Cost Of Redundancy Research Articles

Integrating Statistical Simulation and Optimization for Redundancy Allocation in Smart Grid Infrastructure

It is a critical issue to allocate redundancy to critical smart grid infrastructure for disaster recovery planning. In this study, a framework to combine statistical prediction methods and optimization models for the optimal redundancy allocation problem is presented. First, statistical simulation methods to identify critical nodes of very large-scale smart grid infrastructure based on the topological features of embedding networks are developed, and then a linear integer programming model based on generalized assignment problem (GAP) for the redundancy allocation of critical nodes in smart grid infrastructure is presented. This paper aims to contribute to the field by employing a general redundancy allocation problem (GRAP) model from high-order nonlinear to linear model transformation. The model is specifically implemented in the context of smart grid infrastructure. The innovative linear integer programming model proposed in this paper capitalizes on the logarithmic multiplication property to reframe the inherently nonlinear resource allocation problem (RAP) into a linearly separable function. This reformulation markedly streamlines the problem, enhancing its suitability for efficient and effective solutions. The findings demonstrate that the combined approach of statistical simulation and optimization effectively addresses the size limitations inherent in a sole optimization approach. Notably, the optimal solutions for redundancy allocation in large grid systems highlight that the cost of redundancy is only a fraction of the economic losses incurred due to weather-related outages.

Multi-objective micro phasor measurement unit placement and performance analysis in distribution system using NSGA-II and PROMETHEE-II

The bidirectional flow of electrical power has mandated the monitoring of the distribution system (DS) in real-time using synchronized data to overcome problems linked to grid stability, that can cause cascade failure. This synchronized data is gathered by micro-phasor measurement units (µPMUs) and is beneficial in determining the operational health of the DS. In the present article, a multi-objective optimal µPMU placement problem (µPPP) for DS is addressed for two conflicting objectives viz., minimization of µPMU installation cost and maximization of measurement redundancy using non-dominated sorting genetic algorithm-II (NSGA-II) and multi criteria technique called PROMETHEE-II under practical DS scenarios. The proposed solution methodology is compared with well-established Multiobjective techniques and validated on Indian 85-bus and standard IEEE distribution systems, to establish its superiority in locating Pareto optimal solutions (single/multiple solutions). Finally, cost analysis is done which indicates substantial cost saving when µPMUs with variable cost are considered.

Empirical Study of Large-Scale HLA Simulation of Parallel Region-Matching Knowledge Recognition Algorithm Based on Region Matching.

Most of the existing region-matching algorithms need to match all regions, resulting in a waste of computing resources, increasing the cost of simulation technology and data redundancy, and resulting in the reduction of network data stream transmission efficiency. This paper presents a parallel region-matching knowledge recognition algorithm. Combined with the shortcomings of existing matching algorithms, a simulation technology is constructed to realize the parallel matching of multiple regions in HLA distributed simulation. The algorithm can realize the parallel matching calculation of multiple changed regions in one simulation. At the same time, the basic idea based on mobile intersection is adopted in the matching calculation, and the historical information before and after the region range is moved is used. The matching is limited to the moving interval, and the moving crossover theory is applied to the matching calculation to realize the relevant historical information before and after the region. Simulation results show that the parallel region-matching knowledge recognition algorithm can support HLA distributed simulation evaluation. In the matching calculation, the basic idea based on moving intersection is adopted, and the matching is limited to the moving interval by using the historical information before and after the region is moved, which reduces a large number of irrelevant calculations. Theoretical analysis and experimental results show that the algorithm is particularly suitable for the application needs of building large-scale distributed simulation based on multi-core computing platform.

Autonomous clocks that regulate organelle biogenesis, cytoskeletal organization, and intracellular dynamics.

How do cells perceive time? Do cells use temporal information to regulate the production/degradation of their enzymes, membranes, and organelles? Does controlling biological time influence cytoskeletal organization and cellular architecture in ways that confer evolutionary and physiological advantages? Potential answers to these fundamental questions of cell biology have historically revolved around the discussion of ‘master’ temporal programs, such as the principal cyclin-dependent kinase/cyclin cell division oscillator and the circadian clock. In this review, we provide an overview of the recent evidence supporting an emerging concept of ‘autonomous clocks,’ which under normal conditions can be entrained by the cell cycle and/or the circadian clock to run at their pace, but can also run independently to serve their functions if/when these major temporal programs are halted/abrupted. We begin the discussion by introducing recent developments in the study of such clocks and their roles at different scales and complexities. We then use current advances to elucidate the logic and molecular architecture of temporal networks that comprise autonomous clocks, providing important clues as to how these clocks may have evolved to run independently and, sometimes at the cost of redundancy, have strongly coupled to run under the full command of the cell cycle and/or the circadian clock. Next, we review a list of important recent findings that have shed new light onto potential hallmarks of autonomous clocks, suggestive of prospective theoretical and experimental approaches to further accelerate their discovery. Finally, we discuss their roles in health and disease, as well as possible therapeutic opportunities that targeting the autonomous clocks may offer.

BALANSING OF POWER AND ELECTRICITY IN THE ELECTRIC POWER SYSTEM WITH RENEWABLE ENERGY SOURCES BY CRITERIONAL METHOD

This article considers the features of the development of renewable energy sources in electrical networks. The main changes in the functional properties of power systems, which include a significant reduction in electricity consumption, change in the structure of electricity consumption, rapid increase in the installed capacity of solar and wind power plants. Electricity consumption in 2020 is almost halved compared to 1990 (from 227 to 119 billion kWh) and as a consequence the share of semi-peak thermal generation, which gave the power system basic flexibility, has significantly decreased (from 71 % in 1990 to 35 % in 2020) and at the same time the share of nuclear generation, which operates in base mode, has increased (from 25 % to 51 %). In particular, consumption by industry with a stable load schedule, decreased (from 146 billion kWh (64 %) to 49 billion kWh (42 %)). At the same time, the demand for electricity by the households, whose consumption profile of which is characterized by significant daily unevenness and sensitivity to meteorological factors, has significantly increased (from 21 billion kWh (9 %) to 37 billion kWh (31 %)). Therefore, the article analyses the preconditions for the problem of flexible generation and explores possible ways to solve them. The optimal composition of electricity generation for Ukraine in the period 2021–2025 is proposed, which provides for the preservation and even increase by optimizing the repair campaign of the share of electricity production by nuclear power plants, the introduction of additional 2–2.5 GW of highly flexible generation and up to 2 GW storage systems (taking into account the pumped-storage power plant), as well as a gradual evolutionary decline in both installed capacity and electricity production by semi-peak coal-fired power plants and maintaining a policy of decarbonisation to ensure its own energy security. A comprehensive approach to compensating for the instability of renewable energy sources generation has been developed, which consists in minimizing the cost of power redundancy in various available ways. The problem of cost optimization for ways to compensate for the instability of renewable energy sources generation is solved by the method of criterion programming. The impact of each backup method on total costs is determined using sensitivity theory.

A fast Binary Decision Diagram (BDD)-based reversible logic optimization engine driven by recent meta-heuristic reordering algorithms

Reversible logic has recently gained a remarkable interest due to its information lossless property, which minimizes power dissipation in the circuit. Furthermore, with their natural reversibility, quantum computations can profit from the advances in reversible logic synthesis, as the latter can be easily applied to map practical logic designs to quantum architectures. Although numerous algorithms have been proposed to synthesize reversible circuits with low cost, the increasing demands for scalable synthesis techniques represent a serious barrier in the synthesis process. Furthermore, the enhanced reliability of the synthesized circuits comes at the cost of redundancy in the quantum architecture of the gates composing that circuit, which increases the overall manufacturing cost for fault-tolerant circuits. Binary Decision Diagram (BDD) based synthesis has demonstrated a great evidence in reversible logic synthesis, due to its scalability in synthesizing complex circuits within a reasonable time. However, the cost of the synthesized circuit is roughly correlated to its corresponding BDD size. In this paper, we propose a fast reversible circuit synthesis methodology driven by a BDD-reordering optimization engine implemented by recent meta-heuristic optimization algorithms. Experimental results show that Genetic Algorithm (GA) based reordering supported with Alternating Crossover (AX) and swap mutation outperforms others as it is the least destructive for low-cost BDDs during the optimization recipe.

Erasure Coding for Ultra-Low Power Wireless Networks

In this paper, we study erasure coding for ultra-low power wireless networks with power consumption in order of milliwatts. We propose sparse parallel concatenated coding (SPCC) scheme, in which we optimize sparsity and ratio of coded packets over GF (2) (i.e., Galois field of size two) and larger field size such as GF (32) for different values of ${k}$ so that the total energy cost of the network is minimized. While high sparsity decreases energy cost of encoding, it comes at the tradeoff cost of high reception redundancy. The use of GF (2) packets minimizes the computational cost of encoding and decoding, while the use of small fraction of packets over GF (32) minimizes reception redundancies. Testbed implementation shows that SPCC energy gain increases with increasing packet generation size ${k}$ . We show that for the case where ${k}~\leq $ 40, SPCC reduces energy cost by up to 100% compared with the next best performing coding scheme.

가외성의 정당성과 한계: 지역 원전안전 감시체계 선택의 딜레마

가외성의 정당성과 한계: 지역 원전안전 감시체계 선택의 딜레마

A trust management framework for clouds

In today’s cloud computing platforms, more and more users are now working or collaborating in the multi-cloud environment, in which collaborators, clouds, computing nodes may belong to different institutions or organizations. Those different organizations might have their policies. Security is still a big concern in cloud computing. To help cloud vendors and customers to detect and prevent from being affected by potential attacks, we propose a trust management framework. We consider link/flow’s level trust, node’s level trust, and task/mission’s level trust.We introduced a new security metric trustability (trust–reliability) and a new algorithm to calculate it. Trustability measures how much a system can be trusted under a specific attack vector. Trustability can be used to explore the design space of resource configuration in order be able to choose the right trade-off between trustability and cost of redundancy. We show that our trust management framework can guide the administrators and customers to make decisions. For example, based on the real-time trust information, cloud administrators can migrate tasks from suspect nodes to trustworthy nodes, dynamically allocate a resource, and manage the trade-off between the degree of redundancy and the cost of the resource.

The collective intelligence of random small crowds: A partial replication of Kosinski et al. (2012)

AbstractWe examined the trade-off between the cost of response redundancy and the gain in output quality on the popular crowdsourcing platform Mechanical Turk, as a partial replication of Kosinski et al. (2012) who demonstrated a significant improvement in performance by aggregating multiple responses through majority vote. We submitted single items from a validated intelligence test as Human Intelligence Tasks (HITs) and aggregated the responses from “virtual groups” consisting of 1 to 24 workers. While the original study relied on resampling from a relatively small number of responses across a range of experimental conditions, we randomly and independently sampled from a large number of HITs, focusing only on the main effect of group size. We found that – on average – a group of six MTurkers has a collective IQ one standard deviation above the mean for the general population, thus demonstrating a “wisdom of the crowd” effect. The relationship between group size and collective IQ was characterised by diminishing returns, suggesting moderately sized groups provide the best return on investment. We also analysed performance of a smaller subset of workers who had each completed all 60 test items, allowing for a direct comparison between a group’s collective IQ and the individual IQ of its members. This demonstrated that randomly selected groups collectively equalled the performance of the best-performing individual within the group. Our findings support the idea that substantial intellectual capacity can be gained through crowdsourcing, contingent on moderate redundancy built into the task request.

Design of Low-redundant Cosine-modulated Nonuniform Filter Bank with Flexible Frequency Division

In this paper, a low-redundant cosine-modulated nonuniform filter bank (LR-CMNFB) and its design method are proposed. The proposed LR-CMNFB consists of two parallel subsystems which have the same frequency division scheme. The nonuniform analysis and synthesis filters of the first subsystem are formed by directly merging the consecutive cosine-modulated versions of a lowpass prototype filter, and the filters of the second subsystem are derived to meet the aliasing cancelation condition. Since the aliasing of the two subsystems is structurally canceled without guardband constraint on the filter location, the shift-invariance and flexible nonuniform frequency division, two important properties in many signal and image processing applications, can be achieved simultaneously at the cost of low redundancy (that is less than 2). From a particular analysis on the filter characteristic and the reconstruction error of the whole system, it is found that the good characteristics of filters and the good reconstruction performance of LR-CMNFB can be jointly obtained by constraining the prototype filter to be the linear-phase spectral factor of a 2 Mth band filter. Several design examples are given to illustrate the performance of the proposed LR-CMNFB and its potential in practical applications.

A pilot study regarding basic knowledge of "cortical visual impairment in children" among ophthalmologists.

Purpose:A pilot study was done to evaluate knowledge regarding “cortical visual impairment (CVI) in children” among ophthalmologists.Methods:This study was conducted during the annual conference of a zonal ophthalmological society. All ophthalmologists who attended the conference were requested to participate in this study. Those who agreed were given a validated questionnaire to assess knowledge regarding CVI. Cronbach's alpha of the questionnaire was 0.6. Participants were asked to respond to multiple choice questions by choosing the single best option. The responses obtained were then evaluated.Results:The total number of registered delegates in the conference was 448. A total of 103 ophthalmologists showed interest to participate in the study with a response rate of 22.9%. Only 89/103 interested delegates were included in the study as remaining were unaware of CVI. No participant gave correct answers to all questions. Although more than 80% of them knew the most common association (87%) and site of pathology (84%), only 52% were sure about clinical features and even lesser respondents (39%) knew that magnetic resonance imaging is the correct investigation of choice. The majority responded correctly that these children need eye examination (89%) and can be managed by rehabilitation through multidisciplinary approach (82%), but only 58% could recognize differential diagnoses and had a correct idea regarding the prognosis of CVI. There was no correlation between the number of patients diagnosed per month by the respondent with knowledge of the disease.Conclusion:In this pilot study, ophthalmologists were found to have limited knowledge regarding clinical features, investigation, differential diagnosis, and visual prognosis of CVI in children. There is a need to improve awareness regarding CVI among ophthalmologists.

Reliable Linear, Sesquilinear, and Bijective Operations on Integer Data Streams Via Numerical Entanglement

A new technique is proposed for fault-tolerant linear, sesquilinear and bijective (LSB) operations on $M$ integer data streams ( $M \geq 3$ ), such as: scaling, additions/subtractions, inner or outer vector products, permutations and convolutions. In the proposed method, $M$ input integer data streams are linearly superimposed to form $M$ numerically-entangled integer data streams that are stored in-place of the original inputs. LSB operations can then be performed directly using these entangled data streams. The results are extracted from the $M$ entangled output streams by additions and arithmetic shifts. Any soft errors affecting one disentangled output stream are guaranteed to be detectable via a post-computation reliability check. Additionally, when utilizing a separate processor core for each stream, our approach can recover all outputs after any single fail-stop failure. Importantly, unlike algorithm-based fault tolerance (ABFT) methods, the number of operations required for the entire process is linearly related to the number of inputs and does not depend on the complexity of the performed LSB operations. We have validated our proposal in an Intel processor via several types of operations: fast Fourier transforms, convolutions, and matrix multiplication operations. Our analysis and experiments reveal that the proposed approach incurs between 0.03% to 7% reduction in processing throughput for numerous LSB operations. This overhead is 5 to 1000 times smaller than that of the equivalent ABFT method that uses a checksum stream. Thus, our proposal can be used in fault-generating processor hardware or safety-critical applications, where high reliability is required without the cost of ABFT or modular redundancy.

Algorithm 956

Pseudo-arclength continuation is a well-established method for generating a numerical curve approximating the solution of an underdetermined system of nonlinear equations. It is an inherently sequential predictor-corrector method in which new approximate solutions are extrapolated from previously converged results and then iteratively refined. Convergence of the iterative corrections is guaranteed only for sufficiently small prediction steps. In high-dimensional systems, corrector steps are extremely costly to compute and the prediction step length must be adapted carefully to avoid failed steps or unnecessarily slow progress. We describe a parallel method for adapting the step length employing several predictor-corrector sequences of different step lengths computed concurrently. In addition, the algorithm permits intermediate results of correction sequences that have not converged to seed new predictions. This strategy results in an aggressive optimization of the step length at the cost of redundancy in the concurrent computation. We present two examples of convoluted solution curves of high-dimensional systems showing that speed-up by a factor of two can be attained on a multicore CPU while a factor of three is attainable on a small cluster.

Rate/distortion optimization in multiple description video coding

Multiple Description Coding (MDC) is a technique where multiple streams from a video source are generated, each individually decodable and mutually refinable. MDC is a promising solution to overcome packet loss in video transmission over noisy channels, particularly for real-time applications in which retransmission of lost information is not practical. The error resiliency feature of MDC is achieved at the cost of redundancy, and the required amount of redundancy for each frame depends on the packet loss ratio and also the importance of the frame in the sequence. Due to the error propagation in video transmission over lossy channels, reference frames of a Group of Pictures (GOP) are more important for video reconstruction and, hence, need more redundancy to increase the chance of being received correctly. Therefore a channel adaptive optimization for frame-wise redundancy allocation is needed. In this paper, based on the difference of the side and central decoder outputs, the receiver side distortion is formulated and then used for optimization of a MDC scheme. The performance of the optimizer is verified by experimental results measured from JM 16.0, H.264/AVC reference software.

Preventive and corrective maintenance – cost comparison and cost–benefit analysis

Maintenance can represent a significant portion of the cost in asset intensive organisations, as breakdowns have an impact on the capacity, quality and cost of operation. However, the formulation of a maintenance strategy depends on a number of factors, including the cost of down time, reliability characteristics and redundancy of assets. Consequently, the balance between preventive maintenance (PM) and corrective maintenance (CM) for minimising costs varies between organisations and assets. Nevertheless, there are some rules of thumb on the balance between PM and CM, such as the 80/20 rule. Studies on the relationship between PM and CM in practice are rare. Therefore, PM and CM costs are studied in this article by analysing historical maintenance data. A case study of rail infrastructure historical data is carried out to determine the shares of PM and CM, together with a cost–benefit analysis (CBA) to assess the value of PM. The results show that the PM represents 10% to 30% of the total maintenance cost when user costs, i.e. train delays, are included as a CM cost. The CBA shows the benefit of PM is positive with a benefit–cost ratio at 3.3. However, the results depend on the inclusion/exclusion of user costs, besides individual organisational parameters.

Single Beacon Indoor Localization System Based on Counter-Synchronized Compass and RSSI

Indoor localization system has been a popular research area in recent decades and many of them are based on multiple beacons localization method. However, there are some special applications to which the multiple beacons method is not an optimal solution due to its overdesign and cost of redundancy. Multiple beacons method uses at least three transducers and each transducer’s location must be known to find the location of a target object by using either Triangulation or Trilateration calculation. When the multiple beacons method is applied in an items lost and found system, the precise Cartesian coordinates of a target item can be found, but it is definitely overdesign and incurring redundant cost. It is due to the fact that the target item requires only two simple information i.e. Clock orientation and distance information; therefore, single beacon is enough for the task. In this paper, we propose a single beacon localization method to optimize the solution in the items lost and found system by utilizing clock orientation and estimated distance information. The proposed single beacon localization algorithm has been demonstrated and proven that it can be one of the optimal solutions for items lost and found system.

Evaluation of Redundancy for Power Generating Unit in a Cogeneration Power Plant

Redundancy system is very useful to enhance the performance and reliability of the power generation system of a cogeneration plant. However, the associated operating cost of redundancy system is very high. The common redundancies used in a cogeneration power plant are public utility and generator set. In order to select the best redundancy options which incurs minimum operating cost, it is required to evaluate the cost of different redundancy options. In this paper, net present value model (NPV) is developed to evaluate the cost of redundancy considering availability and reliability of the cogeneration system. Two steps applied to evaluate the redundancy cost of the cogeneration system. The first step is predicting the number of failures and downtime hours using availability and reliability analysis because redundancy is frequently used when the system failed. The second step is evaluating the cost of redundancy using NPV model. The results indicate that the use of public utility as redundancy option is costly compared to generator set option for long period of time. The major operation cost of public utility is contributed by the maximum demand charge cost which is about 57.9% of the total cost of redundancy. The study will be useful as a guide for the cogeneration operation to evaluate and select the redundancy option.

Energy Saving in WSN with Directed Connectivity

Wireless Sensor Networks have been implemented in many indoor applications such as offices, hospitals, laboratories for monitoring the parameters such as temperature, humidity etc. Most of the applications have used omnidirectional antennas. In randomly deployed ad hoc wireless sensor networks, this may be useful to achieve coverage and connectivity with unknown neighbors. In case of deterministic deployments such as in case of food grain storages where locations of the sensor nodes are mostly fixed, the main challenges are unstable and vacillating conditions in the godowns during loading and unloading of sacs as well as unpredictable changes in climate. Most of the commercial motes generally use omnidirectional antennas. Energy overheads increase considerably with omnidirectional antennas. Directivity increases energy saving but may be at the cost of redundancy. This paper is mainly focused on the energy advantage in ad hoc wireless sensor networks deployed in large food grain storages and energy overheads required for obtaining certain level of redundancy using directional antennas. Finally, we conclude that energy advantage can be achieved even if we overcome redundancy to certain extent.

Thread Relocation: A Runtime Architecture for Tolerating Hard Errors in Chip Multiprocessors

As the semiconductor industry continues its relentless push for nano-CMOS technologies, device reliability and occurrence of hard errors have emerged as a dominant concern in multicores. Although regular memory structures are protected against hard errors using error correcting codes or spare rows and columns, many of the structures within the cores are left unprotected. Even if the location of hard errors is known a priori, disabling faulty cores results in a substantial performance loss. Several proposed techniques use microarchitectural redundancy to allow defective cores to continue operation. These techniques are attractive, but limited due to either added cost of additional redundancy that offers no benefits to an error-free core, or limited coverage, due to the natural redundancy offered by the microarchitecture. We propose to exploit the intercore redundancy in chip multiprocessors for hard-error tolerance. Our scheme combines hardware reconfiguration to ensure reduced functionality of cores, and a runtime layer of software (microvisor) to manage mapping of threads to cores. Microvisor observes the changing phase behavior of threads and initiates thread relocation to match the computational demands of threads to the capabilities of cores. Our results show that in the presence of degraded cores, microvisor mitigates performance losses by an average of two percent.