Based on Bezout's theorem, the feasibility condition for interference alignment (IA) is established in a two-way small cell network where part of cells transmit in downlink while the others in uplink. Moreover, the sufficient and necessary condition for the two-way network to achieve as many degrees of freedom (DoFs) as the traditional one-way network is presented. We find that in certain cases every small cell can independently decide to work in either downlink mode or uplink mode as needed without causing performance degradation of IA.

Today's Internet remains faithful to its original design that dates back more than two decades. In spite of tremendous diversity in users, as well as the sheer variety of applications that it supports, it still provides a single, basic, service offering--unicast packet delivery. While this legacy architecture seemed adequate till recently, it cannot support the requirements of newer services and applications which are demanded by the growing, and increasingly sophisticated, user population. The traditional way to solve this impasse has been by using overlay networks to address individual requirements. This does not address the fundamental, underlying problem, i.e., the ossification of the Internet architecture. In this paper, we describe the design of a new Service Oriented Internet framework that enables the flexible and effective deployment of new applications and services. The framework we describe utilizes the existing IP network and presents the abstraction of a service layer that enables communication between service end-points and can better support requirements such as availability, robustness, mobility, etc., that are demanded by the newly emerging applications and services.

In this paper, the research advances in silicon based millimeter wave and THz ICs in the State Key Laboratory of Millimeter Waves is reviewed, which consists of millimeter wave amplifiers, mixers, oscillators at Q, V and W and D band based on CMOS technology, and several research approaches of THz passive ICs including cavity and filter structures using SIW-like (Substrate Integrated Waveguide-like) guided wave structures based on CMOS and MEMs process. The design and performance of these components and devices are presented.

With an annual growth of billions of sensor-based devices, it is an urgent need to do stream mining for the massive data streams produced by these devices. Cloud computing is a competitive choice for this, with powerful computational capabilities. However, it sacrifices real-time feature and energy efficiency. Application-specific integrated circuit (ASIC) is with high performance and efficiency, which is not cost-effective for diverse applications. The general-purpose microcontroller is of low performance. Therefore, it is a challenge to do stream mining on these low-cost devices with scalability and efficiency. In this paper, we introduce an FPGA-based scalable and parameterized architecture for stream mining.Particularly, Dynamic Time Warping (DTW) based k-Nearest Neighbor (kNN) is adopted in the architecture. Two processing element (PE) rings for DTW and kNN are designed to achieve parameterization and scalability with high performance. We implement the proposed architecture on an FPGA and perform a comprehensive performance evaluation. The experimental results indicate thatcompared to the multi-core CPU-based implementation, our approach demonstrates over one order of magnitude on speedup and three orders of magnitude on energy-efficiency.

Tunneling is one of the main methods for the transition from IPv4 to IPv6 networks. By encapsulating IPv6 packets in IPv4 or UDP packets, tunnels like 6to4, Isatap and Teredo provide a feasible way for IPv4 hosts to establish IPv6 connections to hosts in IPv6 internet or IPv6 islands. For IPv4 internet, the use of tunnels varies the traffic and increases the type of packets, making the network environment more complex. In addition to common tunnels, various types of tunnels with more layers are tested in this paper. The results of successful connections prove the usefulness of multi-layer packets with diverse layer-count and type on the internet. To ensure the security of internal networks, the influence on traffic analysis in dual-stack IDS devices caused by the diversity is studied. Three spoofing attacks of “data insertion”, “data evasion” and “attacks using UDP” are proposed to show the influence on IDS caused by tunnels. Compared to the attacks without tunnels, some constraining factors are eliminated, which may increase the security risk of IDS and decrease the attacker's difficulties. To summarize this kind of problem, the concept of “Tunnel Interference” is revealed. And as solutions to this problem, two methods, RA (Record All) and HEH (Hash for Each Header), are presented in this paper which theoretically solve these problems to a great extent. RA records all headers and compares from the outermost to innermost layer. HEH is hash-based and accumulates hash values of each header. Both of them have linear time and space complexity. Experimental results show that RA and HEH will lead to minor space increase and up to 1.2% time increment in each layer compared to the original dual-stack.

It is the key concern for service providers that how a web service stands out among functionally similar services. QoS is a distinct and decisive factor in service selection among functionally similar services. Therefore, how to design services to meet customers' QoS requirements is an urgent problem for service providers. This paper proposes an approach using QFD (Quality Function Deployment) which is a quality methodology to transfer services' QoS requirements into services' design attribute characteristics. Fuzzy set is utilized to deal with subjective and vague assessments such as importance of QoS properties. TCI (Technical Competitive Index) is defined to compare the technical competitive capacity of a web service with those of other functionally similar services in the aspect of QoS. Optimization solutions of target values of service design attributes is determined by GA (Genetic Algorithm) in order to make the technical performance of the improved service higher than those of any other rival service products with the lowest improvement efforts. Finally, we evaluate candidate improvement solutions on cost-effectiveness. As the output of QFD process, the optimization targets and order of priority of service design attributes can be used as an important basis for developing and improving service products.

The basic requirements of the distributed Web crawling systems are: short download time, low communication overhead and balanced load which largely depends on the systems' Web partition strategies. In this paper, we propose a DHT-based distributed Web crawling system and several DHT-based Web partition methods. First, a new system model based on a DHT method called the Content Addressable Network (CAN) is proposed. Second, based on this model, a network-distance-based Web partition is implemented to reduce the crawler-crawlee network distance in a fully distributed manner. Third, by utilizing the locality on the link space, we propose the concept of link-based Web partition to reduce the communication overhead of the system. This method not only reduces the number of inter-links to be exchanged among the crawlers but also reduces the cost of routing on the DHT overlay. In order to combine the benefits of the above two Web partition methods, we then propose 2 distributed multi-objective Web partition methods. Finally, all the methods we propose in this paper are compared with existing system models in the simulated experiments under different datasets and different system scales. In most cases, the new methods show their superiority.

With the emergence of a large quantity of data in science and industry, it is urgent to improve the prediction accuracy and reduce the high complexity of Gaussian process regression (GPR). However, the traditional global approximation and local approximation have corresponding shortcomings, such as global approximation tends to ignore local features, and local approximation has the problem of over-fitting. In order to solve these problems, a large-scale Gaussian process regression algorithm (RFFLT) combining random Fourier features (RFF) and local approximation is proposed. 1) In order to speed up the training time, we use the random Fourier feature map input data mapped to the random low-dimensional feature space for processing. The main innovation of the algorithm is to design features by using existing fast linear processing methods, so that the inner product of the transformed data is approximately equal to the inner product in the feature space of the shift invariant kernel specified by the user. 2) The generalized robust Bayesian committee machine (GRBCM) based on Tsallis mutual information method is used in local approximation, which enhances the flexibility of the model and generates a sparse representation of the expert weight distribution compared with previous work. The algorithm RFFLT was tested on six real data sets, which greatly shortened the time of regression prediction and improved the prediction accuracy.

This paper presents an Application Specific Instruction-set Processor (ASIP) for the SHA-3 BLAKE algorithm family by instruction set extensions (ISE) from an RISC (reduced instruction set computer) processor. With a design space exploration for this ASIP to increase the performance and reduce the area cost, we accomplish an efficient hardware and software implementation of BLAKE algorithm. The special instructions and their well-matched hardware function unit improve the calculation of the key section of the algorithm, namely G-functions. Also, relaxing the time constraint of the special function unit can decrease its hardware cost, while keeping the high data throughput of the processor. Evaluation results reveal the ASIP achieves 335 Mbps and 176 Mbps for BLAKE-256 and BLAKE-512. The extra area cost is only 8.06k equivalent gates. The proposed ASIP outperforms several software approaches on various platforms in cycle per byte. In fact, both high throughput and low hardware cost achieved by this programmable processor are comparable to that of ASIC implementations.

Internet computing is proposed to exploit personal computing resources across the Internet in order to build large-scale Web applications at lower cost. In this paper, a DHT-based distributed Web crawling model based on the concept of Internet computing is proposed. Also, we propose two optimizations to reduce the download time and waiting time of the Web crawling tasks in order to increase the system's throughput and update rate. Based on our contributor-friendly download scheme, the improvement on the download time is achieved by shortening the crawler-crawlee RTTs. In order to accurately estimate the RTTs, a network coordinate system is combined with the underlying DHT. The improvement on the waiting time is achieved by redirecting the incoming crawling tasks to light-loaded crawlers in order to keep the queue on each crawler equally sized. We also propose a simple Web site partition method to split a large Web site into smaller pieces in order to reduce the task granularity. All the methods proposed are evaluated through real Internet tests and simulations showing satisfactory results.

Location-based services (LBSs) are useful for many applications in internet of things(IoT). However, LBSs has raised serious concerns about users' location privacy. In this paper, we propose a new location privacy attack in LBSs called hidden location inference attack, in which the adversary infers users' hidden locations based on the users' check-in histories. We discover three factors that influence individual check-in behaviors: geographic information, human mobility patterns and user preferences. We first separately evaluate the effects of each of these three factors on users' check-in behaviors. Next, we propose a novel algorithm that integrates the above heterogeneous factors and captures the probability of hidden location privacy leakage. Then, we design a novel privacy alert framework to warn users when their sharing behavior does not match their sharing rules. Finally, we use our experimental results to demonstrate the validity and practicality of the proposed strategy.

A novel rough neural network (RNN) structure and its application are proposed in this paper. We principally introduce its architecture and training algorithms: the genetic training algorithm (GA) and the tabu search training algorithm (TSA). We first compare RNN with the conventional NN trained by the BP algorithm in two-dimensional data classification. Then we compare RNN with NN by the same training algorithm (TSA) in functional approximation. Experiment results show that the proposed RNN is more effective than NN, not only in computation time but also in performance.

We discuss the uniqueness of 3-D shape reconstruction of a polyhedron from a single shading image. First, we analytically show that multiple convex (and concave) shape solutions usually exist for a simple polyhedron if interreflections are not considered. Then we propose a new approach to uniquely determine the concave shape solution using interreflections as a constraint. An example, in which two convex and two concave shapes were obtained from a single shaded image for a trihedral corner, has been given by Horn. However, how many solutions exist for a general polyhedron wasn't described. We analytically show that multiple convex (and concave) shape solutions usually exist for a pyramid using a reflectance map, if interreflection distribution is not considered. However, if interreflection distribution is used as a constraint that limits the shape solution for a concave polyhedron, the polyhedral shape can be uniquely determined. Interreflections, which were considered to be deleterious in conventional approaches, are used as a constraint to determine the shape solution in our approach.

This paper presents a detailed simulation method to estimate Doppler power spectrum and mean blood velocity using real CW Doppler transducers with twin-crystal arrangement. The method is based on dividing the sample volume into small cells and using the statistics of the Doppler power spectrum with the same Doppler shift frequency, which predicts the mean blood velocity. The acoustic fields of semicircular transducers across blood vessels were calculated and the effects of acoustical and physiological factors on Doppler power spectrum and mean blood velocity were analyzed. Results show that nonuniformity of the acoustic field of the ultrasonic beam in the blood vessel and blood velocity profiles significantly affect Doppler power spectrum and mean blood velocity. However, Doppler angle, vessel depth, and sample volume length are not sensitive functions. Comparisons between simulation and experimental results illustrated a good agreement for parabolic flow profile. These results will contribute to a better understanding of Doppler power spectrum and mean blood velocity in medical ultrasound diagnostics.

Slow development in battery technology and rapid advances in ultra-capacitor design have motivated us to investigate the possibility of using capacitors as the sole energy storage for wireless sensor nodes to support ubiquitous computing. The starting point of this work is TwinStar, which uses ultra-capacitor as the only energy storage unit. To efficiently use the harvested energy, we design and implement feedback control techniques to match the activity of sensor nodes with the dynamic energy supply from environments. We conduct system evaluation by deploying sensor devices under three typical real-world settings -- indoor, outdoor, and mobile backpack under a wide range of system settings. Results indicate our feedback control can effectively utilize energy and ensure system sustainability. Nodes running feedback control have longer operational time than the ones running non-feedback control.

The copy-move or region duplication forgery technique is a very common type of image manipulation, where a region of the image is copied and then pasted in the same image in order to hide some details. In this paper, a keypoint-based method for copy-move forgery detection is proposed. Firstly, the feature points are detected from the image by using the Förstner Operator. Secondly, the algorithm extracts the features by using MROGH feature descriptor, and then matching the features. Finally, the affine transformation parameters can be estimated using the RANSAC algorithm. Experimental results are presented to confirm that the proposed method is effective to locate the altered region with geometric transformation (rotation and scaling).

Crowd modeling and simulation is an active research field that has drawn increasing attention from industry, academia and government recently. In this paper, we present a generic data-driven approach to generate crowd behaviors that can match the video data. The proposed approach is a bi-layer model to simulate crowd behaviors in pedestrian traffic in terms of exclusion statistics, parallel dynamics and social psychology. The bottom layer models the microscopic collision avoidance behaviors, while the top one focuses on the macroscopic pedestrian behaviors. To validate its effectiveness, the approach is applied to generate collective behaviors and re-create scenarios in the Informatics Forum, the main building of the School of Informatics at the University of Edinburgh. The simulation results demonstrate that the proposed approach is able to generate desirable crowd behaviors and offer promising prediction performance.

In this paper we study the scalability issue in the design of a centralized bandwidth broker model for dynamic control and management of QoS provisioning. We propose and develop a path-oriented, quota-based dynamic bandwidth allocation mechanism for efficient admission control operations under the centralized bandwidth broker model. We demonstrate that this dynamic bandwidth allocation mechanism can significantly reduce the overall number of QoS state accesses/updates, thereby increasing the overall call processing capability of the bandwidth broker. Based on the proposed dynamic bandwidth allocation mechanism, we also extend the centralized architecture with a single bandwidth broker to a hierarchically distributed architecture with multiple bandwidth brokers to further improve its scalability. Our study demonstrates that the bandwidth broker architecture can be designed in such a manner that it scales with the increase in the network capacity.

The IETF Differentiated Services (DiffServ) framework achieves scalability by (1) aggregating traffic flows with coarse grain QoS on the data plane, and (2) allocating network resources with a bandwidth broker (BB) on the control plane. However, there are many issues that need to be addressed under such framework. First, it has been shown that the concatenation of strict priority (SP) scheduler of class-based queues (CBQ) can cause delay jitter unbounded under certain utilization, which is not acceptable to support the premium service (PS). Furthermore, it is not clear how such a DiffServ network can support traffic flows requiring the guaranteed service (GS), which is a desirable feature of the future Internet. This paper presents architecture and mechanisms to support multiple QoS under the DiffServ paradigm. On the data plane, we present a node architecture based on the virtual time reference system (VTRS). The key building block of our node architecture is the core-stateless virtual clock (CSVC) scheduling algorithm, which, in terms of providing delay guarantee, has the same expressive power as a stateful weighted fair queueing (WFQ) scheduler. With the CSVC scheduler as our building block, we design a node architecture that is capable of supporting integrated transport of the GS, the PS, the assured service (AS), and the traditional best effort (BE) service. On the control plane, we present a BB architecture to provide flexible resource allocation and QoS provisioning. Simulation results demonstrate that our architecture and mechanisms can provide scalable and flexible transport of integrated traffic of the GS, the PS, the AS, and the BE services.

This paper investigates the spectrum allocation problem. Under the current spectrum management mode, large amount of spectrum resource is wasted due to uncertainty of user's demand. To reduce the impact of uncertainty, a presale mechanism is designed based on spectrum pool. In this mechanism, the spectrum manager provides spectrum resource at a favorable price for presale aiming at sharing with user the risk caused by uncertainty of demand. Because of the hierarchical characteristic, we build a spectrum market Stackelberg game, in which the manager acts as leader and user as follower. Then proof of the uniqueness and optimality of Stackelberg Equilibrium is given. Simulation results show the presale mechanism can promote profits for both sides and reduce temporary scheduling.