From the perspective of real-time processing, such as autonomous driving, sudden failures could potentially lead to severe and even life-threatening accidents. In particular, hardware faults in AI models used for real-time decision-making can compromise safety. To prevent these accidents before they happen, it is crucial to detect failures promptly. Moreover, for small and power-constrained devices such as drones, it is essential to develop a fault-tolerant AI that is computationally efficient and minimizes memory usage and power consumption. Approximate Triple Modular Redundancy (TMR) with quantization has been proposed for convolutional layers, which enables fault-tolerant inference with reduced computational cost. However, sufficiently efficient and reliable fault-tolerant methods for quantized Vision Transformers based on Transformer blocks have not yet been developed. In this paper, we propose Approximate Dual Modular Redundancy (DMR) for fault detection and Approximate TMR for fault recovery, specifically designed for Vision Transformers. In our evaluation, the proposed Approximate TMR was applied to an 8-bit quantized Swin Transformer. The results show that it reduces the computational cost significantly compared to conventional TMR. Furthermore, it successfully detects faults when single-bit flips occur with a probability exceeding 1%. We also demonstrate that the proposed Approximate TMR maintains higher accuracy than existing methods, such as Ranger and Clipper, even under single-bit flip faults.

In this paper, we propose a battery-powered wild animal tracking device using a Pan-Tilt-Zoom (PTZ) camera and deep learning. The proposed tracking device detects wild animals using YOLOv5 and tracks the detected wild animals using DeepSort. In addition, the proposed tracking device realizes tracking for a wide range by controlling a PTZ camera according to the movement direction of the detected wild animals. In the experiment, we developed a prototype for the proposed tracking device and conducted the field test of the developed prototype. We confirmed and discussed cases where the developed prototype could and could not track wild animals. The energy consumption of the developed prototype during tracking was 526.03J at the daytime and 730.99J at the nighttime.

We discuss network tomography in stochastic environments. In real-world communication networks, routing may exhibit stochastic behavior due to load balancing mechanisms and other factors, and the states of network components, such as links, may fluctuate. In such environments, identifying the internal state of the network from end-to-end measurements typically requires a huge number of measurements. To overcome this difficulty, we propose a network tomography method that efficiently narrows down the state with a limited number of measurements by repeatedly updating the posterior information of the network state. In our method, we introduce the mutual information as an indicator of the effectiveness of the measurement. This allows us to design a combination of measurement paths that is critically effective for state identification, thereby significantly reducing redundant measurements that would generate excessive costs. We show that our method theoretically guarantees the approximation ratio$(1-1/\mathrm {e})$on the basis of submodularity analysis. Numerical evaluations show that our method can identify network states with far fewer measurements than existing methods.

We discuss Boolean network tomography in a probabilistic routing environment. Although the stochastic behavior of routing can be found in load balancing mechanisms and normal routing protocols, it has not been discussed much in network tomography so far. In probabilistic routing, because monitoring paths are not uniquely determined, a huge number of measurements are generally required to identify the network state. To overcome this difficulty, we propose a network tomography method for efficiently narrowing down the states with a limited number of measurements by iteratively updating the posterior of the states. In this method, we introduce mutual information as a measure of the effectiveness of the probabilistic monitoring path. This enables us to prioritize measurements that are critically effective in identifying the state, thus significantly reducing the number of required measurements. We show that our method has a theoretical guarantee of the approximation ratio (1 – 1/e) on the basis of submodularity analysis. Numerical evaluations show that our method can identify the network states with far fewer measurements than existing methods.

In mission-critical systems such as self-driving, medical, and infrastructure systems, hardware faults can lead to serious accidents. Therefore, we need a method to detect hardware faults of artificial intelligence (AI) with high accuracy. A low-cost fault detection method with less computation is required to reduce AI’s chip area and/or energy consumption. In this paper, we propose an approximate Dual Modular Redundancy (DMR) unit using a Random Forest approximation method, which can significantly reduce the computation for inference in the convolutional neural networks (CNNs). We assume various scenarios of faults and evaluate the fault effects. In our experiments, we demonstrate that the proposed approximate DMR unit achieves high fault detection for three types of fault models. In addition, we report a 42.8% to 48.3% reduction in the computation for inference compared to the conventional method.

Cooperative vehicle safety (CVS) systems have been receiving significant attention as key enablers of important intelligent transportation system (ITS) applications, such as cooperative collision warning, emergency braking, and auto driving. In CVS systems, vehicles periodically broadcast short packets that include various types of vehicular information, e.g., position and speed. In this paper, we propose an optimization method for the broadcast rate in vehicle-to-vehicle (V2V) broadcast communications at an intersection based on theoretical analysis. We consider a model in which the locations of vehicles are modeled separately asqueuing, andrunningsegments and derive key performance metrics of V2V broadcast communications through a stochastic geometry approach. We developclosed-formapproximate formulas for the theoretical expressions because they are mathematically intractable. Based on approximate analysis, we optimize the broadcast rate such that the interference at an intersection is mitigated and the overall performance of V2V communications is maximized. Because of the closed-form approximation, the optimal rate can be used as a guideline for areal-timecontrol-method, which cannot be achieved through time-consuming simulations. We evaluate our method through numerical examples and demonstrate its effectiveness.

This paper analyzes network disconnection due to randomly occurring natural disasters in a geographical area, which is divided into sub-areas on the basis of disaster-vulnerable (DV) levels. The DV levels against an earthquake, for example, depend on the soil-foundation-structure. The network is a communications cable network that is planned to be built between two given network nodes. To make the optical cable working between these network nodes, electric supply from a power grid to these nodes is necessary, where the power grid has already existed. In this paper, the geographical conditions are derived under which a cable route of the network maximizes the probability of connecting two given nodes for any level of disaster when the geographical route information of the power grid is given. The achievable maximum probability of connecting two given nodes or its bound is explicitly given.

Correlation of interference affects spatio-temporal aspects of various wireless mobile systems, such as retransmission, multiple antennas and cooperative relaying. In this paper, we study the spatial and temporal correlation of interference in mobile ad-hoc networks under a correlated shadowing environment. By modeling the node locations as a Poisson point process with an i.i.d. mobility model and considering Gudmundson (1991)'s spatially correlated shadowing model, we theoretically analyze the relationship between the correlation distance of log-normal shadowing and the spatial and temporal correlation coefficients of interference. Since the exact expressions of the correlation coefficients are intractable, we obtain their simple asymptotic expressions as the variance of log-normal shadowing increases. We found in our numerical examples that the asymptotic expansions can be used as tight approximate formulas and useful for modeling general wireless systems under spatially correlated shadowing.

The bear attack to human beings is one of the fatal accidents, and it is becoming more critical to avoid such accidents because human 's encountering a bear happens every year, even in a city area. It is required to discover bears quickly and warn people to avoid bear accidents. To realize sensor nodes that detect bears automatically using image recognition technology, we aim to realize an accurate and computationally-efficient bear-presence detection. In this paper, we propose a bear-presence detection method combining region proposal of a low-resolution and image classification. In the experiments, we show that the proposed method achieves 4.9% higher recall and 2.3% higher F-score than image classification with-out region-proposal. Moreover, the proposed method achieved 0.6% higher recall and 18.5% higher F-score than YOLOv3, which is one of state-of-the-art object detection methods while the execution time was reduced to 72.4% for bear images and 55.5% for non-bear images.

This paper proposes a theoretical framework for estimating a target-object shape, the location of which is not given. The framework uses mobile distance sensors and speed meters typically mounted on vehicles, the locations of which are also unknown. Each sensor continuously measures the distance from it to the target object. The proposed framework does not require any positioning function, anchor-location information, or additional mechanisms to obtain side information such as angle of arrival of signal. Under the assumption of a convex polygon target object, each edge length and vertex angle and their combinations are estimated and finally the shape of the target object is estimated. To the best of our knowledge, this is the first result in which a target-object shape was estimated using the data of mobile distance sensors without using their locations.

We discuss the shape estimation of a moving target object by using distributed simple sensors. Since we cannot always carefully design sensor locations or allocate global positioning systems (GPSs) to low-cost sensors, we usually assume that the locations of sensors as well as that of the target object are unknown. We propose a method of estimating the whole shape of a moving target object T that has curved segments. Our method analyzes continuous reports on the measured distance of T from distributed sensors and determines the sensing directions of sensors by deriving T's boundary characteristics, such as curvature, from sensing reports. On the basis of the obtained sensing directions, it estimates the whole shape of T. We conducted numerical simulations and evaluated our method using simple geometric and realistic vehicle-shaped objects.

In this paper, we compare asynchronous circuits from register transfer level (RTL) conversion and gate level (GL) conversion for synchronous circuits. Through the comparison, we show which conversion is better for asynchronous circuits. We also describe the design methods for asynchronous circuits from RTL conversion and GL conversion. The experimental result showed that RTL conversion results in better asynchronous circuits than GL conversion in terms of energy consumption. On average, 11.3% energy consumption was reduced compared to the synchronous counterparts.

This paper proposes an algorithm for disaster avoidance control against heavy rainfall. According to weather information, the algorithm reconfigures a logical network (slice), including the migration of virtual machines (VMs), to avoid disasters. It was applied to a nationwide network of 105 nodes and 140 edges, including cases with more than 10 000 slices. Through numerical simulations using actual data of rainfall that caused significant damage in Japan, we found that the probability of service disruption under the proposed control with suitable parameter settings is 10%–30% of that without control, on average. Our proposed control experimental system is implemented by using the software-defined network technology. It can migrate VMs and estimates VM migration time to determine how many VMs should be migrated. By using the experimental system, we found that the control interval has an optimal value, which depends on the management system processing capacity.

By using directional distance sensors that have unknown locations, this paper proposes a method of estimating the shape of a location-unknown target object T moving with unknown speed on an unknown straight line trajectory. Regardless of many unknown factors, the proposed method can estimate the shape by using each sensor's continuous report of the measured distance to T without using side information or additional mechanisms such as locations of anchor sensors and angle-of-arrival measurements. By using the sensor reports, the proposed method estimates (i) the moving speed of T, (ii) the length and direction of an edge of T, and (iii) the order of consecutive edges. As a result, we can obtain the shape of T.

In this paper, we study the temporal correlation of interference in mobile ad-hoc networks under a correlated shadowing environment. By modeling the node locations as a 1-D Poisson point process with an i.i.d. mobility model and considering spatially correlated shadowing that depends on the distance between nodes, we derive a simple asymptotic expression of the temporal correlation coefficient of interference as the variance of log-normal shadowing increases. This shows a readable relationship between the correlation distance of lognormal shadowing and the temporal correlation of interference and thus can be useful for modeling general wireless systems with spatially correlated shadowing.

This paper proposes a disaster avoidance control method for use against heavy rainfall and discusses its effectiveness through actual weather data. The proposed control method uses geographical information data including weather data, hazard area data, and physical network data. By applying technologies related to meteorology, erosion control, and civil engineering to such data, the proposed method can evaluate the risk of a physical network being disconnected. On the basis of the evaluated risk, the proposed method reconfigures a logical network to reduce service disruption. The proposed method is applied to a cloud computing service network where, in addition to route changes, the relocation of virtual machines is possible, increasing its effectiveness. By using empirical data, we show that the proposed method reduces the probability of service disconnection to almost zero even for heavy rainfall causing landslides. Finally, an experimental system of the proposed method was implemented through software defined network technology and successfully controlled the experimental network.

In this paper, we analyze the performance of vehicle-to-infrastructure (V2I) communications on a highway, in which the transmission distance between a road side unit (RSU) and a vehicle rapidly changes due to movement of vehicles. By theoretically analyzing the interference received at an RSU, we derive a closedform expression of a desired performance metric of V2I communications. Furthermore, by considering the trade-off between the interference at an RSU and the transmission range of a running vehicle, we obtain a closed-form optimal transmission-range for V2I communications. We evaluate our analysis results by conducting numerical simulations and show the effectiveness of the optimal transmissionrange.

This paper geometrically analyzes handover under the assumption that vehicles run in a straight line. When the time-to-trigger of handover is given, the expected time E[tv] that a vehicle can use a desired cell is derived. By introducing a parameter to compensate the error caused by the straight line driving route assumption, the derived E[tv] can be applied to non-straight line routes. Because E[tv] is a function of a cell shape and a car speed and is a good metric that a desired cell is well-used, dynamic cell reconfiguration based on this metric with monitored car speeds is proposed. By using the field data of cells as well as driving data, it is demonstrated that this metric and its application to the dynamic cell configuration are working.

The offloading of cellular traffic through WLAN APs (wireless local area network access points) distributed in a homogeneous Poisson process (HPP) is theoretically evaluated. The probability Pw that a user can use WLAN and the expected number of vertical handovers Nh are evaluated as the basic performance metrics of WLAN AP coverage. Explicit formulas are derived for the metrics, and the fundamental relationships between the metrics and many parameters such as the shape of each WLAN coverage region D1, D2,... are described. These metrics depend on the size and perimeter length of Di but do not depend on their other shape parameters for a convex Di. In addition, it is proven that a disk-shaped Di minimizes Nh for a fixed WLAN coverage size and that Pw is often insensitive to the perimeter length of Di. It is also proven that the Pw of a user at a random location is equal to that moving along a random straight line or a random bounded curve. One hundred empirical location data sets of WLAN APs in Japan, Korea, and the US were used to confirm the theoretical results. Although these locations do not follow an HPP, many theoretical results are shown to be valid. For example, Nh is minimized by a disk-shaped Di. Simultaneously, we find that Pw slightly increases when a slender Di is used for highly clustered AP locations.

In this paper, we propose a task allocation method for multi-core systems based on the Duplication with Temporary Triple-Modular Redundancy and Reconfiguration (DTTR) scheme. The proposed method statically determines task allocation for given task graph and multi-core system model from task scheduling for fault patterns of cores. In the experiments, we evaluate the task allocation time and the overhead for the execution time while changing multi-core system models, task graphs, and upper bound of faulty cores. The proposed method allocates a task graph with 100 tasks to a multi-core system with 16 cores within a practical timeout condition. This task allocation allows the system to operate with a reasonable execution time overhead even if 6 arbitrary cores become faulty.

Interference problems caused by congestion of vehicles at intersections or on highways may significantly affect vehicle-to-vehicle (V2V) communications, especially for active-safety assistance systems due to the importance of emergency information. In this paper, we propose a theoretical interference model of V2V communications at an intersection that uses transmission power control method. To evaluate and address the interference problem at an intersection, we derived an analytical expression of the outage probability of a typical vehicle at an intersection and provide guidelines for an optimal power control method, which cannot be obtained through simulations. We model the location of vehicles in queueing segments and running segments separately and analyze their interference based on a stochastic geometry approach. In our model, a simple power control method is used: the transmission power of each vehicle is determined by the status of the vehicle, i.e., stopping or running. By changing the transmission power of vehicles in queueing segments, we can mitigate the interference received at vehicles running closer to an intersection. By using the theoretical results, we obtain an optimal power control method, which can balance the trade-off between the outage probabilities of vehicles in queueing segments and running segments. We validated our analytical results and the effect of the power control on V2V communications through numerical experiments.

In this paper, we propose a mathematical model for intelligent transportation systems (ITS) in an urban environment, which takes into account both the urban structure and vehicles. Using the stochastic geometry approach, we model the locations of vehicles with a Poisson point process on roads whose interval is a fixed value. We consider typical vehicle-to-infrastructure and vehicle-to-vehicle communication scenarios and derive theoretical values of the probability of successful transmission. Our results from numerical experiments reveal how the urban structure can affect wireless communications in ITS.

Macroscopic diversity (macro-diversity) techniques are attracting much attention in wireless communication. However, the optimal cell planning algorithm for macro-diversity involving sector antennas has not been investigated. We thus propose a metaheuristic algorithm for cell planning with macro-diversity using sector antennas. In the algorithm, the constraint conditions for deploying base stations (BSs) are expressed via homology, which has recently been used in sensor networking. Numerical simulations show that the cell deployment pattern obtained with the proposed algorithm requires about 20% less BSs compared to that obtained with the reference algorithm.

We propose a method for estimating the size, perimeter length, and location of a time-variant target object moving in a monitored area. This method uses only binary information from sensors of which locations are unknown, where the binary information includes whether each sensor has detected the target object or not. Analysis based on integral geometry provides the relationship between the number of sensors detecting the target object and the target object parameters to be estimated. Because this relationship is linear, a linear filter, such as the Kalman filter, is applicable to estimate parameters if we can assume that the dynamics of the parameters are linear. As a concrete example, the size, shape, and location of an active thunder area is estimated. The model discussed in this paper is applicable as a model of participatory sensing.

A geometric model of a physical network affected by a disaster is proposed and analyzed using integral geometry (geometric probability). This analysis provides a theoretical method of evaluating performance metrics, such as the probability of maintaining connectivity, and a network design rule that can make the network robust against disasters. The proposed model is of when the disaster area is much larger than the part of the network in which we are interested. Performance metrics, such as the probability of maintaining connectivity, are explicitly given by linear functions of the perimeter length of convex hulls determined by physical routes. The derived network design rule includes the following: 1) reducing the convex hull of the physical route reduces the expected number of nodes that cannot connect to the destination; 2) the probability of maintaining the connectivity of two nodes on a loop cannot be changed by changing the physical route of that loop; 3) the effect of introducing a loop is identical to that of a single physical route implemented by the straight-line route.

In this paper, we propose a design support tool set for asynchronous circuits with bundled-data implementation to implement them on commercial FPGAs easily considering a latency constraint. The design support tool set consists of six tools to automate constraint generation, timing verification, and delay adjustment for bundled-data implementation. In the experiments, we synthesize two circuits using the proposed tool set and compare area, performance, power consumption, and energy consumption with the synchronous counterparts.

This paper presents an algorithm for evaluating the probability that connectivity can be maintained between two given nodes in a physical network affected by a disaster. Nodes and links in a disaster area are probabilistically broken, and the disaster area is modeled using a half plane. This paper also proves that this probability of connectivity increases for a generic network topology when the perimeter length of the convex hull of a physical link route decreases, and that it becomes maximum when these physical link routes become straight line segments. In addition, this paper proposes an optimal server placement method by considering robustness against disaster and an optimal link/node replacement strategy determining which nodes or links should be replaced with those robust against disaster. Intuitive node (link) replacement strategies are also suggested based on the analysis of this paper.

Macroscopic diversity (macro-diversity) techniques, such as coordinated multi-point transmission in LTE networks, are attracting attention for reducing the error rate of wireless transmission. We propose a cell-planning algorithm with macro- diversity when possible locations of cells are given. To define a cell, we focus on the desired received signal power of uplink determined by fractional power control. We also propose a signal-to-interference-plus-noise ratio (SINR) evaluation method under the obtained cell-deployment pattern, which takes into account frequency scheduling used in LTE networks. Numerical results show that by optimally deploying the cells, we can reduce the required number of cells to cover the defined domain by up to 30% compared to when the cells are selected greedily. Moreover, the SINR evaluation results suggest that reducing the required cells to cover the domain improves uplink SINR at the cell edge.

The optimal geometric configuration of the cells of a wireless network using multiple antennas for each base station and a macrodiversity technique is investigated. The simplest model of a cell of an existing wireless network is disk shaped, and the cell deployment is arranged in a honeycomb tiling pattern. This model has been used as the first-order approximation for designing and evaluating wireless networks. However, the cells of a network using multiple antennas and macrodiversity are no longer disk shaped. This study investigated a network with a cell-and-antenna deployment pattern that covers a given service area using the minimum number of cells. The objective of this paper is to offer a first-order approximation model for a cell-and-antenna deployment pattern of such a network. For this objective, first, by imposing practical conditions, cell-and-antenna deployment patterns are classified. Then, the asymptotic minimum coverage problem is formulated as an optimization problem with a constraint for a set of deployment patterns. To easily obtain the first-order approximation model, a simplified formulation and model are proposed. Numerical examples show that the proposed deployment pattern covers the service area with nearly half the cells required by the existing heuristic pattern.

We propose a method for estimating parameters of multiple target objects by using networked binary sensors whose locations are unknown. These target objects may have different parameters, such as size and perimeter length. Each sensors, which is incapable of monitoring the target object's parameters, sends only binary data describing whether or not it detects target objects coming into, moving around, or leaving the sensing area at every moment. We previously developed a parameter estimation method for a single target object. However, a straight-forward extension of this method is not applicable for estimating multiple heterogeneous target objects. This is because a networked binary sensor at an unknown location cannot provide information that distinguishes individual target objects, but it can provide information on the total perimeter length and size of multiple target objects. Therefore, we propose composite sensor nodes with multiple sensors in a predetermined layout for obtaining additional information for estimating the parameter of each target object. As an example of a composite sensor node, we consider a two-sensor composite sensor node, which consists of two sensors, one at each of the two end points of a line segment of known length. For the two-sensor composite sensor node, measures are derived such as the two sensors detecting target objects. These derived measures are the basis for identifying the shape of each target object among a given set of categories (for example, disks and rectangles) and estimating parameters such as the radius and lengths of two sides of each target object. Numerical examples demonstrate that networked composite sensor nodes consisting of two binary sensors enable us to estimate the parameters of target objects.

In this paper, we propose a synthesis method for asynchronous circuits with bundled-data implementation which iteratively applies behavioral synthesis and floorplanning to obtain an optimum circuit in terms of performance under given design constraints. We evaluate the effectiveness of the proposed method through synthesizing several benchmarks. Experimental results show that the proposed method synthesizes faster circuits compared to ones without considering timing constraints. Also, the proposed method is effective to reduce the number of timing violations.

This paper proposes a tool set for the design of asynchronous circuits with bundled-data implementation. Using the proposed tool set with commercial CAD tools, asynchronous circuits with bundled-data implementation can be designed easily. Through the experiments, this paper evaluates synthesized circuits using the proposed tool set in terms of area, performance, power consumption, and energy consumption comparing with synchronous counterparts.

This paper proposes a floorplan method for asynchronous circuits with bundled-data implementation on FPGAs. The proposed method minimizes the delay of the control circuit while considering timing constraints required for bundled-data implementation. Through the implementation of the proposed method, this paper evaluates the proposed method in terms of performance and area for generated floorplans.

An estimation method for the shape and size of a target object by using networked binary sensors whose locations are unknown is proposed. Each of those sensors, which individually are incapable of monitoring the target object's shape and size, sends only binary data describing whether or not it detects at every moment the target object. By using these data and the explicit formulas derived in this paper, we can estimate the size and the perimeter length of the target object even without sensor location information. An additional parameter, which is a function of the shape of the target object, can also be estimated when the target object is non-convex.

We analyze the path coverage property of a sensor network, where a large number of sensors are randomly deployed. We characterize the path coverage in terms of three metrics:fractionofcoverage,probabilityofcompletecoverage,andprobabilityofpartialcoverage. We derive the expressions for the three coverage metrics as functions of the sensor density, the sensing range of a sensor, and the communication range of a sensor. Based on the derived expressions, we study the impact of the communication range on the path coverage and, for example, show that a sensor should have a long wireless-communication range to obtain large detectability of intruding objects (partial coverage probability of the trajectories of objects) with modest density of sensors.

This paper discusses networked sensors that are randomly distributed to monitor and detect a target object moving on a trajectory. On the basis of analysis results, we propose a method for estimating the shape and size of a target object by using sensors whose locations are unknown. It is surprising that sensors that individually are incapable of monitoring the target object's shape can be used to estimate it without sensor location information. An example shows that a combination of sensors with different sensing areas can increase the shape estimation performance. This estimation method can work for any trajectory and with sensor areas of arbitrary shape and size.

We have presented a new network called the wide area ubiquitous network (WAUN) for ubiquitously networking small devices such as sensors and actuators through a long low-bit-rate wireless link. We set the WAUN basic design requirements to be "low cost, low power consumption, and supporting low-end terminals" and started R&D of the WAUN. Our efforts toward R&D of the WAUN include various areas such as network systems, wireless systems, wireless terminals, and applications. This paper describes them

The wide area ubiquitous network (WAUN), which is used for transmitting and receiving information for sensors and actuators, is proposed and the feasibility study of a new wireless network for the WAUN is described. The WAUN is designed to satisfy the requirements of many new applications using sensors and actuators, which are wirelessly connected to the IP network. One of the basic requirements for the wireless system of the WAUN is wide coverage larger than several km with low wireless terminal output power of 10 mW To meet this requirement, an experimental wireless system, which uses a powerful FEC and the diversity technique, for use in WAUNs is designed, and its feasibility is evaluated by field experiments. The experimental results demonstrate the feasibility of the WAUN. That is, the 10 mW transmission power wireless terminal communicates with the access point (base station) 5 km away

Nowadays, variable delay arithmetic units have been used for implementing a datapath of a target system in pursuit of performance improvement. However, adoption of variable delay arithmetic units requires modification of a typical synchronous control unit design methodology. A telescopic arithmetic unit based methodology is one of representative methodologies to design synchronous control units for variable delay datapaths. In this paper, we propose two optimization methods for it. Proposed optimization techniques will be analyzed in order to show their performance improvement effects explicitly.

Asynchronous speed independent (Sl) circuits based on an unbounded gate delay model often suffer from high area penalty. It happens due to the lack of efficient global optimization. This paper presents a boolean optimization method based on tranduction method to optimize asynchronous Sl circuits while preserving hazard-freeness.

In the age of highly integrated system LSIs, the problem of design methodologies with short time-to-market and higher re-programmability after the chip fabrications has acquired great importance. Although a pure FPGA system is one of the solutions, it cannot give sufficient performance in many real-time applications due to its lower performance and higher power dissipation compared to ASICs. Instead, a hardware/software co-design approach can give best design solutions in terms of such design criteria. In this paper, we introduce a new VLSI architecture called Field Modifiable Architecture (FMA) and its design methodology. Experimental results confirm that our architecture can achieve significant performance improvement in terms of execution cycles.

Describes an interface for multi modal human robot interaction, which enables people to introduce a newcomer robot to different attributes of objects and places in the room through speech commands and hand gestures. The robot makes an environment map of the room based on knowledge learned through communication with human and uses this map for navigation. The developed system consists of several sections including: natural language processing, posture recognition, object localization and map generation. This system uses a combination of multiple sources of information and model matching to detect and track a human hand so that the user can point toward an object of interest and guide the robot to go near to it or locate that object's position in the room. The position of objects in the room is located by a monocular camera vision and depth from focus method.

We have developed a real-time simulator that is connected to the network on-line and continuously uses the monitored IP traffic on AAL5/ATM. The simulator is software running on a real-time OS in a PC containing ATM network interface cards, which can use the information provided by the timestamp, VPI/VCI, IP address, protocol number, and port number of the monitored packets for the simulation. The simulator provides a simulation model of a multiplexer whose output link speed, buffer size, and queueing discipline can be changed by the user. In addition, we propose a simulation server that makes a simulation platform easily available. The simulator enables us to identify the appropriate amount of network resources, such as link speed and buffer size, and the effectiveness of various queueing disciplines. Numerical examples using the simulator in a real network are also shown.

This paper describes a local optimal proportional delay scheduler for relative differentiation in differentiated services (Diffserv). The scheduler achieves a target for the average delay ratio for each class of packet under the assumption that there are no additional arriving packets. A concept is proposed called the 'local optimal' which means the optimal decision when there are no further arriving packets. The proposed idea is applied to derive the scheduler. Numerical examples, including some using real data, show that the performance of the scheduler is at least as good as that of the waiting time priority scheduler, which has the best performance amongst existing schedulers for proportional delay differentiation.

A new asynchronous transfer mode adaptation layer (AAL), called AAL2, is being designed mainly for low-bit-rate voice traffic, and nodes that can assemble and disassemble AAL2 cells are being developed to make AAL2 usage efficient. This paper investigates the delay and performance of AAL2 nodes by an analytical method. Then, using the results, it analyzes a network using AAL2 nodes and shows the bandwidth reduction achieved by using AAL2 switching nodes as transit nodes.

Deep submicron technology calls for new design techniques, in which wire and gate delays are accounted to have equal or nearly equal effect on circuit behaviour. Asynchronous speed-independent (SI) circuits, whose behaviour is only robust to gate delay variations, may be too optimistic. On the other hand, building circuits totally delay-insensitive (DI), for both gates and wires, is impractical. The paper presents an approach for automated synthesis of globally DI and locally SI circuits. It is based on order relaxation, a simple graphical transformation of a circuit's behavioural specification, for which the Signal Transition Graph, an interpreted Petri net, is used. The method is successfully tested on a set of benchmarks and a realistic design example. It proves effective showing average cost of DI interfacing at about 40% for area and 20% for speed.

We have developed new traffic measuring equipment and applied it to the real-time simulation of a network. The measuring equipment monitors IP traffic on an ATM link and continuously transfers the packet length and the timestamp for each IP packet to a post-processing system. The post-processing system receives the data, estimates the arrival epoch to the transmission queue of the ATM link, and simulates the queueing behavior on-line for conditions different from those of the actual system. The measuring equipment and the real-time simulation are a new approach for traffic engineering. A new estimation problem, the arrival sequence estimation, is shown and a simple algorithm is evaluated. Also, a new dimensioning algorithm called the queue decay parameter method, which is expected to be robust and applicable to real-time control, is proposed and evaluated.

The traffic performance of ATM Adaptation Layer 2 (AAL2) cell assembly and disassembly (CLAD) is evaluated by an analytical method where AAL2 is standardized to convey low-bit-rate traffic such as mobile traffic including IMT-2000. The analytical formulas are applicable to dimensioning of the bandwidth of the output link of the CLAD. In particular, this paper evaluates the number of channels that can be multiplexed in the fixed capacity output link of AAL2 CLAD for various timeouts and buffer sizes. The arrival process is modeled as a discrete Markovian arrival process considering the talkspurt and silence period of a voice source, and discrete-time tandem queues modeling a cell assembly queue and a transmission queue are analyzed. An approximation model and its accuracy are also investigated and shown to be good for accuracy and computation time. The short packet loss ratio, which is lower than the cell loss ratio, is derived. Through numerical examples, this paper shows the statistical multiplexing gain of AAL2 and the various parameter ranges that yield higher efficiency than STM. It also shows that timeout has a complicated impact on the performance of AAL2, as a result of changes in the characteristics of cell arrival at the transmission queue.

The asymptotics of cell-loss ratio (CLR) in the regime of large buffers are characterized by two parameters, the asymptotic constant and asymptotic decay rate. Both parameters can be expanded in powers of one minus the link utilization (heavy traffic expansion). Thus, once the coefficients in this expansion are obtained, the CLR can be very easily estimated from the measured link utilization by using CLR asymptotics. This paper proposes an algorithm for estimating these coefficients in real time. For this purpose, the notion of state-space representation for a single-server queue is introduced: the elements of the state vector are the coefficients in the expansion of the asymptotic constant and asymptotic decay rate. Bayesian regression analysis is applied to estimate the state vector based on the buffer measurement. Our approach does not require any models describing the statistics of the traffic other than the asymptotic behavior of the CLR in the regime of large buffers. In addition, it allows us to estimate the effective bandwidth of the aggregated process easily, so it is applicable to a wide range of ATM traffic control methods, such as connection admission control and VP bandwidth control. We describe how this method of CLR estimation will be applied to connection admission control and VP bandwidth control by using results from simulation experiments.

The asynchronous transfer mode (ATM) is a key technology for broadband integrated services digital networks (B-ISDNs), which require high speed transmission. We propose a "self-sizing network operation". This is a traffic engineering, management and operation concept for ATM networks. This concept allows networks to be rapidly operated and flexibly re-dimensioned by the system. We overview the functions of this system. Next, we present the virtual path (VP) bandwidth control function and the network element (NE) interface, which are Step 1 functions in the "self-sizing network operation". Their functions can automatically adjust the VP bandwidth. We show their effectiveness; the VP bandwidth can be reduced by 30% or 40%. To implement the operation system, we considered the actual operation time. This may be restricted for operation control. Then, we evaluated the performance of the Step 1 function. In this evaluation, we measured the basic CMIP performance, and estimated the time necessary for actual operation based on these measurements. A major portion of the total operation time is the time necessary for collecting data. This increases by the cube of the total number of virtual channel handlers (VCHs) with every additional VCH. If we use this system, we must consider its operation cycle and effectiveness. However, fortunately the time necessary for operation is short enough to operate about 50 VCHs in a network which cover all of Japan.

We have measured, at 57.5 GHz, the reflection and transmission coefficients of typical walls, floor, ceiling, window, and partitions and have compared the measured reflection characteristics with the reflection characteristics estimated by multi-layer dielectric models. Although the positional inhomogeneity of structure types gives rise to some variation from one measured position to another, these positional variabilities are not large, The overall trend of reflection coefficients calculated by multi-layer dielectric models thus mainly agrees well with the trend of the measurements. We have shown that the use of circular polarization can reduce the reflection even if the interior parts of the structure have complicated structures. In addition, the shadowing effects of several types of partitions were measured. The transmission coefficients of partitions depend on the materials. The losses due to plywood partitions are very low, but a metallic partition shields millimeter waves.

A typical example of telecommunication system performance estimation during operation is connection admission control (CAC) of asynchronous transfer mode (ATM) networks. This paper investigates adaptive CACs using Bayesian performance estimation. The performance is estimated through Bayesian regression analysis, in which the monitored performance and an a priori estimate are given by conventional techniques such as queueing theory and simulation. Three adaptive CACs are studied: a CA C based on a log-transform of the cell loss ratio (CLR), a CAC based on a maximum queue length during a fixed period, and a CAC based on CLR. Numerical examples show the following results: oscillation of VCs in a VP may occur and may be worse when the measurement period is longer; initial variance is important for accurate estimation; CACs using CLR and the log-transform of CLR can not easily assure the CLR objective; the CAC using the maximum queue size performs well and has rapid convergence; the monitored performance data improves the estimates even when the performance is monitored with different conditions than the target condition.

Call admission control in ATM networks without monitoring network load is proposed. Traffic parameters specified by users are employed to obtain the upper bound of cell loss probability, thereby determining call admission. A cell loss probability standard is guaranteed to be satisfied under this control without assumptions of a cell arrival process. Implementation of this control to quickly evaluate cell loss probability after acceptance of a new call is discussed. The result is also applicable to ATM network dimensioning based on traffic parameters.>

The traffic characteristics of an asynchronous transfer mode (ATM) network are analyzed by theoretical methods. A new method is proposed to express the burstiness of the cell arrival process. Both statistical multiplexing and statistical bandwidth allocation are quantitatively evaluated. When packetized video traffic and voice traffic are multiplexed, the number of multiplexable sources strongly depends on the peak bit rate of the multiplexed video sources, and statistical bandwidth allocation is ineffective without control. On the other hand, lowering the peak bit rate of video traffic effectively improves bandwidth utilization.>

The authors present dynamic call admission control using the distribution of the number of cells arriving during the fixed interval. This distribution is estimated from the measured number of cells arriving at the output buffer during the fixed interval and traffic parameters specified by users. Call acceptance is decided on the basis of online evaluation of the upper bound of cell loss probability, derived from the estimated distribution of the number of calls arriving. QOS (quality of service) standards can be guaranteed using this control when there is no estimation error. The control mechanism is effective when the number of call classes is large. It tolerates loose bandwidth enforcement and loose policing control, and dispenses with modeling of the arrival processes. Numerical examples demonstrate the effectiveness of this control, and implementation is also discussed.>

Queueing disciplines at asynchronous transfer mode (ATM) switching nodes handling various kinds of real-time traffic are investigated. ATM can support various new services including voice, data, and video. However, the characteristics of superposed traffic carried by ATM are not known, and a control effective for a versatile arrival process is required. The optimal discipline which minimizes the number of cells being delayed beyond the specified maximum allowable time, and thus being discarded is derived, without assumptions on the arrival process of cells and buffer management schemes. Also discussed is implementation of the optimal discipline and a method of satisfying cell loss probability requirements of individual classes.>