The module-wise dynamic voltage and frequency scaling (MDVFS) scheme is applied to a single-chip H.264/MPEG-4 audio/visual codec LSI. The power consumption of the target module with controlled supply voltage and frequency is reduced by 40% in comparison with the operation without voltage or frequency scaling. The consumed power of the chip is 63 mW in decoding QVGA H.264 video at 15 fps and MPEG-4 AAC LC audio simultaneously. This LSI keep operating continuously even during the voltage transition of the target module by introducing the newly developed dynamic de-skewing system (DDS) which watches and control the clock edge of the target module.

We propose two sequence design schemes for an overloaded space-time spreading system with multiple antennas. One scheme is for a system in which the amplitude of user signals needs not be adjusted and provides tradeoffs between the user capacity and diversity order. This scheme has a certain similarity to time-sharing, but its performance is further improved by time-diversity. Another is to achieve full diversity order by varying user signal amplitudes. The diversity orders of the respective schemes are theoretically proved and their performances are demonstrated by simulation.

In this letter, we propose adaptive linear detectors in space-time block coded multiuser systems, by exploiting a particular property of the minimum mean square error multiuser detector. The proposed scheme can provide much faster convergence than the existing adaptive scheme [5] and so lower the system overhead requirements.

In this paper, we describe a new interface for a barge-in free spoken dialogue system combining multichannel sound field control and beamforming, in which the response sound from the system can be canceled out at the microphone points. The conventional method inhibits a user from moving because the system forces the user to stay at a fixed position where the response sound is reproduced. However, since the proposed method does not set control points for the reproduction of the response sound to the user, the user is allowed to move. Furthermore, the relaxation of strict reproduction for the response sound enables us to design a stable system with fewer loudspeakers than those used in the conventional method. The proposed method shows a higher performance in speech recognition experiments.

We have clarified both theoretically and experimentally the basic performance of distributed Raman amplification (DRA) transmission systems in trunk networks with DSF or SMF spans with limited pump power where the pump power is limited by practical considerations. The gain and noise characteristics of a fiber span with splice loss are accurately determined by employing three approximation models. A novel pumping scheme called band enhanced pumping (BEP) is proposed that improves the DRA gain and optical SNR (OSNR) by 1.5 and 0.55 dB, respectively, compared with those of a conventional pumping scheme, under typical system conditions. We show that a DRA system with a DSF span has OSNRs that are 2.1 and 2.9 dB higher than those of a system with an SMF span at limited pump powers of 200 and 400 mW, respectively, as typical examples.

Lee et al. recently proposed the first identity-based key agreement protocols for a multiple PKG environment where each PKG has different domain parameters in ICCSA 2005. However, this letter demonstrates that Lee et al.'s scheme does not include the property of implicit key authentication which is the fundamental security requirement, making it vulnerable to an impersonation attack.

This paper proposes novel methods to provide intelligence for characters in fighting action games by using neural networks. First, how a character learns basic game rules and matches against randomly acting opponents is considered. Since each action takes more than one time unit in general fighting action games, the results of a character's action are exposed not immediately but several time units later. We evaluate the fitness of a decision by using the relative score change caused by the decision. Whenever the scores of fighting characters are changed, the decision causing the score change is identified, and then the neural network is trained by using the score difference and the previous input and output values which induced the decision. Second, how to cope more properly with opponents that act with predefined action patterns is addressed. The opponents' past actions are utilized to find out the optimal counter-actions for the patterns. Lastly, a method in order to learn moving actions is proposed. To evaluate the performance of the proposed algorithm, we implement a simple fighting action game. Then the proposed intelligent character (IC) fights with the opponent characters (OCs) which act randomly or with predefined action patterns. The results show that the IC understands the game rules and finds out the optimal counter-actions for the opponents' action patterns by itself.

Mobile applications require software reconfiguration to improve resource usage and availability. We propose a power-aware reconfiguration scheme that (1) moves energy-demanding applications to proxy servers, and (2) adjusts the fidelity of mobile applications as resources diminish. We formulate a cooperative reconfiguration plan which determines when, where, and which components should be deployed and have their fidelity controlled, so as to minimize the power consumption of mobile devices and to utilize the system resources of servers efficiently. We then construct a graph-theoretic model of the cost of migrating components to one proxy server or to a cluster of servers. In this model, changes to the residual energy of mobile devices, available server resources, and the wireless network bandwidth can all accelerate or decelerate the migration and fidelity control of applications. We suggest an approximation algorithm that achieves a near-optimal solution in terms of energy consumption. Our proposal will support mobile applications which require large amount of computation and need to maintain their services for an extended time such as video conferencing, multimedia e-mail, and real-time navigation. Simulation-based experiments verify that our scheme is an efficient way to extend the battery life of mobile devices and to improve the response time of mobile applications.

We consider a network, where a special data called certificate is issued between two users, and all certificates issued by the users in the network can be represented by a directed graph. For any two users u and v, when u needs to send a message to v securely, v's public-key is needed. The user u can obtain v's public-key using the certificates stored in u and v. We need to disperse the certificates to the users such that when a user wants to send a message to the other user securely, there are enough certificates in them to get the reliable public-key. In this paper, when a certificate graph and a set of communication requests are given, we consider the problem to disperse the certificates among the nodes in the network, such that the communication requests are satisfied and the total number of certificates stored in the nodes is minimized. We formulate this problem as MINIMUM CERTIFICATE DISPERSAL (MCD for short). We show that MCD is NP-Complete, even if its input graph is restricted to a strongly connected graph. We also present a polynomial-time 2-approximation algorithm MinPivot for strongly connected graphs, when the communication requests satisfy some restrictions. We introduce some graph classes for which MinPivot can compute optimal dispersals, such as trees, rings, and some Cartesian products of graphs.

Clustering is an effective self-organization approach in wireless sensor networks. LEACH--a representative distributed clustering scheme has been considered an effective model to offer energy-efficient communication for sensor networks. However, its randomness may result in faster death of some nodes i.e. shorten system life. In this letter, we first analyze the reasons why the uncertainty in LEACH degrades system life, and then present a distributed clustering algorithm based on an adaptive backoff strategy. Simulation experiments illustrate that our algorithm is able to significantly prolong system life compared with LEACH.

A simple self-biased receiver system with a dual branch architecture consisting of a low-power consumption receiver and a rectenna is introduced. The system is efficiently integrated with a dual-fed circular sector antenna with harmonic rejection characteristics without a BPF. The receiver portion is designed by utilizing a low-noise amplifier (LNA) with low power consumption and a self-heterodyne mixer, while the rectenna achieves high conversion efficiency up to 80%, thanks to the harmonic rejection of the circular sector antenna. The rectified DC power from the rectenna is applied for a bias of the receiver without any external bias. Simultaneously, an ASK digital signal demodulation without an extra power supply are implemented successfully.

Admission control is becoming an essential technique for IP networks to provide full-fledged multimedia streaming services. Although signaling-based schemes are utilized to achieve this, these are difficult to deploy and can hardly achieve strict admission control taking the properties of packet arrival into consideration. In this paper, we propose a novel admission control strategy called the Tentative Accommodating and Congestion Confirming Strategy (TACCS). The main idea is to accommodate incoming flows tentatively and confirm congestion after a certain period. Since tentative accommodating enables us to generate the same situation as where incoming flows have been accommodated, TACCS makes it possible to control admission considering the properties of packet arrival after they have been accommodated, without collecting resource information in advance. From the results of mathematical analysis, we confirmed that TACCS enabled a domain to control admission without a centralized management agent and we provided guidelines for configuring parameters of TACCS.

The paper presents an adaptive algorithm named adaptive threshold nonlinear algorithm for use in adaptive filters in the complex-number domain (c-ATNA) in applications to digital QAM systems. Although the c-ATNA is very simple to implement, it makes adaptive filters highly robust against impulse noise and at the same time it ensures filter convergence as fast as that of the well-known LMS algorithm. Analysis is developed to derive a set of difference equations for calculating transient behavior as well as steady-state performance. Experiment with simulations and theoretical calculations for some examples of filter convergence in the presence of Contaminated Gaussian Noise demonstrates that the c-ATNA is effective in combating impulse noise. Good agreement between simulated and theoretical convergence proves the validity of the analysis.

This paper presents a method of predicting future human driving behavior under the condition that its resultant behavior and past observations are given. The proposed method makes use of a dynamic Bayesian network and the junction tree algorithm for probabilistic inference. The method is applied to behavior prediction for a vehicle assumed to stop at an intersection. Such a predictive system would facilitate warning and assistance to prevent dangerous activities, such as red-light violations, by allowing detection of a deviation from normal behavior.

Given the availability of high-speed Ethernet and HW based protocol offload, clustered systems using a commodity network fabric (e.g., TCP/IP over Ethernet) are expected to become more attractive for a range of e-business and data center applications. In this paper, we describe a comprehensive simulation to study the performance of clustered database systems using such a fabric. The simulation model currently supports both TCP and SCTP as the transport protocol and models an Oracle 9i like clustered DBMS running a TPC-C like workload. The model can be used to study a wide variety of issues regarding the performance of clustered DBMS systems including the impact of enhancements to network layers (transport, IP, MAC), QoS mechanisms or latency improvements, and cluster-wide power control issues.

This paper proposes new candidate one-way functions constructed with a certain type of endomorphisms on non-supersingular elliptic curves. We can show that the one-wayness of our proposed functions is equivalent to some special cases of the co-Diffie-Hellman assumption. Also a digital signature scheme is explicitly described using our proposed functions.

Elliptic curves offer interesting possibilities for alternative cryptosystems, especially in constrained environments like smartcards. However, cryptographic routines running on such lightweight devices can be attacked with the help of "side channel information"; power consumption, for instance. Elliptic curve cryptosystems are not an exception: if no precaution is taken, power traces can help attackers to reveal secret information stored in tamper-resistant devices. Okeya-Takagi scheme (OT scheme) is an efficient countermeasure against such attacks on elliptic curve cryptosystems, which has the unique feature to allow any size for the pre-computed table: depending on how much memory is available, users can flexibly change the table size to fit their needs. Since the nature of OT scheme is different from other side-channel attack countermeasures, it is necessary to deeply investigate its security. In this paper, we present a comprehensive security analysis of OT scheme, and show that based on information leaked by power consumption traces, attackers can slightly enhance standard attacks. Then, we explain how to prevent such information leakage with simple and efficient modifications.

In this paper the problem of determining optimal workload for a load sharing system is considered. The system is composed of total n components and it functions until (n-k+1) components are failed. The works that should be performed by the system arrive at the system according to a homogeneous Poisson process and it is assumed that the system can perform sufficiently large number of works simultaneously. The system is subject to a workload which can be expressed in terms of the arrival rate of the work and the workload is equally shared by surviving components in the system. We assume that an increased workload induces a higher failure rate of each remaining component. The time consumed for the completion of each work is assumed to be a constant or a random quantity following an Exponential distribution. Under this model, as a measure for system performance, we derive the long-run average number of works performed per unit time and consider optimal workload which maximizes the system performance.

With the growing demand for mobile communications, multicarrier (MC) schemes are receiving an increasing amount of attention, primarily because they handle frequency selective channels better than ordinary single-carrier schemes. However, despite offering several advantages, MC systems have certain weak points. One is their high sensitivity to interchannel interference (ICI). The influence of Doppler shift and ICI are the focus of this paper. Newly proposed B3G/4G systems are developed for data transmission rates higher than those of the IEEE 801.11. It is then necessary that the bandwidth of the subcarrier be small. Moreover, for a higher carrier frequency and mobile speed, the influence of the Doppler shift will be large; therefore, the influence of ICI becomes severer. Using a Markov chain approach, we synthesized a turbo equalizer (TE) that minimizes ICI when interference affects the arbitrary number M of adjacent subchannels. This approach shows the complexity of the proposed algorithm exhibits linear growth with respect to M and independence with respect to the total number of subchannels in the multicarrier system. The proposed ICI cancellation scheme can also be effective in the case of multiple Doppler frequency offsets. This makes the proposed approach attractive for practical implementations.

In this paper, we present the biometric authentication system based on the fusion of two user-friendly biometric modalities: Iris and Face. Using one biometric feature can lead to good results, but there is no reliable way to verify the classification. To achieve robust identification and verification we are combining two different biometric features. We specifically apply 2-D discrete wavelet transform to extract the feature sets of low dimensionality from the iris and face. And then to obtain Reduced Joint Feature Vector (RJFV) from these feature sets, Direct Linear Discriminant Analysis (DLDA) is used in our multimodal system. This system can operate in two modes: to identify a particular person or to verify a person's claimed identity. Our results for both cases show that the proposed method leads to a reliable person authentication system.