Backup Server Research Articles

Assessing the Cost of Large-Scale Power Outages to Residential Customers.

Residents in developed economies depend heavily on electric services. While distributed resources and a variety of new smart technologies can increase the reliability of that service, adopting them involves costs, necessitating tradeoffs between cost and reliability. An important input to making such tradeoffs is an estimate of the value customers place on reliable electric services. We develop an elicitation framework that helps individuals think systematically about the value they attach to reliable electric service. Our approach employs a detailed and realistic blackout scenario, full or partial (20 A) backup service, questions about willingness to pay (WTP) using a multiple bounded discrete choice method, information regarding inconveniences and economic losses, and checks for bias and consistency. We applied this method to a convenience sample of residents in Allegheny County, Pennsylvania, finding that respondents valued a kWh for backup services they assessed to be high priority more than services that were seen as low priority ($0.75/kWh vs. $0.51/kWh). As more information about the consequences of a blackout was provided, this difference increased ($1.2/kWh vs. $0.35/kWh), and respondents' uncertainty about the backup services decreased (Full: $11 to $9.0, Partial: $13 to $11). There was no evidence that the respondents were anchored by their previous WTP statements, but they demonstrated only weak scope sensitivity. In sum, the consumer surplus associated with providing a partial electric backup service during a blackout may justify the costs of such service, but measurement of that surplus depends on the public having accurate information about blackouts and their consequences.

An optimal stopping approach to managing travel-time uncertainty for time-sensitive customer pickup

In dynamic vehicle routing, it is common to respond to real-time information with immediate updates to routes and fleet management. However, even if routes are updated continuously, in practice, some decisions once made are difficult to reverse. At times, it may thus be valuable to wait for additional information before acting on a decision. We use the theory of optimal stopping to determine the optimal timing of a recourse action when vehicles are likely to miss customer deadlines due to travel-time stochasticities and backup services are available. The factors involved in making this decision – that is, the likelihood that the primary vehicle will arrive late, the location of the backup vehicle, and value of waiting for additional travel-time information – each change dynamically over time. We develop a recourse model that accounts for this complexity. We formulate the optimal recourse policy as a stochastic dynamic program. Properties of the optimal policy are derived analytically, and its solution is approximated with a binomial lattice method used in the pricing of American options. Finally, we develop a two-stage stochastic optimization approach to show how the opportunity to take recourse dynamically might be integrated into a priori scheduling and routing. The framework is demonstrated for a stochastic dial-a-ride application in which taxis serve as backup to ridesharing vehicles.

Optimised operation of storage systems integrated with MV photovoltaic plants, considering the impact on the battery lifetime

Nowadays, the energy storage technology is bringing new opportunities to the power systems, not only providing the electric grid with regulation, reserve and backup services, but also filling the gap between the timing of production and consumption. This enables price arbitrage techniques, aimed at maximising the economic revenue obtained by charging or discharging the storage, based on the time variation of electricity prices. This paper shows how to optimise the operation of a storage device in presence of a PV generating plant, possibly combined with a local load. An optimisation technique based on a dynamic programming tool implemented with the open source Modelica language is here proposed and tested on different case studies. In particular, different storage sizes and losses models have been considered, as well as the dependence of the storage lifetime on the depth of discharge of its operational cycles. Finally, a payback analysis calibrated on present and future cost scenarios is presented and discussed.

A bi-objective stochastic model for emergency medical services network design with backup services for disasters under disruptions: An earthquake case study

In the event of a disaster such as natural and human-made, high demand for medical supplies and a large number of injured people will emerge at the affected areas in a short time period. Rapid distribution of medical supplies and the speed of transferring injured to the hospital play an important role in assuring the effectiveness and efficiency of the emergency medical service (EMS). In this paper, a bi-objective stochastic optimization model is developed for location of transfer points and medical supplies distribution centers (MSDCs). When a disaster happens, resources are usually insufficient for all to be treated immediately. For this reason, determining the priority of injured treatments based on the severity of their condition is one the most important issue on EMS, called as triage system. Therefore, for approaching the model to the real world, triage system and failure probabilities of MSDCs and routes are considered. To enhance efficiency of services during such event, backup MSDCs are also utilized. Furthermore, the proposed bi-objective model is converted to a single-objective mixed-integer programming model applying the ε-constraint method. Finally, to show applicability of the model, a case study of earthquake disaster in an urban district in Iran is examined. The proposed model can help interdisciplinary agencies both to prepare and respond to disaster considering the disruption in an efficient manner.

Multi-Cloud Based Data Backup Services for Android Device

Multi-Cloud Based Data Backup Services for Android Device

Fault-tolerant system design on cloud logistics by greener standbys deployment with Petri net model

The cost-aware exploration on enhancing fault-tolerant becomes an important issue of service quality from cloud platform. To approach this goal with greener design, a novel server backup strategy is adopted with two types of standby server with warm standby and cold standby configurations. On such two-level standby scheme, cost elaboration has been explored in terms of deployment ratio between warm standbys and cold standbys. The cold standbys provide a greener power solution than those of conventional warm standbys. The optimal cost policy has been proposed to maintain regulated quality of service for the cloud customers. On qualitative study, a Petri net is developed and designed to visualize the whole system operational flow. On quantitative research for decision support, the theory of finite source queue is elaborated and relevant comprehensive mathematical analysis on cost pattern has been made in detail. Relevant simulations have been conducted to validate the proposed cost optimization model as well. On green contribution, the saving of power consumption has been estimated on the basis of switching warm standbys into cold standbys, which amounts for the reduction of CO2 emission. Hence the proposed approach indeed provides a feasibly standby architecture to meet cloud logistic economy with greener deployment.

PCS: a parity-based personal data recovery service in cloud

As more and more data are generated in an electronic format, the necessity of a data recovery service has increased, and the development of more efficient data backup and recovery technology has been an important issue during the past decade. While lots of effective backup and recovery technologies have been developed for enterprise level, little work has been done for convenient and inexpensive personal data recovery service, i.e., cloud storage service is still inadequate or expensive for backing up tera-scale HDDs. Furthermore, since privacy protection is a crucial issue for providing a personal data recovery service, a plain data backup-based recovery service is not adequate for public service. Users are reluctant to upload their data to internet backup servers until they can fully trust the service provider in terms of privacy protection. We propose a novel data recovery service framework on cloud infrastructure, a parity cloud service, which provides privacy-protected personal data recovery service while requiring a small storage space in the cloud. The proposed framework does not require any user data to be uploaded to the server, but only parity data are uploaded to the server for user data recovery. Also, the necessary server-side resources for providing the service are within a reasonable bound, depending on the data recoverability and recovery time.

Using of virtualized IT-infrastructure under normal operation of automation systems of technological objects

Taking into account the global trends and experience of implementation of modern information technologies in production processes, with the aim of updating and increasing the competitiveness of Ukrainian industrial complexes, the issues and methods for using of hardware and software and technological solutions in the field of virtualization are considered.The main method of research is computer simulation – simulation of real automation systems (including server component) using the tools of virtualization (Microsoft Hyper V). The essence of the method is creation of a virtual environment (infrastructure), including primary and backup server with process control system and workstations. Virtual machines of automation systems are fully meet their physical analogues by heir characteristics.The ways of using of traditional automation systems, which are deployed on the basis of virtualization platform Hyper V, are considered. The main way of using of traditional software automation is their deployment on the basis of server operating system with support for one of the many virtualization technologies, such as: MS Hyper V, VMWare VSphere, Citrix Xen Server, and others.An opportunity of practical operation of automation systems on the basis of virtualized hardware and software server complex with the thin clients as workstations is proved for Experion PKS system and Honeywell C200 controller. The process control system is deployed in a virtualized environment on the basis of server (Windows Server 2012 R2) and normal (Windows 10) operating systems.The possible positive effect of implementation of modern IT infrastructure for technological objects is also analyzed. It lays in the fact of theoretically increase of fault tolerance level, practical simplification of system administration, and creation of bank for backup of virtual machines.This result is associated with a more rational and efficient use of capabilities of modern computer systems (CPU and RAM), data storage systems (using of RAID hard drives) and software.

Brand Influence in Business-to-Business (B2B) Markets : Understanding the Buying Criteria of Different Organizations

The brands make identification of products, services, and businesses convenient, easy, and more acceptable for the buyers. Besides, the brands help to differentiate them from competitors' offerings. The brands also communicate improved value and benefits to the business buyers. And brands also act as a measure of guarantee for quality, performance, and the source; and thus reduce the risk and complexities in buying decisions. The objective of the study was to have a deeper understanding of the various evaluative criteria used in different B2B purchase decisions, and to what extent a brand influences them and how beneficial are those decisions for the buying organizations. The study was focused around the value and importance of branding, the preference towards branded products, and the effect of factors like price, risks involved, information availability, customer support/ after sales services, and value addition on purchase decisions in organizations. The study was conducted with 110 respondents from four different industry categories purchasing and using namely, garment manufacturing machinery, photocopiers, photographic equipment, and medical diagnostic equipments with the help of a questionnaire and interview. The study revealed that more or less, industrial and organizational buyers, though very price conscious, prefer branded products because it gives a mental satisfaction that they are buying a quality product and associated services from a reliable and known source. The companies supplying branded products provide quick backup service and support, and they are more preferred because it assures quick response and solution of any bottleneck and issue with the final end product/ service produced in the buying organization.

Bayesian Method for Source Local Deduplication in Cloud Backup Services

Bayesian Method for Source Local Deduplication in Cloud Backup Services

Context sensitive trust based geographic opportunistic routing in mobile ad hoc networks

Position based opportunistic routing (POR) is a stateless, robust, and reliable geographic routing protocol in Mobile AdHoc NETwork (MANET). The opportunistic routing embraces broadcast property of wireless channels and utilizes it for opportunistic forwarding. Both the malicious node behavior and the backup nodes’ behavior are equally treated as malicious in the existing misbehavior detection mechanisms. Hence, incorporating a general trust model in POR is not combative with routing attacks. It is necessary to determine whether the misbehavior is likely a result of malicious activity or due to the backup scenario of opportunistic forwarding. On the other hand, if context-sensitive trust information is available on every node, it ensures a fair decision making and also supports secured routing in an opportunistic approach. This work investigates the utilization of context attributes along with generic trust model to allow POR for secure and reliable data forwarding. This paper introduces context-sensitive trust for choosing the data forwarding node in POR (CPOR) to assist opportunistic routing in selecting the trusted optimal data forwarding node and to cope with both security and reliability of communications. The proposed work exercises both coarse- and fine-grained trust evaluation to strengthen the trustworthiness. The coarse-grained trust measure includes positive progress per hop and behavioral attribute of the nodes in terms of routing service. The fine-grained trust evaluation differs the opportunistic routing environment from the adverse scenarios and aids the source node such that it builds a highly trusted positive progress set using contextual attributes. The fine-grained trust evaluation deduces the ideal contextual information such as the link quality, battery energy, and the backup service to determine the accurate trust value of nodes. As a result, it involves optimal routes and enables CPOR to maintain the routing performance equal to the POR even in the presence of malicious nodes in the network. The simulation results demonstrate that the packet delivery ratio of the proposed context-aware trust model is substantially high even when 50% of the total nodes are found malicious and outperforms the trust-aware opportunistic routing protocol (TAOR).

Point of Care Neonatal Ultrasound - Head, Lung, Gut and Line Localization.

Knowledge and skills of heart, head, lung, gut and basic abdominal ultrasound is of immense utility to clinicians in their day-to-day patient management, and in acute events, in the absence of specialist service back-up. This review examines the potential role of clinician-performed ultrasound in the neonatal intensive care unit. The bibliographic search of English-language literature was performed electronically using PubMed and EMBASE databases for the different topics we have covered under this review. Bedside head ultrasound can be used to identify and screen for intraventricular hemorrhage, periventricular leukomalacia and post-hemorrhagic ventricular dilatation. It is also a useful adjuvant tool in the evaluation of hypoxic ischemic encephalopathy. The relatively new lung ultrasound technique is useful in identifying transient tachypnea, pneumonia, pneumothorax, fluid overload and pleural effusion. Gut ultrasound is useful in identifying necrotizing enterocolitis and probably is better than X-ray in prognostication. Ultrasound is also useful in identifying vascular line positions without radiation exposure. Ultrasound performed by the clinician has an extensive role in the neonatal intensive care unit. Basic ultrasound knowledge of head, lung and gut is a useful supplement to clinical decision-making.

A cost-effective strategy for Cloud system maintenance

To guarantee the high availability of modern Cloud-based applications, service backup is commonly used to maintain the failed services. However, an ineffective maintenance strategy based on virtual machine (VM) backup will cause a high budget and low resource utilization. This paper proposes a cost-effective multi-VM maintenance strategy to minimize maintenance cost with limited backup VMs in the Cloud. Different from the single-system maintenance strategies that pursue local optima by considering only one system each time, the proposed strategy considers all the running systems simultaneously from a global perspective. We formalize the multi-system maintenance as a restless multi-armed bandit problem, propose the concept of Healthy Indices of VMs with Lagrangian relaxation and develop an index based policy for maintenance scheduling. Given the limited backup VMs, the experiment results show that the proposed cost-effective multi-VM maintenance strategy significantly outperforms single-system maintenance policies in terms of total maintenance cost and system availability.

Performance Evaluation and Scalability of IP-based and Heuristic-based Job Scheduling Algorithm Backup Systems

Background/Objectives: One of the most important factors in the design of enterprise computer networks is data storage method. Increase the volume, recovery and security of stored information is the biggest challenge. Using backup systems is a perfect solution to solve these challenges. Traditional methods can be used to perform backups, but new methods and new backup systems are more efficient. Methods/Statistical Analysis: To analyze and compare overall backup session time, backup session processing time, overhead, fragmentation of large data and efficiency of the IP-based schedule and the heuristic-based job scheduling algorithm. Findings: My analysis show that the simple heuristic-based job scheduling algorithm with adaptive number of active DAs is close to optimal while having no additional computing overhead compared to the compute expensive IP-based solution. The simulator-based on heuristic-based job scheduling algorithm enables the analysis to minimize the number of actively used backup servers while meeting backup window constraints and data restore satisfying rates. Applications/Improvements: This algorithm is close to the results that reduce backup time by 60 percent without additional computing overhead and fragmentation of large data processing compared to IP-based methods. As well as, the algorithm can simulate the analysis of a backup system will help. The proposed approach significantly increases the performance, reliability and quality of implemented solutions.

A Credible Cloud Service Model based on Behavior Graphs and Tripartite Decision-Making Mechanism

The credibility of cloud service is the key to the success of the application of cloud services. The dual servers of master server and backup server are applied to cloud services, which can improve the availability of cloud services. In the past, the failures between master server and backup server could be detected by heartbeat algorithm. Because of lacking cloud user's evaluation, the authors put forward a credible cloud service model based on behavior Graphs and tripartite decision-making mechanism. By the quantitative of cloud users' behaviors evidences, the construction of behavior Graphs and the judgment of behavior, they select the most credible cloud user. They combine the master server, the backup server and the selected credible cloud user to determine the credibility of cloud service by the tripartite decision-making mechanism. Finally, according to the result of credible judgment, the authors could decide whether it will be switched from the master server to the backup server.

Survivable Control Plane Establishment With Live Control Service Backup and Migration in SD-EONs

It is known that software-defined elastic optical networks (SD-EONs) are programmable and application-aware. However, due to the centralized network control and management, SD-EONs are vulnerable to the network failures that can affect control plane operations. In this paper, we study the problem of survivable control plane establishment (SCPE), i.e., the controller placement and related communication planning for control service backup and migration to protect the control plane of an SD-EON against single node failures. We first propose a novel mutual backup model to improve the survivability of the control plane with high protection efficiency. An integer linear programming (ILP) model is then formulated to solve the SCPE problem with the objective to minimize both the number of deployed OpenFlow controllers (OF-Cs) and the average control channel latency. We also propose a time-efficient heuristic and use simulations to verify that it can obtain similar solutions to those of the ILP. On top of the theoretical investigation, we design and implement the system to facilitate live control service backup and migration with SCPE in an SD-EON control plane testbed. Experimental results demonstrate that the proposed scheme works efficiently, and compared with that using a single OF-C, our scheme achieves much shorter average provisioning latency in dynamic provisioning.

A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response

To reduce the uncertain influence of wind power and solar photovoltaic power on virtual power plant (VPP) operation, robust optimization theory (ROT) is introduced to build a stochastic scheduling model for VPP considering the uncertainty, price-based demand response (PBDR) and incentive-based demand response (IBDR). First, the VPP components are described including the wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and demand resource providers (DRPs). Then, a scenario generation and reduction frame is proposed for analyzing and simulating output stochastics based on the interval method and the Kantorovich distance. Second, a bi-level robust scheduling model is proposed with a double robust coefficient for WPP and PV. In the upper layer model, the maximum VPP operation income is taken as the optimization objective for building the scheduling model with the day-ahead prediction output of WPP and PV. In the lower layer model, the day-ahead scheduling scheme is revised with the actual output of the WPP and PV under the objectives of the minimum system net load and the minimum system operation cost. Finally, the independent micro-grid in a coastal island in eastern China is used for the simulation analysis. The results illustrate that the model can overcome the influence of uncertainty on VPP operations and reduce the system power shortage cost by connecting the day-ahead scheduling with the real-time scheduling. ROT could provide a flexible decision tool for decision makers, effectively addressing system uncertainties. ESSs could replace CGT to provide backup service for the WPP and PV, to smooth the VPP output curve and to improve the WPP and PV grid connection by its charging–discharging characteristics. Meanwhile, IBDR and PBDR could smooth the load curve to the maximum extent, link the generation side with the demand side to minimize abandoned power value and reach the optimum benefit of VPP operation.

Robust Service Compositions with Functional and Location Diversity

Service composition provides a means of customized and flexible integration of service functionalities. Quality-of-service (QoS) optimization algorithms select services to adapt workflows to the non-functional requirements of the user. With increasing number of services in a workflow, previous approaches fail to achieve a sufficient reliability. Moreover, expensive ad-hoc replanning is required to deal with service failures. The major problem with such sequential application of planning and replanning is that it ignores the potential costs during the initial planning and they consequently are hidden from the decision maker. Our idea to overcome this problem is to compute a QoS optimized selection of service clusters that includes a sufficient number of backup services for each service employed. These backup services should be sufficiently distributed to prevent a task failure in case of, e.g., a network failure. To support the decision maker in the selection task, our multi-objective approach considers the possible repair costs directly in the initial composition. Our graphical user interface visualizes the resulting QoS of the workflow and the location of the services to enable the decision maker to select compositions in line with risk preferences. We prove the benefits of our approach in our detailed evaluation.

FORESTRY COMPANY SATISFACTION TOWARDS ONLINE INFORMATION SYSTEM IMPLEMENTATION OF FOREST PRODUCT MANAGEMENT (SI-PUHH)

This research was conducted with the aim 1) to analyze gaps that occurs between perception and expectations of the company implementation of SI-PUHH Online, 2) to analyze the level of satisfaction of the company implementation of SI-PUHH Online 3) Formulate a strategy to improve the quality of service implementation PUHH Information System Online. Analysis of the data used is the Importance Performance Analysis (IPA) and the Customer Satisfaction Index (CSI). The results showed that there are five attributes that considered important in determining customer satisfaction. These five attributes are: 1) System Online has a server that is up to date with internet bandwidth that is large so it is not easy down and can be accessed quickly; 2) response rapid administrator/operator; 3) accurate data in accordance with entrian company; 4) There is a backup server; and 5) Officer SI-Online PUHH always willing to help. The fifth attribute is an attribute that has a high level of importance, but in its implementation or performance is still unsatisfactory. Customer Satisfaction Index (CSI) on the implementation of this SIPUHH Online amounted to 72,07%, meaning that customers satisfied on the performance of services carried out by the Ministry of Environment and Forestry, but must maintain and improve the performance SERVQUAL PUHH Information System Online is to be able to satisfy the users company PUHH Information System Online. Keywords: SI-PUHH Online, SERVQUAL, IPA, CSI

Manajemen Risiko Sistem Informasi Perpustakaan (Studi Kasus di Perpustakaan Universitas Gadjah Mada)

Library information systems and information assets administered to users become the backbone of library service with the support of information technology. Howevet the application of library information systems that grows rapidly may raise the riskthat causesfailures threatening librarians in assessing sources of risk threats. Risks may include events and conditions that lead to disruption in information services and the problem of the decision-making process evaluation although not documented in writing. Informants of this study consist of librarians who have social interaction with library information system. The method uses qualitative case study approach with in-depth interviews and direct observation.The results ofthe study identifies the riskin a hang of backup server is high, iThe purpose of this study is to describe the implementation of risk management in information systems at Gadjah Mada University Library using NISTSP 800-30 frame work and to determine factors that affect the implementation of risk management in information systems at the library. Risk management in information systems at Gadjah Mada University Library has been implemented to anticipate the various sources of risk threats by conducting risk assessment, risk mitigation and risk electricity is high, in security systems is high, in passwords is high, in authorization permission is moderate and in human resources is moderate. To reduce and eliminate the risk impact, Gadjah Mada University Library conducts risk mitigation by transferring the risk from a library information systemservers to PSDI (Center for Systems and Information Resources), while the risk evaluation of the activities is carried out continuously and consistently by the librarians to implement control and activities in risk mitigation to the extent acceptable to the library. Factors affectiig the implementation of risk management information systems at the Gadjah Mada University Library are influenced by the policies of the University, the perception of the library's head and human resources and technicalcapabilities in the fi eld of information technology.