On trade-off solution pairs in a special type of transportation problem

Abstract is not available.

The Relay Selection and Transmission Trade-off in Cooperative Communication Systems

A common and practical paradigm in cooperative communication systems is the use of a dynamically selected `best' relay to decode and forward information from a source to a destination. Such systems use two phases - a relay selection phase, in which the system uses transmission time and energy to select the best relay, and a data transmission phase, in which it uses the spatial diversity benefits of selection to transmit data. In this paper, we derive closed-form expressions for the overall throughput and energy consumption, and study the time and energy trade-off between the selection and data transmission phases. To this end, we analyze a baseline non-adaptive system and several adaptive systems that adapt the selection phase, relay transmission power, or transmission time. Our results show that while selection yields significant benefits, the selection phase's time and energy overhead can be significant. In fact, at the optimal point, the selection can be far from perfect, and depends on the number of relays and the mode of adaptation. The results also provide guidelines about the optimal system operating point for different modes of adaptation. The analysis also sheds new insights on the fast splitting-based algorithm considered in this paper for relay selection.

Performance and variability trade-off with gate-to-source/drain overlap length

The impact of gate-to-source/drain overlap length on performance and variability of 65 nm CMOS is presented. The device and circuit variability is investigated as a function of three significant process parameters, namely gate length, gate oxide thickness, and halo dose. The comparison is made with three different values of gate-to-source/drain overlap length namely 5 nm, 0 nm, and -5 nm and at two different leakage currents of 10 nA and 100 nA. The Worst-Case-Analysis approach is used to study the inverter delay fluctuations at the process corners. The drive current of the device for device robustness and stage delay of an inverter for circuit robustness are taken as performance metrics. The design trade-off between performance and variability is demonstrated both at the device level and circuit level. It is shown that larger overlap length leads to better performance, while smaller overlap length results in better variability. Performance trades with variability as overlap length is varied. An optimal value of overlap length of 0 nm is recommended at 65 nm gate length, for a reasonable combination of performance and variability.

Diversity-Rate Trade-off for Fading Channels with Power Control

We consider a complex, additive, white Gaussian noise channel with flat fading. We study its diversity order vs transmission rate for some known power allocation schemes. The capacity region is divided into three regions. For one power allocation scheme, the diversity order is exponential throughout the capacity region. For selective channel inversion (SCI) scheme, the diversity order is exponential in low and high rate region but polynomial in mid rate region. For fast fading case we also provide a new upper bound on block error probability and a power allocation scheme that minimizes it. The diversity order behaviour of this scheme is same as for SCI but provides lower BER than the other policies.

Regenerating codes: A reformulated storage-bandwidth trade-off and a new construction

In this paper, the storage-repair-bandwidth (SRB) trade-off curve of regenerating codes is reformulated to yield a tradeoff between two global parameters of practical relevance, namely information rate and repair rate. The new information-repair-rate (IRR) tradeoff provides a different and insightful perspective on regenerating codes. For example, it provides a new motivation for seeking to investigate constructions corresponding to the interior of the SRB tradeoff. Interestingly, each point on the SRB tradeoff corresponds to a curve in the IRR tradeoff setup. We characterize completely, functional repair under the IRR framework, while for exact repair, an achievable region is presented. In the second part of this paper, a rate-half regenerating code for the minimum storage regenerating point is constructed that draws upon the theory of invariant subspaces. While the parameters of this rate-half code are the same as those of the MISER code, the construction itself is quite different.

A trade-off between maxima in efficiency and specific work output of super- and trans-critical CO2 Brayton cycles

Several operational aspects for thermal power plants in general are non-intuitive and involve simultaneous optimization of a number of operational parameters. In the case of solar operated power plants, it is even more difficult due to varying heat source temperatures induced by variability in insolation levels. This paper introduces a quantitative methodology for load regulation of a CO2 based Brayton cycle power plant using the `thermal efficiency and specific work output' coordinate system. The analysis shows that a transcritical CO2 cycle offers more flexibility under part load performance than the supercritical cycle in case of non-solar power plants. However, for concentrated solar power, where efficiency is important, supercritical CO2 cycle fares better than transcritical CO2 cycle. A number of empirical equations relating heat source temperature, high side pressure with efficiency and specific work output are proposed which could assist in generating control algorithms. (C) 2015 Elsevier B.V. All rights reserved.

On the Selection of Optimum Savitzky-Golay Filters

Savitzky-Golay (S-G) filters are finite impulse response lowpass filters obtained while smoothing data using a local least-squares (LS) polynomial approximation. Savitzky and Golay proved in their hallmark paper that local LS fitting of polynomials and their evaluation at the mid-point of the approximation interval is equivalent to filtering with a fixed impulse response. The problem that we address here is, ``how to choose a pointwise minimum mean squared error (MMSE) S-G filter length or order for smoothing, while preserving the temporal structure of a time-varying signal.'' We solve the bias-variance tradeoff involved in the MMSE optimization using Stein's unbiased risk estimator (SURE). We observe that the 3-dB cutoff frequency of the SURE-optimal S-G filter is higher where the signal varies fast locally, and vice versa, essentially enabling us to suitably trade off the bias and variance, thereby resulting in near-MMSE performance. At low signal-to-noise ratios (SNRs), it is seen that the adaptive filter length algorithm performance improves by incorporating a regularization term in the SURE objective function. We consider the algorithm performance on real-world electrocardiogram (ECG) signals. The results exhibit considerable SNR improvement. Noise performance analysis shows that the proposed algorithms are comparable, and in some cases, better than some standard denoising techniques available in the literature.

Latency, Power and Performance Trade-offs in Network-on-Chips by Link Microarchitecture Exploration

This paper presents a power, latency and throughput trade-off study on NoCs by varying microarchitectural (e.g. pipelining) and circuit level (e.g. frequency and voltage) parameters. We change pipelining depth, operating frequency and supply voltage for 3 example NoCs - 16 node 2D Torus, Tree network and Reduced 2D Torus. We use an in-house NoC exploration framework capable of topology generation and comparison using parameterized models of Routers and links developed in SystemC. The framework utilizes interconnect power and delay models from a low-level modelling tool called Intacte[1]1. We find that increased pipelining can actually reduce latency. We also find that there exists an optimal degree of pipelining which is the most energy efficient in terms of minimizing energy-delay product.

Comprehensive Path-sensitive Data-flow Analysis

Data-flow analysis is an integral part of any aggressive optimizing compiler. We propose a framework for improving the precision of data-flow analysis in the presence of complex control-flow. W initially perform data-flow analysis to determine those control-flow merges which cause the loss in data-flow analysis precision. The control-flow graph of the program is then restructured such that performing data-flow analysis on the resulting restructured graph gives more precise results. The proposed framework is both simple, involving the familiar notion of product automata, and also general, since it is applicable to any forward data-flow analysis. Apart from proving that our restructuring process is correct, we also show that restructuring is effective in that it necessarily leads to more optimization opportunities. Furthermore, the framework handles the trade-off between the increase in data-flow precision and the code size increase inherent in the restructuring. We show that determining an optimal restructuring is NP-hard, and propose and evaluate a greedy strategy. The framework has been implemented in the Scale research compiler, and instantiated for the specific problem of Constant Propagation. On the SPECINT 2000 benchmark suite we observe an average speedup of 4% in the running times over Wegman-Zadeck conditional constant propagation algorithm and 2% over a purely path profile guided approach.

Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

Analysis-By-Synthesis Based Switched Transform Domain Split Vq Using Gaussian Mixture Model

Using analysis-by-synthesis (AbS) approach, we develop a soft decision based switched vector quantization (VQ) method for high quality and low complexity coding of wideband speech line spectral frequency (LSF) parameters. For each switching region, a low complexity transform domain split VQ (TrSVQ) is designed. The overall rate-distortion (R/D) performance optimality of new switched quantizer is addressed in the Gaussian mixture model (GMM) based parametric framework. In the AbS approach, the reduction of quantization complexity is achieved through the use of nearest neighbor (NN) TrSVQs and splitting the transform domain vector into higher number of subvectors. Compared to the current LSF quantization methods, the new method is shown to provide competitive or better trade-off between R/D performance and complexity.

An approach for sensitivity-reduced design of linear regulators

A now procedure for the design of sensitivity-reduced control for linear regulators is described. The control is easily computable and implementable since it requires neither the solution of an increased-order augmented system nor the generation and feedback of a trajectory sensitivity vector. The method provides a trade-off between reduction in sensitivity measure and increase in performance index.

Comparative life-history traits in a fig wasp community: implications for community structure

1. Whether life-history traits can determine community composition and structure is an important question that has been well explored theoretically, but has received scant empirical attention. Life-history traits of a seven-member community of galler and parasitoid fig wasp species (Chalcidoidea), developing within the inflorescences (syconia) of Ficus racemosa (Moraceae) in India, were determined and used to examine community structure and ecology. 2. Gallers were pro-ovigenic (all eggs are mature upon adult emergence) whereas parasitoids were synovigenic (eggs mature progressively during adult lifespan). Initial egg load was correlated with body size for some species, and there was a trade-off between egg number and egg size across all species. Although all species completed their development and left the syconium concurrently, they differed in their adult and pre-adult lifespans. Providing sucrose solutions increased parasitoid lifespan but had no effect on the longevity of some galler species. While feeding regimes and body size affected longevity in most species, an interaction effect between these variables was detected for only one species. 3. Life-history traits of wasp species exhibited a continuum in relation to their arrival sequence at syconia for oviposition during syconium development, and therefore reflected their ecology. The largest number of eggs, smallest egg sizes, and shortest longevities were characteristic of the earliest-arriving galling wasps at the smallest, immature syconia; the converse characterised the later-arriving parasitoids at the larger, already parasitised syconia. Thus life history is an important correlate of community resource partitioning and can be used to understand community structure. 4. This is the first comprehensive study of life-history traits in a fig wasp community. The comparative approach revealed constraints and flexibility in trait evolution.

Low PAPR full-diversity space-frequency codes for MIMO-OFDM systems

Use of precoding transforms such as Hadamard Transforms and Phase Alteration for Peak to Average Power Ratio (PAPR) reduction in OFDM systems are well known. In this paper we propose use of Inverse Discrete Fourier Transform (IDFT) and Hadamard transform as precoding transforms in MIMO-OFDM systems to achieve low peak to average power ratio (PAPR). We show that while our approach using IDFT does not disturb the diversity gains of the MIMO-OFDM systems (spatial, temporal and frequency diversity gains), it offers a better trade-off between PAPR reduction and ML decoding complexity compared to that of the Hadamard transform precoding. We study in detail the amount of PAPR reduction achieved for the following two recently proposed full-diversity Space-Frequency coded MIMO-OFDM systems using both the IDFT and the Hadamard transform: (i) W. Su. Z. Safar, M. Olfat, K. J. R. Liu (IEEE Trans. on Signal Processing, Nov. 2003), and (ii) W. Su, Z. Safar, K. J. R. Liu (IEEE Trans. on Information Theory, Jan. 2005).

Dynamic programming based optimum non-uniform samples for speech reconstruction and coding

Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.