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

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.

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

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.

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

<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>

An Improved Car-Following Model in Vehicle Networking Based on Network Control

Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS). In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.

Research on Influencing Factors of Enterprise Network Resource Coordination

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.