In forthcoming sensor networks, a multitude of sensor nodes deployed over a large geographical area for monitoring traffic, climate, etc. are expected to become an inevitable infrastructure. Clustering algorithms play an important role in aggregating a large volume of data that are produced continuously by the huge number of sensor nodes. In such networks, equal-sized multi-hop clusters which include an equal number of nodes are useful for efficiency and resiliency. In addition, scalability is important in such large-scale networks. In this paper, we mathematically design a decentralized equal-sized clustering algorithm using a partial differential equation based on the Fourier transform technique, and then design its protocol by discretizing the equation. We evaluated through simulations the equality of cluster sizes and the resiliency against packet loss and node failure in two-dimensional perturbed grid topologies.

First, this paper derives the prefix sum-of-products expression (PreSOP) and the number of products in a PreSOP for an interval function. Second, it derives Ψ(n,τp), the number of n-variable interval functions that can be represented with τp products. Finally, it shows that more than 99.9% of the n-variable interval functions can be represented with ⌈ n - 1 ⌉ products, when n is sufficiently large. These results are useful for a fast PreSOP generator and for estimating the size of ternary content addressable memories (TCAMs) for packet classification.

This paper studies stabilization of uncertain systems over finite data rate and lossy channels. Limitations on data rate and packet loss probability are derived, characterized by the product of the eigenvalues of the plant. It is worth noting that even if we assume the most conservative plant dynamics, existing limitations for nominal plants are looser than those given in this paper. This fact implies that plant uncertainties cause strictly higher requirements in communication. We consider linear discrete-time systems with parametric uncertainties and employ uniform quantizers, which have the simplest quantization structure. Under the setup, a necessary condition and a sufficient condition for stability are derived. In particular, for scalar plants case, the conditions are exact. They coincide with the existing results for nominal plants as a special case and hence generalize them to the uncertain case.

Acoustic energy harvesters that function in environments where sound pressure is extremely high (150 dB), such as in engine rooms of aircraft, are expected to be capable of powering wireless health monitoring systems. This paper presents the power generation performance of a lead-zirconate-titanate (PZT) acoustic energy harvester with a vibrating PZT diaphragm. The diaphragm had a diameter of 2 mm, consisting of Al (0.1 µm)/PZT (1 µm)/Pt (0.1 µm)/Ti (0.1 µm)/SiO2 (1.5 µm). The harvester generated a power of 510-14 W under a sound pressure level of 110 dB at the first resonance frequency of 6.28 kHz. It was found that the generated power was increased to 2.010-13 W using a sound-collecting Helmholtz resonator cone with a height of 60 mm. The cone provided a Helmholtz resonance at 5.8 kHz, and the generated power increased from 9.710-15 W to 7.310-13 W at this frequency. The cone was also effective in increasing the bandwidth of the energy harvester.

An artificial fish swarm algorithm for solving symbolic regression problems is introduced in this paper. In the proposed AFSA, AF individuals represent candidate solutions, which are represented by the gene expression scheme in GEP. For evaluating AF individuals, a penalty-based fitness function, in which the node number of the parse tree is considered to be a constraint, was designed in order to obtain a solution expression that not only fits the given data well but is also compact. A number of important conceptions are defined, including distance, partners, congestion degree, and feature code. Based on the above concepts, we designed four behaviors, namely, randomly moving behavior, preying behavior, following behavior, and avoiding behavior, and present their respective formalized descriptions. The exhaustive simulation results demonstrate that the proposed algorithm can not only obtain a high-quality solution expression but also provides remarkable robustness and quick convergence.

High Efficiency Video Coding (HEVC) outperforms H.264 High Profile with bitrate saving of about 43%, mostly because block sizes for hybrid prediction and residual encoding are recursively chosen using a quadtree structure. Nevertheless, the exhaustive quadtree-based partition is not always necessary. This paper takes advantage of all-zero residual blocks at every quadtree depth to accelerate the prediction and residual encoding processes. First, we derive a near-sufficient condition to detect variable-sized all-zero blocks (AZBs). For these blocks, discrete cosine transform (DCT) and quantization can be skipped. Next, using the derived condition, we propose an early termination technique to reduce the complexity for motion estimation (ME). More significantly, we present a two-dimensional pruning technique based on AZBs to constrain prediction units (PU) that contribute negligibly to rate-distortion (RD) performance. Experiments on a wide range of videos with resolution ranging from 416240 to 4k2k, show that the proposed scheme can reduce computational complexity for the HEVC encoder by up to 70.46% (50.34% on average), with slight loss in terms of the peak signal-to-noise ratio (PSNR) and bitrate. The proposal also outperforms other state-of-the-art methods by achieving greater complexity reduction and improved bitrate performance.

We propose an efficient network design algorithm that realizes shared protection. The algorithm iteratively improves the degree of wavelength resource usage and fiber utilization. To achieve this, we newly define two metrics to evaluate the degree of wavelength resource usage of a pair of working/backup paths and the fiber utilization efficiency. The proposed method iteratively redesigns groups of paths that are selected in the order determined by the metrics. A numerical analysis verifies that the proposed algorithm can substantially reduce the required wavelength resources and hence fiber cost. It is also verified that the computational complexity of the proposed algorithm is small enough to terminate within practicable time.

Initial cell search in wideband code-division multiple-access (W-CDMA) systems is a challenging process. On the one hand, channel impairments such as multipath fading, Doppler shift, and noise create frequency and time offsets in the received signal. On the other hand, the residual synchronization error of the crystal oscillator at the mobile station also causes time and frequency offsets. Such offsets can affect the ability of a mobile station to perform cell search. Previous work concentrated on cell synchronization algorithms that considered multipath channels and frequency offsets, but ignored clock and timing offsets due to device tolerances. This work discusses a robust initial cell search algorithm, and quantifies its performance in the presence of frequency and time offsets due to two co-existing problems: channel impairments and clock drift at the receiver. Another desired performance enhancement is the reduction of power consumption of the receiver, which is mainly due to the computational complexity of the algorithms. This power reduction can be achieved by reducing the computational complexity by a divide and conquer strategy during the synchronization process.

In this paper, we study decentralized supervisory control of timed discrete event systems, where we adopt the OR rule for fusing local enablement decisions and the AND rule for fusing local enforcement decisions. For any specification language satisfying a certain assumption, we propose a method for constructing a decentralized supervisor that achieves its sublanguage. The proposed method does not require computing the achieved sublanguage.

A hybrid approach for the synthesis of square thinned arrays with low sidelobes is presented. The proposed method combines the advantages of a genetic algorithm and combinatorial technique-cyclic difference sets (CDSs). The peak sidelobe level (PSL) and the thinning factor are numerically evaluated to show the effectiveness and reliability of the proposed hybrid method. In the proposed GA-enhanced square arrays with the DS and the best CDS, reductions of the PSL, of 4.16 dB and 2.45 dB, respectively, were achieved as compared to the results of conventional rectangular DS and CDS arrays.

The paper describes how a robust and compact on-line handwritten Japanese text recognizer was developed by compressing each component of an integrated text recognition system including a SVM classifier to evaluate segmentation points, an on-line and off-line combined character recognizer, a linguistic context processor, and a geometric context evaluation module to deploy it on hand-held devices. Selecting an elastic-matching based on-line recognizer and compressing MQDF2 via a combination of LDA, vector quantization and data type transformation, have contributed to building a remarkably small yet robust recognizer. The compact text recognizer covering 7,097 character classes just requires about 15 MB memory to keep 93.11% accuracy on horizontal text lines extracted from the TUAT Kondate database. Compared with the original full-scale Japanese text recognizer, the memory size is reduced from 64.1 MB to 14.9 MB while the accuracy loss is only 0.5% from 93.6% to 93.11%. The method is scalable so even systems of less than 11 MB or less than 6 MB still remain 92.80% or 90.02% accuracy, respectively.

Novel joint motion-compensated interpolation using eight-neighbor block motion vectors (8J-MCI) is presented. The proposed method uses bi-directional motion estimation (BME) to obtain the motion vector field of the interpolated frame and adopts motion vectors of the interpolated block and its 8-neighbor blocks to jointly predict the target block. Since the smoothness of the motion vector filed makes the motion vectors of 8-neighbor blocks quite close to the true motion vector of the interpolated block, the proposed algorithm has the better fault-tolerancy than traditional ones. Experiments show that the proposed algorithm outperforms the motion-aligned auto-regressive algorithm (MAAR, one of the state-of-the-art frame rate up-conversion (FRUC) schemes) in terms of the average PSNR for the test image sequence and offers better subjective visual quality.

We present an optimization algorithm for the design of multilayer antireflection (AR) coatings for organic photovoltaic (OPV) cells. When a set of available materials for the AR films is given, the proposed method allows for searching the globally optimized AR structure that maximizes the short-circuit current density (JSC) under simulated solar light illumination (AM 1.5). By applying this method to an OPV solar cell with a configuration of Al/P3HT:PCBM/MoO3/ITO, we demonstrated that JSC can increase by 7.5% with a 6-layer AR coating, consisting of MgF2, ZnS, and Al2O3. A notable feature of this method is that it can find not only the optimal solution, which maximizes JSC , but also the quasi-optimal solutions, which increase JSC to nearly maximum levels. We showed that the quasi-optimal solution may have higher robustness against deviations in film thicknesses, from their designated values. This method indicates the importance of practically useful, non-optimal solutions for designing AR coatings. The present method allows for extending the user's choices and facilitates the realization of a practical design for an AR coating.

The quadtree-based variable block sized prediction makes the biggest contribution for dramatically improved coding efficiency in the new video coding standard named HEVC. However, this technique takes about 75–80% computational complexity of an HEVC encoder. This paper brings forward an adaptive scheme that exploits temporal, spatial and transform-domain features to speed up the original quadtree-based prediction, targeting at high resolution videos. Before encoding starts, analysis on utilization ratio of each coding depth is performed to skip rarely adopted coding depths at frame level. Then, texture complexity (TC) measurement is applied to filter out none-contributable coding blocks for each largest coding unit (LCU). In this step, a dynamic threshold setting approach is proposed to make filtering adaptable to videos and coding parameters. Thirdly, during encoding process, sum of absolute quantized residual coefficient (SAQC) is used as criterion to prune useless coding blocks for both LCUs and 3232 blocks. By using proposed scheme, motion estimation is performed for prediction blocks within a narrowed range. Experiments show that proposed scheme outperforms existing works and speeds up original HEVC by a factor of up to 61.89% and by an average of 33.65% for 4kx2k video sequences. Meanwhile, the peak signal-to-noise ratio (PSNR) degradation and bit increment are trivial.

Broadcast encryption scheme with personalized messages (BEPM) is a new primitive that allows a broadcaster to encrypt both a common message and individual messages. BEPM is necessary in applications where individual messages include information related to user's privacy. Recently, Fujii et al. suggested a BEPM that is extended from a public key broadcast encryption (PKBE) scheme by Boneh, Gentry, and Waters. In this paper, we point out that 1) Conditional Access System using Fujii et al.'s BEPM should be revised in a way that decryption algorithm takes as input public key as well, and 2) performance analysis of Fujii et al.'s BEPM should be done depending on whether the public key is transmitted along with ciphertext or stored into user's device. Finally, we propose a new BEPM that is transmission-efficient, while preserving O(1) user storage cost. Our construction is based on a PKBE scheme suggested by Park, Kim, Sung, and Lee, which is also considered as being one of the best PKBE schemes.

We present a new approach for sparse Cholesky factorization on a heterogeneous platform with a graphics processing unit (GPU). The sparse Cholesky factorization is one of the core algorithms of numerous computing applications. We tuned the supernode data structure and used a parallelization method for GPU tasks to increase GPU utilization. Results show that our approach substantially reduces computational time.

BLOCKSUM, also known as KEISANBLOCK in Japanese, is a Latin square filling type puzzle, such as Sudoku. In this paper, we prove that the decision problem whether a given instance of BLOCKSUM has a solution or not is NP-complete.

To support mobility, multihoming, routing scalability, and security, there are a lot of proposals based on ID/Locator split approach not only for the current Internet but also for the future Internet. However, none of them meet the requirements for practical operation such as (1) support heterogeneous network layer protocols, (2) scalability of ID/Locator mapping system, (3) independence of mapping information management, and (4) avoidance of locator leakage beyond the administrative boundary. This paper proposes a network layer protocol called Z Network Protocol (ZNP) for the future Internet based on the clean slate approach. ZNP supports heterogeneity of network layer protocols by “Internetworking with a Common ID Space”. Its mapping systems meet the requirements (1)–(4) described above. For manipulating the mapping systems, Z Control Message Protocol (ZCMP) is designed. For resolving the link layer (L2) address from the ZNP Locator, Z Neighbor Discovery Protocol (ZNDP) is designed. We implement ZNP and ZNDP in the Linux kernel, ZCMP in the user space and measure the times needed for transmission, reception, forwarding, and locator conversion. The results show the practicability of ZNP as a network layer protocol for the future Internet.

This paper presents a joint linear processing scheme for two-hop and half-duplex distributed amplify-and-forward (AF) relaying networks with one source, one destination and multiple relays, each having multiple antennas. By using the minimum mean-square error (MMSE) criterion and the Wiener filter principle, the joint relay and destination design with perfect channel state information (CSI) is first formulated as an optimization problem with respect to the relay precoding matrix under the constraint of a total relay transmit power. The constrained optimization with an objective to design the relay block-diagonal matrix is then simplified to an equivalent problem with scalar optimization variables. Next, it is revealed that the scalar-version optimization is convex when the total relay power or the second-hop SNR (signal to noise ratio) is above a certain threshold. The underlying optimization problem, which is non-convex in general, is solved by complementary geometric programming (CGP). The proposed joint relay and destination design with perfect CSI is also extended for practical systems where only the channel mean and covariance matrix are available, leading to a robust processing scheme. Finally, Monte Carlo simulations are undertaken to demonstrate the superior MSE (mean-square error) and SER (symbol error rate) performances of the proposed scheme over the existing relaying method in the case of relatively large second-hop SNR.

With the increased deployment of wireless sensor networks (WSNs) in location-based services, the need for accurate localization of sensor nodes is gaining importance. Sensor nodes in a WSN localize themselves with the help of anchors that know their own positions. Some anchors may be malicious and provide incorrect information to the sensor nodes. In this case, accurate localization of a sensor node may be severely affected. In this study, we propose a secure and lightweight localization method. In the proposed method, uncertainties in the estimated distance between the anchors and a sensor node are taken into account to improve localization accuracy. That is, we minimize the weighted summation of the residual squares. Simulation results show that our method is very effective for accurate localization of sensor nodes. The proposed method can accurately localize a sensor node in the presence of malicious anchors and it is computationally efficient.