We describe in this paper our experience of developing a large-scale, highly distributed multi-agent system using wireless-networked sensors. We provide solutions to the problems of localization (position estimation) and dynamic, real-time mobile object tracking, which we call PET problems for short, using wireless sensor networks. We propose system architectures and a set of distributed algorithms for organizing and scheduling cooperative computation in distributed environments, as well as distributed algorithms for localization and real-time object tracking. Based on these distributed algorithms, we develop and implement a hardware system and software simulator for the PET problems. Finally, we present some experimental results on distance measurement accuracy using radio signal strengths of the wireless sensors and discuss future work.

Interoperability between different systems is becoming a more important issue for open distributed systems. In this paper, we investigate what kind of framework we need for constructing open distributed systems. Firstly, we enumerate the features and functions which the framework should have. We then evaluate a proposed multi-agent framework, Bee-gent, by using a typical example of open distributed systems. Lastly, we show clearly what is required for such a framework.

Autonomous distributed manufacturing systems (ADMS) consist of multiple intelligent components with each component acting according to its own judgments. The ADMS objective is to realize more agile and adaptive manufacturing systems. This paper presents the introduction of context-dependent agents (CDAs) in ADMS that switch strategies depending on system conditions to achieve better performance than can be realized by agents that use the same strategies under all system conditions. For the real-time job scheduling problem, the paper presents a basic CDA architecture and the results of an extensive empirical evaluation of its performance relative to other rule-based schemes based on several common indices for real-time dispatch.

Model checking is a technique that can make a verification for finite state systems absolutely automatic. We propose a method for automatic verification of fault-tolerant concurrent systems using this technique. Unlike other related work, which is tailored to specific systems, we are aimed at providing an approach that can be used to verify various kinds of systems against fault tolerance. The main obstacle in model checking is state explosion. To avoid the problem, we design this method so that it can use a symbolic model checking tool called SMV (Symbolic Model Verifier). Symbolic model checking can overcome the problem by expressing the state space and the transition relation by Boolean functions. Assuming that a system to be verified is modeled as a guarded command program, we design a modeling language and propose a translation method from the modeling language to the input language of SMV. We show the results of applying the proposed method to various examples to demonstrate the feasibility of the method.

In this paper, we consider a flexible method for designing n-entities communication protocols and services. The proposed technique considers alternative and parallel composition of n service specifications and n protocol specifications, where n 2. The specifications are specified in Basic LOTOS which is a Formal Description Technique (FDT). We use the weak bisimulation equivalence () to represent the correctness properties between the service specification and the protocol specification.

A siphon-trap of a Petri net N is defined as a place set S with ^・S = S^・, where ^・S = { u| N has an edge from u to a vertex of S} and S^・ = { v| N has an edge from a vertex of S to v}. A minimal siphon-trap is a siphon-trap such that any proper subset is not a siphon-trap. The following polynomial-time algorithms are proposed: (1) FDST for finding, if any, a minimal siphon-trap or even a maximal class of mutually disjoint minimal siphon-traps of a given Petri net; (2) FDST_i that repeats FDST i times in order to extract more minimal siphon-traps than FDST. (3) STFM_T (STFM_T_i, respectively) which is a combination of the Fourier-Motzkin method and FDST (FDST_i) and which has high possibility of finding, if any, at least one minimal-support nonnegative integer invariant.

In this paper, we clarify the properties of the contract net protocol based on its formal specification. To specify the contract net protocol, we propose a formal specification method for an agent system. In this method, agents are modeled as communicating finite state machines. To deal with the behavior of agents and its time passage explicitly, we incorporate the concept of time into the communicating finite state machine. The contract net protocol is specified based on the specification method proposed in this paper. From the specification, we analyze the possibility about agent deadlock and its avoidance solution.

Finite-state vector quantization (FSVQ) is a well-known block encoding technique for digital image compression at low bit rate application. In this paper, an improved feature map finite-state vector quantization (IFMFSVQ) algorithm using three-sided side-match prediction is proposed for image coding. The new three-sided side-match improves the prediction quality of input blocks. Precoded blocks are used to alleviate the error propagation of side-match. An edge threshold is used to classify the blocks into nonedge or edge blocks to improve bit rate performance. Furthermore, an adaptive method is also obtained. Experimental results reveal that the new IFMFSVQ reduces bit rate significantly maintaining the same subjective quality, as compared to the basic FMFSVQ method.

An efficient algorithm is proposed for finding all dc solutions of piecewise-linear (PWL) circuits. This algorithm is based on a powerful test (termed the LP test) for nonexistence of a solution to a system of PWL equations in a given region using the dual simplex method. The proposed algorithm also uses a special technique that decreases the number of regions on which the LP test is performed. By numerical examples, it is shown that the proposed algorithm could find all solutions of large scale problems, including those where the number of variables is 500 and the number of linear regions is 10⁵⁰⁰, in practical computation time.

To design a high-speed m-bit parallel inversion circuit over GF(2^m), we study two variations for the repetition-operation of the numerical formula, AB², in employing square-first and multiply-first type operations. From the proposed two variations, we propose four inversion architectures, adopting the multiplier and square in [10], as follows: simple duplication semi-systolic architecture for multiply-first inversion circuit (MFIC), m-bit parallel semi-systolic architecture for MFIC, simple duplication semi-systolic architecture for square-first inversion circuit (SFIC), and simplified m-bit parallel semi-systolic architecture for SFIC. Among them, performance of the simplified m-bit parallel semi-systolic architecture for SFIC is recommended for a high-speed applications to get a maximum throughput in the sense of small hardware-complexity, and low latency. When we implement the simplified 8-bit parallel semi-systolic architecture for SFIC over GF(2⁸) by using 0.25 µm CMOS library, necessary are 2495 logic-gates and 1848 latches, and the latency is 56 and the estimated clock-rate is 580 MHz at 100% throughput.

The main contribution of this work is to propose energy-efficient protocols that compute the sum of n numbers over any commutative and associative binary operator stored in n wireless sensor nodes arranged in a two-dimensional grid of size nn. We first present a protocol that computes the sum on a Wireless Sensor Network (WSN) in O(r²+(n/r²)^1/3) time slots with no sensor node being awake for more than O(1) time slots, where r is the transmission range of the sensor nodes. We then go on to present a fault-tolerant protocol which computes the sum in the same number of time slots with no sensor node being awake for more than O(log r) time slots. Finally, we show that in a WSN where the sensor nodes are empowered with the ability to dynamically adjust their transmission range r during the execution of the protocol, the sum can be computed in O(log n) time slots and no sensor node needs to awake for more than O(log n) time slots.

A digital watermarking method for moving pictures is proposed in which a watermark can be retrieved from an MPEG bitstream directly. In the proposed method, the watermark is embedded in multiple frames of an original moving picture, and it is detected statistically using multiple frames. Embedding is based on the modification of DCT coefficients that are in the chosen pixel blocks in each video frame. These pixel blocks are chosen differently per video frame in order to avoid regularity and periodicity. The features of the proposed method are that it does not need the original picture nor MPEG decoding processing. The proposed method is evaluated through various attacks including MPEG encoding and StirMark tools. It is shown that the watermark can survive MPEG encoding and frequency domain attacks. The reliability of watermark retrieval is also discussed in terms of statistical test.

DS/CDMA systems employing long-period PN sequences are becoming a widespread standard of wireless communication systems. However, fast acquisition of long-period PN sequences at a low hardware cost is conventionally a difficult problem. This paper proposes a new fast acquisition algorithm for a class of PN sequences, which includes m- and GMW sequences as special cases, and shows that the mean (correct) acquisition time can be considerably reduced under input SNR values well below those used in modern DS/CDMA systems. Its fast acquisition capability is based on a decomposition of long PN sequences into a number of short ones and achieves a significantly reduced code phase uncertainty of acquisition at relatively small hardware cost. It can be applied as a (part of) acquisition system of a DS/CDMA system instead of a slow sliding correlator or a costly matched filter.

We study the optimal transmission strategy of a multiple-input multiple-output (MIMO) communication system with covariance feedback. We assume that the receiver has perfect channel state information while the transmitter knows only the channel covariance matrix. We consider the common downlink transmission model where the base station is un-obstructed while the mobile station is surrounded by local scatterer. Therefore the channel matrix is modeled with Gaussian complex random entries with independent identically distributed rows and correlated columns. For this transmission scenario the capacity achieving eigenvectors of the transmit covariance matrix are known. The capacity achieving eigenvalues can not be computed easily. We analyze the optimal transmission strategy as a function of the transmit power. A MIMO system using only one eigenvalue performs beamforming. We derive a necessary and sufficient condition for when beamforming achieves capacity. The theoretical results are illustrated by numerical simulations.

This letter presents text-independent speaker identification results for telephone speech. A speaker identification system based on Karhunen-Loeve transform (KLT) derived from codebook design using genetic algorithm (GA) is proposed. We have combined genetic algorithm (GA) and the vector quantization (VQ) algorithm to avoid typical local minima for speaker data compression. Identification accuracies of 91% were achieved for 100 Mandarin speakers.

This letter presents a new approximation algorithm suitable for Taylor series expansion. The algorithm can effectively reduce the approximation error by using only a small number of terms in series expansion. The proposed algorithm can be more easily implemented and has better performance than the conventional Euler approximation algorithm. Also, the approximation performance of the proposed algorithm is compared with direct approaches, such as least-squares and Chebyshev approximation algorithm to show the relative advantages of the proposed algorithm. This letter also presents an application example of the proposed approximation algorithm in carrier recovery of OFDM (Orthogonal Frequency Division Multiplexing) modem.

The present study introduces the adaptive BPF to the BPSK coherent detection system and the characteristic of the resulting system is investigated.

This paper presents a flexible learning algorithm for the binary neural network that can realize a desired Boolean function. The algorithm determines hidden layer parameters using a genetic algorithm. It can reduce the number of hidden neurons and can suppress parameters dispersion. These advantages are verified by basic numerical experiments.

To secure the interactive multimedia applications in WLANs (wireless local area networks), it is pertinent to implement a number of security services such as authentication, key exchange and real-time encryption/decryption. The implementation of those security services in WLANs presents a complex and challenging environment because these services may deplete the limited network resources and increases the burden of supporting the quality of service for multimedia applications. As an alternative solution, we thus introduce a new security system, which is based on RCNC (Random Connection Node Convolutional) code and M-sequence. The architecture of RCNC code formed by developing the conventional convolutional code structure has an excellent security operation as well as an error correction function. To verify the performance of our proposed system, the computer simulations have been performed in IEEE 802.11b environment.

In this letter, our proposed approach exploits the use of original and simplest Cellular Neural Network (CNN) for 2D Doubly Complementary (DC) Infinite Impulse Response (IIR) filter banks design. The properties of feedback and feedforward templates are studied for this purpose. Through some examples it is shown how generalizations of these templates can be used for DC IIR filter banks design. We modify Lagrangian function which is used for optimizing a low-pass filter design considering the constraint for stability of CNN. The brief conclusions with design examples that illustrate the proposed method and an image enhancement and restoration applications of designed filter banks are presented.

In this letter, we propose a two-stage object-based error-concealment technique for MPEG-2 video transmitted in a burst-packet-loss environment. A burst packet loss typically destroys a large area of MPEG-2 coded video. In the first stage, the missing area is intra-picture estimated and concealed in terms of a region-based approach. In the second stage, irregular-moving objects with respect to the background are identified and compensated from the predictive picture. As compared with conventional concealment approaches, the proposed method achieves better PSNR performance and reduces the visual artifacts.