Asymptotic behavior of networked control systems

Local area computer network simulations are inherently non-Markovian in that the underlying stochastic process cannot be modeled as a Markov chain with countable state space. We restrict attention to local network simulations whose underlying stochastic process can be represented as a generalized semi-Markov process (GSMP). Using new better than used distributional assumptions and sample path properties of the GSMP, we provide a geometric trials criterion for recurrence in this setting. We also provide conditions which ensure that a GSMP is a regenerative process and that the expected time between regeneration points is finite. Steady-state estimation procedures for ring and bus network simulations follow from these results.

Network-on-Chip (NoC) links consume a significant fraction of the total NoC power. We present Selective Packet Interleaving (SPI), a flit transmission scheme that reduces power consumption in NoC links. SPI decreases the number of bit transitions in the links by exploiting the multiplicity of virtual channels in a NoC router. SPI multiplexes flits to the router's output link so as to minimize the number of bit transitions from the previously transmitted flit. Analysis and simulations demonstrate a reduction of up to 55% in the number of bit transitions and up to 40% savings in power consumed on the link. SPI benefits grow with the number of virtual channels. SPI works better for links with a small number of bits in parallel. While SPI compares favorably against bus inversion, combining both schemes helps to further reduce bit transitions.

A slotted-ring protocol that performs well across the full range of message length distributions is presented. The relative performance of the protocol is best at low to medium ring utilization, which is the most usual operating condition for local area computer networks. The protocol is not subject to the normal requirement for repeating source and destination addresses in each slot of a multiple-slot message. This reduced overhead feature is a main reason for the performance gains that are achieved. The protocol does not depend on any central control station for assigning slot usage to individual stations. However, it does require each ring station to keep track of the current status and source station usage of each slot on the ring. Implementation of the protocol would require significantly more complex logic circuits than are normally needed in either token rings or conventional slotted rings, and error recovery would be more difficult. Hence, its main value is that it serves as an indicator of the maximum achievable performance of the slotted format for local computer network rings operating at low to medium utilization levels under fully distributed access control. >

Analysis is given to a nonpreemptive priority queueing system with P classes of messages where the class of message to be served next is the highest priority class waiting at the time of service start. (If this were the highest priority class waiting at the service completion epoch, we would have a classical nonpreemptive head-of-line priority queueing system.) We assume that the message service time distribution is identical for all classes. The mean message waiting time is obtained explicitly for each class, and numerically compared to the values in the corresponding head-of-line system. We have also proposed and evaluated a fairness measure to demonstrate the degree of discrimination. This model can be applied to the performance analysis of the prioritized token-ring scheme in local area computer networks when the propagation delay and bit latency are negligible compared to the frame transmission time.

Exhaustive self-testing of combinational circuitry within the framework of the level-sensitive scan design (LSSD) discipline requires that every output node depend on a small number of input nodes. We present here efficient algorithms that take an arbitrary block of combinational logic and add to it the smallest number of bits of new LSSD registers necessary to: (1) partition the logic so that no output depends on more thank inputs, and (2) maintain timing within the block (so that all input-to-output paths encounter the same number of bits of register). Our partitioning algorithms conform to two different design constraints. We also show that the unconstrained partitioning problem is NP-complete.

This paper studies the stabilizability of an n-dimensional quantized feedforward nonlinear system. The state of that system is first quantized into a finite number of bits, and then sent through a digital network to the controller. We want to minimize the number of transmitted bits subject to maintaining asymptotic stability. In the prior literature, n bits are used to stabilize the n-dimensional system by assigning one bit to each state variable (dimension). Under the stronger assumption of global Lipschitz continuity, this paper extends that result by stabilizing the system with a single bit. Its key contribution is a dynamic quantization policy which dynamically assigns the single bit to the most “important” state variable. Under this policy, the quantization error exponentially converges to 0 and the stability of the system can, therefore, be guaranteed. Because 1 is the minimum number of quantization bits (per sampling step), the proposed dynamic quantization policy achieves the minimum stabilizable bit number for that n-dimensional feedforward nonlinear system.

Robotic control is an interesting subject due to its extensive industrial applications. This paper proposes a new continuous control design for tracking problem of a three degree-of-freedom (DOF) robot manipulator in presence of uncertainties and bounded external disturbances. The proposed method is based on the combination of the recently developed robust integral of the sign of the error (RISE) feedback and neural network (NN) feed forward terms. In this control strategy, a feed forward NN is utilized to compensate uncertainties of the nonlinear system. Furthermore, the RISE feedback control term is used to eliminate the NN approximation error and bounded external disturbances. Typical NN-based controllers generally provide the convergence only with uniformly ultimately bounded (UUB) error due to the NN reconstruction error. However, the proposed method guarantees asymptotic tracking by eliminating this error. Using Lyapunov stability analysis, a semi-global asymptotic tracking of the robot joints is achieved. Besides, a comparative study on the system performance is conducted between the proposed control strategy and an NN-based controller. Simulation results demonstrate that the proposed controller is robust to deal with uncertainties, and verify the effectiveness of the proposed control scheme.

In this paper, finite horizon optimal control and communication co-design problem has been investigated for uncertain networked control system (NCS) with limited transmit power. Firstly, the mathematical relation between network imperfections (e.g. network-induced delays and packet dropouts) and practical wireless communication channel quality has been studied. Then, a novel networked control system model has been represented that includes both physical system dynamics and network dynamics. Next, adopting the emerging neuro dynamics programming (NDP) technique and actor-critic-identifier (ACI) architecture, a novel time-based finite horizon optimal control and communication co-design has been proposed. The proposed scheme cannot only learn the optimal co-design within fixed final time, but also relax the requirement of NCS dynamics and satisfy the practical transmit power constraint. The Lyapunov Theorem is used to validate the effectiveness of proposed scheme. With the proper NN weight update law, proposed scheme can ensure all closed-loop signals and NN weights are uniformly ultimately bounded (UUB). Moreover, simulation results are also included to demonstrate the effectiveness of the proposed scheme.

Based on digitized TV frames a computer simulation study was conducted on a motion -adaptive TV data compression scheme, defined as one in which a 2- dimensional transformapplied to subblocks is followed by the transmission to the receiving site of only changedsubblocks. Performance was measured both by calculation of Normalized Mean Square Errorand by subjective viewing of reconstructed frames. Two systems designs leading to 512x512resolution operation (one based on the Hadamard and one on the Discrete Cosine Transform)were prepared.IntroductionThe motion -adaptive TV data compression described herein is more effective than conven-tional intraframe techniques because it encompasses them and furthermore takes advantageof the correlation between frames by updating only those subblocks which have changed.Following a 2 -D transform performed on small (e.g. 8x8) subblocks, intraframe compressionis achieved by assigning a small number of bits (or none) to each transform coefficient.This bit allocation is made adaptive by assigning fewer bits to those subblocks within aframe which exhibit less busyness or activity. Next, motion -adaptivity, a form of inter -frame compression, is provided by having the amount of change in coefficients between thecurrent subblock and the corresponding subblock of the previous frame determine which trans-form subblocks to transmit. This process has been simulated and an approach to hardwareimplementation derived.BackgroundTwo -dimensional transforms combined with frame to frame motion -adaptivity achieve highcompression ratios because they exploit pixel correlation in all three dimensions.

A steganographic technique inspired by rook is presented in this paper to ensure privacy and secrecy. In this approach, the cover image is partitioned into n × 1 pixel blocks and converted equivalent n × 8 binary bit planes. Then the functional output of each block is calculated on the basis of the number of rook positions, which are attacked by opponent rooks. The rook is a chess piece that moves only forward and backward in a straight line. In binary bit plane, 0 and 1 are considered as a black and white opponent rook, respectively. The secret information is considered as stream of binary bits. The binary bits of secret information are compared with the functional output of the corresponding block. If it is equal to the functional output of the corresponding block, then nothing needs to be done. In case of inequality, the small number of bits needs to be flipped in such a way that the functional output of the corresponding block becomes equal to the corresponding secret binary bits and the distortion of the cover is minimized.

This paper introduces a best approach for Least Significant Bit (LSB) based on image steganography that enhances the existing LSB substitution techniques to improve the security level of hidden information. It is a new approach to substitute LSB of RGB true color image. The new security conception hides secret information within the LSB of image where a secret key encrypts the hidden information to protect it from unauthorized users. In general, in LSB methods, hidden information is stored into a specific position of LSB of image. For this reason, knowing the retrieval methods, anyone can extract the hidden information. In our paper, hidden information is stored into different position of LSB of image depending on the secret key. As a result, it is difficult to extract the hidden information knowing the retrieval methods. We have used the Peak Signal-to-Noise Ratio (PSNR) to measure the quality of the stego images. The value of PSNR gives better result because our proposed method changes very small number of bits of the image. The obtained results show that the proposed method results in LSB based image steganography using secret key which provides good security issue and PSNR value than general LSB based image steganography methods.

Halftoning is a process that deliberately injects noise into the original image in order to obtain visually pleasing output images with a smaller number of bits per pixel for displaying or printing purposes. In this paper, a novel inverse halftoning method is proposed to restore a continuous tone image from the given halftone image. A set theoretic formulation is used where three sets are defined using the prior information about the problem. A new space domain projection is introduced assuming the halftoning is performed with error diffusion, and the error diffusion filter kernel is known. The space domain, frequency domain, and space-scale domain projections are used alternately to obtain a feasible solution for the inverse halftoning problem which does not have a unique solution.

This paper presents an efficient method to block unknowns for temporal compactors. The proposed blocking logic can reduce data volume required to control the blocking logic and increase the number of scan cells that are observed by temporal compactors. Control patterns, which specify values required at the control signals of the blocking logic, are compressed by linear feedback shift register reseeding. In this paper, the blocking logic gates for some scan chains that do not capture unknowns are bypassed. Since all scan cells in these scan chains can be observed without specifying the corresponding bits in control patterns, more scan cells are observed while a smaller number of bits are required to be specified. The seed size is further reduced by reducing the numbers of specified bits in the densely specified control patterns. The proposed method can always achieve the same fault coverage that can be achieved by directly observing scan chains without any output compaction. Experiments with large industrial designs clearly demonstrate that the proposed method is scalable to large circuits. Hardware overhead for the proposed unknown blocking scheme is very low.

We propose an AVF-driven parity selection method for protecting modern microprocessor in-core memory arrays against MBUs. As MBUs constitute more than 50% of the upsets in latest technologies, error correcting codes or physical interleaving are typically employed to effectively protect out-of-core memory structures, such as caches. However, such methods are not applicable to high-performance in-core arrays, due to computational complexity, high delay and area overhead. To this end, we revisit parity as an effective mechanism to detect errors and we resort to pipeline flushing and checkpointing for correction. We demonstrate that optimal parity tree construction for MBU detection is a computationally complex problem, which we then formulate as an integer-linear-program (ILP). Experimental results on Alpha 21264 and Intel P6 in-core memory arrays demonstrate that optimal parity tree selection can achieve great vulnerability reduction, even when a small number of bits are added to the parity trees, compared to simple heuristics. Furthermore, the ILP formulation allows us to find better solutions by effectively exploring the solution space in the presence of multiple parity trees; results show that the presence of 2 parity trees offers a vulnerability reduction of more than 50% over a single parity tree.

We consider decentralized estimation of a noise-corrupted deterministic parameter by a bandwidth-constrained sensor network with a fusion center. The sensor noises are assumed to be additive, zero mean, spatially uncorrelated, but otherwise unknown and possibly different across sensors due to varying sensor quality and inhomogeneous sensing environment. The classical best linear unbiased estimator (BLUE) linearly combines the real-valued sensor observations to minimize the mean square error (MSE). Unfortunately, such a scheme cannot be implemented in a practical bandwidth-constrained sensor network due to its requirement to transmit real-valued messages. In this paper, we construct a decentralized estimation scheme (DES) where each sensor compresses its observation to a small number of bits with length proportional to the logarithm of its local signal-to-noise ratio (SNR). The resulting compressed bits from different sensors are then collected and combined by the fusion center to estimate the unknown parameter. The proposed DES is universal in the sense that each sensor compression scheme requires only the knowledge of local SNR, rather than the noise probability distribution functions (pdf), while the final fusion step is also independent of the local noise pdfs. We show that the MSE of the proposed DES is within a constant factor of 25/8 of that achieved by the classical centralized BLUE estimator.