Search results

Information-centric networking (ICN) is an innovative paradigm for the future internet architecture. This paper aims to provide a view on how academic video lectures can exploit the ICN paradigm. It discusses the design of academic video lectures over named data networking (NDN) (an ICN architecture) and speculates their future development. To the best of author’s knowledge, a similar study has not been presented.

The paper is a visionary essay that introduces the background, elaborates the basic concepts and presents the author’s views and insights into academic video lectures that exploit the latest development of NDN approach and its applications.

The ICN paradigm is closely related to the levels of automation and large-scale uptake of multimedia applications that provide video lectures. Academic video lectures over NDN have: improved efficiency, better scalability with respect to information/bandwidth demand and better robustness in challenging communication scenarios. A framework of academic video lectures over NDN must take into account various key issues such as naming (name resolution), optimized routing, resource control, congestion control, security and privacy. The size of the network in which academic video lectures are distributed, the content location dynamics and the popularity of the stored video lectures will determine which routing scheme must be selected. If semantic information is included into academic video lectures, the network dynamically may assist video (streaming) lecture service by permitting the network to locate the proper version of the requested video lecture that can be better delivered to e-learners and/or select the appropriate network paths.

The paper helps researchers already working on video lectures in finding a direction for designing and deploying platforms that will provide content-centric academic video lectures.

The paper pioneers the investigation of academic video lecture distribution in ICN and presents an in-depth view to its potentials and research trends.

Named Data Networking (NDN) is a content-centric network differing from the traditional IP-based network. It adopts the name prefix to identify, query and route the information content instead of IP-based addressing and routing. NDN provides a convenient way to access the content without knowing the originated location of the requested information. However, the length of name prefix varies. It is not like the fixed-length IP addresses that makes handling queries or searching the requested information in NDN easier. An efficient name lookup mechanism of name prefix will efficiently increase the performance of prefix identifying, name searching and content retrieving. Therefore, this paper aims to propose a partial name prefix merging and shortening scheme for enhancing the efficiency of name lookup in NDN.

To reduce the work involved in name prefix identifying, querying, storing and routing, this work adopts a cyclic redundancy check-based encoding scheme to shorten the variable length of the name prefix into a proper and fixed length of encoded numerical information. In fact, the structure of a name prefix is presented in a combination of word segments with the slash symbol. The shortening procedure of name prefix can also be applied to adjacent word segments forming fixed-length encoded data for further efficiently matching the name prefix for name lookup in NDN.

The experimental results show that the shorter length of encoded name prefix can effectively reduce the access time of name lookup and increasingly retrieve the corresponding named content in NDN. Through partial merging and shortening of name prefix, the length of encoded prefix name may be larger than the whole encoding of name prefix. It retains the information differences from different parts of various name prefixes. Thus, it can avoid collision problems with the same encoded information from various name prefixes.

From the experimental results, it is observed that partial merging and shortening of name prefix is useful for name look up in NDN. It can increase the efficiency of name prefix matching and retrieving in NDN. It can also save memory space to store the name prefix in an NDN node.

The purpose of this paper is to measure the degree of interdisciplinary collaboration in Big Data research based on the co-occurrences of subject categories using Stirling’s diversity index and specialization index.

Interdisciplinarity was measured utilizing the descriptive statistics of disciplines, network indicators showing relationships between disciplines and within individual disciplines, interdisciplinary communities, Stirling’s diversity index and specialization index, and a strategic diagram revealing the development status and trends of discipline communities.

Comprehensively considering all results, the degree of interdisciplinarity of Big Data research is increasing over time, particularly, after 2013. There is a high level of interdisciplinarity in Big Data research involving a large number of disciplines, but it is unbalanced in distribution. The interdisciplinary collaborations are not intensive on the whole; most disciplines are aggregated into a few distinct communities with computer science, business and economics, mathematics, and biotechnology and applied microbiology as the core. Four major discipline communities in Big Data research represent different directions with different development statuses and trends. Community 1, with computer science as the core, is the most mature and central to the whole interdisciplinary network. Accounting for all network indicators, computer science, engineering, business and economics, social sciences, and mathematics are the most important disciplines in Big Data research.

This study deepens our understanding of the degree and trend of interdisciplinary collaboration in Big Data research through a longitudinal study and quantitative measures based on two indexes. It has practical implications to study and reveal the interdisciplinary phenomenon and characteristics of related developments of a specific research area, or to conduct comparative studies between different research areas.

The purpose of this paper is to understand the emerging challenges of cybersecurity governance by analyzing the internet’s early history.

Tracing the design and management of early internet and network security technologies in the USA in the 1970s and 1980s.

The US Department of Defense separated the research and management regimes for networks and network security, with the latter restricted to military networks. As such, the absence of cybersecurity technologies on the early internet was not an oversight, but a necessary compromise. This ordering of networks and security had enduring technological, political and even cultural consequences, which are breaking down today.

Political, technological and metaphoric distinctions between networks and security should be challenged; cybersecurity will transform internet governance.

New historical sources and analysis provide a novel perspective on contemporary challenges of cybersecurity governance.

The purpose of this paper is to minimize energy usage by maximizing network life in the creation of applications and protocols

This paper presents a novel methodology for optimum energy consumption in wireless sensor networks. The proposed methodology introduces some protocols and logarithms that effectively contributed to reducing energy consumption in these types of networks.

The results of that comparison showed the ability of those logarithms and protocols to reduce that energy but in varying proportions. It can be concluded that a significant reduction in energy consumption approximately 50% could be obtained by the proposed methodology.

Here, a novel methodology for optimum energy consumption in wireless sensor networks has been introduced.

The purpose of this paper is to identify and analyze the key uncertainties and to construct alternative future scenarios for Internet content delivery. The relative positions and roles of different actors and content delivery technologies in each scenario are then discussed. As traffic volume rapidly grows, the current Internet architecture faces scalability issues. To meet the demand, technical solutions utilizing caching and name-based routing are developed.

This work followed a scenario planning process, and two workshops were organized for identifying the key trends and uncertainties. Industry architecture notation was used to systematically illustrate and compare the constructed scenarios.

Of the 94 forces identified, the revenue model and Internet service provider's (ISP’s) role in content provision were singled out as the two most important uncertainties, upon which four scenarios were constructed. In-network caching technologies are strong candidates in ISP-dominated scenarios. Content delivery networks are more likely outcomes in scenarios, where content providers’ role is significant.

The paper focuses on qualitative analysis of scenarios. Utilizing, for instance, system dynamics to model interdependencies between the trends and uncertainties could provide a path toward quantitative analysis.

The paper increases understanding of relative positions and roles of different actors and technologies in possible future scenarios. The findings are important, especially for ISPs, content providers and technology vendors. The scenarios can be used to identify desirable futures and strategies to achieve them and to make informed choices in technology design to meet the demands of key actors.

Crypto-currencies, decentralized electronic currencies systems, denote a radical change in financial exchange and economy environment. Consequently, it would be attractive for designers and policy-makers in this area to make out what social media users think about them on Twitter. The purpose of this study is to investigate the social opinions about different kinds of crypto-currencies and tune the best-customized classification technique to categorize the tweets based on sentiments.

This paper utilized a lexicon-based approach for analyzing the reviews on a wide range of crypto-currencies over Twitter data to measure positive, negative or neutral sentiments; in addition, the end result of sentiments played a training role to train a supervised technique, which can predict the sentiment loading of tweets about the main crypto-currencies.

The findings further prove that more than 50 per cent of people have positive beliefs about crypto-currencies. Furthermore, this paper confirms that marketers can predict the sentiment of tweets about these crypto-currencies with high accuracy if they use appropriate classification techniques like support vector machine (SVM).

Considering the growing interest in crypto-currencies (Bitcoin, Cardano, Ethereum, Litcoin and Ripple), the findings of this paper have a remarkable value for enterprises in the financial area to obtain the promised benefits of social media analysis at work. In addition, this paper helps crypto-currencies vendors analyze public opinion in social media platforms. In this sense, the current paper strengthens our understanding of what happens in social media for crypto-currencies.

For managers and decision-makers, this paper suggests that the news and campaign for their crypto in Twitter would affect people’s perspectives in a good manner. Because of this fact, the firms, investing in these crypto-currencies, could apply the social media as a magnifier for their promotional activities. The findings steer the market managers to see social media as a predictor tool, which can analyze the market through understanding the opinions of users of Twitter.

While there is a large volume of entrepreneurial social capital research, the philosophical assumptions have received limited attention. The purpose of this paper is to review and classify entrepreneurial social capital studies according to the following approaches – objectivist (positivist-realist, structuralist) and subjectivist (social constructionist). There is a neglect of structure and agency, and the authors encourage a critical realist approach that permits an understanding of observable network structure, constraint-order and human agency as a dynamic system.

The ontological and epistemological assumptions, and associated strengths and weaknesses of objectivist (positivist-realist, structuralist) and subjectivist (social constructionist) entrepreneurial social capital studies are discussed. The case for a more progressive critical realist approach is developed.

The authors demonstrate that objectivist (positivist-realist, structuralist) research with findings bereft of situated meaning and agency dominates. The emergence of subjectivist research – narratively examining different network situations from the perspective of those embedded in networks – is an emerging and competing approach. This dualism is unlikely to comprehensively understand the complex system-level properties of social capital. Future research should adopt critical realism and fuse: objective data to demonstrate the material aspects of network structures and what structural social capital exists in particular settings; and subjective data that enhances an understanding of situated meaning, agency and intention in a network.

This paper contributes a review of entrepreneurial social capital research and philosophical foundations. The development of a critical realist approach to understanding social capital gestation permits a system-level analysis of network structure influencing conduct, and agency.

Social media, especially microblog, has become one of the most popular platforms for public opinion dissemination. However, so far few studies have been conducted to explore information dissemination under the mobile environment. This paper aims to introduce the approach to analyze the public opinion information dissemination in mobile social networks.

This paper chooses “network attack” as the research topic and extracts 23,567 relevant messages from Sina Microblogs to study the structure of nodes for public opinion dissemination and the characteristics of propagation paths on mobile internet. Public opinion dissemination is compared on both mobile and non-mobile terminals.

The results reveal the characteristics of public opinion dissemination in mobile environment and identify three patterns of information propagation path. This study concludes that public opinion on mobile internet propagates more widely and efficiently and generates more impact than that on the non-mobile internet.

The methods used in this study can be useful for the government and other organizations to analyze and identify problems in online information dissemination.

This paper explores the mechanism of public opinion dissemination on mobile internet in China and further investigates how to improve public opinion management through a case study related to “network attack.”

Blockchain is evolving to become a platform for securing Internet of things (IoT) ecosystems. Still, challenges remain. The purpose of this literature review is to highlight the applicability of blockchain as a medium to secure IoT ecosystems. A two-dimensional framework anchored on (1) IoT layers and (2) security goals is used to organize the existent IoT security threats and their corresponding countermeasures identified in the reviewed literature. The framework helped in mapping the IoT security threats with the inherent features of blockchain and accentuate their prominence to IoT security.

An approach integrating computerized natural language processing (NLP) with a systematic literature review methodology was adopted. A large corpus of 2,303 titles and abstracts of blockchain articles was programmatically analyzed in order to identify the relevant literature. The identified literature was subjected to a systematic review guided by a well-established method in IS research.

The literature evidently highlights the prominence of blockchain as a mean to IoT security due to the distinctive features it encompasses. The authors’ investigation revealed that numerous existent threats are better addressed with blockchain than conventional mechanisms. Nevertheless, blockchain consumes resources such as electricity, time, bandwidth and disk space at a rate that is not yet easily accessible to common IoT ecosystems.

Results suggest that a configurational approach that aligns IoT security requirements with the resource requirements of different blockchain features is necessary in order to realize the proper balance between security, efficiency and feasibility.

Practitioners can make use of the classified lists of convention security mechanisms and the IoT threats they address. The framework can help underline the countermeasures that best achieve their security goals. Practitioners can also use the framework to identify the most important features to seek for in a blockchain technology that can help them achieve their security goals.

This study proposes a novel framework that can help classify IoT threats based on the IoT layer impacted and the security goal at risk. Moreover, it applies a combined man-machine approach to systematically analyze the literature.