scholarly journals The Programmable Data Plane: Abstractions, Architectures, Algorithms, and Applications

2020 ◽  
Author(s):  
Oliver Michel ◽  
Roberto Bifulco ◽  
Gábor Rétvári ◽  
Stefan Schmid
Keyword(s):  
Network Services ◽  
Future Research ◽  
Next Generation ◽  
Low Level ◽  
Design And Implementation ◽  
The Past ◽  
Data Plane ◽  
Recent Trends ◽  
Key Driver ◽  
Processing Steps

<div><div>Programmable data plane technology enables the systematic reconfiguration of the low-level processing steps applied to network packets and is a key driver in realizing the next generation of network services and applications. This survey presents recent trends and issues in the design and implementation of programmable network devices, focusing on prominent architectures, abstractions, algorithms, and applications proposed, debated, and realized over the past years. We elaborate on the trends that led to the emergence of this technology and highlight the most important pointers from the literature, casting different taxonomies for the field and identifying avenues for future research.</div></div>

scholarly journals The Programmable Data Plane: Abstractions, Architectures, Algorithms, and Applications

2020 ◽  
Author(s):  
Oliver Michel ◽  
Roberto Bifulco ◽  
Gábor Rétvári ◽  
Stefan Schmid
Keyword(s):  
Network Services ◽  
Future Research ◽  
Next Generation ◽  
Low Level ◽  
Design And Implementation ◽  
The Past ◽  
Data Plane ◽  
Recent Trends ◽  
Key Driver ◽  
Processing Steps

<div><div>Programmable data plane technology enables the systematic reconfiguration of the low-level processing steps applied to network packets and is a key driver in realizing the next generation of network services and applications. This survey presents recent trends and issues in the design and implementation of programmable network devices, focusing on prominent architectures, abstractions, algorithms, and applications proposed, debated, and realized over the past years. We elaborate on the trends that led to the emergence of this technology and highlight the most important pointers from the literature, casting different taxonomies for the field and identifying avenues for future research.</div></div>

scholarly journals The Programmable Data Plane

2021 ◽  
Vol 54 (4) ◽  
pp. 1-36
Author(s):  
Oliver Michel ◽  
Roberto Bifulco ◽  
Gábor Rétvári ◽  
Stefan Schmid
Keyword(s):  
Network Services ◽  
Future Research ◽  
Next Generation ◽  
Low Level ◽  
Design And Implementation ◽  
The Past ◽  
Data Plane ◽  
Recent Trends ◽  
Key Drivers ◽  
Processing Steps

Programmable data plane technologies enable the systematic reconfiguration of the low-level processing steps applied to network packets and are key drivers toward realizing the next generation of network services and applications. This survey presents recent trends and issues in the design and implementation of programmable network devices, focusing on prominent abstractions, architectures, algorithms, and applications proposed, debated, and realized over the past years. We elaborate on the trends that led to the emergence of this technology and highlight the most important pointers from the literature, casting different taxonomies for the field, and identifying avenues for future research.

scholarly journals Deep Learning for Cyber Security Applications: A Comprehensive Survey

2021 ◽  
Author(s):  
vinayakumar R ◽  
Mamoun Alazab ◽  
Soman KP ◽  
Sriram Srinivasan ◽  
Sitalakshmi Venkatraman ◽  
...  
Keyword(s):  
Deep Learning ◽  
Language Processing ◽  
Cyber Security ◽  
Smart Cities ◽  
Critical Discussion ◽  
Future Research ◽  
Next Generation ◽  
Security Applications ◽  
The Past ◽  
Comprehensive Survey

Deep Learning (DL), a novel form of machine learning (ML) is gaining much research interest due to its successful application in many classical artificial intelligence (AI) tasks as compared to classical ML algorithms (CMLAs). Recently, DL architectures are being innovatively modelled for diverse applications in the area of cyber security. The literature is now growing with DL architectures and their variations for exploring different innovative DL models and prototypes that can be tailored to suit specific cyber security applications. However, there is a gap in literature for a comprehensive survey reporting on such research studies. Many of the survey-based research have a focus on specific DL architectures and certain types of malicious attacks within a limited cyber security problem scenario of the past and lack futuristic review. This paper aims at providing a well-rounded and thorough survey of the past, present, and future DL architectures including next-generation cyber security scenarios related to intelligent automation, Internet of Things (IoT), Big Data (BD), Blockchain, cloud and edge technologies. <br>This paper presents a tutorial-style comprehensive review of the state-of-the-art DL architectures for diverse applications in cyber security by comparing and analysing the contributions and challenges from various recent research papers. Firstly, the uniqueness of the survey is in reporting the use of DL architectures for an extensive set of cybercrime detection approaches such as intrusion detection, malware and botnet detection, spam and phishing detection, network traffic analysis, binary analysis, insider threat detection, CAPTCHA analysis, and steganography. Secondly, the survey covers key DL architectures in cyber security application domains such as cryptography, cloud security, biometric security, IoT and edge computing. Thirdly, the need for DL based research is discussed for the next generation cyber security applications in cyber physical systems (CPS) that leverage on BD analytics, natural language processing (NLP), signal and image processing and blockchain technology for smart cities and Industry 4.0 of the future. Finally, a critical discussion on open challenges and new proposed DL architecture contributes towards future research directions.

scholarly journals Deep Learning for Cyber Security Applications: A Comprehensive Survey

2021 ◽  
Author(s):  
vinayakumar R ◽  
Mamoun Alazab ◽  
Soman KP ◽  
Sriram Srinivasan ◽  
Sitalakshmi Venkatraman ◽  
...  
Keyword(s):  
Deep Learning ◽  
Language Processing ◽  
Cyber Security ◽  
Smart Cities ◽  
Critical Discussion ◽  
Future Research ◽  
Next Generation ◽  
Security Applications ◽  
The Past ◽  
Comprehensive Survey

Deep Learning (DL), a novel form of machine learning (ML) is gaining much research interest due to its successful application in many classical artificial intelligence (AI) tasks as compared to classical ML algorithms (CMLAs). Recently, DL architectures are being innovatively modelled for diverse applications in the area of cyber security. The literature is now growing with DL architectures and their variations for exploring different innovative DL models and prototypes that can be tailored to suit specific cyber security applications. However, there is a gap in literature for a comprehensive survey reporting on such research studies. Many of the survey-based research have a focus on specific DL architectures and certain types of malicious attacks within a limited cyber security problem scenario of the past and lack futuristic review. This paper aims at providing a well-rounded and thorough survey of the past, present, and future DL architectures including next-generation cyber security scenarios related to intelligent automation, Internet of Things (IoT), Big Data (BD), Blockchain, cloud and edge technologies. <br>This paper presents a tutorial-style comprehensive review of the state-of-the-art DL architectures for diverse applications in cyber security by comparing and analysing the contributions and challenges from various recent research papers. Firstly, the uniqueness of the survey is in reporting the use of DL architectures for an extensive set of cybercrime detection approaches such as intrusion detection, malware and botnet detection, spam and phishing detection, network traffic analysis, binary analysis, insider threat detection, CAPTCHA analysis, and steganography. Secondly, the survey covers key DL architectures in cyber security application domains such as cryptography, cloud security, biometric security, IoT and edge computing. Thirdly, the need for DL based research is discussed for the next generation cyber security applications in cyber physical systems (CPS) that leverage on BD analytics, natural language processing (NLP), signal and image processing and blockchain technology for smart cities and Industry 4.0 of the future. Finally, a critical discussion on open challenges and new proposed DL architecture contributes towards future research directions.

Past evolution and recent trends in accounting research

2017 ◽  
pp. 51-60
Author(s):  
Annalisa Prencipe
Keyword(s):  
A Priori ◽  
Future Research ◽  
Positive Approach ◽  
Accounting Research ◽  
Current Accounting ◽  
Accounting Practice ◽  
The Past ◽  
Recent Trends ◽  
Empirical Tests ◽  
Tests Of Hypotheses

Research in accounting is relatively young compared to other disciplines. Originally, normative research based on a priori reasoning and aimed at improving accounting practice was predominant among accounting scholars. After the 60's, accounting academics started using an empirical positive approach, aimed to better understand accounting phenomena through empirical tests of hypotheses. As from then, research in accounting has gone through several changes in terms of approaches, research methods and topics. This paper aims at highlighting the main stages of the past evolution and recent trends in accounting research. After describing the main drivers of the shift from normative to positive approach, the dominant traits that have characterized accounting research for the last two decades are briefly analyzed. Particular emphasis is put on methods and topics. In the last section, the main limitations of current accounting research are highlighted, and some directions for future research are outlined.

scholarly journals Mixed Reality: A Bridge or a Fusion Between Two Worlds?

10.5334/bck.i ◽  
2021 ◽  
pp. 93-103
Author(s):  
Mafkereseb Kassahun Bekele
Keyword(s):  
Virtual Reality ◽  
Real World ◽  
Interaction Design ◽  
Mixed Reality ◽  
Future Research ◽  
The Real ◽  
Design And Implementation ◽  
The Past ◽  
Virtual Reconstruction ◽  
Microsoft Hololens

Virtual heritage (VH) is one of the few domains to adopt immersive reality technologies at early stages, with a significant number of studies employing the technologies for various application themes. More specifically, virtual reality has persisted as a de facto immersive reality technology for virtual reconstruction and virtual museums. In recent years, however, mixed reality (MxR) has attracted attention from the VH community following the introduction of new devices, such as Microsoft HoloLens, to the technological landscape of immersive reality. Two variant perceptions of MxR have been observed in the literature over the past two decades. First, MxR is perceived as an umbrella/collective term for a virtual reality (VR) and augmented reality (AR) environment. Second, it is also presented as a distinctive form of immersive reality that enables merging virtual elements with their real-world counterparts. These perceptions influence our choice of immersive reality technology, interaction design, and implementation, and the overall objective of VH applications. To address these concerns, this chapter attempts to answer two critical questions: (1) what MxR from VH perspective is and (2) whether MxR is just a form of immersive reality that serves as a bridge to connect the real world with a virtual one or a fusion of both that neither the real nor the virtual world would have meaning without a contextual relationship and interaction with each other. To this end, this chapter will review VH applications and literature from the past few years and identify how MxR is presented. It will also suggest how the VH community can benefit from MxR and discuss limitations in existing technology and identify some areas and direction for future research in the domain.

scholarly journals “What? So What”: The Next-Generation JHOVE2 Architecture for Format-Aware Characterization

2009 ◽  
Vol 4 (3) ◽  
pp. 123-136 ◽  
Author(s):  
Stephen Abrams ◽  
Sheila Morrissey ◽  
Tom Cramer
Keyword(s):  
Feature Extraction ◽  
Digital Library ◽  
Digital Information ◽  
Stanford University ◽  
Next Generation ◽  
Digital Object ◽  
Design And Implementation ◽  
The Past ◽  
Digital File ◽  
Preservation Repositories

The JHOVE characterization framework is widely used by international digital library programs and preservation repositories. However, its extensive use over the past four years has revealed a number of limitations imposed by idiosyncrasies of design and implementation. With funding from the Library of Congress under its National Digital Information Infrastructure Preservation Program (NDIIPP), the California Digital Library, Portico, and Stanford University are collaborating on a two-year project to develop and deploy a next-generation architecture providing enhanced performance, streamlined APIs, and significant new features. The JHOVE2 Project generalizes the concept of format characterization to include identification, validation, feature extraction, and policy-based assessment. The target of this characterization is not a simple digital file, but a (potentially) complex digital object that may be instantiated in multiple files.

scholarly journals Product Diversification in Sustainability Transition: The Forest-Based Bioeconomy in Finland

2019 ◽  
Vol 11 (12) ◽  
pp. 3293
Author(s):  
Jukka Luhas ◽  
Mirja Mikkilä ◽  
Ville Uusitalo ◽  
Lassi Linnanen
Keyword(s):  
Narrative Analysis ◽  
Economies Of Scale ◽  
Construction Material ◽  
Product Diversification ◽  
Future Research ◽  
Network Development ◽  
The Past ◽  
Dominant Market Position ◽  
Recent Trends ◽  
Lock In

The forest-based bioproduct field has diversified into the chemical, medical, energy, nanoproduct, and construction material sectors. This paper argues that forest-based bioeconomy has kept the focus on conventional products and new bioproducts have primarily been developed as extensions to existing product portfolios due to a lock-in mechanism, i.e., a state where an economy gradually locks itself to a dominant market position due to technical interrelatedness, economies of scale, and quasi-irreversibility of investment. The study examines forest-based product transition in the context of lock-in mechanisms through narrative analysis over the past 170 years. A theoretical framework is formulated based on complex system studies and the economics of lock-in mechanisms. The relation between the lock-in mechanisms of the regime and product diversification is described for the forest-based bioeconomy in Finland. The study supports previous findings indicating that interactions occur between the lock-in mechanisms. Furthermore, lock-in mechanisms can have a neutral, adverse, or beneficial effect on product diversification. The paper extends knowledge about the role and functioning of lock-in mechanisms in changing market environments. Recent trends in network development and foreign investment, and their effects on industrial symbiosis and product diversification, is recommendable to consider in future research.

Old-growth forest reserves in Slovenia: the past, present, and future

2012 ◽  
Vol 163 (6) ◽  
pp. 240-246 ◽  
Author(s):  
Thomas A. Nagel ◽  
Jurij Diaci ◽  
Dusan Rozenbergar ◽  
Tihomir Rugani ◽  
Dejan Firm
Keyword(s):  
Stand Structure ◽  
Growth Conditions ◽  
Ecosystem Functions ◽  
Future Research ◽  
Old Growth ◽  
Forest Reserves ◽  
The Past ◽  
Old Growth Forest ◽  
Forest Remnants ◽  
Basic Characteristics

Old-growth forest reserves in Slovenia: the past, present, and future Slovenia has a small number of old-growth forest remnants, as well as many forest reserves approaching old-growth conditions. In this paper, we describe some of the basic characteristics of these old-growth remnants and the history of their protection in Slovenia. We then trace the long-term development of research in these old-growth remnants, with a focus on methodological changes. We also review some of the recent findings from old-growth research in Slovenia and discuss future research needs. The conceptual understanding of how these forests work has slowly evolved, from thinking of them in terms of stable systems to more dynamic and unpredictable ones due to the influence of natural disturbances and indirect human influences. In accordance with this thinking, the methods used to study old-growth forests have changed from descriptions of stand structure to studies that address natural processes and ecosystem functions.

Chinese Medicine Protein and Peptide in Gene and Cell Therapy

2019 ◽  
Vol 20 (3) ◽  
pp. 251-264 ◽  
Author(s):  
Yinlu Feng ◽  
Zifei Yin ◽  
Daniel Zhang ◽  
Arun Srivastava ◽  
Chen Ling
Keyword(s):  
Chinese Medicine ◽  
Cell Therapy ◽  
Future Research ◽  
The Past ◽  
Promising Strategy ◽  
Wide Range ◽  
New Directions ◽  
Gene And Cell Therapy ◽  
Proteins And Peptides

The success of gene and cell therapy in clinic during the past two decades as well as our expanding ability to manipulate these biomaterials are leading to new therapeutic options for a wide range of inherited and acquired diseases. Combining conventional therapies with this emerging field is a promising strategy to treat those previously-thought untreatable diseases. Traditional Chinese medicine (TCM) has evolved for thousands of years in China and still plays an important role in human health. As part of the active ingredients of TCM, proteins and peptides have attracted long-term enthusiasm of researchers. More recently, they have been utilized in gene and cell therapy, resulting in promising novel strategies to treat both cancer and non-cancer diseases. This manuscript presents a critical review on this field, accompanied with perspectives on the challenges and new directions for future research in this emerging frontier.

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