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  Subjects -> COMPUTER SCIENCE (Total: 1985 journals)
    - ANIMATION AND SIMULATION (29 journals)
    - ARTIFICIAL INTELLIGENCE (98 journals)
    - AUTOMATION AND ROBOTICS (98 journals)
    - CLOUD COMPUTING AND NETWORKS (63 journals)
    - COMPUTER ARCHITECTURE (9 journals)
    - COMPUTER ENGINEERING (9 journals)
    - COMPUTER GAMES (16 journals)
    - COMPUTER PROGRAMMING (23 journals)
    - COMPUTER SCIENCE (1153 journals)
    - COMPUTER SECURITY (45 journals)
    - DATA BASE MANAGEMENT (13 journals)
    - DATA MINING (32 journals)
    - E-BUSINESS (22 journals)
    - E-LEARNING (27 journals)
    - ELECTRONIC DATA PROCESSING (21 journals)
    - IMAGE AND VIDEO PROCESSING (40 journals)
    - INFORMATION SYSTEMS (104 journals)
    - INTERNET (92 journals)
    - SOCIAL WEB (50 journals)
    - SOFTWARE (33 journals)
    - THEORY OF COMPUTING (8 journals)

COMPUTER SCIENCE (1153 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: 12)
Abakós     Open Access   (Followers: 3)
Academy of Information and Management Sciences Journal     Full-text available via subscription   (Followers: 67)
ACM Computing Surveys     Hybrid Journal   (Followers: 23)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 13)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 4)
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: 12)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 3)
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: 9)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 4)
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: 21)
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: 6)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Artificial Neural Systems     Open Access   (Followers: 4)
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: 3)
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 Factors/Ergonomics     Full-text available via subscription   (Followers: 25)
Advances in Human-Computer Interaction     Open Access   (Followers: 19)
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  
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 6)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
Air, Soil & Water Research     Open Access   (Followers: 7)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 10)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 3)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 6)
American Journal of Sensor Technology     Open Access   (Followers: 2)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 5)
Analysis in Theory and Applications     Hybrid Journal  
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 8)
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: 1)
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: 32)
Applied Medical Informatics     Open Access   (Followers: 9)
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: 4)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 118)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 5)
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: 3)
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: 45)
British Journal of Educational Technology     Hybrid Journal   (Followers: 121)
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: 13)
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: 19)
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: 1)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 8)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 13)
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: 28)
Computer     Full-text available via subscription   (Followers: 83)
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: 14)
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)

        1 2 3 4 5 6 | Last

Journal Cover ACM Transactions on Embedded Computing Systems (TECS)
  [SJR: 0.408]   [H-I: 20]   [4 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1539-9087 - ISSN (Online) 1558-3465
   Published by ACM Homepage  [45 journals]
  • Editorial: Cyber Security, IoT, Block Chains—Risks and Opportunities
    • Abstract: Sandeep K. Shukla


      PubDate: Fri, 07 Jul 2017 00:00:00 GMT
       
  • Seamless Vision-assisted Placement Calibration for Wearable Inertial
           Sensors
    • Abstract: Jian Wu, Roozbeh Jafari

      Wearable inertial devices are being widely used in the applications of activity tracking, health care, and professional sports, and their usage is on a rapid rise. Signal processing algorithms for these devices are often designed to work with a known location of the wearable sensor on the body. However, in reality, the wearable sensor may be worn at different body locations due to the user's preference or unintentional misplacement. The calibration of the sensor location is important to ensure that the algorithms operate correctly. In this article, we propose an auto-calibration technique for determining the location of wearables on the body by fusing the 3-axis accelerometer data from the devices and three-dimensional camera (i.e., Kinect) information obtained from the environment.
      PubDate: Fri, 07 Jul 2017 00:00:00 GMT
       
  • Collaborative PCA/DCA Learning Methods for Compressive Privacy
    • Abstract: Sun-Yuan Kung, Thee Chanyaswad, J. Morris Chang, Peiyuan Wu

      In the Internet era, the data being collected on consumers like us are growing exponentially, and attacks on our privacy are becoming a real threat. To better ensure our privacy, it is safer to let the data owner control the data to be uploaded to the network as opposed to taking chance with data servers or third parties. To this end, we propose compressive privacy, a privacy-preserving technique to enable the data creator to compress data via collaborative learning so that the compressed data uploaded onto the Internet will be useful only for the intended utility and not be easily diverted to malicious applications.
      PubDate: Fri, 07 Jul 2017 00:00:00 GMT
       
  • Serial Arithmetic Strategies for Improving FPGA Throughput
    • Abstract: Aaron Landy, Greg Stitt

      Serial arithmetic has been shown to offer attractive advantages in area for field-programmable gate array (FPGA) datapaths but suffers from a significant reduction in throughput compared to traditional bit-parallel designs. In this work, we perform a performance and trade-off analysis that counterintuitively shows that, despite the decreased throughput of individual serial operators, replication of serial arithmetic can provide a 2.1 × average increase in throughput compared to bit-parallel pipelines for common FPGA applications. We complement this analysis with a novel SerDes architecture that enables existing FPGA pipelines to be replaced with serial logic with potentially higher throughput.
      PubDate: Fri, 07 Jul 2017 00:00:00 GMT
       
  • Guest Editorial: Special Issue on Embedded Computing for IoT
    • Abstract: Marilyn Wolf, Jason Xue


      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Preserving Smart Sink-Location Privacy with Delay Guaranteed Routing
           Scheme for WSNs
    • Abstract: Anfeng Liu, Xiao Liu, Zhipeng Tang, Laurence T. Yang, Zili Shao

      A Semi Random Circle routing for mobile Sink joint Ray Routing for data (SRCRR) scheme is proposed for preserving sink-location privacy with a delay guaranteed. In the SRCRR scheme, the data are directionally routed along ray paths and stored at intermediate nodes probabilistically. The Sink moves in a semirandom circular pattern to collect data from the local nodes occasionally, which guarantees that the data will be collected with an acceptable delay and prevents attackers from predicting their locations and movements. The experimental results indicate that the performance of the SRCRR scheme is better than that of the previous schemes.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Distributed Multi-Representative Re-Fusion Approach for Heterogeneous
           Sensing Data Collection
    • Abstract: Anfeng Liu, Xiao Liu, Tianyi Wei, Laurence T. Yang, Seungmin (Charlie) Rho, Anand Paul

      A multi-representative re-fusion (MRRF) approximate data collection approach is proposed in which multiple nodes with similar readings form a data coverage set (DCS). The reading value of the DCS is represented by an R-node. The set near the Sink is smaller, while the set far from the Sink is larger, which can reduce the energy consumption in hotspot areas. Then, a distributed data-aggregation strategy is proposed that can re-fuse the value of R-nodes that are far from each other but have similar readings. Both comprehensive theoretical and experimental results indicate that the MRRF approach increases lifetime and energy efficiency.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Corrections to and Discussion of “Implementation and Evaluation of
           Mixed-criticality Scheduling Approaches for Sporadic Tasks”
    • Abstract: Tom Fleming, Huang-Ming Huang, Alan Burns, Chris Gill, Sanjoy Baruah, Chenyang Lu

      The AMC-IA mixed-criticality scheduling analysis was proposed as an improvement to the AMC-MAX adaptive mixed-criticality scheduling analysis. However, we have identified several necessary corrections to the AMC-IA analysis. In this article, we motivate and describe those corrections, and discuss and illustrate why the corrected AMC-IA analysis cannot be shown to outperform AMC-MAX.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Schedulability of Bounded-Rate Multimode Systems
    • Abstract: Rajeev Alur, Vojtěch Forejt, Salar Moarref, Ashutosh Trivedi

      Bounded-rate multimode systems are hybrid systems that switch freely among a finite set of modes, and whose dynamics are specified by a finite number of real-valued variables with mode-dependent rates that vary within given bounded sets. The scheduler repeatedly proposes a time and a mode, while the environment chooses an allowable rate for that mode; the state of the system changes linearly in the direction of the rate. The scheduler aims to keep the state within a safe set, while the environment aims to leave it.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • An FPGA-Based Architecture for High-Speed Compressed Signal Reconstruction
    • Abstract: Guoxian Huang, Lei Wang

      Compressive Sensing (CS) is an emerging research area that allows efficient signal acquisition under the sub-Nyquist rate while still promising reliable data recovery. However, practical applications of CS in hardware platforms are limited as signal reconstruction is still challenging due to its high computational complexity, especially for autonomous real-time signal recovery. In this article, we propose an algorithmic transformation technique referred to as Matrix Inversion Bypass (MIB) to improve the signal recovery efficiency of the Orthogonal Matching Pursuit (OMP)-based CS reconstruction. The basic idea of MIB is to decouple the computations of intermediate signal estimates and matrix inversions, thereby enabling parallel processing of these two time-consuming operations in the OMP algorithm.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Guest Editorial: Special Issue on “Secure and Fault-Tolerant
           Embedded Computing”
    • Abstract: Dr. Jimson Mathew, Dr. Rajat Subhra Chakraborty, Prof. Dhiraj K. Pradhan


      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Fault-Tolerant Dynamic Task Mapping and Scheduling for
           Network-on-Chip-Based Multicore Platform
    • Abstract: Navonil Chatterjee, Suraj Paul, Santanu Chattopadhyay

      In Network-on-Chip (NoC)-based multicore systems, task allocation and scheduling are known to be important problems, as they affect the performance of applications in terms of energy consumption and timing. Advancement of deep submicron technology has made it possible to scale the transistor feature size to the nanometer range, which has enabled multiple processing elements to be integrated onto a single chip. On the flipside, it has made the integrated entities on the chip more susceptible to different faults. Although a significant amount of work has been done in the domain of fault-tolerant mapping and scheduling, existing algorithms either precompute reconfigured mapping solutions at design time while anticipating fault(s) scenarios or adopt a hybrid approach wherein a part of the fault mitigation strategy relies on the design-time solution.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Petri Net Models and Collaborativeness for Parallel Processes with
           Resource Sharing and Message Passing
    • Abstract: Guanjun Liu, Mengchu Zhou, Changjun Jiang

      Petri nets are widely used to model and analyse concurrent systems. There exist two distinct classes of Petri nets that focus on different features of concurrent systems. The first one features multiple parallel processes sharing a group of common resources but not interacting/collaborating with each other. The second one allows multiple parallel processes to interact/collaborate with each other via message exchange but does not share any common resources. However, in many distributed environments, multiple processes both interact/collaborate with each other and share some common resources. To model and analyse such systems, this article defines a new class of Petri nets called Parallel Process Nets (P2Ns) that may be viewed as a generalization of the two mentioned above.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Efficient Automated Code Partitioning for Microcontrollers with Switchable
           Memory Banks
    • Abstract: Michal Ciszewski, Konrad Iwanicki

      Switching active memory banks at runtime allows a processor with a narrow address bus to access memory that exceeds ranges normally addressable via the bus. Switching code memory banks is regaining interest in microcontrollers for the Internet of Things (IoT), which have to run continuously growing software, while at the same time consuming ultra-small amounts of energy. To make use of bank switching, such software must be partitioned among the available banks and augmented with bank-switching instructions. In contrast to the augmenting, which is done automatically by a compiler, today the partitioning is normally done manually by programmers. However, since IoT software is cross-compiled on much more powerful machines than its target microcontrollers, it becomes possible to partition it automatically during compilation.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • Efficient Kernel Management on GPUs
    • Abstract: Yun Liang, Xiuhong Li

      Graphics Processing Units (GPUs) have been widely adopted as accelerators for compute-intensive applications due to its tremendous computational power and high memory bandwidth. As the complexity of applications continues to grow, each new generation of GPUs has been equipped with advanced architectural features and more resources to sustain its performance acceleration capability. Recent GPUs have been featured with concurrent kernel execution, which is designed to improve the resource utilization by executing multiple kernels simultaneously. However, it is still a challenge to find a way to manage the resources on GPUs for concurrent kernel execution. Prior works only achieve limited performance improvement as they do not optimize the thread-level parallelism (TLP) and model the resource contention for the concurrently executing kernels.
      PubDate: Fri, 26 May 2017 00:00:00 GMT
       
  • ACM Transactions on Embedded Computing Systems (TECS) Volume 16 Issue 4,
           May 2017 (Issue-in-Progress)
    • PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Protecting Caches from Soft Errors: A Microarchitect’s Perspective
    • Abstract: Yohan Ko, Reiley Jeyapaul, Youngbin Kim, Kyoungwoo Lee, Aviral Shrivastava

      Soft error is one of the most important design concerns in modern embedded systems with aggressive technology scaling. Among various microarchitectural components in a processor, cache is the most susceptible component to soft errors. Error detection and correction codes are common protection techniques for cache memory due to their design simplicity. In order to design effective protection techniques for caches, it is important to quantitatively estimate the susceptibility of caches without and even with protections. At the architectural level, vulnerability is the metric to quantify the susceptibility of data in caches. However, existing tools and techniques calculate the vulnerability of data in caches through coarse-grained block-level estimation.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • A Novel Method for Online Detection of Faults Affecting Execution-Time in
           Multicore-Based Systems
    • Abstract: Stefano Esposito, Massimo Violante, Marco Sozzi, Marco Terrone, Massimo Traversone

      This article proposes a bounded interference method, based on statistical evaluations, for online detection and tolerance of any fault capable of causing a deadline miss. The proposed method requires data that can be gathered during the profiling and worst-case execution time (WCET) analysis phase. This article describes the method, its application, and then it presents an avionic mixed-criticality use case for experimental evaluation, considering both dual-core and quad-core platforms.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Area, Throughput, and Power Trade-Offs for FPGA- and ASIC-Based Execution
           Stream Compression
    • Abstract: Maria Isabel Mera, Jonah Caplan, Seyyed Hasan Mozafari, Brett H. Meyer, Peter Milder

      An emerging trend in safety-critical computer system design is the use of compression—for example, using cyclic redundancy check (CRC) or Fletcher checksum (FC)—to reduce the state that must be compared to verify correct redundant execution. We examine the costs and performance of CRC and FC as compression algorithms when implemented in hardware for embedded safety-critical systems. To do so, we have developed parameterizable hardware-generation tools targeting CRC and two novel FC implementations. We evaluate the resulting designs implemented for FPGA and ASIC and analyze their efficiency. While CRC is often best, FC dominates when high throughput is needed.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Formal Model-Based Synthesis of Application-Specific Static RTOS
    • Abstract: Kabland Toussaint Gautier Tigori, Jean-Luc Béchennec, Sébastien Faucou, Olivier Henri Roux

      In an embedded system, the specialization of the code of the real-time operating system (RTOS) according to the requirements of the application allows one to remove unused services and other sources of dead code from the binary program. The typical specialization process is based on a mix of precompiler macros and build scripts, both of which are known for being sources of errors. In this article, we present a new model-based approach to the design of application-specific RTOS. Starting with finite state models describing the RTOS and the application requirements, the set of blocks in the RTOS code actually used by the application is automatically computed.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • The Perfect Getaway: Using Escape Analysis in Embedded Real-Time Systems
    • Abstract: Isabella Stilkerich, Clemens Lang, Christoph Erhardt, Christian Bay, Michael Stilkerich

      The use of a managed, type-safe language such as Java in real-time and embedded systems offers productivity and, in particular, safety and dependability benefits at a reasonable cost. It has been shown for commodity systems that Escape Analysis (EA) enables a set of useful optimizations, and benefits from the properties of a type-safe language. In this article, we explore the application of escape analysis in KESO [Stilkerich et al. 2012], a Java ahead-of-time compiler targeting embedded real-time systems.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • PMC: A Requirement-Aware DRAM Controller for Multicore Mixed Criticality
           Systems
    • Abstract: Mohamed Hassan, Hiren Patel, Rodolfo Pellizzoni

      We propose a novel approach to schedule memory requests in Mixed Criticality Systems (MCS). This approach supports an arbitrary number of criticality levels by enabling the MCS designer to specify memory requirements per task. It retains locality within large-size requests to satisfy memory requirements of all tasks. To achieve this target, we introduce a compact time-division-multiplexing scheduler, and a framework that constructs optimal schedules to manage requests to off-chip memory. We also present a static analysis that guarantees meeting requirements of all tasks. We compare the proposed controller against state-of-the-art memory controllers using both a case study and synthetic experiments.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Refining Cache Behavior Prediction Using Cache Miss Paths
    • Abstract: Kartik Nagar, Y. N. Srikant

      Worst-Case Execution Time (WCET) is an important metric for programs running on real-time systems, and finding precise estimates of a program’s WCET is crucial to avoid wastage of hardware resources and to improve the schedulability of task sets. Caches have a major impact on a program’s execution time, and accurate estimation of a program’s cache behavior can lead to significant reduction in its estimated WCET. The traditional approach to cache analysis generally targets the worst-case cache behavior of individual cache accesses and provides a safe hit-miss classification for every individual access. In this work, we show that these classifications are not sufficient to precisely capture cache behavior, since they apply to individual accesses, and often, more precise predictions can be made about groups of accesses.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Automatic Synthesis of Switching Controllers for Linear Hybrid Systems:
           Reachability Control
    • Abstract: Massimo Benerecetti, Marco Faella

      We consider the problem of computing the controllable region of a Linear Hybrid Automaton with controllable and uncontrollable transitions, w.r.t. a reachability objective. We provide an algorithm for the finite-horizon version of the problem, based on computing the set of states that must reach a given non-convex polyhedron while avoiding another one, subject to a polyhedral constraint on the slope of the trajectory. Experimental results are presented, based on an implementation of the proposed algorithm on top of the tool SpaceEx.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Task Transition Scheduling for Data-Adaptable Systems
    • Abstract: Nathan Sandoval, Casey Mackin, Sean Whitsitt, Vijay Shankar Gopinath, Sachidanand Mahadevan, Andrew Milakovich, Kyle Merry, Jonathan Sprinkle, Roman Lysecky

      Data-adaptable embedded systems operate on a variety of data streams, which requires a large degree of configurability and adaptability to support runtime changes in data stream inputs. Data-adaptable reconfigurable embedded systems, when decomposed into a series of tasks, enable a flexible runtime implementation in which a system can transition the execution of certain tasks between hardware and software while simultaneously continuing to process data during the transition. Efficient runtime scheduling of task transitions is needed to optimize system throughput and latency of the reconfiguration and transition periods. In this article, we provide an overview of a runtime framework enabling the efficient transition of tasks between software and hardware in response to changes in system inputs.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Real-Time Simulation Support for Runtime Verification of Cyber-Physical
           Systems
    • Abstract: Xi Zheng, Christine Julien, Hongxu Chen, Rodion Podorozhny, Franck Cassez

      In Cyber-Physical Systems (CPS), cyber and physical components must work seamlessly in tandem. Runtime verification of CPS is essential yet very difficult, due to deployment environments that are expensive, dangerous, or simply impossible to use for verification tasks. A key enabling factor of runtime verification of CPS is the ability to integrate real-time simulations of portions of the CPS into live running systems. We propose a verification approach that allows CPS application developers to opportunistically leverage real-time simulation to support runtime verification. Our approach, termed BraceBind, allows selecting, at runtime, between actual physical processes or simulations of them to support a running CPS application.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Dynamic Power and Energy Management for Energy Harvesting Nonvolatile
           Processor Systems
    • Abstract: Kaisheng Ma, Xueqing Li, Huichu Liu, Xiao Sheng, Yiqun Wang, Karthik Swaminathan, Yongpan Liu, Yuan Xie, John Sampson, Vijaykrishnan Narayanan

      Self-powered systems running on scavenged energy will be a key enabler for pervasive computing across the Internet of Things. The variability of input power in energy-harvesting systems limits the effectiveness of static optimizations aimed at maximizing the input-energy-to-computation ratio. We show that the resultant gap between available and exploitable energy is significant, and that energy storage optimizations alone do not significantly close the gap. We characterize these effects on a real, fabricated energy-harvesting system based on a nonvolatile processor. We introduce a unified energy-oriented approach to first optimize the number of backups, by more aggressively using the stored energy available when power failure occurs, and then optimize forward progress via improving the rate of input energy to computation via dynamic voltage and frequency scaling and self-learning techniques.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Lightweight Architectures for Reliable and Fault Detection Simon and Speck
           Cryptographic Algorithms on FPGA
    • Abstract: Prashant Ahir, Mehran Mozaffari-Kermani, Reza Azarderakhsh

      The widespread use of sensitive and constrained applications necessitates lightweight (low-power and low-area) algorithms developed for constrained nano-devices. However, nearly all of such algorithms are optimized for platform-based performance and may not be useful for diverse and flexible applications. The National Security Agency (NSA) has proposed two relatively recent families of lightweight ciphers, that is, Simon and Speck, designed as efficient ciphers on both hardware and software platforms. This article proposes concurrent error detection schemes to provide reliable architectures for these two families of lightweight block ciphers. The research work on analyzing the reliability of these algorithms and providing fault diagnosis approaches has not been undertaken to date to the best of our knowledge.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • Exploiting Multiple Write Modes of Nonvolatile Main Memory in Embedded
           Systems
    • Abstract: Chen Pan, Mimi Xie, Chengmo Yang, Yiran Chen, Jingtong Hu

      Existing Nonvolatile Memories (NVMs) have many attractive features to be the main memory of embedded systems. These features include low power, high density, and better scalability. Recently, Multilevel Cell (MLC) NVM has gained more and more popularity as it can provide a higher density than the traditional Single-Level Cell (SLC) NVM. However, there are also drawbacks in MLC NVM, namely, limited write endurance and expensive write operation. These two drawbacks have to be overcome before MLC NVM can be practically adopted as the main memory. In MLC Nonvolatile Main Memory (NVMM), two different types of write operations with very diverse data retention times are allowed.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • WCET-Aware Function-Level Dynamic Code Management on Scratchpad Memory
    • Abstract: Yooseong Kim, David Broman, Aviral Shrivastava

      Scratchpad memory (SPM) is a promising on-chip memory choice in real-time and cyber-physical systems where timing is of the utmost importance. SPM has time-predictable characteristics since its data movement between the SPM and the main memory is entirely managed by software. One way of such management is dynamic management. In dynamic management of instruction SPMs, code blocks are dynamically copied from the main memory to the SPM at runtime by executing direct memory access (DMA) instructions. Code management techniques try to minimize the overhead of DMA operations by finding an allocation scheme that leads to efficient utilization. In this article, we present three function-level code management techniques.
      PubDate: Thu, 11 May 2017 00:00:00 GMT
       
  • A Load-Balancing Divide-and-Conquer SVM Solver
    • Abstract: Xiaogang Chen, Z. Jane Wang, Xiangyang Ji

      Scaling up kernel support vector machine (SVM) training has been an important topic in recent years. Despite its theoretical elegance, training kernel SVM is impractical when facing millions of data. The divide-and-conquer (DC) strategy is a natural framework of handling gigantic problems, and the divide-and-conquer solver for kernel SVM (DC-SVM) is able to train kernel SVM with millions of data with limited time cost. However, there are some drawbacks of the DC-SVM approach. First, it used an unsupervised clustering method to partition the whole problem, which is prone to construct singular subsets, and, second, it is hard to balance the computation load between sub-problems.
      PubDate: Tue, 09 May 2017 00:00:00 GMT
       
  • Parallel Sparse Subspace Clustering via Joint Sample and Parameter
           Blockwise Partition
    • Abstract: Bo Liu, Xiao-Tong Yuan, Yang Yu, Qingshan Liu, Dimitris N. Metaxas

      Sparse subspace clustering (SSC) is a classical method to cluster data with specific subspace structure for each group. It has many desirable theoretical properties and has been shown to be effective in various applications. However, under the condition of a large-scale dataset, learning the sparse sample affinity graph is computationally expensive. To tackle the computation time cost challenge, we develop a memory-efficient parallel framework for computing SSC via an alternating direction method of multiplier (ADMM) algorithm. The proposed framework partitions the data matrix into column blocks and then decomposes the original problem into parallel multivariate Lasso regression subproblems and samplewise operations.
      PubDate: Tue, 09 May 2017 00:00:00 GMT
       
  • Low-Cost Standard Signatures for Energy-Harvesting Wireless Sensor
           Networks
    • Abstract: Giuseppe Ateniese, Giuseppe Bianchi, Angelo T. Capossele, Chiara Petrioli, Dora Spenza

      This work is motivated by a general question: can micro-scale energy-harvesting techniques be exploited to support low-cost standard security solutions on resource-constrained devices? We focus on guaranteeing integrity and authentication in Internet of Things (IoT) and Wireless Sensor Network (WSN) applications. In this article, we propose techniques to make ECDSA signatures low cost and implementable on resource-constrained devices. By combining precomputation techniques and energy-harvesting capabilities of modern sensor nodes, we achieve significant improvement over prior works. In addition, we show that the cost of ECDSA signatures can be reduced by up to a factor 10 by using harvesting-aware optimizations.
      PubDate: Fri, 28 Apr 2017 00:00:00 GMT
       
  • Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in
           Intermittently-Powered IoT Devices
    • Abstract: Hrishikesh Jayakumar, Arnab Raha, Jacob R. Stevens, Vijay Raghunathan

      Forecasts project that by 2020, there will be around 50 billion devices connected to the Internet of Things (IoT), most of which will operate untethered and unplugged. While environmental energy harvesting is a promising solution to power these IoT edge devices, it introduces new complexities due to the unreliable nature of ambient energy sources. In the presence of an unreliable power supply, frequent checkpointing of the system state becomes imperative, and recent research has proposed the concept of in-situ checkpointing by using ferroelectric RAM (FRAM), an emerging non-volatile memory technology, as unified memory in these systems. Even though an entirely FRAM-based solution provides reliability, it is energy inefficient compared to SRAM due to the higher access latency of FRAM.
      PubDate: Fri, 28 Apr 2017 00:00:00 GMT
       
  • Axiom: DTLS-Based Secure IoT Group Communication
    • Abstract: Marco Tiloca, Kirill Nikitin, Shahid Raza

      This article presents Axiom, a DTLS-based approach to efficiently secure multicast group communication among IoT-constrained devices. Axiom provides an adaptation of the DTLS record layer, relies on key material commonly shared among the group members, and does not require one to perform any DTLS handshake. We made a proof-of-concept implementation of Axiom based on the tinyDTLS library for the Contiki OS and used it to experimentally evaluate performance of our approach on real IoT hardware. Results show that Axiom is affordable on resource-constrained platforms and performs significantly better than related alternative approaches.
      PubDate: Fri, 28 Apr 2017 00:00:00 GMT
       
  • A PUF-Based Secure Communication Protocol for IoT
    • Abstract: Urbi Chatterjee, Rajat Subhra Chakraborty, Debdeep Mukhopadhyay

      Security features are of paramount importance for the Internet of Things (IoT), and implementations are challenging given the resource-constrained IoT setup. We have developed a lightweight identity-based cryptosystem suitable for IoT to enable secure authentication and message exchange among the devices. Our scheme employs a Physically Unclonable Function (PUF) to generate the public identity of each device, which is used as the public key for each device for message encryption. We have provided formal proofs of security in the Session Key Security and Universally Composable Framework of the proposed protocol, which demonstrates the resilience of the scheme against passive and active attacks.
      PubDate: Fri, 28 Apr 2017 00:00:00 GMT
       
  • Data-Driven Synchronization for Internet-of-Things Systems
    • Abstract: Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari

      The Internet of Things (IoT) is fueled by the growth of sensors, actuators, and services that collect and process raw sensor data. Wearable and environmental sensors will be a major component of the IoT and provide context about people and activities that are occurring. It is imperative that sensors in the IoT are synchronized, which increases the usefulness and value of the sensor data and allows data from multiple sources to be combined and compared. Due to the heterogeneous nature of sensors (e.g., synchronization protocols, communication channels, etc.) , synchronization can be difficult. In this article, we present novel techniques for synchronizing data from multi-sensor environments based on the events and interactions measured by the sensors.
      PubDate: Fri, 28 Apr 2017 00:00:00 GMT
       
  • A Multi-Quadcopter Cooperative Cyber-Physical System for Timely Air
           Pollution Localization
    • Abstract: Zhaoyan Shen, Zhijian He, Shuai Li, Qixin Wang, Zili Shao

      We propose a cyber-physical system of unmanned quadcopters to locate air pollution sources in a timely manner. The system consists of a physical part and a cyber part. The physical part includes unmanned quadcopters equipped with multiple sensors. The cyber part carries out control laws. We simplify the control laws by decoupling the quadcopters’ horizontal-plane motion control from vertical motion control. To control the quadcopter’s horizontal-plane motions, we propose a controller that combines pollutant dynamics with quadcopter physics. To control the quadcopter’s vertical motions, we adopt an anti-windup proportional-integral (PI) controller. We further extend the horizontal-plane control laws from a single quadcopter to multiple quadcopters.
      PubDate: Fri, 28 Apr 2017 00:00:00 GMT
       
  • Guest Editorial for ACM TECS Special Issue on Effective
           Divide-and-Conquer, Incremental, or Distributed Mechanisms of Embedded
           Designs for Extremely Big Data in Large-Scale Devices
    • Abstract: Bo-Wei Chen, Wen Ji, Zhu Li


      PubDate: Fri, 28 Apr 2017 00:00:00 GMT
       
  • Hardware Architectures for Embedded Speaker Recognition Applications: A
           Survey
    • Abstract: Hasna Bouraoui, Chadlia Jerad, Anupam Chattopadhyay, Nejib Ben Hadj-Alouane

      Authentication technologies based on biometrics, such as speaker recognition, are attracting more and more interest thanks to the elevated level of security offered by these technologies. Despite offering many advantages, such as remote use and low vulnerability, speaker recognition applications are constrained by the heavy computational effort and the hard real-time constraints. When such applications are run on an embedded platform, the problem becomes more challenging, as additional constraints inherent to this specific domain are added. In the literature, different hardware architectures were used/designed for implementing a process with a focus on a given particular metric. In this article, we give a survey of the state-of-the-art works on implementations of embedded speaker recognition applications.
      PubDate: Fri, 28 Apr 2017 00:00:00 GMT
       
  • On Space Utilization Enhancement of File Systems for Embedded Storage
           Systems
    • Abstract: Tseng-Yi Chen, Yuan-Hao Chang, Shuo-Han Chen, Nien-I Hsu, Hsin-Wen Wei, Wei-Kuan Shih

      Since the mid-2000s, mobile/embedded computing systems conventionally have limited computing power, Random Access Memory (RAM) space, and storage capacity due to the consideration of their cost, energy consumption, and physical size. Recently, some of these systems, such as mobile phone and embedded consumer electronics, have more powerful computing capability, so they manage their data in small flash storage devices (e.g., Embedded Multi Media Card (eMMC) and Secure Digital (SD) cards) with a simple file system. However, the existing file systems usually have low space utilization for managing small files and the tail data of large files. In this work, we thus propose a dynamic tail packing scheme to enhance the space utilization of file systems over flash storage devices in embedded computing systems by dynamically aggregating/packing the tail data of (small) files together.
      PubDate: Tue, 11 Apr 2017 00:00:00 GMT
       
  • DMS-Based Energy Optimizations for Clustered WSNs
    • Abstract: Maryam Bandari, Robert Simon, Hakan Aydin

      In this article, we consider clustered wireless sensor networks where the nodes harvest energy from the environment. We target performance-sensitive applications that have to collectively send their information to a cluster head by a predefined deadline. The nodes are equipped with Dynamic Modulation Scaling (DMS)-capable wireless radios. DMS provides a tuning knob, allowing us to trade off communication latency with energy consumption. We consider two optimization objectives, maximizing total energy reserves and maximizing the minimum energy level across all nodes. For both objectives, we show that optimal solutions can be obtained by solving Mixed Integer Linear Programming problems.
      PubDate: Tue, 11 Apr 2017 00:00:00 GMT
       
  • Fault-Tolerant Preemptive Aperiodic RT Scheduling by Supervisory Control
           of TDES on Multiprocessors
    • Abstract: Rajesh Devaraj, Arnab Sarkar, Santosh Biswas

      Safety-critical real-time systems must meet stringent timing and fault-tolerance requirements. This article proposes a methodology for synthesizing an optimal preemptive multiprocessor aperiodic task scheduler using a formal supervisory control framework. The scheduler can tolerate single/multiple permanent processor faults. Further, the synthesis framework has been empowered with a novel BDD-based symbolic computation mechanism to control the exponential state-space complexity of the optimal exhaustive enumeration-oriented synthesis methodology.
      PubDate: Tue, 11 Apr 2017 00:00:00 GMT
       
  • LiBrA-CAN: Lightweight Broadcast Authentication for Controller Area
           Networks
    • Abstract: Bogdan Groza, Stefan Murvay, Anthony Van Herrewege, Ingrid Verbauwhede

      Despite realistic concerns, security is still absent from vehicular buses such as the widely used Controller Area Network (CAN). We design an efficient protocol based on efficient symmetric primitives, taking advantage of two innovative procedures: splitting keys between nodes and mixing authentication tags. This results in a higher security level when compromised nodes are in the minority, a realistic assumption for automotive networks. Experiments are performed on state-of-the-art Infineon TriCore controllers, contrasted with low-end Freescale S12X cores, while simulations are provided for the recently released CAN-FD standard.
      PubDate: Thu, 06 Apr 2017 00:00:00 GMT
       
  • ACM Transactions on Embedded Computing Systems (TECS) Volume 16 Issue 3,
           March 2017 (Issue-in-Progress)
    • PubDate: Tue, 28 Mar 2017 00:00:00 GMT
       
  • AdaFT: A Framework for Adaptive Fault Tolerance for Cyber-Physical Systems
    • Abstract: Ye Xu, Israel Koren, C. Mani Krishna

      Cyber-physical systems (CPS) frequently have to use massive redundancy to meet application requirements for high reliability. While such redundancy is required, it can be activated adaptively, based on the current state of the controlled plant. Most of the time, the plant is in a state that allows for a lower level of fault tolerance. Avoiding the continuous deployment of massive fault tolerance will greatly reduce the workload of the CPS, and lower the operating temperature of the cyber sub-system, thus increasing its reliability. In this article, we extend our prior research by demonstrating a software simulation framework Adaptive Fault Tolerance (AdaFT) that can automatically generate the sub-spaces within which our adaptive fault tolerance can be applied.
      PubDate: Tue, 28 Mar 2017 00:00:00 GMT
       
  • Accelerators for Breast Cancer Detection
    • Abstract: Daniele Jahier Pagliari, Mario R. Casu, Luca P. Carloni

      Algorithms used in microwave imaging for breast cancer detection require hardware acceleration to speed up execution time and reduce power consumption. In this article, we present the hardware implementation of two accelerators for two alternative imaging algorithms that we obtain entirely from SystemC specifications via high-level synthesis. The two algorithms present opposite characteristics that stress the design process and the capabilities of commercial HLS tools in different ways: the first is communication bound and requires overlapping and pipelining of communication and computation in order to maximize the application throughput; the second is computation bound and uses complex mathematical functions that HLS tools do not directly support.
      PubDate: Tue, 28 Mar 2017 00:00:00 GMT
       
  • On Static Binary Translation of ARM/Thumb Mixed ISA Binaries
    • Abstract: Jiunn-Yeu Chen, Wuu Yang, Wei-Chung Hsu, Bor-Yeh Shen, Quan-Huei Ou

      Code discovery has been a main challenge for static binary translation, especially when the source instruction set architecture has variable-length instructions, such as the x86 architectures. Due to embedded data such as PC (program counter)-relative data, jump tables, or paddings in the code section, a binary translator may be misled to translate data as instructions. For variable-length instructions, once a piece of data is mis-translated as instructions, decoding subsequent bytes could also go wrong. We are concerned with static binary translation for the very popular Advanced RISC Machine (ARM) architectures. Although ARM is considered a reduced instruction set computer architecture, it does allow the mix of 32-bit (ARM) instructions and 16-bit (Thumb) instructions in the same executables.
      PubDate: Tue, 28 Mar 2017 00:00:00 GMT
       
  • An Indoor Test Methodology for Solar-Powered Wireless Sensor Networks
    • Abstract: Wilson M. Tan, Paul Sullivan, Hamish Watson, Joanna Slota-Newson, Stephen A. Jarvis

      Repeatable and accurate tests are important when designing hardware and algorithms for solar-powered wireless sensor networks (WSNs). Since no two days are exactly alike with regard to energy harvesting, tests must be carried out indoors. Solar simulators are traditionally used in replicating the effects of sunlight indoors; however, solar simulators are expensive, have lighting elements that have short lifetimes, and are usually not designed to carry out the types of tests that hardware and algorithm designers require. As a result, hardware and algorithm designers use tests that are inaccurate and not repeatable (both for others and also for the designers themselves).
      PubDate: Tue, 28 Mar 2017 00:00:00 GMT
       
  • Configurable Detection of SDC-causing Errors in Programs
    • Abstract: Qining Lu, Guanpeng Li, Karthik Pattabiraman, Meeta S. Gupta, Jude A. Rivers

      Silent Data Corruption (SDC) is a serious reliability issue in many domains, including embedded systems. However, current protection techniques are brittle and do not allow programmers to trade off performance for SDC coverage. Further, many require tens of thousands of fault-injection experiments, which are highly time- and resource-intensive. In this article, we propose two empirical models, SDCTune and SDCAuto, to predict the SDC proneness of a program’s data. Both models are based on static and dynamic features of the program alone and do not require fault injections to be performed. The main difference between them is that SDCTune requires manual tuning while SDCAuto is completely automated, using machine-learning algorithms.
      PubDate: Tue, 28 Mar 2017 00:00:00 GMT
       
 
 
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