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  • A Calculational Deductive System for Linear Temporal Logic
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-17
    J. Stanley Warford; David Vega; Scott M. Staley

    This article surveys the linear temporal logic (LTL) literature and presents all the LTL theorems from the survey, plus many new ones, in a calculational deductive system. Calculational deductive systems, developed by Dijkstra and Scholten and extended by Gries and Schneider, are based on only four inference rules—Substitution, Leibniz, Equanimity, and Transitivity. Inference rules in the older Hilbert-style

    更新日期:2020-07-05
  • Blockchains: A Systematic Multivocal Literature Review
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-17
    Bert-Jan Butijn; Damian A. Tamburri; Willem-Jan van den Heuvel

    Blockchain technology has gained tremendous popularity both in practice and academia. The goal of this article is to develop a coherent overview of the state of the art in blockchain technology, using a systematic (i.e., protocol-based, replicable), multivocal (i.e., featuring both white and grey literature alike) literature review to (1) define blockchain technology, (2) elaborate on its architecture

    更新日期:2020-07-05
  • Driver Emotion Recognition for Intelligent Vehicles: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-17
    Sebastian Zepf; Javier Hernandez; Alexander Schmitt; Wolfgang Minker; Rosalind W. Picard

    Driving can occupy a large portion of daily life and often can elicit negative emotional states like anger or stress, which can significantly impact road safety and long-term human health. In recent decades, the arrival of new tools to help recognize human affect has inspired increasing interest in how to develop emotion-aware systems for cars. To help researchers make needed advances in this area

    更新日期:2020-07-05
  • In Memoriam Eliezer Dekel (1948-2020)
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-26
    Sartaj Sahni; Albert Y. Zomaya

    No abstract available.

    更新日期:2020-07-02
  • Trade-offs between Distributed Ledger Technology Characteristics
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Niclas Kannengießer; Sebastian Lins; Tobias Dehling; Ali Sunyaev

    When developing peer-to-peer applications on distributed ledger technology (DLT), a crucial decision is the selection of a suitable DLT design (e.g., Ethereum), because it is hard to change the underlying DLT design post hoc. To facilitate the selection of suitable DLT designs, we review DLT characteristics and identify trade-offs between them. Furthermore, we assess how DLT designs account for these

    更新日期:2020-07-02
  • A Survey on Automatic Parameter Tuning for Big Data Processing Systems
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-26
    Herodotos Herodotou; Yuxing Chen; Jiaheng Lu

    Big data processing systems (e.g., Hadoop, Spark, Storm) contain a vast number of configuration parameters controlling parallelism, I/O behavior, memory settings, and compression. Improper parameter settings can cause significant performance degradation and stability issues. However, regular users and even expert administrators grapple with understanding and tuning them to achieve good performance

    更新日期:2020-07-02
  • A Survey of IIoT Protocols: A Measure of Vulnerability Risk Analysis Based on CVSS
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-26
    Santiago Figueroa-Lorenzo; Javier Añorga; Saioa Arrizabalaga

    Industrial Internet of Things (IIoT) is present in many participants from the energy, health, manufacturing, transport, and public sectors. Many factors catalyze IIoT, such as robotics, artificial intelligence, and intelligent decentralized manufacturing. However, the convergence between IT, OT, and IoT environments involves the integration of heterogeneous technologies through protocols, standards

    更新日期:2020-07-02
  • Security Issues and Challenges for Virtualization Technologies
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-17
    Federico Sierra-Arriaga; Rodrigo Branco; Ben Lee

    Virtualization-based technologies have become ubiquitous in computing. While they provide an easy-to-implement platform for scalable, high-availability services, they also introduce new security issues. Traditionally, discussions on security vulnerabilities in server platforms have been focused on stand-alone (i.e., non-virtualized) environments. For cloud and virtualized platforms, the discussion

    更新日期:2020-07-02
  • SLA Management for Big Data Analytical Applications in Clouds
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Xuezhi Zeng; Saurabh Garg; Mutaz Barika; Albert Y. Zomaya; Lizhe Wang; Massimo Villari; Dan Chen; Rajiv Ranjan

    Recent years have witnessed the booming of big data analytical applications (BDAAs). This trend provides unrivaled opportunities to reveal the latent patterns and correlations embedded in the data, and thus productive decisions may be made. This was previously a grand challenge due to the notoriously high dimensionality and scale of big data, whereas the quality of service offered by providers is the

    更新日期:2020-06-12
  • Exploiting Errors for Efficiency
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Phillip Stanley-Marbell; Armin Alaghi; Michael Carbin; Eva Darulova; Lara Dolecek; Andreas Gerstlauer; Ghayoor Gillani; Djordje Jevdjic; Thierry Moreau; Mattia Cacciotti; Alexandros Daglis; Natalie Enright Jerger; Babak Falsafi; Sasa Misailovic; Adrian Sampson; Damien Zufferey

    When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, system software, and programming language compilers or their runtime systems can trade deviations from correct behavior for lower resource usage. We present, for the first time, a synthesis of research results on computing systems that only make as many

    更新日期:2020-06-12
  • Outlier Detection
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Azzedine Boukerche; Lining Zheng; Omar Alfandi

    Over the past decade, we have witnessed an enormous amount of research effort dedicated to the design of efficient outlier detection techniques while taking into consideration efficiency, accuracy, high-dimensional data, and distributed environments, among other factors. In this article, we present and examine these characteristics, current solutions, as well as open challenges and future research

    更新日期:2020-06-12
  • Computing Server Power Modeling in a Data Center
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Leila Ismail; Huned Materwala

    Data centers are large-scale, energy-hungry infrastructure serving the increasing computational demands as the world is becoming more connected in smart cities. The emergence of advanced technologies such as cloud-based services, internet of things (IoT), and big data analytics has augmented the growth of global data centers, leading to high energy consumption. This upsurge in energy consumption of

    更新日期:2020-06-12
  • Deep Learning for Source Code Modeling and Generation
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Triet H. M. Le; Hao Chen; Muhammad Ali Babar

    Deep Learning (DL) techniques for Natural Language Processing have been evolving remarkably fast. Recently, the DL advances in language modeling, machine translation, and paragraph understanding are so prominent that the potential of DL in Software Engineering cannot be overlooked, especially in the field of program learning. To facilitate further research and applications of DL in this field, we provide

    更新日期:2020-06-12
  • Generalizing from a Few Examples
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Yaqing Wang; Quanming Yao; James T. Kwok; Lionel M. Ni

    Machine learning has been highly successful in data-intensive applications but is often hampered when the data set is small. Recently, Few-shot Learning (FSL) is proposed to tackle this problem. Using prior knowledge, FSL can rapidly generalize to new tasks containing only a few samples with supervised information. In this article, we conduct a thorough survey to fully understand FSL. Starting from

    更新日期:2020-06-12
  • An Overview of Service Placement Problem in Fog and Edge Computing
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Farah Aït Salaht; Frédéric Desprez; Adrien Lebre

    To support the large and various applications generated by the Internet of Things (IoT), Fog Computing was introduced to complement the Cloud Computing and offer Cloud-like services at the edge of the network with low latency and real-time responses. Large-scale, geographical distribution, and heterogeneity of edge computational nodes make service placement in such infrastructure a challenging issue

    更新日期:2020-06-12
  • Adversarial Examples on Object Recognition
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Alex Serban; Erik Poll; Joost Visser

    Deep neural networks are at the forefront of machine learning research. However, despite achieving impressive performance on complex tasks, they can be very sensitive: Small perturbations of inputs can be sufficient to induce incorrect behavior. Such perturbations, called adversarial examples, are intentionally designed to test the network’s sensitivity to distribution drifts. Given their surprisingly

    更新日期:2020-06-12
  • A Survey on Ethereum Systems Security
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-06-12
    Huashan Chen; Marcus Pendleton; Laurent Njilla; Shouhuai Xu

    Blockchain technology is believed by many to be a game changer in many application domains. While the first generation of blockchain technology (i.e., Blockchain 1.0) is almost exclusively used for cryptocurrency, the second generation (i.e., Blockchain 2.0), as represented by Ethereum, is an open and decentralized platform enabling a new paradigm of computing—Decentralized Applications (DApps) running

    更新日期:2020-06-12
  • Visual Question Generation
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Charulata Patil; Manasi Patwardhan

    Visual question generation (VQG) is an interesting problem that has recently received attention. The task of VQG involves generating meaningful questions based on the input image. It is a multi-modal problem involving image understanding and natural language generation, especially using deep learning methods. VQG can be considered as complementary task of visual question answering. In this article

    更新日期:2020-05-28
  • A Survey and Classification of Software-Defined Storage Systems
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Ricardo Macedo; João Paulo; José Pereira; Alysson Bessani

    The exponential growth of digital information is imposing increasing scale and efficiency demands on modern storage infrastructures. As infrastructure complexity increases, so does the difficulty in ensuring quality of service, maintainability, and resource fairness, raising unprecedented performance, scalability, and programmability challenges. Software-Defined Storage (SDS) addresses these challenges

    更新日期:2020-05-28
  • Real-time Illumination and Visual Coherence for Photorealistic Augmented/Mixed Reality
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    A’Aeshah Alhakamy; Mihran Tuceryan

    A realistically inserted virtual object in the real-time physical environment is a desirable feature in augmented reality (AR) applications and mixed reality (MR) in general. This problem is considered a vital research area in computer graphics, a field that is experiencing ongoing discovery. The algorithms and methods used to obtain dynamic and real-time illumination measurement, estimating, and rendering

    更新日期:2020-05-28
  • Resource Management and Scheduling in Distributed Stream Processing Systems
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Xunyun Liu; Rajkumar Buyya

    Stream processing is an emerging paradigm to handle data streams upon arrival, powering latency-critical application such as fraud detection, algorithmic trading, and health surveillance. Though there are a variety of Distributed Stream Processing Systems (DSPSs) that facilitate the development of streaming applications, resource management and task scheduling is not automatically handled by the DSPS

    更新日期:2020-05-28
  • The Effect of Context on Small Screen and Wearable Device Users’ Performance - A Systematic Review
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Elgİn Akpinar; Yelİz Yeşİlada; Selİm Temİzer

    Small screen and wearable devices play a key role in most of our daily tasks and activities. However, depending on the context, users can easily experience situationally induced impairments and disabilities (SIIDs). Previous studies have defined SIIDs as a new type of impairment in which an able-bodied user’s behaviour is impaired by the context including the characteristics of a device and the environment

    更新日期:2020-05-28
  • A Survey on Fuzzy Deep Neural Networks
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Rangan Das; Sagnik Sen; Ujjwal Maulik

    Deep neural networks are a class of powerful machine learning model that uses successive layers of non-linear processing units to extract features from data. However, the training process of such networks is quite computationally intensive and uses commonly used optimization methods that do not guarantee optimum performance. Furthermore, deep learning methods are often sensitive to noise in data and

    更新日期:2020-05-28
  • Scheduling on Two Types of Resources
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Olivier Beaumont; Louis-Claude Canon; Lionel Eyraud-Dubois; Giorgio Lucarelli; Loris Marchal; Clément Mommessin; Bertrand Simon; Denis Trystram

    The evolution in the design of modern parallel platforms leads to revisit the scheduling jobs on distributed heterogeneous resources. The goal of this survey is to present the main existing algorithms, to classify them based on their underlying principles, and to propose unified implementations to enable their fair comparison, in terms of running time and quality of schedules, on a large set of common

    更新日期:2020-05-28
  • A Survey of Machine Learning Approaches for Student Dropout Prediction in Online Courses
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Bardh Prenkaj; Paola Velardi; Giovanni Stilo; Damiano Distante; Stefano Faralli

    The recent diffusion of online education (both MOOCs and e-courses) has led to an increased economic and scientific interest in e-learning environments. As widely documented, online students have a much higher chance of dropping out than those attending conventional classrooms. It is of paramount interest for institutions, students, and faculty members to find more efficient methodologies to mitigate

    更新日期:2020-05-28
  • On Resilience in Cloud Computing
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Thomas Welsh; Elhadj Benkhelifa

    Cloud infrastructures are highly favoured as a computing delivery model worldwide, creating a strong societal dependence. It is therefore vital to enhance their resilience, providing persistent service delivery under a variety of conditions. Cloud environments are highly complex and continuously evolving. Additionally, the plethora of use-cases ensures requirements for persistent service delivery vary

    更新日期:2020-05-28
  • A Deep Journey into Super-resolution
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-28
    Saeed Anwar; Salman Khan; Nick Barnes

    Deep convolutional networks–based super-resolution is a fast-growing field with numerous practical applications. In this exposition, we extensively compare more than 30 state-of-the-art super-resolution Convolutional Neural Networks (CNNs) over three classical and three recently introduced challenging datasets to benchmark single image super-resolution. We introduce a taxonomy for deep learning–based

    更新日期:2020-05-28
  • Multi-Core Devices for Safety-Critical Systems: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-06
    Jon Perez; Roman Obermaisser; Jaume Abella; Francisco Cazorla; Kim Grüttner; Irune Agirre; Hamidreza Ahmadian; Imanol Allende

    No abstract available.

    更新日期:2020-05-06
  • Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-05
    Bin Qian; Jie Su; Zhenyu Wen; Devki Nandan Jha; Yinhao Li; Yu Guan; Deepak Puthal; Philip James; Renyu Yang; Albert Y. Zomaya; Omer Rana; Lizhe Wang; Maciej Koutny; Rajiv Ranjan

    Machine Learning (ML) and Internet of Things (IoT) are complementary advances: ML techniques unlock complete potentials of IoT with intelligence, and IoT applications increasingly feed data collected by sensors into ML models, thereby employing results to improve their business processes and services. Hence, orchestrating ML pipelines that encompasses model training and implication involved in holistic

    更新日期:2020-05-05
  • Deep Learning on Mobile and Embedded Devices: State-of-the-Art, Challenges and Future Directions
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-04
    Yanjiao Chen; Baolin Zheng; Zihan Zhang; Qian Wang; Chao Shen; Qian Zhang

    No abstract available.

    更新日期:2020-05-04
  • A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-04
    Xinyi Zhou; Reza Zafarani

    The explosive growth in fake news and its erosion to democracy, justice, and public trust has increased the demand for fake news analysis, detection and intervention. This survey comprehensively and systematically reviews fake news research. The survey identifies and specifies fundamental theories across various disciplines, e.g., psychology and social science, to facilitate and enhance the interdisciplinary

    更新日期:2020-05-04
  • Attribute-Based Encryption for Cloud Computing Access Control: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-05-03
    Yinghui Zhang; Robert Deng; Shengmin Xu; Jianfei Sun; Qi Li; Dong Zheng

    Attribute-based encryption (ABE) for cloud computing access control is reviewed in this article. A taxonomy and comprehensive assessment criteria of ABE are first proposed. In the taxonomy, ABE schemes are assorted into key-policy ABE (KP-ABE) schemes, ciphertext-policy ABE (CP-ABE) schemes, anti-quantum ABE schemes and generic constructions. In accordance with functional features, CP-ABE is further

    更新日期:2020-05-03
  • Context-Sensitive Rewriting
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-29
    Salvador Lucas

    The appropriate selection of the arguments of functions that *can be evaluated* in function calls is often useful to improve efficiency, speed, termination behavior, etc. This is essential, e.g., in the conditional if-then-else operator. We can specify this by just associating a set mu(f) of indices of *evaluable arguments* to each function symbol *f*. With *mu(if-then-else)={1}*, only the boolean

    更新日期:2020-04-29
  • A Survey of Multitier Programming
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-28
    Pascal Weisenburger; Johannes Wirth; Guido Salvaneschi

    No abstract available.

    更新日期:2020-04-28
  • Understanding Optical Music Recognition
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-28
    Jorge Calvo-Zaragoza; Jan Hajič Jr.; Alexander Pacha

    For over 50 years, researchers have been trying to teach computers to read music notation, referred to as Optical Music Recognition (OMR). However, this field is still difficult to access for new researchers, especially those without a significant musical background: few introductory materials are available, and furthermore the field has struggled with defining itself and building a shared terminology

    更新日期:2020-04-28
  • A Survey of Learning Causality with Data: Problems and Methods
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-27
    Ruocheng Guo; Lu Cheng; Jundong Li; P. Richard Hahn; Huan Liu

    The era of big data provides researchers with convenient access to copious data. However, we often have little knowledge of such data. The increasing prevalence of massive data is challenging the traditional methods of learning causality because they were developed for the cases with limited amount of data and strong prior causal knowledge. This survey aims to close the gap between big data and learning

    更新日期:2020-04-27
  • Binary Classification Tree of Rigid Error Detection and Correction Techniques
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-27
    Angeliki Kritikakou; Rafail Psiakis; Francky Catthoor; Olivier Sentieys

    Due to technology scaling and harsh environments, a wide range of fault tolerant techniques exists to deal with the error occurrences. Selecting a fault tolerant technique is not trivial, whereas more than the necessary overhead is usually inserted during the system design. To avoid over-designing, it is necessary to in-depth understand the available design options. However, an exhaustive listing is

    更新日期:2020-04-27
  • Survey on Algorithms for Self-Stabilizing Overlay Networks
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-27
    Michael Feldmann; Christian Scheideler; Stefan Schmid

    The maintenance of efficient and robust overlay networks is one of the most fundamental and reoccurring themes in networking. This paper presents a survey of state-of-the-art algorithms to design and repair overlay networks in a distributed manner. In particular, we discuss basic algorithmic primitives to preserve connectivity, review algorithms for the fundamental problem of graph linearization, and

    更新日期:2020-04-27
  • The Future of False information Detection on Social Media: New Perspectives and Trends
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-22
    Bin Guo; Yasan Ding; Lina Yao; Yunji Liang; Zhiwen Yu

    The massive spread of misinformation in social networks has become a global risk, implicitly in?uencing public opinion and threatening social/political development. Misinformation detection (MID) has thus become a surging research topic in recent years. As a promising and rapid developing research feld, we fnd that many e?orts have been paid to new research problems and approaches of MID. Therefore

    更新日期:2020-04-22
  • Paving the Way for NFV Acceleration: A Taxonomy, Survey and Future Directions
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-20
    Xincai Fei; Fangming Liu; Hai Jin; Hongxin Hu

    As a recent innovation, network functions virtualization (NFV), with its core concept of replacing hardware middleboxes with software network functions (NFs) implemented in commodity servers, promises cost savings and flexibility benefits. However, transitioning NFs from special-purpose hardware to commodity servers has turned out to be more challenging than expected, as it inevitably incurs performance

    更新日期:2020-04-20
  • A Survey on Device-Free Indoor Localization and Tracking in the Multi-Resident Environment
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-20
    Kan Ngamakeur; Sira Yongchareon; Jian Yu; Saeed Ur Rehman

    Non-intrusive indoor device-free localization and tracking can bring both convenience and privacy to users compared with traditional solutions such as camera-based surveillance and RFID tag-based tracking. Technologies such as WI-FI, wireless sensor, and infrared have been used to localize and track people living in care homes and office buildings. However, the presence of multiple residents introduces

    更新日期:2020-04-20
  • Foundations, Properties, and Security Applications of Puzzles: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-20
    Isra Mohamed Ali; Maurantonio Caprolu; Roberto Di Pietro

    Cryptographic algorithms have been used not only to create robust ciphertexts, but also to generate cryptograms that, contrary to the classic goal of cryptography, are meant to be broken. These cryptograms, generally called puzzles, require the use of a certain amount of resources to be solved, introducing a time delay and, in general, a cost. These powerful features have made puzzles the core of many

    更新日期:2020-04-20
  • Tools for Reduced Precision Computation: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Stefano Cherubin; Giovanni Agosta

    The use of reduced precision to improve performance metrics such as computation latency and power consumption is a common practice in the embedded systems field. This practice is emerging as a new trend in High Performance Computing (HPC), especially when new error-tolerant applications are considered. However, standard compiler frameworks do not support automated precision customization, and manual

    更新日期:2020-04-16
  • Content Delivery Networks: State of the Art, Trends, and Future Roadmap
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Behrouz Zolfaghari; Gautam Srivastava; Swapnoneel Roy; Hamid R. Nemati; Fatemeh Afghah; Takeshi Koshiba; Abolfazl Razi; Khodakhast Bibak; Pinaki Mitra; Brijesh Kumar Rai

    Recently, Content Delivery Networks (CDN) have become more and more popular. The technology itself is ahead of academic research in this area. Several dimensions of the technology have not been adequately investigated by academia. These dimensions include outline management, security, and standardization. Discovering and highlighting aspects of this technology that may have or have not been covered

    更新日期:2020-04-16
  • A Survey of Network Virtualization Techniques for Internet of Things Using SDN and NFV
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Iqbal Alam; Kashif Sharif; Fan Li; Zohaib Latif; M. M. Karim; Sujit Biswas; Boubakr Nour; Yu Wang

    Internet of Things (IoT) and Network Softwarization are fast becoming core technologies of information systems and network management for the next-generation Internet. The deployment and applications of IoT range from smart cities to urban computing and from ubiquitous healthcare to tactile Internet. For this reason, the physical infrastructure of heterogeneous network systems has become more complicated

    更新日期:2020-04-16
  • Graph Generators: State of the Art and Open Challenges
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Angela Bonifati; Irena Holubová; Arnau Prat-Pérez; Sherif Sakr

    The abundance of interconnected data has fueled the design and implementation of graph generators reproducing real-world linking properties or gauging the effectiveness of graph algorithms, techniques, and applications manipulating these data. We consider graph generation across multiple subfields, such as Semantic Web, graph databases, social networks, and community detection, along with general graphs

    更新日期:2020-04-16
  • Knowledge Transfer in Vision Recognition: A Survey
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Ying Lu; Lingkun Luo; Di Huang; Yunhong Wang; Liming Chen

    In this survey, we propose to explore and discuss the common rules behind knowledge transfer works for vision recognition tasks. To achieve this, we firstly discuss the different kinds of reusable knowledge existing in a vision recognition task, and then we categorize different knowledge transfer approaches depending on where the knowledge comes from and where the knowledge goes. Compared to previous

    更新日期:2020-04-16
  • A Survey of Hierarchical Energy Optimization for Mobile Edge Computing: A Perspective from End Devices to the Cloud
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Peijin Cong; Junlong Zhou; Liying Li; Kun Cao; Tongquan Wei; Keqin Li

    With the development of wireless technology, various emerging mobile applications are attracting significant attention and drastically changing our daily lives. Applications such as augmented reality and object recognition demand stringent delay and powerful processing capability, which exerts enormous pressure on mobile devices with limited resources and energy. In this article, a survey of techniques

    更新日期:2020-04-16
  • A Critical Survey of the Multilevel Method in Complex Networks
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Alan Valejo; Vinícius Ferreira; Renato Fabbri; Maria Cristina Ferreira de Oliveira; Alneu de Andrade Lopes

    Multilevel optimization aims at reducing the cost of executing a target network-based algorithm by exploiting coarsened, i.e., reduced or simplified, versions of the network. There is a growing interest in multilevel algorithms in networked systems, mostly motivated by the urge for solutions capable of handling large-scale networks. Notwithstanding the success of multilevel optimization in a multitude

    更新日期:2020-04-16
  • A Taxonomy of Supervised Learning for IDSs in SCADA Environments
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Jakapan Suaboot; Adil Fahad; Zahir Tari; John Grundy; Abdun Naser Mahmood; Abdulmohsen Almalawi; Albert Y. Zomaya; Khalil Drira

    Supervisory Control and Data Acquisition (SCADA) systems play an important role in monitoring industrial processes such as electric power distribution, transport systems, water distribution, and wastewater collection systems. Such systems require a particular attention with regards to security aspects, as they deal with critical infrastructures that are crucial to organizations and countries. Protecting

    更新日期:2020-04-16
  • A Survey on Renamings of Software Entities
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-16
    Guangjie Li; Hui Liu; Ally S. Nyamawe

    More than 70% of characters in the source code are used to label identifiers. Consequently, identifiers are one of the most important source for program comprehension. Meaningful identifiers are crucial to understand and maintain programs. However, for reasons like constrained schedule, inexperience, and unplanned evolution, identifiers may fail to convey the semantics of the entities associated with

    更新日期:2020-04-16
  • Machine Learning Methods for Data Association in Multi-Object Tracking
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-13
    Patrick Emami; Panos M. Pardalos; Lily Elefteriadou; Sanjay Ranka

    Data association and track-to-track association, two fundamental problems in single-sensor and multi-sensor multi-target tracking, are instances of an NP-hard combinatorial optimization problem known as the multidimensional assignment problem (MDAP). In this work, we argue that viewing multi-target tracking from the perspective of an assignment problem helps to conceptualize the wide variety of data-driven

    更新日期:2020-04-13
  • Touch-dynamics based Behavioural Biometrics on Mobile Devices ? A Review from a Usability and Performance Perspective
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-13
    ELAKKIYA ELLAVARASON; Richard Guest; Farzin Deravi; RAUL SANCHEZ-REILLO; BARBARA CORSETTI

    Over the past few years, there has been an exponential increase in the percentage of people owning and using a smartphone. These devices have sensor-rich touch screens that can capture sensitive biometric features such as keystroke typing and finger swiping patterns. Touch-based behavioural biometrics is a time-based assessment of how a user performs a particular touch task on a mobile device. Several

    更新日期:2020-04-13
  • Homomorphic Encryption for Machine Learning in Medicine and Bioinformatics
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-13
    Alexander Wood; Kayvan Najarian; Delaram Kahrobaei

    No abstract available.

    更新日期:2020-04-13
  • Computation Offloading and Retrieval for Vehicular Edge Computing:Algorithms, Model and Classification
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-04-01
    Azzedine Boukerche; Victor Sotoro

    Thee rapid evolution of mobile devices, their applications, and the amount of data generated by them causes a significant increase in bandwidth consumption, leading to performance drawbacks such as delay and packet loss. Edge Computing offers a solution to these performance drawbacks by extending the cloud paradigm to the edge of the network using capable nodes, such as vehicles or server nodes with

    更新日期:2020-04-01
  • The Landscape of Exascale Research: A Data-Driven Literature Analysis
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-03-13
    Stijn Heldens; Pieter Hijma; Ben Van Werkhoven; Jason Maassen; Adam S. Z. Belloum; Rob V. Van Nieuwpoort

    The next generation of supercomputers will break the exascale barrier. Soon we will have systems capable of at least one quintillion (billion billion) floating-point operations per second (1018 FLOPS). Tremendous amounts of work have been invested into identifying and overcoming the challenges of the exascale era. In this work, we present an overview of these efforts and provide insight into the important

    更新日期:2020-03-13
  • A Survey on Computational Metaphor Processing
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-03-13
    Sunny Rai; Shampa Chakraverty

    In the last decade, the problem of computational metaphor processing has garnered immense attention from the domains of computational linguistics and cognition. A wide panorama of approaches, ranging from a hand-coded rule system to deep learning techniques, have been proposed to automate different aspects of metaphor processing. In this article, we systematically examine the major theoretical views

    更新日期:2020-03-13
  • Attack and System Modeling Applied to IoT, Cloud, and Mobile Ecosystems: Embedding Security by Design
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-03-13
    João B. F. Sequeiros; Francisco T. Chimuco; Musa G. Samaila; Mário M. Freire; Pedro R. M. Inácio

    Over the years, pervasive computing and communication technologies have enabled the emergence of new computing paradigms that have gained importance across a wide spectrum of domains. The three most notable that have witnessed significant advancements and have a solid track record of exponential growth in diverse applications are the Internet of Things (IoT), Cloud, and Mobile Computing. The ubiquity

    更新日期:2020-03-13
  • A Survey of Profit Optimization Techniques for Cloud Providers
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-03-13
    Peijin Cong; Guo Xu; Tongquan Wei; Keqin Li

    As the demand for computing resources grows, cloud computing becomes more and more popular as a pay-as-you-go model, in which the computing resources and services are provided to cloud users efficiently. For cloud providers, the typical goal is to maximize their profits. However, maximizing profits in a highly competitive cloud market is a huge challenge for cloud providers. In this article, a survey

    更新日期:2020-03-13
  • A Survey of Blockchain-Based Strategies for Healthcare
    ACM Comput. Surv. (IF 7.99) Pub Date : 2020-03-13
    Erikson Júlio De Aguiar; Bruno S. Faiçal; Bhaskar Krishnamachari; Jó Ueyama

    Blockchain technology has been gaining visibility owing to its ability to enhance the security, reliability, and robustness of distributed systems. Several areas have benefited from research based on this technology, such as finance, remote sensing, data analysis, and healthcare. Data immutability, privacy, transparency, decentralization, and distributed ledgers are the main features that make blockchain

    更新日期:2020-03-13
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