Abstract:This thesis introduced the solution of influence maximization and analyzed the advantages and disadvantages of those solutions. After studying the weak tie in social network, it is found that weak ties can effectively break the information barriers between different societies in social network and make information circulate in different societies. Making use of the weak tie's advantages, this thesis proposes a new solution, the BWTG algorithm, based on the greedy thought to resolve influence maximization problem. According to different solution spaces, the BWTG algorithm is divided into two different types:BCWTG and BNCWTG algorithm. There are two traditional evaluation indexes of influence maximization problem, namely, time complexity and the final activated nodes number. But considering the practical situation, a new evaluation index named ANNI is proposed to measure the ratio of profit and pay. Besides, in order to verify the performance of the proposed algorithm, different scales and types of data are used to carry out the experiment. The time complexity, the final activated nodes number and ANNI are compared with the classical Greedy algorithm. The experimental result finds that BCWTG and BNCWTG algorithm have lower time complexity and higher ANNI, but lower final activated nodes number than Greedy algorithm. But under some certain conditions, BCWTG and BNCWTG can be almost equal to Greedy in activated nodes number.

Abstract:To ensure the communication security in a public network, a hierarchical identity-based key agreement protocol based on the present identity-based cryptosystem is proposed in this paper. The new protocol which is able to solve the problem of the certification transfering and verifying in the traditional public key cryptosystem efficiently achieves all of the known security attributes and can be achieved in the state-of-art speed which can meet the demand of large scale network applications.

Abstract:The forwarding performance of general-purpose multi-core server cannot satisfy the demand of wire-speed processing of high-speed traffic very well. Although the heterogeneous network processing platforms combining software and hardware have been applied widely in network processing field for their high performance and flexibility, the problem of designing high-efficiency routing table lookup algorithm in this platform still needs further study. The main problems restricting the performance improvement of heterogeneous network processing platform include low utilization of multi-core resources, serious shared-resources access conflict and large amounts of memory access. Thus, this paper proposes a routing lookup mechanism named CPL (Configurable Parallel Lookup) based on heterogeneous network processing platform NPP (Network processing Platform). The technologies of multi-thread parallel lookup and multi-copy management of routing tables in CPL improve the utilization of multi-core resources and accessing routing tables with zero-conflict. In addition, given that the distribution differences of routing prefix in different scenarios, CPL regulates the structure of multi-level routing table by configuration, which reduces the number of routing table accesses efficiently. At last, after making the performance comparison of CPL and traditional lookup algorithm, the experiments demonstrate the availability and high-efficiency.

Abstract:Incremental performance gain, especially in terms of higher I/O bandwidth and more complex packet processing capability, has made general purpose and multicore processors a preferable option building network devices in core networks, which brings unprecedented flexibility and universality into forwarding plane. However, challenges still exist because of lagging processing and forwarding performance. Firstly, with network link rate continuing booming, the multicore processor needs to offer corresponding higher processing throughput. Secondly, the increasing complexity of network services and applications will introduce more packet processing overhead inside network devices in forwarding and processing processes, indirectly resulting in higher requirements on pure I/O capabilities. Self-Described Buffer (SDB) is a hardware-based buffer management mechanism proposed in this paper which features low overhead in hardware and high performance in software. Furthermore, NPDK, a general network processing development environment has been designed and built based on SDB. It adopts zero interrupt and zero copy technology, provides kernel space and user space drivers and can be applied for general purposes and multicore systems. NPDK is not only easy to implement, flexible to program, feasible to deploy, but it also supports per-CPU-based hierarchical packet processing programmability in the kernel space, as well as monopolistic multi-threaded and shared multi-process programming in the user space. Experimental results show that NPDK can reach near line rate forwarding under 10Gbps link rate. Specifically 7.49Gbps for 64 Bytes packets. Currently NPDK has already been deployed and applied in Click routers, OpenFlow switches and network probing applications.

Abstract:Some problems exist in current WiFi campus networks, such as limited range of mobile communication, limited host network configuration. Many approaches have been proposed to introduce programmability in wireless networks, and all these systems require special software or hardware in the access point, which raises the issues of practicality. Aiming at single-hop infrastructured network, a solution of software defined mobile communication is proposed for campus WiFi networks, in which mobile hosts can access with free configuration and communicate in high mobility. In this architecture, OpenFlow network is chosen as network infrasture and commercial access points connect to OpenFlow switch directly. The controller is responsible for downloading flowitems containing mobile location, providing mobiles with name-based routing and adjusting reverse path actively for all traffic. A prototype has been implemented and experiments are carried out about mobile communication, in which the performance is measured and analyzed under different configurations. Experimental results show that mobile hosts can achieve mobile communication and the handover delay is not influenced by network configuration for mobile hosts and performance of OpenFlow switch.

Abstract:Understanding the utilization of IP addresses is very important for the research of network administrators and network security. This paper proposes a methodology of detecting active IP addresses based on sampled flow records. The core idea of the methodology is that IP addresses with two-way communication traffic are active. The method is based on passive measurements and uses sampled flow records as data source, making it possible to be deployed at the boundary of backbones. Furthermore, the impacts of flows' sampling and spoofed traffic on the method are discussed. DPI technology is used to validate accuracy and efficiency of the method. Finally, the method is deployed at all 38 nodes of CERNET, detecting active IP address space in the whole CERENT network.

Abstract:The closure of network equipment hardware makes scientific research and teaching staffs difficult to learn the details of the network device hardware. Hardware research and teaching face enormous challenges. To solve these problems, this paper proposes a hardware packet processing monitoring technology based on Finite State Machine called PktScope, to monitor the processing of packets in the hardware in real time by designing hardware packet processing state machine coding standard and formulating standard packet data and processing reporting interface, which can be effectively applied to the network equipment research and teaching field. The prototype system is implemented based on MagicRouter. The PktScope technology can effectively realize the real-time monitoring of network flows, and has the characteristic of low additional hardware resource consumption.

Abstract:This paper proposes a framework of gesture detection and classification in continuous sequence data. The goal of detection is to determine the start and end frame of a gesture in the continuous sequence. The detection method using multi-modal features ensures the robustness and high accuracy. To classify the detected gestures represented by covariance matrices, a distance measurement on Grassmann manifold is presented to strengthen the discriminative power. The framework is evaluated on ChaLearn Multimodal Gesture dataset 2013 and achieves high accuracy. Both Recall and Precision are higher than 93%.

Abstract:This paper proposes a method to estimate the spectrographic speech mask based on a two-dimensional (2-D) correlation model. The proposed method is motivated by a fact that the time and frequency correlations of speech presence are interwoven with each other in the time-frequency domain. Conventional Markov chain is incapable of simultaneously modeling the time and frequency correlations in an adaptive way. The 2-D correlation model is presented to describe the correlation of speech presence in the TF domain, where the speech presence and absence are taken as two states of the model. The time correlation is modeled by the time state-transition probability and the forward factor, while the frequency state-transition probability and the corresponding neighbor factor are defined to describe the frequency correlation. The time and frequency correlations are incorporated into the model by maximizing the Q-function. A sequential scheme is presented to online estimate the parameter set. Given the observed spectrum and the parameter set, the state matrix that maximizes the posteriori probability is regarded as the optimal estimate of the speech mask. The proposed method was compared with some well-established methods. The experimental results confirmed its superiority.

Abstract:In the natural human-computer dialogue system, environmental noises, accents and some other factors may cause the speech recognition errors which leads to computers' error responses to human. The dialogs are often interrupted by the system's bad responses. Three types of human computer interruptions are considered in this paper:improper feedback for topic, improper response for a vague user query, and improper feedback for an exact user query. According to the records of the user and computer dialogue analysis, the interruptions caused by three situations above are compared and used to analyze the importance of intention classification in human-computer conversation. The statistical data find that the dialogue interruption caused by the inappropriate topic feedback is the most obvious problem, amounting to 60.1%. Under the correct feedback of the topic, the interrupt ratio of the subject caused by accurate answer and fuzzy answer is 22.2% and 21.6% respectively. In the case of error speech recognition, semantic analysis can bring more feedback error to the error of speech recognition. The analysis of experimental data shows that the speech recognition errors, can effectively reduce the man-machine conversation interrupt and improve the naturalness of human-computer dialogue system according to the context information to improve the accuracy of the computer on the topic of user feedback,. This paper provides the importance of intention classification in human machine dialogue, which helps to improve the performance of human-computer dialogue system.

Abstract:As the computer's use of people's cognitive load and mental stress will help the achievement of smart life in the future, meanwhile recent studies show that the PPG signal which reflects the changes of blood volume in the microvascular will help to analyze the mental stress and emotion measurement. The paper introduces a novel photoplethysmogram-based stress induced vascular index (sVRI) to measure cognitive load and stress by using a reflective PPG signal sensor. This model demonstrates the applicability of the reflective PPG signal sensor. The experiment in this paper does not only compare the waveform difference of using the transmission mode and reflective mode to acquire the PPG signal, it also uses the reflective green light compared with the red and infrared light. The mental stress is evaluated based on reflective photoplethysmogram. Baed on the comparison and discussion, the applicability of the reflective PPG signal sensor is proved. At last, the paper applies the results of the experiment to the model of the mouse. It has a great influence on the individual health problems in daily life and the advantage of comfort for the individuals and the mobility convenience can expand considerably the range of wearable smart devices and high-performance medical care devices used for pulse detection system.

Abstract:Potential Intention Detection aims to detect implicit intention by user behavior, so as to understand the real intention of the users at a higher level. A human-computer interaction model as well as the corresponding technical framework for intention understanding and reasoning is presented under multi-domain data environment. An extension of Dynamic Intention Structure (DIS) is proposed to adapt to the requirement of multi-domain data and interactive reasoning. A set of interactive primitives is provided to regulate human-computer interface. The technical framework makes it technically possible to implement a system to deduce potential intention.

Abstract:Chrome browser provides a RRTCC (receiver-side real-time congestion control) algorithem for WebRTC, but it exhibits poor performance in the mobile network environment. It cannot effectively compete with other TCP flow applications, causing WebRTC starvation. Furthermore, in the case of multi-WebRTC concurrent flow, new entrants will impact the existing flows. This paper proposes a transmission control strategy MTCIS. The core of MTCIS is the use of an improved RRTCC algorithm in consideration of mobile network scenarios and QoE, and the proper control of WebRTC, which can avoid the problem of excessive concession when competing with TCP flow. While in multi-WebRTC flow concurrent scenarios, the MTCIS can dynamically adjust the transmission parameters of video streaming, based on the analysis of rational utilize bandwidth and priority to satisfy users' QoE. Experimental results show that MTCIS can be used in mobile network environment of flows competition, ensure reasonable competition, stability and robustness of WebRTC, which improves the users' QoE.

Abstract:No reference video quality assessment (NR-VQA) measures distorted videos quantitatively without the reference of original high quality videos. Conventional NR-VQA methods are generally designed for specific types of distortions, or not consistent with human's perception. This paper innovatively introduces 3D deep convolutional neural network (3D-CNN) into VQA and proposes a 3D-CNN based NR-VQA method, which is universal for non-specific types of distortions. First, the proposed method utilizes 3D patches to learn spatio-temporal features that represent video content effectively. Second, the original 3D-CNN model is modified which is used to classify videos to make it adapt to VQA task. Experiments demonstrate that the proposed method is highly consistent with human's perception across numerous distortions and metrics. Compared with other state-of-the-art no-reference VQA methods, the proposed method runs much faster while keeping the similar performance. As a no-reference VQA method, it is even comparable with many of the state-of-the-art full-reference VQA methods, which provides the proposed method with better application prospects.

Abstract:Binarization, possibility model and the entropy engine are the three stages of the arithmetic coding. In order to deal with the new syntax elements in a screen content codec, the binary tree base binarization decision method is proposed in this paper. The syntax probability distribution is derived, and then the bit probability distribution is calculated with the different binarization method. The binary tree method is used to get the optimal bit grouping. Experimental results show that the method proposed in this paper can improve the compression rate by 18.06% in average.

Abstract:Explosive growth in medical information has exceeded human's cognitive skills and abilities. Traditional information management tools are challenged in satisfying people's needs of information service due to the diversity of clinical service environment and users. The existing medical service is difficult to meet the needs of the massive information processing and utilizing due to the development of intelligence and visualization of clinical service. This paper analyzes the collaborative cognitive feature between human and computer on the basis of scenarios of clinical process; presents an approach to information organization based on sematic; and proposes the technique of visual organization and interaction for large-scale medical data. Moreover, a user-centered visual analysis framework is proposed for clinical decision-making and reasoning. Finally an example of application is given to illustrate how to facilitate users to gain useful insights from the massive data by combining automated analysis techniques with interactive visualizations. Experiments show that visual analytics facilitate users to deal with information overloads and aid medical diagnosis decision.

Abstract:Speech emotion recognition is an important research area in human computer interaction (HCI). The speech emotion recognition system used in the intervention therapy for autistic children is helpful for their rehabilitation. However, the variation and complexity in speech emotion features, the extraction of which itself is a challenging task, will contribute to the difficulty to improve the recognition performance of the whole system. In view of this problem, this paper proposes a new method of speech emotion feature extraction with unsupervised auto-encoding network to learn emotional feature in speech signal automatically. By constructing a 3-layer auto-encoding network to extract the speech emotional feature, the high level feature is used as the input of extreme learning machine classifier to make final recognition. The speech emotion recognition rate of the system reaches 84.14%, which is higher than the traditional method based on human defined feature extraction.

Abstract:Focusing on the problem of human movementidentification in the application of natural human-computer interaction, this paper summarizes the shortcomings of the traditional machine learning model in the identification of body movement.Based on the unique requirements of natural human-computer interaction application, it proposesRandom Increased Hybrid Learning Machine for human body movement identification. Combined with the Error Back Propagation Model, the Increased Extreme Learning Machine and Bidirectional Extreme Learning Machine, the model overcomes the shortcomings of traditional methods. This paper describes in detailthe algorithm theory, model rationality and implementation scheme of the Random Increased Hybrid Learning Machine. Finally, by comparing the experimental results, the paper verifies the Random Increased Hybrid Learning Machine's a better robustness, accuracy and timeliness in identification of human body movement.

Abstract:Visual fatigue cannot only lead to decreased productivity and vision, it might also bring various accidental injuries. How to detect visual fatigue in a simple and fast way is an urgent topic. This paper proposes a visual fatigue detection approach with the aid of special characters searching and reading tasks. Participants are required to locate these special characters from the reading materials through scanning, and at the same time complete the corresponding reading comprehension tasks. The experiment is conducted under the monitoring of Tobii X230 eye tracker. Eye tracking data, such as pupil diameter ratio, number of AOIs etc. are recorded. BP neural network is employed to determine the state of visual fatigue. The experimental results on 10 users show a classification accuracy of 95.2%, which confirms the effectiveness of the approach.

Abstract:With the growing popularity of smart mobile devices such as tablet PCs, smart phones and smart watches, the use of portable smart mobile devices in health evaluation has received extensive attention of scholars at home and abroad. The characteristics of multimodal, interactive and collaborative computing in human-computer interaction (HCI) can effectively improve the accuracy of nerve function assessment. However, little research has been done on the important role of human computer interaction in medical assessment, and no model of nerve function assessment in mobile environment has been established. Therefore, this paper firstly analyzes the mainstream method of nerve function assessment in mobile environment, and summarizes a set of interaction primitives and interaction tasks for the application on this scenario. Then it proposes a multimodal human-computer interaction model for nerve function assessment in mobile environment:MINA, and analyzes the characteristics of mobile health assessment and multimodal fusion in MINA. Finally, one application that builds on MINA has been demonstrated. The practice shows that MINA can better guide the development of interactive nerve assessment applications, and the multimodal fusion can effectively improve the accuracy of medical assessment.

Abstract:This paper introduces a local pose prior based real-time online approach to capture 3D human animation from a single depth camera. The key idea is to learn a series of local pose prior models with K motion capture examples from a pre-established large and heterogeneous human motion database, based on automatically extracted labelled virtual sparse 3D markers from captured depth image. Then, by solving a Maximum A Posterior (MAP) problem via an iteratively optimization process, the system automatically tracks the 3D human motion sequence. The experiments show that the proposed approach robustly captures the accurate 3D human motions at 25fps. The proposed tracking system can easily applied to different actors with large different body sizes via an automatically individual body parameters calibration process. The proposed system can widely apply to 3D game/movie produce, human-machine interaction.

Abstract:This paper proposes a novel method for piecewise polynomial image approximation based on the capacity-constrained power diagram. By associating the weights of a power diagram with the image color information, an efficient image approximation algorithm is designed which alternately optimizes the positions and the weights of a capacity-constrained power diagram. This method defines the density function by using error feedbacks and the saliency information of the original image, which guides the generation of the initial point distributions in the optimization. It solves the color image approximation problem by constructing the optimal power diagram. A capacity-constrained energy function is defined to measure the approximate error based on power diagram, and the explicit formulas are given for computation of the gradients of the energy function. The optimization of the energy function is converted into two sub-problems, which are tackled by alternately moving the point positions and updating the weights of the points of the power diagram. Experimental results show the correctness and efficiency of the method above.

Abstract:This paper proposes a method for constructing a virtual-real fusion system integrated with multiple videos aiming to create an augmented virtual environment, where images and videos captured from real world are fused to virtual scene. With the help of textures from images and motion from videos, the virtual environment is more realistic. Unmanned Aerial Vehicles are used to take photos and reconstruct the 3D virtual scene. By matching features, video frames can be registered to the virtual environment. Then images are projected to virtual scene with the method of projective texture mapping. Due to lack of the corresponding 3D models in the virtual environment, distortions will occur when images are directly projected and the viewpoint changes. This paper first detects and tracks those moving objects, then it gives multiple ways of displaying moving objects to solve the distortion problem. Fusion of multiple videos with overlapping areas in the virtual environment is also considered in this system. The experimental results show that the virtual-real fusion environment that is build based in this paper has lots of benefits and advantages.

Abstract:This paper proposes a sketch-based interactive geological modeling method, aiming at helping geologists to effectively create data-free conceptual geological models at the early stage of geological exploration. Up to date, the majority of the existing professional modeling tools take expensive measured data to build sophisticated 3D geological models, and usually suffer from the drawbacks of time-consuming and difficult to learn and use. Therefore, this paper exploits the intuitiveness of "paper-pencil" metaphor and develops a complete sketch-based interactive geological modeling framework, including 3D sketching, surfacing and sketch-based model editing. Geological sketches can be drawn on user-defined 3D drawing planes. Intersecting sketches constitute a sketch network, from which the corresponding 3D model is generated on the fly with the surface patching method. Specifically, surface patching employs the idea of divide-and-conquer and takes three steps. Based on the topology of the sketch network, planar cycles are first collected by minimizing their geometric energies, i.e. the corners. Then, surface patches are generated for each cycle by Laplacian optimization of the target mean curvatures and normals, which are pre-computed by harmonic functions. Finally, surface patches are stitched to make a complete 3D model. Geological phenomena such as folding and faulting can be modeled by over-sketching and cutting operations, respectively. In addition, the hierarchy of models is preserved in a hierarchical tree structure. To maintain the contact between geo-bodies, the deformation of an edited model is automatically transferred to its siblings and parents on the basis of their hierarchies. Compared to the existing sketch-based modeling tools, awareness of the geological knowledge makes the method advantageous in effectively describing geo-bodies with fewer expressive sketches. Based on user experiences, this method is intuitive and easy-to-use for both professionals and inexperienced users to model illustrative geological scenarios.

Abstract:Computational aesthetics has become an active research area in recent years, but current works mainly focus on aesthetic evaluation of photographs and oil paintings. Chinese wash painting differs significantly from photograph and oil painting in visual features because it uses ink blended with water and a few colors to depict objects. This paper proposes a framework for computational aesthetic evaluation of Chinese wash paintings. The framework first extracts several features in color, composition and texture from Chinese wash paintings, and then uses 60 Chinese paintings by the famous artist Qi Baishi to verify it. Specifically, human ratings of aesthetics are conducted on these paintings and human evaluated aesthetics are regressed on calculated feature variables to obtain the computational aesthetic evaluation model. Experimental results show that the Pearson correlation coefficient between the computational aesthetic evaluation results and human aesthetic evaluation results is 0.949. This paper provides a reference framework for aesthetic evaluation of Chinese wash paintings, and also furthers the understanding of the relationship between human aesthetics and computational visual features extracted from Chinese wash paintings.

Abstract:Named Data Networking (NDN) improves the transfer efficiency by caching the contents in routers. To prevent polluted content from being spread in NDN, NDN routers should verify every content that is published in NDN. Since the verification scheme in NDN applies the asymmetric encryption algorithm to sign the content, the verification speed is too slow to satisfy the high speed requirement. This paper proposes a Staining-based verification scheme to improve the verification speed by reducing the computation complexity of the content verification. Staining-based verification scheme stains the content that is sent to the network for the first time; then when the stained content is sent to the network again, the router can utilize the staining information to verify this content. By replacing the asymmetric encryption algorithm with symmetric encryption algorithm, Staining-based scheme can improve the verification speed effectively.

Abstract:There are many optional paths between any server pair in modern data center networks. Traffic balancing among the paths is an important issue. Many solutions have been proposed to cope with this problem. This paper analyzes traffic balancing in data center networks with multi-tier Clos-based topology. The feature of data center networks is introduced and the traffic balancing problem is defined as minimizing the maximum potential packet loss among different equivalent links. Then the reasons of potential packet loss are summarized in data center networks and two main challenges are discussed related to traffic balancing:packet out-of-order and burst congestion. Ten existing solutions are classified into four categories:active scheduling, slice spraying, probing and adjusting, and others. The advantages of these solutions are described one by one in details, as well as their disadvantages. A comparison is made among these solutions and possible research directions are pointed out on traffic balancing in data center networks.

Abstract:With the rapid growth of the scale of the data center networks, the low network bandwidth utilization has posed a problem due to network congestion. How to improve data center network link bandwidth utilization and throughput by load balancing has become a research focus. How to reasonably schedule flow by making use of traffic characteristics, link state and application requirements is the key to realize the network link load balancing. Aiming at scheduling problem of elephant flow that bursts and highly occupies bandwidth in the data center, this paper proposes a maximum probability path scheduling algorithm (MPP_SA) for SDN data center network. The algorithm firstly computes all paths that can meet the scheduled flow's demand, and then calculates bandwidth ration between flow bandwidth and minimum link bandwidth combining with all the bandwidth ratio to compute path probability for each path. Finally, the path of largest path probability will be likely selected. The algorithm does not only consider flow's bandwidth and usage of link bandwidth, but also the global flow scheduling and bandwidth fragmentation. The experimental results show that the MPP_SA algorithm can effectively alleviate network congestion, improve the bandwidth utilization and throughput, and reduce network delay, so as to improve the overall network performance and quality of service.

Abstract:In order to improve the quality of service for network users, the cognitive network and the trusted network provide guarantee mechanisms with intelligence and credibility. On the basis of the intelligent characteristics of artificial immune system, a trusted QoS multicast routing algorithm is proposed based on the asexual propagation optimization under the framework of the cognitive network using technologies of the trusted network. Meanwhile, the sliding window method is used to design the trust evaluation mechanism. It records and evaluates the behavior of each network node in order to keep the credibility of the network. According to the optimization mechanism of asexual propagation, the routing selection is based on the user satisfaction and node trust value, and the optimal solution which satisfies the QoS for users is obtained. Finally, the performances of the proposed multicast routing algorithm and classical multicast routing algorithms are evaluated on the simulation platform. The results show that the trusted QoS routing mechanism can provide better quality of service for network users than the other ones.

Abstract:The existing network, which implements the packets forwarding based on the destination IP address, ignores the source IP address in the transmission process, hence its forwarding strategy is not flexible. Based on the destination IP address and the source IP address, the two-dimensional routing supports the network to provide a more flexible forwarding service. But the introduction of the source IP address dramatically increases the storage space of the Forward Information Base (FIB), in addition, it significantly increases the cost of the hardware. This paper presents a decomposition and storage model of two-dimensional FIB (DSTF). According to the destination IP prefixes, DSTF divides the two-dimensional FIB into blocks. And the collection of the two-dimensional routing entries (REs) that are included in the same Cluster-head IP Prefix (CP) is treated as a sub two-dimension block (STB). Then, depending on the different CPs that the STBs belong to, every STB is stored in the different line cards (LC). Meanwhile, in the process of the packets forwarding, according to the corresponding relationship between the CPs and the LCs, the forwarding mechanism can quickly locate the host LC (LC_host) of this packet, and implement the packets forwarding in the LC_host. Experimental results show that DSTF can decompose and store the two-dimensional FIB in different LCs averagely. Furthermore, it is effective to reduce the storage space of the two-dimensional FIB in the routing system.

Abstract:LISP is one of representative identity/locator separation proposals. IETF Internet Engineering Steering Group (IESG) proposes LISP-MN (LISP Mobile Node) to support mobility base on LISP. However, this scheme needs to modify protocol stack of joined hosts, which restricts access of existing mobile terminals. So, it's hard to achieve large-scale popularization and application. This paper designs a mobility support Identity/Locator separation scheme named LISP-MNet, based on standard LISP. It achieves fast mapping entries delivery and synchronization through mapping delivery mechanism. In addition, it allows terminals to access to sites arbitrarily and switchover among different sites through active registration mechanism deployed in edge access devices without modifying protocol stack of terminals. These two mechanisms do improve mobile access ability of terminals. At last, LISP-MNet prototype is established and evaluated in areal network environment. A pressure experiment is firstly conducted on a single mapping server, of which results prove that its scale can be up to 100M. And then mobile switching delay is measured by using VLC video applications. The experimental results show that mobile switching delay is less than 2s and VLC server and client can complete synchronization in 2s after mobile terminal accesses to mobile site.

Abstract:With the increasing demand for mobile network services, users need to realize the seamless handover between different access technologies in the complex heterogeneous networks, so the handover decision scheme with always best connected support and the quality of service has become the key research content of the next generation Internet. In order to satisfy users' demand, a handoff decision scheme is designed based on the fast continuous ant colony algorithm, considering the fuzzy network information, the user quality of service requirement, user preferences, charges that the user is willing to pay and the revenue of the network provider. The knowledge of negotiation game and Nash equilibrium concept are introduced to solve the collusion between users to ensure the fairness of the handoff decision. Simulation results show that the handoff decision scheme designed in this paper can meet the quality of service requirement of the user,maximize the utility of both sides and best fit the user's preference,which has a better performance in solving the always best connected supported handoff decision problem in next generation Internet.

Abstract:UDP reflection DDoS attacks have become one of the primary means of network attack because of its simple realization and significant effect. BAF(bandwidth amplification factor) is the main measure to evaluate the ability of amplification. In this paper, considering the condition of IP slice message, the whole message load is used to modify the formula of BAF, so that it can more accurately reflect the amplification ability of reflection attacks. This paper obtains the hosts with 19, 161, 123, 1900 port reflection behavior in the CERNET (China Education and Research Computer Network) by NBOS (network behavior observation system) to implement the attack test to get the BAF data. On the basis of this, the BAF data are analyzed in terms of statistics and stability. Analysis results show that the BAF of 19 and 123 port is relatively large, but the stability is poor. The paper also uses the results of the analysis to evaluate the risk degree of all amplifiers. Amplifiers with high degree of risk are usually used by the attacker and should be the focus of attention in attack prevention.

Abstract:Recently, the online car sharing is on the rise which improves the car resource utilization. In order to stimulate car sharing, the study on travel demand and user experience is essential. This paper measures the aggregation degree of travel demand in urban city through DBSCAN algorithm, which verifies the feasibility of car sharing. Mathematical models are provided based on Logit model to capture user experience and car utilization, and the user selection is predicted. Both real data and the survey result are leveraged to make the measurement and model realistic. The evolution of urban traffic mode is observed and analyzed, and it is found that the quantity of the travel demand and the traffic aggregation degree are the main factors influencing the evolution. The evolution can reach a steady state if and only if the travel demand reaches some certain value. The higher the traffic aggregation degree is, the more travelers will participate in car sharing and gain higher utilities. All the travelers will participate in the car sharing when the travel demand is larger than 290 as well as the traffic aggregation degree is larger than 0.9. Ultimately, the evolution of Beijing traffic mode is analyzed based on the real travel data from CAR Inc., which shows that the traffic mode will not reach a steady state now if car sharing is implemented without the involvement of economic factors and policies.

Abstract:With the increasing complication and variation of embedded applications in recent decades, both industry and academia have been proposing to use main memory databases to meet the ever-growing demand of high-performance data processing in embedded systems. Nevertheless, the existing main memory databases all rely on the secondary storage, such as magnetic disks and SSD, to maintain the real database persistently. Moreover, they have large overhead in synchronizing the data between memory and storage via slow I/O operations. Even though they are deployed in the emerging Non-Volatile Memory (NVM), the existing main memory databases are unable to get rid of disks for their temporary in-memory data structures cannot survive system reboot. In solving the persistency problem of main memory databases, this paper proposes to manage the NVM by the database itself that is independent from the memory management system. The information of NVM and the metadata of the database are persistently fixed on the NVM. The proposed ideas are implemented in an open-sourced main memory database, Redis. The experimental results show that compared with the existing persistency scheme of Redis AOF, the proposed approach improves the speeds of starting database, closing database, set operations, and delete operations by 2400 times, 5 times, 58 times, and 34 times, respectively.

Abstract:System performance becomes more and more important in modern embedded systems. Traditionally, system performance is measured after the system has been implemented. When it fails to meet the requirement due to the design of the application at this stage, the cost of fixing them would be high. This paper presents a framework of formal method-based performance analysis (FMPA), whose goal is to detect potential performance problems at the early stage of the model-based procedure of system development. FMPA is aimed to analyse multiple performance criteria. It provides unified input models (UML-MARTE) and various formal models as analysis models. The feasibility of FMPA is illustrated by throughput and response time analysis with real-time model checking, by system reliability prediction using probabilistic model checking, and is further confirmed by the implementation of its support tool FMPAer.