Backup Operation Research Articles

A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search

Monte-Carlo Tree Search (MCTS) is a class of methods for solving complex decisionmaking problems through the synergy of Monte-Carlo planning and Reinforcement Learning (RL). The highly combinatorial nature of the problems commonly addressed by MCTS requires the use of efficient exploration strategies for navigating the planning tree and quickly convergent value backup methods. These crucial problems are particularly evident in recent advances that combine MCTS with deep neural networks for function approximation. In this work, we propose two methods for improving the convergence rate and exploration based on a newly introduced backup operator and entropy regularization. We provide strong theoretical guarantees to bound convergence rate, approximation error, and regret of our methods. Moreover, we introduce a mathematical framework based on the use of the α-divergence for backup and exploration in MCTS. We show that this theoretical formulation unifies different approaches, including our newly introduced ones, under the same mathematical framework, allowing to obtain different methods by simply changing the value of α. In practice, our unified perspective offers a flexible way to balance between exploration and exploitation by tuning the single α parameter according to the problem at hand. We validate our methods through a rigorous empirical study from basic toy problems to the complex Atari games, and including both MDP and POMDP problems.

Design of a spin–orbit-torque-based self-terminated nonvolatile register for a write/leakage-energy-minimized backup operation

A self-terminated nonvolatile (NV) register that is a key component of a energy-efficient LSI is proposed and its impact on minimizing write and leakage energies during a backup operation before a power-off mode is presented by combining spin–orbit-torque (SOT) devices with CMOS circuitry. The self-terminated NV-register can automatically cut off the write current pulse by continuously monitoring the voltage change due to the state transition of the SOT device. Moreover, the write completion signals can be utilized for a flag whether the circuit can go into the power-off mode which results in the minimization of leakage energy consumption. A case study is performed using a 45nm CMOS technology which results in 71% of total energy reduction in the backup operation compared to that of a typical worst-case design.

Part-load thermal efficiency enhancement in gas turbine combined cycles by exhaust gas recirculation

Gas turbine power plants are popular for offshore power generation due to high power density and their reliability. However, growing usage of renewable energies put gas turbines in a load following backup operation. These power plants suffer part-load efficiency losses when operating at less than full capacity, resulting in higher carbon dioxide (CO2) emission from natural gas combined cycles or higher consumption of carbon-free fuels in decarbonized gas turbines. In this article, a solution is proposed for enhancement of power plant part-load thermal efficiency based on exhaust gas recirculation in the gas turbine cycle. Recirculating exhaust gas into the gas turbine have been studied by several researchers and engineers due to its benefit for carbon-free combustion and carbon capture mechanisms. The proposed operation strategy is evaluated for single-spool and two-spool gas turbines operating jointly with a steam bottoming cycle harvesting the waste heat for further power production. In the suggested strategy, eliminating the necessity to cool down the recirculated gas resulted in less equipment footprint for the power plant which makes it more favorable for offshore applications. An in-house design and simulation tool is developed for evaluating gas turbines with modern gas recirculating systems and a flexibility in operation with carbon-free fuel mixtures. The enhancement in efficiency boost, emission reduction, and fuel consumption is quantified demonstrating the improvements with the proposed solution.

Priority-based Mutual Power Sharing between Microgrids in a Community Microgrid

Several microgrids (MG) operating in the neighborhood can be integrated to form a community of MGs to harness several benefits of a larger networked system. The present research is an investigation of the coordination between the several AC and DC MGs of such community MG. Individual MGs may function as self-contained entities, but they might also collaborate with other nearby MGs to provide backup operations in the community MG. In this paper a coordination technique is suggested for transmitting excess power of a MG to the community bus under the control of the community MG controller so that nearby MGs can use it as needed, while maintaining stable operation of the participating MGs. A centralized controller called the community MG controller maintains the coordination between the neighboring MGs. The controller receives power shortage report from the MGs facing power shortage problem and decides as to which MG can draw this excess power. The controller uses a priority-based distribution algorithm to decide the allocation of power. The algorithm takes into consideration the presence of critical loads like hospital, industry, academic institution, etc. An infrastructure of smart metering (SM) is used to check the amount of power flow into any MG. The MGs will be penalized if they draw power more than that allocated to them. Thus, each MG is able to maintain stable operation without having to resort to spinning reserve for excess load and dump load to remove the excess power from the system. The obtained simulation results show that the suggested approach is a practical and efficient means of coordinating power flow in an islanded community MGs.

A fully non-volatile reconfigurable magnetic decoder

In recent years, emerging technologies like spintronics are gaining importance for their ability to tackle issues pertaining to CMOS like high leakage effect, complex data backup operation, and power gating. In this regard, Magnetic Tunnel Junction (MTJ), the most prominent spin device is chosen for our application. A fully Non-Volatile Reconfigurable Magnetic Decoder (NVRMD), using fully NVR NAND/AND and fully NVR NOR/OR logic gates is presented in this paper, following the Logic-In-Memory (LIM) architecture in attempts to mitigate the von Neumann Bottleneck. The proposed designs are superior to their contemporaries in terms of low power, less delay, and dynamic reconfigurability. Reduction in read energy by 79% and write energy by 28% has been achieved in the proposed NVR NAND/AND NOR/OR circuit compared to its counterpart. Corner analysis is performed to establish the robustness of the circuit under extreme conditions in CMOS and reliability analysis is done to understand the effect of process variations of MTJ parameters on the circuit performance.

Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games

Function approximation (FA) has been a critical component in solving large zero-sum games. Yet, little attention has been given towards FA in solving general-sum extensive-form games, despite them being widely regarded as being computationally more challenging than their fully competitive or cooperative counterparts. A key challenge is that for many equilibria in general-sum games, no simple analogue to the state value function used in Markov Decision Processes and zero-sum games exists. In this paper, we propose learning the Enforceable Payoff Frontier (EPF)---a generalization of the state value function for general-sum games. We approximate the optimal Stackelberg extensive-form correlated equilibrium by representing EPFs with neural networks and training them by using appropriate backup operations and loss functions. This is the first method that applies FA to the Stackelberg setting, allowing us to scale to much larger games while still enjoying performance guarantees based on FA error. Additionally, our proposed method guarantees incentive compatibility and is easy to evaluate without having to depend on self-play or approximate best-response oracles.

Adaptive Task-Based Intermittent Computing System With Parallel State Backup

Energy harvesting promises to power billions of Internet-of-Things devices without being restricted by battery life. Since the energy harvester generally outputs weak and unstable energy, the system may suffer frequent and unpredictable power failures, thus falling into cyclically reboots without forward progress. Task-based intermittent computing system which periodically backs up system states into Non-Volatile Memory (NVM) is proposed to solve the non-progress problem, with the non-trivial cost of frequent backups. How to reduce the backup overhead becomes a major research problem for intermittent computing. Our paper, for the first time, proposes to parallelize state backup and program execution with asynchronous Direct Memory Access (DMA) to hide the backup latency into the program’s execution. But, straightforwardly executing the state backup and the program in parallel may cause inconsistent system state. In specific, the system state may be modified by the program during backup, and therefore may be backed up incorrectly and further cause the system to deliver an incorrect computation result. We make deep analysis on the system behavior and observe that, although the system state may be backed up incorrectly, the incorrect backup will be covered by the subsequent correct backups soon as the backup operations are performed frequently. In addition, only a small part of variables among all the program states may cause incorrect computation result. So, in this paper, we aggressively allow incorrect backups to occur, and propose a backup error detection method and a fault-tolerant backup management to guarantee the correctness of the system’s execution. To augment the parallel backup method, an adaptive execution method is further proposed to reduce the number of backups and balance the ratio between task execution time and backup latency. We design a run-time system to implement the proposed approach, and experimental results conducted on an STM32F7-based platform show that the proposed method can achieve a 2.6× average speedup.

Adaptive overcurrent protection scheme for distribution networks with connection of mobile energy storage devices

The increasing penetration of renewable energy sources in distribution networks has caused great challenges to the reliable operation of the conventional overcurrent protection schemes. In particularly, serious underreach and overreach problems of protection scope may occur under the ever growing application of mobile energy storage (MES) devices. To improve the adaptability to the connection of MES devices under distribution networks, this paper proposes an adaptive overcurrent protection scheme, which can avoid the unfavorable effects caused by infeed currents and out flowing currents. Firstly, the effects of MES device on the protection scope of the overcurrent protection strategy are investigated, considering the charging, discharging, and backup operation modes of MES device. Secondly, to adapt to the different operation modes, the equivalent impedance of MES device is calculated, and then it is introduced to determine the adaptive settings of fast current protection and time-critical fast current protection. Finally, the constructed adaptive overcurrent protection scheme can adapt to varied fault conditions, including different operation modes and output power of MES device, connection locations, fault locations, and fault types. Large amounts of simulation results show that the proposed adaptive overcurrent method can overcome the underreach and overreach problems of protection scope, demonstrating its good application prospects.

A Secured Database Monitoring Method to Improve Data Backup and Recovery Operations in Cloud Computing

In general, the company sometimes uses unregistered functions in database, which significantly improves performance, but does not leave the possibility of recovery except for backup. That is, actions must be performed immediately after passing the session. A queue problem is likely to cause data loss and downtime of about a week. In modern conditions, this can lead to the bankruptcy of the company. It can be seen that backup systems have been installed and configured, but despite this, they have not succeeded in restoring within the time frame specified in the SLA. In this study, a secured database monitoring method was proposed to improve data backup and recovery operations in cloud computing. In this proposed method, the backup speed is directly proportional to the amount of data, while having at least 30% annual data growth. In 3–4 years, the data at least doubled, but for some companies, this number is even higher, while the backup speed does not change. Those terms and those SLAs that were relevant 3–4 years ago now need to be at least doubled. At the same time, business requirements for data recovery (recovery point objective/recovery time objective) continue to grow

Backup Encryption and Encrypted Backup Operation Performance in SQL Server

Database security features are important ceses to be focused on database system development. However, using security features can affect the system's performance. Encryption database backup is a kind of security algorithm option, that includes keys and certificates. It is essential for additional layer of security. This study aims to observe how Transparent Data Encryption (TDE) feature, as a solution tool for data security on Microsoft SQL Server, will impact the database performance. In this study, there will be an overview of database backup encryption and encrypted backup operation through backup testing in SQL Server. Hence, the research will be conducted on backup testing for monitoring database system's performance when implementing TDE solution. The study will contribute to the literature with using backup encryption algorithms in SQL Server in terms of efficiency and benchmarking of encrypted backup operation performance with TDE by finding how significant performance change is happening.

Relative Performance of Various Types of Repositories for MySQL Archive Backup and Restore Operations

The backup and restore operations are essential part of database system's administration process. Usually, the size of the database is a major factor that determines numerous practical issues, among which is what backup and recovery methods to be used. However, in addition, there are various types of storage systems (repositories) available in MySQL 8.0, for example MyISAM, Merge, Memory, InnoDB, CSV, Blackhole, Archive and Federated, which in general sense determine how to store each table into at least one file. Each of these storage systems have their own positive and negative characteristics, so when constructing logical archives, it is vital to compare the performance of those various types of repositories.

Optimal data backup policies for information systems subject to sudden failure

PurposeWith the irresistible growth in digitization, data backup policies become essential more than ever for organizations seeking to improve reliability and availability of organizations' information systems. However, since backup operations do not come free, there is a need for a data-informed policy to decide how often and which type of backups should be taken. In this paper, the authors present a comprehensive mathematical framework to explore the design space for backup policies and to optimize backup type and interval in a given system. In the authors' framework, three separate cost factors related to the backup process are identified: backup cost, recovery cost and data loss cost. The objective function has a multi-criteria structure leading to a backup policy minimizing a weighed function of these factors. To formalize the cost and objective functions, the authors get help from renewal theory in reliability modeling. The authors' optimization framework also formulates mixed policies involving both full and incremental backups. Through numerical examples, the authors show how the authors' optimization framework could facilitate cost-saving backup policies.Design/methodology/approachThe methodology starts with designing different backup policies based on system parameters. Each constructed policy is optimized in terms of backup period using renewal theory. After selecting the best back-up policy, the results are demonstrated through numerical studies.FindingsData backup polices that are tailored to system parameters can result in significant gains for IT (Information Technology) systems. Collecting the necessary parameters to design intelligent backup policies can also help managers understand managers' systems better. Designed policies not only provides the frequency of back up operations, but also the type of backups.Originality/valueThe original contribution of this study is the explicit construction and determination of the best backup policies for IT systems that are prone to failure. By applying renewal theory in reliability, the authors present a mathematical framework for the joint optimization of backup cost factors, i.e. backup cost, recovery time cost and data loss cost.

Optimal coordination of DOCRs in interconnected networks using shifted user-defined two-level characteristics

This paper introduces a protection scheme for interconnected networks based on proposed Directional Overcurrent Relays (DOCRs) with user-defined two-level characteristics. By getting usage of the capabilities available in modern digital DOCRs, the proposed relay will have two user-defined characteristics; one for its primary operation and another for its backup operation (two-level characteristics) to fit a specific application or system. The coordination between the proposed relays is formulated and solved as a non-linear optimization problem to minimize their operating time and reduce the thermal impact caused by short circuit currents through electrical equipment while maintaining the technical constraints.Extensive comparative studies have been performed to ensure the effectiveness of the proposed protection scheme. Firstly, the performance of the traditional one-level characteristic relay (COLC) with two settings is compared to the conventional two-level characteristic relay (CTLC) with three settings. Then a further investigation is carried out by suggesting increasing the number of settings to seven, named as the user-defined two-level characteristic relay (UDTLC), and then to nine settings, named as the shifted-user-defined two-level characteristic relay (SUDTLC). Finally, different multi-objective functions with proper weighting factors are investigated to determine the most effective one with the best performance for the proposed idea.The distribution portion of the IEEE 30-bus system has been used to test and verify the proposed characteristics extensively. The optimal coordination problem is solved using thefminconfunction in MATLAB. Based on the achieved results, the proposed characteristics of UDTLC and SUDTLC guaranteed a considerable reduction in operating times. In addition, the achieved results deduced that using a different multi-objective formulation has little impact on reducing operating time due to using the proposed characteristics UDTLC and SUDTLC, which means solving the coordination problem is mainly dependent on the applied characteristics.

An Adaptive Overcurrent Coordination Scheme Withstanding Active Network Operations

This paper aims to present a centralized adaptive protection scheme (APS) for the directional overcurrent relays (DOCRs) considering system dynamics such as load demand variations, topology changes and DGs to mitigate the above-mentioned effects. The scheme is suitable for different types of networks whether its radial or meshed. Afterall, it can determine the actual topology with the micro-PMUs and breaker status, automatically generate relay names accordingly with the topology bus locations, establish protection coordination pairs, coordinate DOCRs for parallel lines, identify transformers to offer backup operation for differential protection, perform load flow and fault studies, execute contingency and sensitivity analysis, and lastly, coordinate the DOCRs using differential evolution algorithm so that they always have the proper settings to operate in appropriate time providing selectivity. The performance of the proposed centralized adaptive overcurrent protection scheme is tested on the highly meshed IEEE 14 bus system. The proposed scheme has shown that it can adequately consider impacts of system dynamics and DG.

Performance-oriented cache management scheme based on a retention state for energy-harvesting nonvolatile processors

In this paper, we address the challenges of frequent backup and recovery operations associated with an unstable energy supply in energy-harvesting nonvolatile processors (NVPs). To address this problem, this paper adopts a retention state, which can allow the system to retain data in a volatile cache to wait for power recovery instead of immediately backing up the data. In addition, in an energy-harvesting NVP, important issues include how to back up and recover data, how to perform cache replacement, and how to transmit data to different parts of the cache in such a way that the performance and energy consumption can be improved and a successful backup can be guaranteed. Therefore, we propose a performance-oriented cache management scheme based on a retention state to generate near-optimal data migration, replacement and backup solutions for applications in polynomial time. This scheme uses two energy thresholds to pre-back up and back up data to reduce the backup and recovery operations according to the retention state. We evaluate the performance and energy consumption of our proposed algorithms in comparison with those of the dual-threshold SLC STT-RAM scheme and morphable cache scheme. The evaluation shows that the proposed scheme can achieve 18.58% and 4.54% lower average energy consumption than the SLC STT-RAM and morphable cache schemes, respectively, with comparable performance. The experimental results also show that compared with the SLC STT-RAM and morphable cache schemes, the proposed algorithm can achieve 17.90% and 8.85% performance improvement, respectively, on average.

Field oriented control of PMSM drive with backup power supply

The primary purpose of the article is to examine the field oriented control system of permanent magnet synchronous machine (PMSM) electric drive with backup power supply. Authors propose to use bi-directional DC-DC converter to ensure the «hot» backup operation mode in case of grid fault. The change-over switching system, which provide transfer of voltage-source inverter (VSI) from DC link to the backup power source is considered. The presented system provides a good dynamic transient process; the results are confirmed by simulation in Psim software. Moreover, based on the results acquired, an electric drive based on PMSM with field oriented control and a backup power supply system from the battery via a bi-directional DC-DC converter is capable of operating according to the principles of «hot» backup.

Preservation of shared backup path ink‐node content based elastic optical datacenter networks

AbstractEfficient path selection and content availability in the optical datacenter networks are essential for business continuity. To measure quantitatively the connectivity of content and give protection to diverse type of contents, the idea ofk‐node content connectivity is becoming popular. However, the assignment of dedicated spectrum for each end‐to‐end content path consumes too many resources. In order to enhance the resource efficiency, the spectrum can be shared between end‐to‐content paths of various requests. The spectrum sharing minimizes the backup spectrum requirement and has been a topic of research. In this study, an innovative model, namely, end‐to‐end content connectivity based quasi‐bipartite graphs (E‐QBG) for the possible path prediction and maximum matching by Hungarian path prediction (MM‐HPP) are implemented for the spectrum efficiency and the disaster resilient datacenter networks. The objective is to minimize the entire backup spectrum resource and operations path. The quasi‐bipartite graph is used for the end‐to‐end content backup route evaluation including spectrum sharing on various links, while the Hungarian algorithm is utilized for accurate maximum matching prediction between various end‐to‐end route sets. We introduce the concept of maximum dissortativity path based on the weight factor. The proposed E‐QBG and MM‐HPP reduces spectrum consumption which guarantees survivability against multi‐failure and natural disasters. This method leads to an approach for more effective utilization of the resources for end‐to‐end content connected elastic optical datacenter networks as compared with the existing techniques.

MOMDPs: A Solution for Modelling Adaptive Management Problems

In conservation biology and natural resource management, adaptive management is an iterative process of improving management by reducing uncertainty via monitoring. Adaptive management is the principal tool for conserving endangered species under global change, yet adaptive management problems suffer from a poor suite of solution methods. The common approach used to solve an adaptive management problem is to assume the system state is known and the system dynamics can be one of a set of pre-defined models. The solution method used is unsatisfactory, employing value iteration on a discretized belief MDP which restricts the study to very small problems. We show how to overcome this limitation by modelling an adaptive management problem as a restricted Mixed Observability MDP called hidden model MDP (hmMDP). We demonstrate how to simplify the value function, the backup operator and the belief update computation. We show that, although a simplified case of POMDPs, hm-MDPs are PSPACE-complete in the finite-horizon case. We illustrate the use of this model to manage a population of the threatened Gouldian finch, a bird species endemic to Northern Australia. Our simple modelling approach is an important step towards efficient algorithms for solving adaptive management problems.

РЕЗУЛЬТАТЫ ПРИМЕНЕНИЯ МОДИФИЦИРОВАННОЙ ЛАПАРОСКОПИЧЕСКОЙ ЭЗОФАГОГАСТРАЛЬНОЙ ДЕВАСКУЛЯРИЗАЦИИ

Background. Transabdominal gastroesophageal devascularization is a technically feasible backup operation for most general surgeons in case of failure of endoscopic prophylaxis of bleeding from esophageal varices. There is an emerging trend in the development of laparoscopic technologies in the surgical correction of complications of portal hypertension. Purpose. Assessment of the clinical efficacy of laparoscopic esophagogastric devascularization in its own modification. Material and methods. In the period from 2009 to 2020, the results of treatment of 31 patients were studied. The patients were divided into 2 groups by the method of simple randomization. In the control group, surgery was performed in a standard way, in the main group - in the modification we proposed. Results. The use of our proposed technological methods when performing the stage of transection of the abdominal esophagus during laparoscopic esophagogastric devascularization in its own modification reduced the frequency of technical difficulties at this stage, which caused conversions, anastomotic leakage and other intra and postoperative complications. In the long-term period, there was a decrease in the degree of esophageal varices, a decrease in the frequency of recurrent bleeding and mortality, as well as an improvement in the quality of life in patients after a modified operation in comparison with the standard technique. Laparoscopic esophagogastric devascularization in our modification shows better results as a method of secondary prevention of bleeding from esophageal varices in cirrhosis of the liver in patients with a high risk of recurrence than the use of endoscopic sclerosis of esophageal varices, is characterized by a lower incidence of repeated episodes of bleeding from esophageal varices and less lethality. Conclusions. Based on the analysis of the immediate and long-term results of the use of laparoscopic esophagogastric devascularization in its own modification in the clinic, it should be noted the reproducibility of the surgical intervention, its effectiveness and safety.

PLEASE: Palm Leaf Search for POMDPs with Large Observation Spaces

This paper provides a novel POMDP planning method, called Palm LEAf SEarch (PLEASE), which allows the selection of more than one outcome when their potential impacts are close to the highest one during its forward exploration. Compared with existing trial-based algorithms, PLEASE can save considerable time to propagate the bound improvements of beliefs in deep levels of the search tree to the root belief because of fewer backup operations. Experiments showed that PLEASE scales up SARSOP, one of the fastest algorithms, by orders of magnitude on some POMDP tasks with large observation spaces.