A Trusted NUMFabric Algorithm for Congestion Price Calculation at the Internet-of-Things Datacenter

The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information.However,it is difficult to predict the congestion state of the link-end accurately at the source.In this paper,we presented an improved NUMFabric algorithm for calculating the overall congestion price.In the proposed scheme,the whole network structure had been obtained by the central control server in the Software Defined Network,and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated.In this scheme,the first hierarchy algorithm was set up in a central control server like Opendaylight and the guiding parameter B is obtained based on the intelligent data of global link state information.Based on the historical data,the congestion state of the network and the guiding parameter B is accurately predicted by the machine learning algorithm.The second hierarchy algorithm was installed in the Openflow link and the link price was calculated based on guiding parameter B given by the first algorithm.We evaluate this evolved NUMFabric algorithm in NS3,which demonstrated that the proposed NUMFabric algorithm could efficiently increase the link bandwidth utilization of cloud computing IoT datacenters.

A Computational Model for Measuring Trust in Mobile Social Net works Using Fuzzy Logic

Large-scale mobile social networks(MSNs)facilitate communications through mobile devices.The users of these networks can use mobile devices to access,share and distribute information.With the increasing number of users on social networks,the large volume of shared information and its propagation has created challenges for users.One of these challenges is whether users can trust one another.Trust can play an important role in users'decision making in social networks,so that,most people share their information based on their trust on others,or make decisions by relying on information provided by other users.However,considering the subjective and perceptive nature of the concept of trust,the mapping of trust in a computational model is one of the important issues in computing systeins of social networks.Moreover,in social networks,various communities may exist regarding the relationships between users.These connections and communities can affect trust among users and its complexity.In this paper,using user characteristics on social networks,a fuzzy clustering method is proposed and the trust between users in a cluster is computed using a computational model.Moreover,through the processes of combination,transition and aggregation of trust,the trust value is calculated between users who are not directly connected.Results show the high performance of the proposed trust inference method.

Trust Calculation and Delivery Control in Trust-Based Access Control

Trust management system has been a promising approach to solve the access control problems in open multi-domain environments. However, the calculation of trust and the delivery of the trust are not addressed effectively in the existing trust management systems. To address the problems, this paper proposes a scheme of trust calculation and delivery control. Compared with the other schemes, it is simpler and more flexible, and also easier to be implemented.