A Novel Refreshment Circuit for 2T1M Neuromorphic Synapse

2021 ◽  
pp. 2250047
Author(s):  
Mai M. Goda ◽  
Ahmed H. Hassan ◽  
Hassan Mostafa ◽  
Ahmed M. Soliman
Keyword(s):  
Matrix Multiplication ◽  
Computing System ◽  
Signal Shape ◽  
Circuit Element ◽  
Computing Systems ◽  
Ion Drift ◽  
Weight Value ◽  
Correct Weight ◽  
Main Components ◽  
Memristor Synapse

Neuromorphic systems are the future computing systems to overcome the von Neumann’s power consumption and latency wall between memory and processing units. The two main components of any neuromorphic computing system are neurons and synapses. Synapses carry the weight of the system to be multiplied by the neuromorphic attributes, which represent the features of the task to be solved. Memristor (memoryresistor) is the most suitable circuit element to act as a synapse. Its ability to store, update and do matrix multiplication in nanoscale die area makes it very useful in neuromorphic synapses. One of the most popular memristor synapse configurations is the two-transistor–one-memristor (2T1M) synapse. This configuration is very useful in neuromorphic synapses for its ability to control reading and updating the weight on a chip by signals. The main problem with this synapse is that the reading operation is destructive, which results in changing the stored weight value. In this paper, a novel refreshment circuit is proposed to restore the correct weight in case of any destructive reading operations. The circuit makes a small interrupt time during operation without disconnecting the memristor, which makes the circuit very practical. The circuit has been simulated by using hardware-calibrated CMOS TSMC 130[Formula: see text]nm technology on Cadence Virtuoso and linear ion drift memristor Verilog-A model. The proposed circuit achieves the refreshment task accurately for several error types. It is used to refresh 2T1M synapse with any destructive reading signal shape.

scholarly journals Evaluating the E-Health Cloud Computing Systems Adoption in Taiwan’s Healthcare Industry

Life ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 310
Author(s):  
Shih-Chia Chang ◽  
Ming-Tsang Lu ◽  
Tzu-Hui Pan ◽  
Chiao-Shan Chen
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Multiple Criteria Decision Making ◽  
Cloud Service ◽  
Computing System ◽  
Healthcare Industry ◽  
Computing Systems ◽  
Factors Affecting ◽  
Cloud Computing System ◽  
Health Cloud

Although the electronic health (e-health) cloud computing system is a promising innovation, its adoption in the healthcare industry has been slow. This study investigated the adoption of e-health cloud computing systems in the healthcare industry and considered security functions, management, cloud service delivery, and cloud software for e-health cloud computing systems. Although numerous studies have determined factors affecting e-health cloud computing systems, few comprehensive reviews of factors and their relations have been conducted. Therefore, this study investigated the relations between the factors affecting e-health cloud computing systems by using a multiple criteria decision-making technique, in which decision-making trial and evaluation laboratory (DEMATEL), DANP (DEMATEL-based Analytic Network Process), and modified VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) approaches were combined. The intended level of adoption of an e-health cloud computing system could be determined by using the proposed approach. The results of a case study performed on the Taiwanese healthcare industry indicated that the cloud management function must be primarily enhanced and that cost effectiveness is the most significant factor in the adoption of e-health cloud computing. This result is valuable for allocating resources to decrease performance gaps in the Taiwanese healthcare industry.

scholarly journals A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5458
Author(s):  
Sangjun Kim ◽  
Kyung-Joon Park
Keyword(s):  
Machine Learning ◽  
Physical System ◽  
Large Scale ◽  
Computing System ◽  
Future Research ◽  
Physical Security ◽  
Computing Systems ◽  
Physical Systems ◽  
Security Research ◽  
Simultaneous Control

A cyber-physical system (CPS) is the integration of a physical system into the real world and control applications in a computing system, interacting through a communications network. Network technology connecting physical systems and computing systems enables the simultaneous control of many physical systems and provides intelligent applications for them. However, enhancing connectivity leads to extended attack vectors in which attackers can trespass on the network and launch cyber-physical attacks, remotely disrupting the CPS. Therefore, extensive studies into cyber-physical security are being conducted in various domains, such as physical, network, and computing systems. Moreover, large-scale and complex CPSs make it difficult to analyze and detect cyber-physical attacks, and thus, machine learning (ML) techniques have recently been adopted for cyber-physical security. In this survey, we provide an extensive review of the threats and ML-based security designs for CPSs. First, we present a CPS structure that classifies the functions of the CPS into three layers: the physical system, the network, and software applications. Then, we discuss the taxonomy of cyber-physical attacks on each layer, and in particular, we analyze attacks based on the dynamics of the physical system. We review existing studies on detecting cyber-physical attacks with various ML techniques from the perspectives of the physical system, the network, and the computing system. Furthermore, we discuss future research directions for ML-based cyber-physical security research in the context of real-time constraints, resiliency, and dataset generation to learn about the possible attacks.

scholarly journals Flexible computation offloading in a fuzzy-based mobile edge orchestrator for IoT applications

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
VanDung Nguyen ◽  
Tran Trong Khanh ◽  
Tri D. T. Nguyen ◽  
Choong Seon Hong ◽  
Eui-Nam Huh
Keyword(s):  
Cloud Computing ◽  
Augmented Reality ◽  
Mobile Devices ◽  
Computing System ◽  
Mobile User ◽  
Computation Offloading ◽  
Context Aware ◽  
Computing Systems ◽  
Iot Applications ◽  
Service Times

AbstractIn the Internet of Things (IoT) era, the capacity-limited Internet and uncontrollable service delays for various new applications, such as video streaming analysis and augmented reality, are challenges. Cloud computing systems, also known as a solution that offloads energy-consuming computation of IoT applications to a cloud server, cannot meet the delay-sensitive and context-aware service requirements. To address this issue, an edge computing system provides timely and context-aware services by bringing the computations and storage closer to the user. The dynamic flow of requests that can be efficiently processed is a significant challenge for edge and cloud computing systems. To improve the performance of IoT systems, the mobile edge orchestrator (MEO), which is an application placement controller, was designed by integrating end mobile devices with edge and cloud computing systems. In this paper, we propose a flexible computation offloading method in a fuzzy-based MEO for IoT applications in order to improve the efficiency in computational resource management. Considering the network, computation resources, and task requirements, a fuzzy-based MEO allows edge workload orchestration actions to decide whether to offload a mobile user to local edge, neighboring edge, or cloud servers. Additionally, increasing packet sizes will affect the failed-task ratio when the number of mobile devices increases. To reduce failed tasks because of transmission collisions and to improve service times for time-critical tasks, we define a new input crisp value, and a new output decision for a fuzzy-based MEO. Using the EdgeCloudSim simulator, we evaluate our proposal with four benchmark algorithms in augmented reality, healthcare, compute-intensive, and infotainment applications. Simulation results show that our proposal provides better results in terms of WLAN delay, service times, the number of failed tasks, and VM utilization.

The Parallel Digital Differential Analyzer and its Application as a Hybrid Computing System Element

SIMULATION ◽  
1965 ◽  
Vol 4 (2) ◽  
pp. 104-116 ◽  
Author(s):  
Otto A. Reichardt ◽  
Merlin W. Hoyt ◽  
W. Thad Lee
Keyword(s):  
Differential Equations ◽  
Nonlinear Differential Equations ◽  
Computing System ◽  
Unique Combination ◽  
Computing Systems ◽  
Hybrid Computing ◽  
Hybrid Element ◽  
Speed Accuracy ◽  
Differential Analyzer ◽  
Digital Computers

TRICE hybrid computing systems are currently in volved in aerospace simulations that are interesting and sophisticated. Indeed it would seem that these applications are so successful that an increasing wave of interest can be expected in such DDA applications. Unlike earlier DDA's, the parallel digital differential analyzer, we believe, combines more of the best fea tures of analog and digital machines: It boasts speed, accuracy, and ease of programming. Because the machine itself is entirely digital, it couples naturally and inexpensively with convention al digital computers. Unlike other digital machines with central memory and sequential operation, all elements of this DDA operate simultaneously, thus providing rapid solutions to nonlinear differential equations characteristic of analog computers. And like its analog cousin, our DDA is programmed read ily via a patchboard, by connecting its computing elements in direct correspondence to the elements of differential equations. In one sense, TRICE is more properly a hybrid— a unique combination of analog and digital machine characteristics—than are the combinations of analog and digital computers currently being interfaced. Yet it can also be connected with analog and/or digital computers. Here we would like to explain how TRICE works, compare its advantages as a hybrid element, and con clude with a review of some current applications.

scholarly journals Scheduling under Open stack – The Current State and Future Enhancements

2019 ◽  
Vol 8 (2) ◽  
pp. 375-382
Keyword(s):  
Cloud Computing ◽  
Open Source ◽  
Task Scheduling ◽  
Computing System ◽  
Important Task ◽  
Shared Resources ◽  
Computing Systems ◽  
Current State ◽  
Cloud Computing System ◽  
Research Findings

Cloud computing is being heavily used for implementing different kinds of applications. Many of the client applications are being migrated to cloud for the reasons of cost and elasticity. Cloud computing is generally implemented on distributing computing wherein the Physical servers are heavily distributed considering both hardware and software, the connectivity among which is established through Internet. The cloud computing systems as such have many physical servers which contain many resources. The resources can be made to be shared among many users who are the tenants to the cloud computing system. The resources can be virtualized so as to provide shared resources to the clients. Scheduling is one of the most important task of a cloud computing system which is concerned with task scheduling, resource scheduling and scheduling Virtual Machin Migration. It is important to understand the issue of scheduling within a cloud computing system more in-depth so that any improvements with reference to scheduling can be investigated and implemented. For carrying in depth research, an OPEN source based cloud computing system is needed. OPEN STACK is one such OPEN source based cloud computing system that can be considered for experimenting the research findings that are related to cloud computing system. In this paper an overview on the way the Scheduling aspect per say has been implemented within OPEN STACK cloud computing system

Dynamic Control of Computation Consistency in the Parallel Dataflow Computing System

2021 ◽  
Vol 27 (12) ◽  
pp. 625-633
Author(s):  
N. N. Levchenko ◽  
◽  
D. N. Zmejev ◽  
Keyword(s):  
Computational Model ◽  
High Performance ◽  
Dynamic Control ◽  
Computing System ◽  
Computational Process ◽  
Computing Systems ◽  
Systems Software ◽  
Dataflow Computing

When developing high-performance multiprocessor computing systems, much attention is paid to ensuring uninterrupted operation, both in terms of hardware and software. In traditional computing systems, software is the main focus in address­ing these issues. The article discusses the solution to the issue of ensuring uninterrupted operation for the parallel dataflow computing system (PDCS), which implements the dataflow computational model with a dynamically formed context. Due to the features of the PDCS, it is proposed to implement this type of control in hardware, which will increase its efficiency, since the computational process will be controlled in dynamics, and not only in statics.

Mobile Healthcare Computing in the Cloud

2014 ◽  
pp. 275-294 ◽  
Author(s):  
Tae-Gyu Lee
Keyword(s):  
Information Management ◽  
Wearable Computing ◽  
Computing System ◽  
Healthcare Services ◽  
Data Generation ◽  
Computing Environment ◽  
Computing Systems ◽  
Mobile Healthcare ◽  
Data Capacity ◽  
Generation Cycle

Previous medical services for humans provided healthcare information using the static-based computing of space-constrained hospitals or healthcare centers. In contrast, current mobile health information management computing and services are being provided so that they utilize both the mobility of mobile computing and the scalability of cloud computing to monitor in real-time the health status of patients who are moving. In addition, data capacity has sharply increased with the expansion of the principal data generation cycle from the traditional static computing environment to the dynamic computing environment. This chapter presents mobile cloud healthcare computing systems that simultaneously leverage the portability and scalability of healthcare services. This chapter also presents the wearable computing system as an application of mobile healthcare.

Design of Wearable Computing Systems for Future Industrial Environments

2011 ◽  
pp. 1226-1245
Author(s):  
Pierre Kirisci ◽  
Ernesto Morales Kluge ◽  
Emanuel Angelescu ◽  
Klaus-Dieter Thoben
Keyword(s):  
Mobile Computing ◽  
Design Process ◽  
Reference Model ◽  
Wearable Computing ◽  
Computing System ◽  
Context Aware ◽  
Context Model ◽  
Computing Systems ◽  
Model Driven ◽  
Industrial Environments

During the last two decades a lot of methodology research has been conducted for the design of software user interfaces (Kirisci, Thoben 2009). Despite the numerous contributions in this area, comparatively few efforts have been dedicated to the advancement of methods for the design of context-aware mobile platforms, such as wearable computing systems. This chapter investigates the role of context, particularly in future industrial environments, and elaborates how context can be incorporated in a design method in order to support the design process of wearable computing systems. The chapter is initiated by an overview of basic research in the area of context-aware mobile computing. The aim is to identify the main context elements which have an impact upon the technical properties of a wearable computing system. Therefore, we describe a systematic and quantitative study of the advantages of context recognition, specifically task tracking, for a wearable maintenance assistance system. Based upon the experiences from this study, a context reference model is proposed, which can be considered supportive for the design of wearable computing systems in industrial settings, thus goes beyond existing context models, e.g. for context-aware mobile computing. The final part of this chapter discusses the benefits of applying model-based approaches during the early design stages of wearable computing systems. Existing design methods in the area of wearable computing are critically examined and their shortcomings highlighted. Based upon the context reference model, a design approach is proposed through the realization of a model-driven software tool which supports the design process of a wearable computing system while taking advantage of concise experience manifested in a well-defined context model.

Security Issues in Distributed Computing System Models

2017 ◽  
pp. 211-259 ◽  
Author(s):  
Ghada Farouk Elkabbany ◽  
Mohamed Rasslan
Keyword(s):  
Distributed Systems ◽  
Distributed Computing ◽  
Computing System ◽  
Computing Environment ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Research Directions ◽  
System Models ◽  
Security Issues ◽  
Systems Security

Distributed computing systems allow homogenous/heterogeneous computers and workstations to act as a computing environment. In this environment, users can uniformly access local and remote resources in order to run processes. Users are not aware of which computers their processes are running on. This might pose some complicated security problems. This chapter provides a security review of distributed systems. It begins with a survey about different and diverse definitions of distributed computing systems in the literature. Different systems are discussed with emphasize on the most recent. Finally, different aspects of distributed systems security and prominent research directions are explored.

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