To solve the high Bit Error Rate (BER) caused by rate oscillation in traditional Data Rate Change (DRC) algorithm, an improved DRC algorithm based on Adaptive Frame Length (AFL) was proposed for short-wave communication. Firstly, in the initialization phase, the frame length and transmission rate of the initial transmission were determined by the parameters of the current channel and the information of previous empirical values, and the data transmission was started. Then, if two frames with the same length were successively sent in the transmission process, the frame length would be accordingly increased. If the retransmission failed twice in a row, the frame length would be halved in the next transmission. Finally, the frame error rate was calculated based on the current frame length. The data rate would be increased if the value was less than the preset threshold. Compared with RapidM DRC, the average link BER of the proposed algorithm was decreased by 1.8 percentage points, and the link availability was increased by 11 percentage points. Experimental results show that the proposed algorithm can eliminate the rate oscillation and improve the communication capability of the short-wave communication system.

There is a large amount of advertising content in micro-blog space, which seriously affects user experience and related research work. Much of existing research on micro-blog process uses classification algorithm such as Support Vector Machine (SVM) and random forest algorithm. However, it is difficult to classify a large volume of data in the classification method manually. A micro-blog advertisement publisher identification method based on clustering analysis was proposed. For user dimension, a concept of core micro-blog was put forward to deal with the phenomenon that ordinary micro-blogs were posted to dilute advertising content. Then the extracted main themes of each user and corresponding micro-blog sequences could be used to calculate user characteristics as well as the text characteristics. After that, a clustering algorithm was used to cluster the features and identify the micro-blog advertisers. The experiment result shows that the precision is 93%, the recall is 97%, and the F value is 95%, which proves that the proposed method can accurately identify the micro-blog advertisement publisher under the condition that the content of the advertisement is artificially diluted. It provides theoretical support and practical methods for the recognition and cleaning work of micro-blog spam information.

In wide-area Software Defined Networking (SDN) deployments, logically centralized controllers are usually physically placed in a distributed manner. To address the unbalanced controller load problem in controller placement, a load-aware optimal placement for heterogeneous controllers based on unbalanced graph partitioning was proposed. First, the controller placement problem and related metrics, controller load balance and latency, were analyzed. Secondly, controller load balance and latency caused by controller placement were quantified and computed using graph theory and cosine similarity. Moreover, based on graph partitioning theory, the load-aware controller placement problem was transformed into a specified graph partitioning problem. Finally, a load-aware optimal controller placement scheme was presented based on multi-level graph partitioning. Simulation experiments conducted on real network topologies indicate that the proposed scheme can effectively achieve nearly optimal controller load balance.

A rapid and automatic deployment solution of cloud platform based on OpenStack was presented in order to improve OpenStack deployment efficiency. Firstly, the solution created image template files of different node types, and then replicated the image template by node types (such as network node, computing node), and according to the properties of the nodes (such as IP address, hostname tag), automatically modified the configuration file in the use of scripts in order to complete single node deployment. Then, the same strategy was used to achieve rapid deployment of other nodes. After that, the solution took advantage of network service (PXE(Preboot eXecute Environment), DHCP (Dynamic Host Configuration Protocol) and TFTP (Trivial File Transfer Protocol)) which were provided by management servers, mounted the image-block-file. Finally, nodes were started up to complete Dandelion. In addition, performance evaluation model was established to determine the optimal number of image copies and storage servers in order to optimize the storage network topology. Compared with other deployment schemes,such as Cobbler, NFS (Network File System), whether using the same size storage network to deploy different size cloud platforms, or using different size storage network to deploy the same size cloud platform, the experimental results show that the proposed solution can greatly reduce deployment time and improve efficiency of the deployment.

With the popularization of cloud computing technology, many enterprises have migrated or are planning to migrate their business and applications to the cloud. But it may face the problems of application performance degradation, and the key business and applications may suffer security threats. Therefore, migrating to cloud or deploying in independent server is a problem that needs to be further studied. In this paper, based on the Tsinghua cloud platform, Tsinghua cloud monitoring platform was set up based on Nagios. Firstly, Tsinghua cloud platform and its architecture were introduced, and then Nagios and the architecture of Tsinghua cloud monitoring platform were discussed. For cloud migration performance evaluation, Ubuntu and Windows were used as operating system platforms, CPU load and memory usage were used as evaluation indexes, two applications of CPU computing type and server load type respectively ran on the cloud server and the independent server. At last, the experimental results were analyzed and compared. The experimental result shows that some applications have better performance on independent servers that may not be suitable for migrating to cloud platform.

Concerning the phenomenon that common parking service could not satisfy the increasing demand of the private vehicle owners, an intelligent parking guidance system based on ZigBee network and geomagnetic sensors was designed. Real-time vehicle position or related traffic information was collected by geomagnetic sensors around parking lots and updated to center sever via ZigBee network. On the other hand, out-door Liquid Crystal Display (LCD) screens controlled by center sever displayed information of available parking places. In this paper, guidance strategy was divided into 4 levels, which could provide clear and effective information to drivers. The experimental results prove that the distance detection accuracy of geomagnetic sensors was within 0.4m, and the lowest loss packet rate of the wireless network in the range of 150m is 0%. This system can possibly provide solution for better parking service in intelligent cities.

Trust chain is one of the key technologies in trusted computing, and how to express it and assess it is a current hot research focus. According to the complex factors which influence the trust assessment and the uncertainty and dynamism of trust relation in trust computing environment, a trust computing assessment method was proposed based on fuzzy theory. This method established level five space for the trust particle, the historical measurement record and time attenuation factor were introduced to construct the direct trust, and a fuzzy evaluation method of indirect trust was also given. By defining similar degree function with the improved Einstein operator, the trust entity fuzzy reasoning and evaluation process of trust chain was given. This method combined fuzzy reasoning with trust transferring, and it could assess the trust of entity in trust chain fully. The simulation experiments show that, the proposed method has a better ability to resist the malicious assessment and has better credibility and reliability in the results of the assessment as compared with other similar methods. It is a new method for the trust assessment in trusted computing.

Pattern match search oriented to planar graphs is widely used in biological networks, social networks, fingerprint identification and image segmentation. Meanwhile, data extracted from those applications is inherently uncertain due to noise, incompleteness and inaccuracy, and query processing techniques of certain planar graphs cannot be applied to uncertain graph data. Therefore, in this paper, the pattern match query oriented to uncertain planar graphs was studied under the probabilistic semantics. Specifically, Uncertain Pattern Match (UPM) queries using the possible world semantics were investigated. Firstly, to avoid enumerating all possible worlds, a basic deterministic algorithm that can exactly compute UPM query was proposed. To further speed up the basic algorithm, an improved deterministic approach was developed based on tighten bounds. Secondly, a sampling algorithm that can quickly and accurately estimate matching probability was designed. The effectiveness of the proposed solutions for UPM queries was verified through extensive experiments on real uncertain planar graph datasets. Finally, UPM queries were applied to the segmentation on pulmonary CT images. The results show that the proposed approaches are superior to classical techniques of image segmentation.

A currently prevalent and mature technique of Linux embedded system on the ARM9 platform combined with the MiniGUI graphics library was introduced.A kind of ARM+Linux+MiniGUI embedded exchanger for temperature control was designed.It consists of a net control system for the electrical heating based on the double net link.As a result,it boasts the characteristics of low cost,high security and multi-purpose of the embedded system.