Complex Network Information Exchange in Random Wireless Environments

2012 ◽  
Author(s):  
Andrea J. Goldsmith ◽  
Stephen Boyd ◽  
H. V. Poor ◽  
Yonina Eldar
Keyword(s):  
Complex Network ◽  
Information Exchange ◽  
Network Information ◽  
Wireless Environments ◽  
Network Information Exchange

ONIX: Open Radio Network Information eXchange

2021 ◽  
Vol 59 (10) ◽  
pp. 14-20
Author(s):  
Estefania Coronado ◽  
Francesco Raviglione ◽  
Marco Malinverno ◽  
Claudio Casetti ◽  
Ana Cantarero ◽  
...  
Keyword(s):  
Information Exchange ◽  
Radio Network ◽  
Network Information ◽  
Network Information Exchange

scholarly journals Design of IEC-61968-Based Distribution Network Information Exchange Interface

2011 ◽  
Vol 24 ◽  
pp. 69-77 ◽  
Author(s):  
Li Guo ◽  
Gao Li-Ke ◽  
Chen Bo ◽  
Huang Hai-Long ◽  
Li Yong-Gang ◽  
...  
Keyword(s):  
Information Exchange ◽  
Distribution Network ◽  
Network Information ◽  
Network Information Exchange

Enhanced Routing Schedule - Imbalanced Classification Algorithm for IOT based Software Defined Networks

2021 ◽  
Vol 8 (1) ◽  
pp. 01-09
Author(s):  
Jayaprakash Mayilsamy ◽  
Devi Priya Rangasamy
Keyword(s):  
Information Exchange ◽  
Classification Algorithm ◽  
Route Optimization ◽  
Traffic Load ◽  
Research Network ◽  
Maximum Throughput ◽  
Imbalanced Classification ◽  
Network Information ◽  
Network Information Exchange ◽  
Route Scheduling

Route scheduling optimization is important in SDN network. The SDN network needs the best solution for route optimization. Limited networking of software is the most interesting development in this field as it is important to provide a fast and reliable routing path based on its need. The IoT supports software defined applications interface in the overall networks. The SDN is recommended by enhancing the SDN architecture's benefits in improving research network quality. SDN network information exchange is one of the most important factor. It is important to plan the information accordingly and adjust a load of information to the SDN. A Maximum throughput scheduling process is proposed, which is upgraded using the Imbalanced Classification Algorithm. SDN has shown the advantage in many ways compared to the traditional network. But the problem of load inconstancy still occurs in SDN. The imbalanced classification method supports the maximum throughput schedule function and integrates load balancing strategies to improve SDN networks' Performance. Classification is to be proposed based on machine command in QoS. An imbalanced classification learning method is used for improving the QoS requirements and shows that the simulated results of the identified traffic load balance and maximum throughputs in the proposed solutions. Functionality has been improved much better than previous functions in the same area.

scholarly journals A PROPOSAL TO USE SEMANTIC WEB TECHNOLOGIES FOR IMPROVED ROAD NETWORK INFORMATION EXCHANGE

2018 ◽  
Vol IV-4 ◽  
pp. 147-154 ◽  
Author(s):  
M. G. Niestroj ◽  
D. A. McMeekin ◽  
P. Helmholz ◽  
M. Kuhn
Keyword(s):  
Semantic Web ◽  
Asset Management ◽  
Information Exchange ◽  
Data Standards ◽  
Semantic Web Technologies ◽  
Network Information ◽  
Web Technologies ◽  
Network Information Exchange ◽  
Asset Data ◽  
Data Harmonisation

<p><strong>Abstract.</strong> Data harmonisation improves the coherence between data sets within and across themes and is, therefore, a very helpful tool for governmental agencies, companies and other organisations that share their data. This research focuses on horizontal infrastructures, namely roads, and proposes a new strategy to apply Semantic Web Technologies. The aim is to understand if their application is efficient and effective in filling the gap of data harmonisation in Australia’s and New Zealand’s road asset management systems within the definition of location. The proposed strategy has three stages. First, available international data standards for road assets will be analysed to identify the gaps within these standards and create recommendations towards an improved standard. The second stage is for the location aspect within each stage of the life cycle of asset management with respect to existing road asset data standards. Finally, in a third stage Semantic Web Technologies, ontologies and semantic rules will be used to build a prototype solution for road asset data conflation by merging multiple data sources that share no common lineage. The application of these technologies will allow for easier search and discovery of this data as well as facilitate the automated processing and updating of this data over the Web.</p>

scholarly journals Spread of Risk Information Through Microblogs: Twitter Users with More Mutual Connections Relay News That is More Dreadful

2019 ◽  
Author(s):  
Masashi Komori ◽  
Asako Miura ◽  
Naohiro Matsumura ◽  
Kai Hiraishi ◽  
Kazutoshi Maeda
Keyword(s):  
Information Exchange ◽  
Risk Information ◽  
High Ratio ◽  
The Other ◽  
Network Information ◽  
Perception Model ◽  
Social Sharing ◽  
Twitter Users ◽  
Network Information Exchange ◽  
Transmission Pathways

In elucidating the spread of risk information through microblogging, it is important to understand the behaviors of numerous average users, in addition to the activities of authorities. We followed the transmission pathways of 10 actual widely spread tweets concerning several risk information topics, including natural disasters, nuclear disasters, and infectious diseases, and we identified the types of risk that affected retweeting by classifying each tweet based on Slovic’s risk perception model. Furthermore, we examined the types of users who did and did not retweet the information. Users with few connections in the form of followers (i.e., people who are following a user) or followees (people a user is following), or with a low ratio of mutual followers within their connections, had a tendency to retweet a large amount of risk information, regardless of the type of risk involved. On the other hand, users with a high ratio of mutual followers exhibited a greater tendency to retweet risk information when it was perceived as dreadful, though they did not retweet risk information much on the whole. These results suggest that there are two mechanisms by which risk information is spread within the Twitter network: information exchange and social sharing of personal reactions.

Research on Influencing Factors of Enterprise Network Resource Coordination

2012 ◽  
Vol 220-223 ◽  
pp. 3041-3044
Author(s):  
Yong Gui Shi ◽  
Hai Xia Li ◽  
Xue Shuang Xin ◽  
Jian Fen Yan
Keyword(s):  
Influencing Factors ◽  
Information Exchange ◽  
Hierarchical Organization ◽  
Coordination Mechanism ◽  
Network Resource ◽  
Enterprise Network ◽  
External Resources ◽  
Network Information ◽  
Cultural Compatibility ◽  
Network Information Exchange

Enterprise network refers to the summary of relationships based on common social and cultural background and the basis of mutual trust, connected with information technology, and forged by a group of interconnected enterprise behavior actors and institutions in the process of sharing resources, exchanging resources, and delivering resources in order to respond to market changes quickly. It represents a new organizational structure different from traditional hierarchical organization form. Enterprise network is the innovation of enterprise organizational form, which is beneficial for enterprises to obtain external resources, form rapidly, and maintain a lasting competitive advantage. But because each enterprise in enterprise network is an independent corporate entity, they occupy a certain resources and have a certain decision making authority, it is necessary to establish effective coordination mechanism to improve the performance of enterprise network. The influencing factors on the enterprise network coordination mainly include the structure of the enterprise network, information exchange among enterprise network behavior, trust degree, coordination cost, cultural compatibility and enterprise network environment.

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