
  • Searching the Web of Things: State of the Art, Challenges, and Solutions
    • Abstract: Nguyen Khoi Tran, Quan Z. Sheng, Muhammad Ali Babar, Lina Yao

      Technological advances allow more physical objects to connect to the Internet and provide their services on the Web as resources. Search engines are the key to fully utilize this emerging Web of Things, as they bridge users and applications with resources needed for their operation. Developing these systems is a challenging and diverse endeavor due to the diversity of Web of Things resources that they work with. Each combination of resources in query resolution process requires a different type of search engine with its own technical challenges and usage scenarios. This diversity complicates both the development of new systems and assessment of the state of the art.
      PubDate: Fri, 25 Aug 2017 00:00:00 GMT
       
  • Software Vulnerability Analysis and Discovery Using Machine-Learning and
           Data-Mining Techniques: A Survey
    • Abstract: Seyed Mohammad Ghaffarian, Hamid Reza Shahriari

      Software security vulnerabilities are one of the critical issues in the realm of computer security. Due to their potential high severity impacts, many different approaches have been proposed in the past decades to mitigate the damages of software vulnerabilities. Machine-learning and data-mining techniques are also among the many approaches to address this issue. In this article, we provide an extensive review of the many different works in the field of software vulnerability analysis and discovery that utilize machine-learning and data-mining techniques.
      PubDate: Fri, 25 Aug 2017 00:00:00 GMT
       
  • Analysis of JavaScript Programs: Challenges and Research Trends
    • Abstract: Kwangwon Sun, Sukyoung Ryu

      JavaScript has been a de facto standard language for client-side web programs, and now it is expanding its territory to general purpose programs. In this article, we classify the client-side JavaScript research for the last decade or so into six topics: static analysis, dynamic analysis, formalization and reasoning, type safety and JIT optimization, security for web applications, and empirical studies. Because the majority of the research has focused on static and dynamic analyses of JavaScript, we evaluate research trends in the analysis of JavaScript first and then the other topics. Finally, we discuss possible future research directions with open challenges.
      PubDate: Fri, 25 Aug 2017 00:00:00 GMT
       
  • A Survey on Post-Silicon Functional Validation for Multicore Architectures
    • Abstract: Padma Jayaraman, Ranjani Parthasarathi

      During a processor development cycle, post-silicon validation is performed on the first fabricated chip to detect and fix design errors. Design errors occur due to functional issues when a unit in a design does not meet its specification. The chances of occurrence of such errors are high when new features are added in a processor. Thus, in multicore architectures, with new features being added in core and uncore components, the task of verifying the functionality independently and in coordination with other units gains significance. Several new techniques are being proposed in the field of functional validation. In this article, we undertake a survey of these techniques to identify areas that need to be addressed for multicore designs.
      PubDate: Fri, 25 Aug 2017 00:00:00 GMT
       
  • Nudges for Privacy and Security: Understanding and Assisting Users’
           Choices Online
    • Abstract: Alessandro Acquisti, Idris Adjerid, Rebecca Balebako, Laura Brandimarte, Lorrie Faith Cranor, Saranga Komanduri, Pedro Giovanni Leon, Norman Sadeh, Florian Schaub, Manya Sleeper, Yang Wang, Shomir Wilson

      Advancements in information technology often task users with complex and consequential privacy and security decisions. A growing body of research has investigated individuals’ choices in the presence of privacy and information security tradeoffs, the decision-making hurdles affecting those choices, and ways to mitigate such hurdles. This article provides a multi-disciplinary assessment of the literature pertaining to privacy and security decision making. It focuses on research on assisting individuals’ privacy and security choices with soft paternalistic interventions that nudge users toward more beneficial choices.
      PubDate: Tue, 08 Aug 2017 00:00:00 GMT
       
  • Data-Driven Techniques in Computing System Management
    • Abstract: Tao Li, Chunqiu Zeng, Yexi Jiang, Wubai Zhou, Liang Tang, Zheng Liu, Yue Huang

      Modern forms of computing systems are becoming progressively more complex, with an increasing number of heterogeneous hardware and software components. As a result, it is quite challenging to manage these complex systems and meet the requirements in manageability, dependability, and performance that are demanded by enterprise customers. This survey presents a variety of data-driven techniques and applications with a focus on computing system management. In particular, the survey introduces intelligent methods for event generation that can transform diverse log data sources into structured events, reviews different types of event patterns and the corresponding event-mining techniques, and summarizes various event summarization methods and data-driven approaches for problem diagnosis in system management.
      PubDate: Thu, 27 Jul 2017 00:00:00 GMT
       
  • Encoding Arguments
    • Abstract: Pat Morin, Wolfgang Mulzer, Tommy Reddad

      Many proofs in discrete mathematics and theoretical computer science are based on the probabilistic method. To prove the existence of a good object, we pick a random object and show that it is bad with low probability. This method is effective, but the underlying probabilistic machinery can be daunting. “Encoding arguments” provide an alternative presentation in which probabilistic reasoning is encapsulated in a “uniform encoding lemma.” This lemma provides an upper bound on the probability of an event using the fact that a uniformly random choice from a set of size n cannot be encoded with fewer than log 2n bits on average.
      PubDate: Thu, 27 Jul 2017 00:00:00 GMT
       
  • Fog Computing for Sustainable Smart Cities: A Survey
    • Abstract: Charith Perera, Yongrui Qin, Julio C. Estrella, Stephan Reiff-Marganiec, Athanasios V. Vasilakos

      The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, especially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g., network, storage, etc.) . The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • Arabic Online Handwriting Recognition (AOHR): A Survey
    • Abstract: Baligh M. Al-Helali, Sabri A. Mahmoud

      This article comprehensively surveys Arabic Online Handwriting Recognition (AOHR). We address the challenges posed by online handwriting recognition, including ligatures, dots and diacritic problems, online/offline touching of text, and geometric variations. Then we present a general model of an AOHR system that incorporates the different phases of an AOHR system. We summarize the main AOHR databases and identify their uses and limitations. Preprocessing techniques that are used in AOHR, viz. normalization, smoothing, de-hooking, baseline identification, and delayed stroke processing, are presented with illustrative examples. We discuss different techniques for Arabic online handwriting segmentation at the character and morpheme levels and identify their limitations.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • A Survey on Reinforcement Learning Models and Algorithms for Traffic
           Signal Control
    • Abstract: Kok-Lim Alvin Yau, Junaid Qadir, Hooi Ling Khoo, Mee Hong Ling, Peter Komisarczuk

      Traffic congestion has become a vexing and complex issue in many urban areas. Of particular interest are the intersections where traffic bottlenecks are known to occur despite being traditionally signalized. Reinforcement learning (RL), which is an artificial intelligence approach, has been adopted in traffic signal control for monitoring and ameliorating traffic congestion. RL enables autonomous decision makers (e.g., traffic signal controllers) to observe, learn, and select the optimal action (e.g., determining the appropriate traffic phase and its timing) to manage traffic such that system performance is improved. This article reviews various RL models and algorithms applied to traffic signal control in the aspects of the representations of the RL model (i.e., state, action, and reward), performance measures, and complexity to establish a foundation for further investigation in this research field.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • GPU Virtualization and Scheduling Methods: A Comprehensive Survey
    • Abstract: Cheol-Ho Hong, Ivor Spence, Dimitrios S. Nikolopoulos

      The integration of graphics processing units (GPUs) on high-end compute nodes has established a new accelerator-based heterogeneous computing model, which now permeates high-performance computing. The same paradigm nevertheless has limited adoption in cloud computing or other large-scale distributed computing paradigms. Heterogeneous computing with GPUs can benefit the Cloud by reducing operational costs and improving resource and energy efficiency. However, such a paradigm shift would require effective methods for virtualizing GPUs, as well as other accelerators. In this survey article, we present an extensive and in-depth survey of GPU virtualization techniques and their scheduling methods. We review a wide range of virtualization techniques implemented at the GPU library, driver, and hardware levels.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • Cross Domain Recommender Systems: A Systematic Literature Review
    • Abstract: Muhammad Murad Khan, Roliana Ibrahim, Imran Ghani

      Cross domain recommender systems (CDRS) can assist recommendations in a target domain based on knowledge learned from a source domain. CDRS consists of three building blocks: domain, user-item overlap scenarios, and recommendation tasks. The objective of this research is to identify the most widely used CDRS building-block definitions, identify common features between them, classify current research in the frame of identified definitions, group together research with respect to algorithm types, present existing problems, and recommend future directions for CDRS research. To achieve this objective, we have conducted a systematic literature review of 94 shortlisted studies. We classified the selected studies using the tag-based approach and designed classification grids.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • A Survey of Power and Energy Predictive Models in HPC Systems and
           Applications
    • Abstract: Kenneth O’brien, Ilia Pietri, Ravi Reddy, Alexey Lastovetsky, Rizos Sakellariou

      Power and energy efficiency are now critical concerns in extreme-scale high-performance scientific computing. Many extreme-scale computing systems today (for example: Top500) have tight integration of multicore CPU processors and accelerators (mix of Graphical Processing Units, Intel Xeon Phis, or Field Programmable Gate Arrays) empowering them to provide not just unprecedented computational power but also to address these concerns. However, such integration renders these systems highly heterogeneous and hierarchical, thereby necessitating design of novel performance, power, and energy models to accurately capture these inherent characteristics. There are now several extensive research efforts focusing exclusively on power and energy efficiency models and techniques for the processors composing these extreme-scale computing systems.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • A New Classification Framework to Evaluate the Entity Profiling on the
           Web: Past, Present and Future
    • Abstract: Ahmad Abdollahzadeh Barforoush, Hossein Shirazi, Hojjat Emami

      Recently, we have witnessed entity profiling (EP) becoming increasingly one of the most important topics in information extraction, personalized applications, and web data analysis. EP aims to identify, extract, and represent a compact summary of valuable information about an entity based on the data related to it. To determine how EP systems have developed, during the last few years, this article reviews EP systems through a survey of the literature, from 2000 to 2015. To fulfill this aim, we introduce a comparison framework to compare and classify EP systems. Our comparison framework is composed of thirteen criteria that include: profiling source, the entity being modeled, the information that constitutes the profile, representation schema, profile construction technique, scale, scope/target domain, language, updating mechanism, enrichment technique, dynamicity, evaluation method, and application among others.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • A Survey on Malware Detection Using Data Mining Techniques
    • Abstract: Yanfang Ye, Tao Li, Donald Adjeroh, S. Sitharama Iyengar

      In the Internet age, malware (such as viruses, trojans, ransomware, and bots) has posed serious and evolving security threats to Internet users. To protect legitimate users from these threats, anti-malware software products from different companies, including Comodo, Kaspersky, Kingsoft, and Symantec, provide the major defense against malware. Unfortunately, driven by the economic benefits, the number of new malware samples has explosively increased: anti-malware vendors are now confronted with millions of potential malware samples per year. In order to keep on combating the increase in malware samples, there is an urgent need to develop intelligent methods for effective and efficient malware detection from the real and large daily sample collection.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • Corrections to “A Menagerie of Timed Automata”
    • Abstract: Jeroen J. A. Keiren, Peter Fontana, Rance Cleaveland

      This note corrects a technical error in the ACM Computing Surveys article mentioned in the title. The flaw involved constructions for showing that timed automata with urgent locations have the same expressiveness as timed automata that allow false location invariants. Corrected constructions are presented in this note, and the affected results are reproved.
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • Data Science: A Comprehensive Overview
    • Abstract: Longbing Cao

      The 21st century has ushered in the age of big data and data economy, in which data DNA, which carries important knowledge, insights, and potential, has become an intrinsic constituent of all data-based organisms. An appropriate understanding of data DNA and its organisms relies on the new field of data science and its keystone, analytics. Although it is widely debated whether big data is only hype and buzz, and data science is still in a very early phase, significant challenges and opportunities are emerging or have been inspired by the research, innovation, business, profession, and education of data science. This article provides a comprehensive survey and tutorial of the fundamental aspects of data science: the evolution from data analysis to data science, the data science concepts, a big picture of the era of data science, the major challenges and directions in data innovation, the nature of data analytics, new industrialization ...
      PubDate: Thu, 29 Jun 2017 00:00:00 GMT
       
  • ACM Computing Surveys (CSUR) Volume 50 Issue 3, May 2017
           (Issue-in-Progress)
    • PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Optimization of Complex Dataflows with User-Defined Functions
    • Abstract: Astrid Rheinländer, Ulf Leser, Goetz Graefe

      In many fields, recent years have brought a sharp rise in the size of the data to be analyzed and the complexity of the analysis to be performed. Such analyses are often described as dataflows specified in declarative dataflow languages. A key technique to achieve scalability for such analyses is the optimization of the declarative programs; however, many real-life dataflows are dominated by user-defined functions (UDFs) to perform, for instance, text analysis, graph traversal, classification, or clustering. This calls for specific optimization techniques as the semantics of such UDFs are unknown to the optimizer. In this article, we survey techniques for optimizing dataflows with UDFs.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Searchable Symmetric Encryption: Designs and Challenges
    • Abstract: Geong Sen Poh, Ji-Jian Chin, Wei-Chuen Yau, Kim-Kwang Raymond Choo, Moesfa Soeheila Mohamad

      Searchable Symmetric Encryption (SSE) when deployed in the cloud allows one to query encrypted data without the risk of data leakage. Despite the widespread interest, existing surveys do not examine in detail how SSE’s underlying structures are designed and how these result in the many properties of a SSE scheme. This is the gap we seek to address, as well as presenting recent state-of-the-art advances on SSE. Specifically, we present a general framework and believe the discussions may lead to insights for potential new designs. We draw a few observations. First, most schemes use index table, where optimal index size and sublinear search can be achieved using an inverted index.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
 
Home (Search)
Subjects A-Z
Publishers A-Z
Customise
APIs
Your IP address: 54.224.50.28
 
About JournalTOCs
API
Help
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2016