This paper presents an optimal cooperative routing protocol (OCRP) aiming to improve the in-network cache utilization of the Content-Centric Networking (CCN). The objective of OCRP is to selectively aggregate the multiple flows of interest messages onto the same path in order to improve the cache utilization while mitigating the cache contention of the Content Stores (CSs) of CCN routers on the routing path. The proposed routing protocol consists of three processes: (1) Prefix Popularity Observation; (2) Prefix Group (Un)Subscription; and (3) Forwarding Information Base (FIB) Reconstruction. Prefix Popularity Observation observes the popularly cited prefixes to activate a prefix group (un)subscription function, which lets the Designated Router (DR) know which requester router wants to either join or leave a prefix group. Prefix Group (Un)Subscription lets the DR know which requester router is demanding to join or leave which prefix group. FIB Reconstruction reconstructs the FIB entries of the CCN routers involved in the newly computed optimal cooperative path of all prefix groups. The optimal routing path is obtained by binary linear optimization under a flow conservation constraint, cache contention mitigating constraint, and path length constraint. Two metrics of server load and round-trip hop distance are used to measure the performance of the proposed routing protocol. Simulation results from various network scenarios and various settings show advantages over the shortest path routing and our previously proposed cooperative routing schemes.

An orthogonal ray graph is an intersection graph of horizontal and vertical rays (closed half-lines) in the plane. Such a graph is 3-directional if every vertical ray has the same direction, and 2-directional if every vertical ray has the same direction and every horizontal ray has the same direction. We derive some structural properties of orthogonal ray graphs, and based on these properties, we introduce polynomial-time algorithms that solve the dominating set problem, the induced matching problem, and the strong edge coloring problem for these graphs. We show that for 2-directional orthogonal ray graphs, the dominating set problem can be solved in O(n2 log5 n) time, the weighted dominating set problem can be solved in O(n4 log n) time, and the number of dominating sets of a fixed size can be computed in O(n6 log n) time, where n is the number of vertices in the graph. We also show that for 2-directional orthogonal ray graphs, the weighted induced matching problem and the strong edge coloring problem can be solved in O(n2+m log n) time, where m is the number of edges in the graph. Moreover, we show that for 3-directional orthogonal ray graphs, the induced matching problem can be solved in O(m2) time, the weighted induced matching problem can be solved in O(m4) time, and the strong edge coloring problem can be solved in O(m3) time. We finally show that the weighted induced matching problem can be solved in O(m6) time for orthogonal ray graphs.

This paper presents an efficient method using Hadoop MapReduce for constructing a K-nearest neighbor graph (K-NNG) from a large-scale data set. K-NNG has been utilized as a data structure for data analysis techniques in various applications. If we are to apply the techniques to a large-scale data set, it is desirable that we develop an efficient K-NNG construction method. We focus on NN-Descent, which is a recently proposed method that efficiently constructs an approximate K-NNG. NN-Descent is implemented on a shared-memory system with OpenMP-based parallelization, and its extension for the Hadoop MapReduce framework is implied for a larger data set such that the shared-memory system is difficult to deal with. However, a simple extension for the Hadoop MapReduce framework is impractical since it requires extremely high system performance because of the high memory consumption and the low data transmission efficiency of MapReduce jobs. The proposed method relaxes the requirement by improving the MapReduce jobs, which employs an appropriate key-value pair format and an efficient sampling strategy. Experiments on large-scale data sets demonstrate that the proposed method both works efficiently and is scalable in terms of a data size, the number of machine nodes, and the graph structural parameter K.

This paper proposes a name-based routing mechanism called Routing Guidance Name (RGN) that offers new routing management functionalities within the basic characteristics of CCN. The proposed mechanism names each CCN router. Each router becomes a Data Provider for its name. When a CCN Interest specifies a router's name, it is forwarded to the target router according to the standard mechanism of CCN. Upon receiving an Interest, each router reacts to it according to RGN. This paper introduces a new type of node called a Scheduler which calculates the best routes based on link state information collected from routers. The scheduler performs its functions based on RGN. This paper discusses how the proposed system builds CCN FIB (Forwarding Information Base) in routers. The results of experiments reveal that RGN is more efficient than the standard CCN scheme. It is also shown that the proposal provides mobility support with short delay time. We explain a practical mobile scenario to illustrate the advantages of the proposal.

This paper represents an illumination modeling method for lighting control which can model the illumination distribution inside office buildings. The algorithm uses data from the illumination sensors to train Radial Basis Function Neural Networks (RBFNN) which can be used to calculate 1) the illuminance contribution from each luminaire to different positions in the office 2) the natural illuminance distribution inside the office. This method can be used to provide detailed illumination contribution from both artificial and natural light sources for lighting control algorithms by using small amount of sensors. Simulations with DIALux are made to prove the feasibility and accuracy of the modeling method.

As interdomain routing protocol, BGP is fairly simple, and allows plenty of policies based on ISPs' preferences. However, recent studies show that BGP routes are often non-optimal in end-to-end performance, due to technological and economic reasons. To obtain improved end-to-end performance, overlay routing, which can change traffic routing in application layer, has gained attention. However, overlay routing often violates BGP routing policies and harms ISPs' interest. In order to take the advantage of overlay to improve the end-to-end performance, while overcoming the disadvantages, we propose a novel interdomain overlay structure, in which overlay nodes are operated by ISPs within an ISP alliance. The traffic between ISPs within the alliance could be routed by overlay routing, and the other traffic would still be routed by BGP. As economic structure plays very important role in interdomain routing, so we propose an effective and fair charging and pricing scheme within the ISP alliance in correspondence with the overlay routing structure. Finally, we give a simple pricing algorithm, with which ISPs can find the optimal prices in the practice. By mathematical analysis and numerical experiments, we show the correctness and convergence of the pricing algorithm.

This paper presents a framework for reducing the energy consumption of embedded real-time systems. We implemented the presented framework as both an optimization toolchain and an energy-aware real-time operating system. The framework consists of the integration of multiple techniques to optimize the energy consumption. The main idea behind our approach is to utilize trade-offs between the energy consumption and the performance of different processor configurations during task checkpoints, and to maintain memory allocation during task context switches. In our framework, a target application is statically analyzed at both intra-task and inter-task levels. Based on these analyzed results, runtime optimization is performed in response to the behavior of the application. A case study shows that our toolchain and real-time operating systems have achieved energy reduction while satisfying the real-time performance. The toolchain has also been successfully applied to a practical application.

We applied a roll-to-sheet imprinting process to a large-scale substrate. Patterned ruthenium oxide (RuO$_{2}$) electrodes were fabricated on both glass and flexible substrates. The resistivity of the electrodes on a glass substrate was $3.5 imes 10^{-5} Omega $ cm, which indicates that this technique is useful for the fabrication of thin-film transistor (TFT) electrodes.

The amplitude damping (AD) quantum channel is one of the models describing evolution of quantum states. The construction of quantum error correcting codes for the AD channel based on classical codes has been presented, and Shor et al. proposed a class of classical codes over F3 which are efficiently applicable to this construction. In this study, we expand Shor's construction to that over F7, and succeeded to construct an AD code that has better parameters than AD codes constructed by Shor et al.

The combined linear frequency modulation continuous wave (LFMCW) and inverse synthetic aperture radar (ISAR) can be used for imaging long-distance targets because of its long-distance and high resolution imaging abilities. In this paper, we find and study the dechirp distortion phenomenon (DDP) for imaging long-distance targets by a dechirp-on-receive LFMCW radar. If the targets are very far from the radar, the maximum delay-time is not much smaller than a single sweep duration, and the dechirp distortion is triggered since the distance of the target is unknown in a LFMCW-ISAR system. DDP cannot be ignored in long-distance imaging because double images of a target appear in the frequency domain, which reduces resolution and degrades image quality. A novel LFMCW-ISAR signal model is established to analyze DDP and its negative effects on long-distance target imaging. Using the proportionately distributed energy of double images, the authors propose a method to correct dechirp distortion. In addition, the applicable scope of the proposed method is also discussed. Simulation results validate the theoretical analysis and the effectiveness of the proposed method.

In typical end-to-end recovery protocols, an ACK segment is delivered to a source node over a single path. ACK loss requires the source to retransmit the corresponding data packet. However, in underwater wireless sensor networks which prefer flooding-based routing protocols, the source node has redundant chances to receive the ACK segment since multiple copies of the ACK segment can arrive at the source node along multiple paths. Since existing RTO calculation algorithms do not consider inherent features of underlying routing protocols, spurious packet retransmissions are unavoidable. Hence, in this letter, we propose a new ACK loss-aware RTO calculation algorithm, which utilizes statistical ACK arrival times and ACK loss rate, in order to reduce such retransmissions.

A method to synthesize facial caricatures with non-planar expression is proposed. Several methods have been already proposed to synthesize facial caricatures automatically, but they mainly synthesize plane facial caricatures which look somewhat monotonous. In order to generate expressive facial caricature, the image should be expressed in non-planar style, expressing the depth of the face by shading and highlighting. In this paper, a new method to express such non-planar effect in facial caricatures is proposed by blending the grayscale information of the real face image into the plane caricature. Some methods also have been proposed to generate non-planar facial caricature, but the proposed method can adjust the degree of non-planar expression by interactive evolutionary computing, so that the obtained expression is satisfied by the user based on his/her subjective criteria. Since the color of the face looks changed, when the grayscale information of the natural face image is mixed, the color information of the skin area are also set by interactive evolutionary computing. Experimental results show the high performance of the proposed method.

In this paper, we evaluate a method of agile software development for carrier Cloud service platform development. It is generally said that agile software development is suitable for small-scale development, but we adopt it for the development which has more than 30 members. We attempted to enable automatic regression tests for each iteration when we adopted agile software development, so that we could start our Cloud service sufficiently fast. We compared and evaluated software reliability growth curves, regression test efforts and bug causes with waterfall development.

A global tone mapping operation (TMO) for high dynamic range (HDR) images with fixed-point arithmetic is proposed and evaluated in this paper. A TMO generates a low dynamic range (LDR) image from an HDR image by compressing its dynamic range. Since an HDR image is generally expressed in a floating-point data format, a TMO also deals with floating-point data even though a resultant LDR image is integer data. The proposed method treats a floating-point number as two 8-bit integer numbers which correspond to an exponent part and a mantissa part, and applies tone mapping to these integer numbers separately. Moreover, the method conducts all calculations in the tone mapping with only fixed-point arithmetic. As a result, the method reduces a memory cost and a computational cost. The evaluation shows that the proposed method reduces 81.25% of memory usage. The experimental results show that the processing speed of the proposed method with fixed-point arithmetic is 23.1 times faster than the conventional method with floating-point arithmetic. Furthermore, they also show the PSNR of LDR images obtained by the proposed method are comparable to those of the conventional method, though reducing computational and memory cost.

In this paper, we investigate unitary precoder design for multiple-input multiple-output (MIMO) multicasting, where multiple common data streams are sent to a group of users. Assuming that zero-forcing decision feedback equalizers (ZF-DFE) are adopted at the receiver side, we can convert the multicast channel into multiple parallel subchannels. To improve the receiving quality of all data streams, we focus on maximizing the minimal signal-to-noise ratio (SNR) of all data streams. To effectively handle this non-convex optimization problem, we first consider the special case of two data streams and derive the closed-form solution of the SNR vectors for both subchannels. Based on these results, a gradient-based iterative algorithm is developed for the proposed precoder design. For the general case, a Givens rotation-based iterative algorithm is proposed, where at each iteration the original problem of unitary precoder design is transformed into a dual-stream subproblem. Hence it can be solved efficiently by the gradient-based iterative algorithm. Finally, simulation results are presented to demonstrate the outstanding performance of the proposed design.

A simple, low reflection, and highly-efficient pilot-plant scale microwave irradiation reactor for woody biomass pretreatment was fabricated. Pretreatment is an essential process for effective bioethanol production. The fabricated reactor consists of 8 microwave irradiators which are attached to a metal pipe. The woody biomass mixture which contains water and organic acid flows through the metal pipe and is heated by microwaves at a total power of 12,kW. To design the microwave irradiators, we used a 3D Finite Element Method (FEM) simulator, which was based on the measured complex permittivity data of the woody biomass mixture. The simulation results showed that the reflection coefficient $|S_{11}|$ from the reactor was less than -30,dB when the woody biomass mixture temperature was between 30$^{circ}$C and 90$^{circ}$C. Finally, we experimentally confirmed that the fabricated irradiation reactor yielded a microwave absorption efficiency of 79%.

To lengthen the operational time of mobile devices, power must be managed effectively. To achieve this objective, a Discontinuous Reception (DRX) mechanism is proposed for use in the long-term evolution (LTE) network to enable user equipment (UE) to consume power efficiently. The DRX mechanism provides parameters related to base stations such as evolved Node B (eNB) to configure and manage the transition of UEs between idle (sleep) and active states. Although these parameters can be adjusted dynamically in cooperation with the traffic scheduler, a high signaling overhead and processing load might be introduced in practical deployment if the parameters are adjusted too frequently. In this study, to examine power-saving efficiency, distinct traffic types were scheduled that were constrained by various quality of service (QoS) factors without dynamically changing the DRX parameters. The concept of burst-based scheduling is proposed, based on considering the state transitions and channel conditions of each UE, to increase power-saving efficiency while concurrently satisfying the desired QoS. Both Hypertext Transfer Protocol (HTTP) and video-stream traffic models were exhaustively simulated to examine the performance of the proposed scheme and numerous scheduling alternatives were tested to compare the proposed scheme with other schemes. The simulation results indicate that video-streaming traffic is more sensitive to the scheduling schemes than HTTP traffic. The simulation results were further analyzed in terms of traffic scheduling and parameter adjustment and the analysis results can help design future studies on power management in the LTE network.

As the development of Internet-of-Things is moving towards large scale industry, such as logistic and manifacturing, there is a need for end-users to get involved in the process of creating IoT easily. In this paper, we introduce PaperIO, a paper-based 3D I/O interface, in which a single piece of paper can be sensed and actuated at the same time in three dimensions using the technology of selective inductive power transmission. With this technology, paper material with multiple embedded receivers, can not only selectively receive inductive power to perform paper-computing behavior, but also work as input sensors to communicate with power transmitter wirelessly. This technology allows the creation of paper-based sensor and actuators, and forms an Interent of Embedded Paper-craft. This paper presents the detailed implementation of the system, results of the technical experiments, and a few sample applications of the presented paper-based 3D I/O interface, and finally discusses the future plan of this research.

Cloud computing, a novel distributed paradigm to provide powerful computing capabilities, is usually adopted by developers and researchers to execute complicated IoT applications such as complex workflows. In this scenario, it is fundamentally important to make an effective and efficient workflow application scheduling and execution by fully utilizing the advantages of the cloud (as virtualization and elastic services). However, in the current stage, there is relatively few research for workflow scheduling in cloud environment, where they usually just bring the traditional methods directly into cloud. Without considering the features of cloud, it may raise two kinds of problems: (1) The traditional methods mainly focus on static resource provision, which will cause the waste of resources; (2) They usually ignore the performance fluctuation of virtual machines on the physical machines, therefore it will lead to the estimation error of task execution time. To address these problems, a novel mechanism which can estimate the probability distribution of subtask execution time based on background VM load series over physical machines is proposed. An elastic performance fluctuations-aware stochastic scheduling algorithm is introduced in this paper. The experiments show that our proposed algorithm can outperform the existing algorithms in several metrics and can relieve the influence of performance fluctuations brought by the dynamic nature of cloud.

This paper describes the design method of a broadband CMOS stacked power amplifier using harmonic control over wide bandwidths in a 0.11,$mu $m standard CMOS process. The high-efficiency can be obtained over wide bandwidths by designing a load impedance circuit as purely reactive as possible to the harmonics with broadband fundamental matching, which is based on continuous Class-F mode of operation. Furthermore, the stacked topology overcomes the low breakdown voltage limit of CMOS transistor and increases output impedance. With a 5-V supply and a fixed matching circuitry, the suggested power amplifier (PA) achieves a saturated output power of over 26.7,dBm and a drain efficiency of over 38% from 1.6,GHz to 2.2,GHz. In W-CDMA modulation signal measurements, the PA generates linear power and power added efficiency of over 23.5,dBm and 33% (@ACLR $=-33$,dBc).