Optimal Redundancy Research Articles

Optimal redundancies of parallel–series systems in irrelevancy coverage model

A common method for increasing the reliability of a system is to introduce redundant components. However, when the coverage of a fault is imperfect, the system may fail prior to the exhaustion of spares because of noncovered component failures, and an excessive level of redundancy may reduce rather than improve the system reliability. This study investigates the optimal redundancy of parallel–series systems in an irrelevancy coverage model (ICM), which is an extension of the imperfect fault coverage model (IFCM). Three different optimal strategies are studied in ICM, namely optimal redundancies for reliability maximization, cost minimization, and both. Experimental results demonstrate that the optimal redundancies in the ICM are different from those in the IFCM, and the ICM can accommodate more redundant subsystems for parallel–series systems to achieve higher reliability and lower cost than the IFCM in general.

A risk-averse stochastic approximation of the optimal allocation of active redundancies to coherent systems

This article deals with the active redundancy allocation to coherent systems. We extend the optimal allocation policy uniformly maximizing the redundant system reliability function to that maximizing the mean lower semi-deviation of the redundant system lifetime, and then we propose a stochastic algorithm to approximate the optimal redundancy allocation policy through maximizing the mean lower semi-deviation of the system lifetime. Some numerical examples are presented to illustrate the algorithm as well.

Designing of fault-tolerant computer system structures using residue number systems

AbstractThis article discusses computing systems that operate in residue number systems (RNSs). The main direction of improving computer systems (CSs) is increasing the speed of implementation of arithmetic operations and the reliability of their functioning. Encoding data in RNS solves the problem of optimal redundancy, i.e., the creation of such computing systems provides maximum reliability with restrictions on weight and size characteristics. This article proposes new structures of fault-tolerant CSs operating in RNS in the case of the application with an active fault-tolerant method. The use of the active fault-tolerant method (dynamic redundancy) in the RNSs provides higher reliability. In addition, with an increase in the digits of CSs, the efficiency of using the proposed structures increases.

Secrecy Energy Efficiency Maximization in UAV-Enabled Wireless Sensor Networks Without Eavesdropper’s CSI

Unmanned aerial vehicles (UAVs) are anticipated to be a potential data collection solution for wireless sensor networks (WSNs). The main challenges of integrating UAVs in WSNs are security threats and UAV’s onboard energy limitation. To cope with these two challenges, this article examines the secrecy energy efficiency (SEE) maximization problem in UAV-enabled WSN. Specifically, a full-duplex (FD) UAV gathers confidential information from ground sensor nodes (SNs) in the uplink while sending jamming signals to confound a ground eavesdropper (Eve) in the downlink. Considering a passive eavesdropping scenario lacking Eve’s instantaneous channel state information (CSI), the resulting problem is subject to the constraints of connection outage probability (COP), secrecy outage probability (SOP), securely collected bits, and flight trajectory. To tackle the intractable nonconvex problem, we first derive the optimal codeword rate and redundancy rate in closed-form expressions and then develop a low-complexity algorithm using the block coordinate descent (BCD) approach to alternatively optimize the SN scheduling, SN transmit power, UAV transmit power, and UAV trajectory. Simulation results verify the performance gains of the proposed scheme compared with the benchmark schemes. In particular, the proposed scheme achieves nearly the same secrecy rate gains at a lower UAV’s energy consumption cost than the sum secrecy rate maximization (SSRM) baseline. Moreover, it is revealed that trajectory optimization of the proposed scheme plays a crucial role in improving SEE performance compared with the circle trajectory (CT) baseline.

PROPOSAL OF AN OPTIMAL REDUNDANCY AND RELIABILITY ALLOCATION APPROACH FOR DESIGNING COMPLEX SYSTEMS

Problems of optimal reliability and redundancy allocation are not new. However, the literature describes two isolated situations, either when redundancy allocation is the target and the reliability metrics of the components are known, or focusing on the reliability allocation, that demands the metrics to be known in advance and the use of some optimization approach. In the present paper, we consider a combined situation, i.e., when both situations must be considered together. To guide the allocation process, we developed a cost function that considers the costs of acquisition, development and/or improvement as a function of monetary effort, along with the reliability target and expected failure costs. The results considering two classical test problems in the literature demonstrated the efficacy of the proposed approach to deal with similar situations.

Hybrid MMC Redundancy Configuration Calculation Method Based on Heuristic Algorithm

Most of the existing redundant configuration methods of modular level converters (MMC) only consider the reliability of the MMC, and rarely consider the utilization of insulated gate bipolar transistors (IGBT). A heuristic algorithm-based calculation method for hybrid MMC redundancy configuration is proposed in order to better meet the engineering practicality. Firstly, the topology of the hybrid MMC is introduced, and the correlation between submodules is introduced into the calculation of its reliability. Secondly, the index of IGBT utilization is proposed to judge the economic advantage. The effects of correlation and service life on the reliability of the hybrid MMC and the IGBT utilization are analyzed. Then, heuristic factors are constructed with reliability and IGBT utilization, and the optimal redundancy configuration scheme of hybrid MMC is obtained by heuristic algorithm. Finally, based on the parameters of Kunliulong multi-terminal hybrid DC transmission project, the calculation is verified in Matlab and compared with the results of the difference method to illustrate the feasibility and superiority of the proposed redundancy configuration calculation method.

APPLICATION OF OFFICE INFORMATION TECHNOLOGIES TO SOLVE THE PROBLEMS OF OPTIMAL STRUCTURAL RESERVATION OF SYSTEMS

Problem statement. The problems of optimal structural redundancy of systems are usually formulated as a nonlinear problem of mathematical programming with integer variables, and to solve them, usually, various optimization methods are used, which requires the development of special algorithms and appropriate software. However, in the case of clarifying the original task of optimal redundancy, there is often a need to adjust the developed algorithms and software. All this greatly complicates obtaining the desired results. Another approach to solving problems of optimal redundancy of systems is the use of office information technology, the tool environment of which is adapted to solve mathematical problems, including optimization problems. This approach does not require the development of special algorithms and software. However, issues related to the effectiveness of the information technology used to solve this problem require further scientific and practical study. This article formulates a model of optimal design of redundant systems according to the criterion of minimum cost while ensuring the required level of reliability during a given time. This model is written in terms of a nonlinear problem of mathematical programming with integer variables and is numerically implemented in the operating environment of an Excel spreadsheet when the main object of the designed system consists of 6 elements. The optimal options for reserving this object according to the schemes of "hot" and "cold" redundancy are obtained. The purpose of the article is to show the effectiveness and efficiency of the MS Excel spreadsheet to solve problems of optimal structural redundancy of systems. Conclusions. This article discusses issues related to the problem of solving problems of optimal design of redundant systems in the tool environment of the MS Excel spreadsheet. Examples of solving the problems of separate "hot" and separate "cold" redundancy of a 6-element object prove the effectiveness and efficiency of the MS Excel spreadsheet to solve this problem. In addition, the developed optimization model can be successfully used in practical tasks to ensure the reliability of technical systems in the early stages of their design.

Life cycle improvement of serially connected batteries system by redundancy based on failure distribution analysis

The utilization of redundant batteries is seen as an effective method to promote battery life cycle. On account of the diminishing marginal effect, it is necessary to reasonably configure redundant batteries quantity according to battery characteristics. Based on failure distribution analysis, an evaluated method for serially connected batteries system is proposed to improve lifetime by redundant batteries. The optimal redundancy quantity with maximum cycle numbers can be obtained against the various number of serially connected batteries and the different shape parameter of battery failure distribution by multivariate rational function with rounding. Besides, the scheduling control strategy for serially connected batteries is presented in light of battery health and cycle times. The proposed method is suitable for different batteries type, battery station as well as other devices with similar characteristics to batteries.

Reliability and Cost-Oriented Analysis, Comparison and Selection of Multi-Level MVdc Converters

DC technology has gained considerable interest in the medium voltage applications due to the benefits over the AC counterpart. However, to utilize the full capacity of this development, the selection of a suitable power electronic converter topology is a key aspect. From the pool of voltage source converters (VSC's), it is unclear which topology is suitable for multi-megawatt applications at medium voltage dc (MVdc) levels. To address this, the paper proposes a selection guideline based on reliability and optimum redundancy levels of VSCs for MVdc applications. This will be combined with other functional factors such as operational efficiency and return-on-investment. Three candidate multi-level topologies namely three-level neutral point clamped converter (3L-NPC), modular multi-level converter (MMC) and cascaded 3L-NPC (which is being used for the first MVdc link in the U.K.) have been evaluated over two-level-VSC from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 10 kV to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 50 kV. Results show that with the increase of MVdc voltage level MMC shows better performance whereas at low MVdc voltage levels 3L-NPC is the prominent topology.

Optimal activation order vs. redundancy strategies in reliability optimization problems

The optimal activation order (OAO) is introduced as a new concept in reliability optimization problems (ROPs), which sharply contrasts with the conventional redundancy strategies. ROPs commonly comprise one of the four active, standby, Mixed, or K-Mixed redundancy strategies with varying numbers of active components and different times of activation for standby parts. The novel concept of OAO, in contrast, introduces the activation order/sequence of components as a trait with great flexibility that enables system designers to improve system reliability without having to manipulate system structure. The efficiency of this new concept is evaluated through its application to both a specific subsystem with five warm-standby components and a famous benchmark test problem. Results indicate the superiority of the proposed optimal activation order over all previous rival strategies.

Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm

The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm is based on the hybridization of two metaheuristics, which are the bat algorithm (BA) and the generalized evolutionary walk algorithm (GEWA), also called BAG (bat algorithm with generalized flight). The approach is combined with the Ushakov method, the universal moment generating function (UMGF), to evaluate the reliability of the multi-state series-parallel system. The multi-objective design aims to minimize the design cost, and to maximize the reliability and the performance of the electric power generation system from solar and gas generators by taking into account the reliability indices. Power subsystem devices are labeled according to their reliabilities, costs and performances. Reliability hangs on an operational system, and implies likewise satisfying customer demand, so it depends on the amassed batch curve. Two different design allocation problems, commonly found in power systems planning, are solved to show the performance of the algorithm. The first is a bi-objective formulation that corresponds to the minimization of system investment cost and maximization of system availability. In the second, the multi-objective formulation seeks to maximize system availability, minimize system investment cost, and maximize the capacity of the system.

Maximizing the Probability of Message Delivery Over Ever-Changing Communication Scenarios in Tactical Networks

This letter introduces a stochastic model to maximize the probability of message delivery over ever-changing communication scenarios in tactical networks. Our model improves modern tactical systems implementing store-and-forward mechanisms organized in a hierarchy of layers for messages, IP packets and radios. The goal is to estimate the optimum redundancy for the user data-flow to overcome packet loss during changes in the link data rate, including disconnections. Experiments in a VHF network illustrate the numerical results from our model using messages with different sizes over two patterns of data rate change.

Redundancy allocation of heterogeneous components by simulation-based optimization

The present study proposes a novel simulation-based optimization model for a series-parallel redundancy allocation problem (RAP) under heterogeneous components for reliability maximization subjected to system-level constraints through the identification of the optimal redundancy strategy, component type, and subsystem component count. To obtain higher practicality, active, cold-standby, mixed, and K-mixed redundancy strategies are incorporated as the decision variables. In general, as it is difficult to determine a closed-form (excluding active redundancy strategies), it is not possible to analytically assess system reliability. Earlier studies on system reliability optimization applied convenient lower bound approximation. This limits higher reliability levels. In order to tackle this problem, this study adopted simulation sampling to make unbiased efficient reliability estimates. To this end, 4Dscript interpreting programming was utilized to develop a simulation model. As RAP has a combinatorial nature and is a random and NP-hard problem, this study adopted the genetic algorithm (GA) optimization. To validate the model and assess GA efficiency, the numerical findings of some benchmark tests were employed. The proposed approach outperformed earlier approaches in reliability and confidence.

Efficient Replication for Fast and Predictable Performance in Distributed Computing

Master-worker distributed computing systems use task replication to mitigate the effect of slow workers on job compute time. The master node groups tasks into batches and assigns each batch to one or more workers. We first assume that the batches do not overlap. Using majorization theory, we show that a balanced replication of batches minimizes the average job compute time for a general class of service time distributions. We then show that the balanced assignment of non-overlapping batches achieves a lower average job compute time than the overlapping schemes proposed in the literature. Next, we derive the optimum redundancy level as a function of the task service time distribution. We show that the redundancy level that minimizes the average job compute time may not coincide with the redundancy level that maximizes job compute time predictability. Therefore, there is a trade-off in optimizing the two metrics. By running experiments on Google cluster traces, we observe that redundancy can reduce the job compute time by one order of magnitude. The optimum level of redundancy depends on the distribution of task service time.

Globally Optimal Redundancy Resolution with Dynamic Programming for Robot Planning: A ROS Implementation

Dynamic programming techniques have proven much more flexible than calculus of variations and other techniques in performing redundancy resolution through global optimization of performance indices. When the state and input spaces are discrete, and the time horizon is finite, they can easily accommodate generic constraints and objective functions and find Pareto-optimal sets. Several implementations have been proposed in previous works, but either they do not ensure the achievement of the globally optimal solution, or they have not been demonstrated on robots of practical relevance. In this communication, recent advances in dynamic programming redundancy resolution, so far only demonstrated on simple planar robots, are extended to be used with generic kinematic structures. This is done by expanding the Robot Operating System (ROS) and proposing a novel architecture meeting the requirements of maintainability, re-usability, modularity and flexibility that are usually required to robotic software libraries. The proposed ROS extension integrates seamlessly with the other software components of the ROS ecosystem, so as to encourage the reuse of the available visualization and analysis tools. The new architecture is demonstrated on a 7-DOF robot with a six-dimensional task, and topological analyses are carried out on both its state space and resulting joint-space solution.

Strength–redundancy allocation problem using artificial bee colony algorithm for multi-state systems

The system reliability optimization design is an indispensable part in the reliability engineering. The traditional reliability–redundancy allocation problem (RRAP) is widely studied and used to optimize the system reliability. However, researchers mainly focused on the optimal redundancy and subsystem reliability strategies, which is relatively blurry in the aspect of giving designers an explicit orientation to improve the system reliability. Therefore, this paper raises a newly-defined reliability-based strength–redundancy allocation problem (SRAP) for multi-state systems based on the load–strength interference model and formulates its corresponding reliability optimization design model with the proposed continuous multi-state system reliability model as the objective function. To obtain the more specific optimal component strength and redundancy strategies, we improve the basic artificial bee colony (ABC) algorithm to solve the reliability optimization design model since the SRAP is a mixed-integer nonlinear programming problem. An illustrative example about the reliability optimization design of the solar module is given to demonstrate the availability of the proposed model.

Reliability Optimization of Wind Farm Power Systems Using Bat Algorithm with Generalized Flight

In this paper, two metaheuristics, namely the Bat algorithm (BAT) and a recent hybridization of bat algorithm with generalized walk evolutionary algorithm are presented. The bat algorithm and the Bat algorithm with generalized flight (BAG) are used to solve the problem of optimal redundancy design of series-parallel electrical systems. In order to assess the reliability of the heterogeneous system of multi-state series-parallel, the Ushakov method a universal moment generating function (UMGF) is used to allow fast estimation. The design objective is to maximize the reliability of the bulk power generation system from wind farm. The components of each electrical subsystem are characterized by their performance (capacity), cost and reliability. Reliability is defined as the ability to satisfy consumer demand that is given by a cumulative load curve. By comparing three algorithms cited in this study, the results show that the hybridization of Bat and Generalized Evolutionary Walk Algorithm (BAG) are effective in solving the reliability redundancy optimization problem (RROP). Two illustrative examples are presented.

On Optimal k-Deletion Correcting Codes

Levenshtein introduced the problem of constructing k-deletion correcting codes in 1966, proved that the optimal redundancy of those codes is O(k log N) for constant k, and proposed an optimal redundancy single-deletion correcting code (using the so-called VT construction). However, the problem of constructing optimal redundancy k-deletion correcting codes remained open. Our key contribution is a major step towards a complete solution to this longstanding open problem for constant k. We present a k-deletion correcting code that has redundancy 8 klog N + o(log N) when k = o(√{loglog N}) and encoding/decoding algorithms of complexity O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2 k+1</sup> ).

Balancing the demand and supply of a power grid system via reliability modeling and maintenance optimization

In this research, we modeled the reliability of a power grid with consideration of the power sharing among different regions. By extending the universal generating function technique, a reliability evaluation algorithm for a general power grid was suggested. A joint optimization model was formulated to determine the optimal redundancy and maintenance strategy in order to minimize the economic cost while meeting the reliability requirement. Numerical examples were used to illustrate the effects of different grid configurations and maintenance strategies on the reliability and cost of the power grid. It was shown that the system operation cost could be minimized by determining the optimal allocation of generators and the optimal maintenance strategy.

Data dissemination with interoperability in IoT network

SummaryInternet of Things (IoT) is connected to heterogeneous devices. Efficient adaptive scheduling with encoding and decoding of data is an unaddressed issue in IoT. This paper processes the data under three major hierarchy: namely, adaptability, scheduling of data, and network coding for that data. The reliable access to the information is ensured by a device which is a primary eminence in IoT. Device must be able to adapt itself according to the changes in the network and to maintain its reliability as well as transparency and seamless access to the resources. To enhance the performance of the data dissemination, the scheduling process is investigated using the spatial grouping in IoT devices; this is achieved by joint spatial and code domain scheduling scheme, and the novel preconfigured access scheme is coined in order to minimize the collision rate of arbitrary access; during the data dissemination, the erasure coding scheme is used for the encoding and decoding of packets which provides optimal redundancy. We carried the simulation using Contiki and it shows the proposed Polymorphic Erasure Coding with Markov decision Adaptability and Neural networks (PECMAN) improves in terms of cost, overhead, and delay when compared with Multi‐user Shared Access (EMUSA), Polynomial‐time Optimal Storage Allocation (OSA) scheme, and Event‐Aware Back pressure Scheduling Scheme (EABS).