Power consumption is one of the most important factors in successfully designing of wireless sensor networks since it directly affects network lifetime. We propose a topology control scheme that reduces power consumption by minimizing, as much as possible, the number of active nodes, in a highly dense region as well as to decrease packet transmission delay. Simulation results show that our scheme can effectively solve the energy inefficiency problem caused by unbalanced power consumption, and can significantly reduce packet transmission delay.

We propose a novel epidemic routing policy, named energy optimal epidemic routing, for delay tolerant networks (DTNs). By investigating the tradeoff between delay and energy, we found the optimal transmission range as well as the optimal number of infected nodes for the minimal energy consumption, given a delivery requirement, specifically delay bound and delivery probability to the destination. We derive an analytic model of the Binary Spraying routing to find the optimal values, describing the delay distributions with respect to the number of infected nodes.

This paper presents an efficient algorithm for incremental buffer insertion and module resizing for a full-placed floorplan. Our algorithm offers a method to use the white space in a given floorplan to resize modules and insert buffers, and at the same time keeps the resultant floorplan as close to the original one as possible. Both the buffer insertion and module resizing are modeled as geometric programming problems, and can be solved extremely efficiently using new developed solution methods. The experimental results suggest that the the wire length difference between the initial floorplan and result are quite small (less than 5%), and the global structure of the initial floorplan are preserved very well.

We report the growth of carbon nanofibers (CNFs) from carbon particles by chemical vapor deposition (CVD) with ultrasonic neblizer using ethanol as carbon source. Dense CNFs having diameters of several tens of nanometers have been successfully synthesized by the CVD without using any metal catalysts. The carbon particles formed from decompostion of fullerene were found to be suitable for the synthesis of CNFs. Details of the optimum conditions for producing CNFs and the expected growth mechanism are also described.

This paper describes an incremental parser based on an adjoining operation. By using the operation, we can avoid the problem of infinite local ambiguity. This paper further proposes a restricted version of the adjoining operation, which preserves lexical dependencies of partial parse trees. Our experimental results showed that the restriction enhances the accuracy of the incremental parsing.

An extreamly large scale periodic array antenna is required for transmitting power from space solar power systems. Analysis of the huge-scale array antenna is important to estimate the radiation property of the array antenna, but a full-wave analysis requires too much computer memory and excessive CPU time. In order to overcome these difficulties, the impedance extension method is proposed as a method of approximate analysis for huge periodic array antennas. From the results of actual gain pattern obtained by the proposed method and its relative error, it is shown that edge effects of a huge-scale array antenna can be ignored in calculating the radiation property.

OFDM (Orthogonal Frequency Division Multiplexing) is widely used in wideband wireless communication systems due to its excellent performance. One of the most important operations in OFDM receivers is preamble detection. This paper addresses a general form of extended differential detection methods, which is a combination of differential detection and a moving average filter. This paper also presents a filter size determination method that achieves satisfactory performance in various channel environments.

A metallic waveguide that has an array of dielectric rods located at a distance from the side wall of approximately one quarter the waveguide width was previously proposed for single mode propagation over a wide frequency range. In this study, the S parameters of such a waveguide were measured for the TE10 mode.

In this paper, the issue of carrier frequency offset (CFO) compensation in interleaved orthogonal frequency division multiple access (OFDMA) uplink system is investigated. To mitigate the effect of multiple access interference (MAI) caused by CFOs of different users, a new parallel interference cancellation (PIC) compensation algorithm is proposed. This scheme uses minimum mean square error (MMSE) criterion to obtain the estimation of interference users, then circular convolutions are employed to restore MAI and compensate CFO. To tackle the complexity problem of circular convolutions, an efficient MAI restoration and cancellation method is developed. Simulations illustrate the good performance and low computational complexity of the proposed algorithm.

The need for data encryption that protects sensitive data in a database has increased rapidly. However, encrypted data can no longer be efficiently queried because nearly all of the data should be decrypted. Several order-preserving encryption schemes that enable indexes to be built over encrypted data have been suggested to solve this problem. They allow any comparison operation to be directly applied to encrypted data. However, one of the main disadvantages of these schemes is that they expose sensitive data to inference attacks with order information, especially when the data are used together with unencrypted columns in the database. In this study, a new order-preserving encryption scheme that provides secure queries by hiding the order is introduced. Moreover, it provides efficient queries because any user who has the encryption key knows the order. The proposed scheme is designed to be efficient and secure in such an environment. Thus, it is possible to encrypt only sensitive data while leaving other data unencrypted. The encryption is not only robust against order exposure, but also shows high performance for any query over encrypted data. In addition, the proposed scheme provides strong updates without assumptions of the distribution of plaintext. This allows it to be integrated easily with the existing database system.

This paper proposes an architecture of an interference canceller for satellite communications with super-posed transmission, which is applicable not only to QPSK but also to 16QAM transmission to get higher satellite capacity. We implement it as an FPGA-based prototype and verify its performance. We propose here to use a new method to measure the satellite round-trip delay using an extended matched filter (EMF), which can work in low C/N conditions such as 0 dB and under. Given this performance, our canceller can work in a network in which forward and reverse links have the same power level. The results of the laboratory tests for QPSK show that interference can be suppressed by about 30 dB and that the BER degradation due to the canceller was small enough for operation.

While the problem of multicast routing and wavelength assignment (MC-RWA) in optical wavelength division multiplexing (WDM) networks has been investigated, relatively few researchers have considered network survivability for multicasting. This paper provides an optimization framework to solve the MC-RWA problem in a multi-fiber WDM network that can recover from a single-link failure with shared protection. Using the light-tree (LT) concept to support multicast sessions, we consider two protection strategies that try to reduce service disruptions after a link failure. The first strategy, called light-tree reconfiguration (LTR) protection, computes a new multicast LT for each session affected by the failure. The second strategy, called optical branch reconfiguration (OBR) protection, tries to restore a logical connection between two adjacent multicast members disconnected by the failure. To solve the MC-RWA problem optimally, we propose an integer linear programming (ILP) formulation that minimizes the total number of fibers required for both working and backup traffic. The ILP formulation takes into account joint routing of working and backup traffic, the wavelength continuity constraint, and the limited splitting degree of multicast-capable optical cross-connects (MC-OXCs). After showing some numerical results for optimal solutions, we propose heuristic algorithms that reduce the computational complexity and make the problem solvable for large networks. Numerical results suggest that the proposed heuristic yields efficient solutions compared to optimal solutions obtained from exact optimization.

Incremental Redundancy Hybrid ARQ (IR-HARQ) based on rate-compatible punctured low-density parity-check (LDPC) codes can achieve high throughput over a wide range of SNRs. One drawback of such IR-HARQ schemes is high computational complexity of decoding for early transmission at high rates. In order to overcome this problem, a HARQ scheme based on rate-compatible LDPC codes by shortening and extending is presented in this paper. In the HARQ scheme, a high-rate mother code is transmitted at first, and parity-bits of a shortened code are transmitted for early retransmission requests. With a low-complexity decoder of the high-rate mother code, this shortened-code approach would result in low computational complexity of decoding, but it causes smaller length and larger number of shortened codes to be decoded as retransmission repeats. To prevent the resultant degradation of performance and complexity, extending is efficiently applied to the shortened codes after predetermined retransmission-times. A multi-edge type code-design is employed to construct irregular LDPC codes that meet the requirement of the HARQ scheme. Simulation results show that the HARQ scheme can achieve lower computational complexity of decoding than a conventional IR-HARQ scheme with good throughput over a wide range of SNRs.

We investigate and propose the utilization of regenerative and non-regenerative relaying terminals in downlink cooperative MIMO communications, such as in base-station/router-relay-user transmission under different schemes. The source is equipped with multiple antennas, while the relays and destination are single-antenna terminals. From the source to the relays, symbols are transmitted using MIMO spatial-multiplexing technique. Depending on the type of relaying scheme, the relays either fully decode or amplify the received signal before retransmitting it to the destination using simple TDM transmission or Alamouti's space-time coding. We show that the proposed system realizes MIMO performance in single-antenna system environment, and performance-wise it is superior to existing transmission schemes, especially in low-SNR conditions. Furthermore, the proposed system is shown to give a diversity order of N-M+1, similar to that of MIMO V-BLAST system.

The characteristics of a left-handed traveling-wave transistor, which is formulated as two composite right- and left-handed (CRLH) transmission lines with both passive and active couplings, are discussed for generating unattenuated waves having left-handedness. The design criteria for convective instability are described, together with results of numerical calculations that solve the transmission equation for the device.

This paper presents a prototype group modem for a hyper-multipoint data gathering satellite communication system. It can handle arbitrarily and dynamically assigned FDMA signals by employing a novel FFT-type block demultiplexer/multiplexer. We clarify its configuration and operational principle. Experiments show that the developed modem offers excellent performance.

The minimum initial marking problem of Petri nets (MIM) is defined as follows: "Given a Petri net and a firing count vector X, find an initial marking M0, with the minimum total token number, for which there is a sequence δ of transitions such that each transition t appears exactly X(t) times in δ, the first transition is enabled at M0 and the rest can be fired one by one subsequently." In a production system like factory automation, economical distribution of initial resources, from which a schedule of job-processings is executable, can be formulated as MIM. AAD is known to produce best solutions among existing algorithms. Although solutions by AMIM+ is worse than those by AAD, it is known that AMIM+ is very fast. This paper proposes new heuristic algorithms AADO and AMDLO, improved versions of existing algorithms AAD and AMIM+, respectively. Sharpness of solutions or short CPU time is the main target of AADO or AMDLO, respectively. It is shown, based on computing experiment, that the average total number of tokens in initial markings by AADO is about 5.15% less than that by AAD, and the average CPU time by AADO is about 17.3% of that by AAD. AMDLO produces solutions that are slightly worse than those by AAD, while they are about 10.4% better than those by AMIM+. Although CPU time of AMDLO is about 180 times that of AMIM+, it is still fast: average CPU time of AMDLO is about 2.33% of that of AAD. Generally it is observed that solutions get worse as the sizes of input instances increase, and this is the case with AAD and AMIM+. This undesirable tendency is greatly improved in AADO and AMDLO.

Invariants of Petri nets are fundamental algebraic characteristics of Petri nets, and are used in various situations, such as checking (as necessity of) liveness, boundedness, periodicity and so on. Any given Petri net N has two kinds of invariants: a P-invariant is a |P|-dimensional vector Y with Yt A = and a T-invariant is a |T|-dimensional vector X with A X = for the place-transition incidence matrix A of N. T-invariants are nonnegative integer vectors, while this is not always the case with P-invariants. This paper deals only with nonnegative integer invariants (invariants that are nonnegative vectors) and shows results common to the two invariants. For simplicity of discussion, only P-invariants are treated. The Fourier-Motzkin method is well-known for computing all minimal support integer invariants. This method, however, has a critical deficiency such that, even if a given Perti net N has any invariant, it is likely that no invariants are obtained because of an overflow in storing intermediate vectors as candidates for invariants. The subject of the paper is to give an overview and results known to us for efficiently computing minimal-support nonnegative integer invariants of a given Petri net by means of the Fourier-Motzkin method. Also included are algorithms for efficiently extracting siphon-traps of a Petri net.

This paper presents a reconfigurable SAD Tree (RSADT) architecture based on adaptive sub-sampling algorithm for HDTV application. Firstly, to obtain the the feature of HDTV picture, pixel difference analysis is applied on each macroblock (MB). Three hardware friendly sub-sampling patterns are selected adaptively to release complexity of homogeneous MB and keep video quality for texture MB. Secondly, since two pipeline stages are inserted, the whole clock speed of RSADT structure is enhanced. Thirdly, to solve data reuse and hardware utilization problem of adaptive algorithm, the RSADT structure adopts pixel data organization in both memory and architecture level, which leads to full data reuse and hardware utilization. Additionally, a cross reuse structure is proposed to efficiently generate 16 pixel scaled configurable SAD (sum of absolute difference). Experimental results show that, our RSADT architecture can averagely save 61.71% processing cycles for integer motion estimation engine and accomplish twice or four times processing capability for homogeneous MBs. The maximum clock frequency of our design is 208 MHz under TSMC 0.18 µm technology in worst work conditions(1.62 V, 125C). Furthermore, the proposed algorithm and reconfigurable structure are favorable to power aware real-time encoding system.

This paper focuses on fusion estimation algorithms weighted by matrices and scalars, and relationship between them is considered. We present new algorithms that address the computation of matrix weights arising from multidimensional estimation problems. The first algorithm is based on the Cholesky factorization of a cross-covariance block-matrix. This algorithm is equivalent to the standard composite fusion estimation algorithm however it is low-complexity. The second fusion algorithm is based on an approximation scheme which uses special steady-state approximation for local cross-covariances. Such approximation is useful for computing matrix weights in real-time. Subsequent analysis of the proposed fusion algorithms is presented, in which examples demonstrate the low-computational complexity of the new fusion estimation algorithms.