Data Recovery Time Research Articles

WR-enhanced TDM-PON with nanosecond clock and data recovery and picosecond time synchronization

Access networks require higher bandwidth and throughput to handle rapidly increasing traffic. However, in the time-division multiplexing passive optical network (TDM-PON) system, improving system throughput in such a time-slotted network faces two technical challenges. First, because optical network units transmit packets with individual clock frequency, receivers at the optical line terminal side must instantly recover the frequency to guarantee the throughput, while no valid data can be received before the clock and data recovery (CDR) is completed. Second, the time-slotted mechanism requires fine-granularity of time-slot edge alignment, where the interpacket interval used to compensate the misalignment deteriorates the throughput. In this paper, these two challenges are simultaneously addressed by white rabbit (WR) protocol-based enhancements for the first time, to our best knowledge, in a TDM-PON system. With the synchronous Ethernet of WR protocol, the physical-layer frequency synchronization efficiently accelerates the CDR via eliminating the time-consuming frequency tracking process. Moreover, after improving the time precision to the subnanosecond level via a digital dual mixer time difference phase detector, the precise delay model in the WR protocol can accurately elaborate the compensation and adjustment on time. The experimental results validate that the proposed network achieves 38.6 ns CDR time and 341 ps time synchronization precision.

Multicloud Based Backup and Disaster Recovery Service

In the recently years organizations have started to generate huge amounts of information of different formats. Availability of this huge amount of data collected is required for continuity of business during disasters .It is one of the main necessities of the time. Currently these backup and recovery services run with disadvantages of being very expensive with high restore and backup time. Solution to the above issues is cloud based platforms which will be used for these services. Cloud based platforms can be used for any amount of resources limited or boundless. Scheduling strategy COST-RTO tradeoffs scheduling algorithm is used to find the right server location to back up the replicated data. This algorithm mainly reduces the cost and data recovery time during a disaster. Here 3 backups are made and storage of these replicas of the data is done by this replica scheduler. Methods like incremental backup is being used to reduce backup time, metadata of the backed up data will be generated. This generated meta-data will help to retrieve data faster while restoring .Delivering these solutions as cloud services for faster and lowered cost accessing is the main objective which is fulfilled by the application..

A Synchronous Distributed Communication and Control System for SiC-Based Modular Impedance Measurement Units

Single-phase modular impedance measurement unit (IMU) is a promising solution to power system stability analysis. Yet, existing designs only have modularity at the power-stage level other than the control-platform level, which restricts the scalability of modular IMUs. As such, this article proposes a distributed communication and control system (DCCS) for high-frequency large-scale modular IMUs with tight synchronization and low latency to enhance the controller-level modularity and scalability. The new architecture is realized on a widely adopted DSP+FPGA control platform that can be adapted from most existing centralized control systems (CCSs) of modular converters. In this article, the influence of synchronization accuracy (SA) on converter harmonics under carrier-based PWM is first investigated, followed by the study of communication latency’s impact on the system control frequency. Subsequently, the synchronization method of a combined oversampling clock and data recovery (CDR) plus precision time protocol (PTP) method is presented. Furthermore, a communication protocol to maximize control frequencies and a system-level control strategy are elaborated. Finally, controller- and converter-level experimental results are demonstrated on a 520-V, 20-A, SiC-MOSFET-based IMU prototype at 120-kHz equivalent switching frequency, achieving a well-performed ±12.5-ns SA and 60-kHz control frequency.

Modeling the Performance of the Clock Phase Caching Approach to Clock and Data Recovery

Optical switching could enable data center networks to keep pace with the rapid growth of intra-data center traffic, however, sub-nanosecond clock and data recovery time is crucial to enabling optically-switched data center networks to transport small packet dominated data center traffic with over 90% efficiency. We review the clock-synchronized approach to clock and data recovery, which enables sub-nanosecond switching time in optically switched networks. We then introduce an analytical model to mathematically explore the operation of clock phase caching, and use this model to explore the impact of factors such as fiber temperature, clock jitter and symbol rate on the BER and clock and data recovery locking time performance of the clock phase caching approach, as well as their impact on scalability. Using commercial data center parameters matching those used in our previous experimental research, we find that our analytical model provides estimates that closely match our previous experimental results, validating its use for making predictions of the performance of clock phase cached systems.

Clock Synchronized Transmission of 51.2 GBd Optical Packets for Optically Switched Data Center Interconnects

Optical switching has attracted significant attention in recent research on data center networks (DCNs) as it is a promising viable route for the further scaling of hyper scale data centers, so that DCNs can keep pace with the rapid growth of machine-to-machine traffic. It has been shown that optical clock synchronization enables sub-nanosecond clock and data recovery time and is crucial to high performance optically switched DCN. Moreover, the interconnect data rate is expected to increase from the current 100 Gb/s per fiber to scale to 800 Gb/s and beyond, requiring high baud rate signaling at >50 GBd. Thus, future optically switched DCN should support >50 GBd data transmission with optical clock synchronization. Here, we demonstrate the clock-synchronized transmission of 128-byte optical packets at 51.2 GBd and study the impact of reference clock phase noise on system performance, focusing on the tolerance to the clock phase misalignment that affects the system scalability and reliability. By comparing the tolerable sampling clock phase offsets using different reference clocks, we show that a clock phase offset window of about 8 ps could be achieved with a <0.2ps source clock. Furthermore, we model and numerically study the de-correlation of clock phase noise. This allows the total jitter to be estimated, and thereby, the estimation of the transmission performance for future generations of high baud rate, clock synchronized DC interconnects.

Provides an Approach based on Adaptive Forwarding and Label Switching to Improve the Speed of Packet Forwarding in NDN Networks

Named Data Networking (NDN) is a recently designed Internet architecture that benefits data names instead of locations and creates essential changes in the abstraction of network services from "delivering packets to specific destinations” to "retrieving data with special names" makes. This fundamental change creates new opportunities and intellectual challenges in all areas, especially network routing and communication, communication security, and privacy. The focus of this dissertation is on the forwarding aircraft feature introduced by NDN. Communication in NDN is done by exchanging interest and data packets. Consumers send interest packets to request data, routers send them based on the data prefix name, and manufacturers respond with data packets exactly how interest is received. During this process, routers maintain information about the status of suspended interests. As regards NDN is still in its early stage, none of these strong efficiency features have done systematically designed, measured, or tracked in data retrieval and multi-path detection. This paper tries to improve transport performance by combining label switching with adaptive transport methods. For this purpose, in addition to RTT, another timer called T is used, an RTT factor for interface rating. And uses the BDP to choose the best interface to respond to interest. During this process, response time, throughput, and data recovery time are improved by 12%, 10%, and 5%, respectively.

DLFT: Data and Layout Aware Fault Tolerance Framework for Big Data Transfer Systems

Various scientific research organizations generate several petabytes of data per year through computational science simulations. These data are often shared by geographically distributed data centers for data analysis. One of the major challenges in distributed environments is failure; hardware, network, and software might fail at any instant. Thus, high-speed and fault tolerant data transfer frameworks are vital for transferring such large data efficiently between the data centers. In this study, we proposed a bloom filter-based data aware probabilistic fault tolerance (DAFT) mechanism that can handle such failures. We also proposed a data and layout aware mechanism for fault tolerance (DLFT) to effectively handle the false positive matches of DAFT. We evaluated the data transfer and recovery time overheads of the proposed fault tolerance mechanisms on the overall data transfer performance. The experimental results demonstrated that the DAFT and DLFT mechanisms exhibit a maximum of 10% and a minimum of 2% recovery time overhead at 80% and 20% fault points respectively. However, we observed minimum to negligible overhead with respect to the overall data transfer rate.

Theoretical analysis of the data recovery time in the fault-tolerant disk arrays RAID-5 and RAID-6 with data striping

This scientific paper deals with the fault-tolerant disk arrays RAID-5 and RAID-6 with data striping. The structure of the disk arrays RAID-5 and RAID-6 and mathematical model of the redundant data coding in these disk arrays, based on the arithmetic of the binary Galois field GF (28), are discussed. The obtained by the authors theoretical formulas for estimation of the data recovery time in the case of failure and replacement of single disk in the RAID-5 arrays, and data recovery time in the cases of failure and replacement of single and two disks in the RAID-6 arrays are also presented. Finally, the examples of theoretical estimation of the data recovery time in the RAID-5 and RAID-6 arrays are also discussed.

Optimization of the Recovery Time of Pyramid Code in Distributed Storage System

In large scale distributed storage systems, erasure code is a basic technology that provides high reliability at low cost. Compared with traditional redundancy technology, erasure coding technology has low redundancy and high flexibility. Therefore, it is a good choice for distributed systems to construct Pyramid codes that are flexible and suitable for a variety of application scenarios, but its disadvantage is that the data recovery time is still long. To address the above problems, in this paper, we propose an Active Fault-Tolerant Pyramid (AFTP) based code, which dynamically adjusts the length of the group in the Pyramid code and the original data block correlation with redundant blocks by using the hard disk fault prediction model based on the decision tree to reduce the length of the group of data blocks in a potentially faulty hard disk, which can be used for multiple hard disk failures. All read and recovery operations are performed within the group, reducing recovery time without adding additional storage overhead. To verify the validity of the AFTP code, we conduct intensive experiments on the distributed storage system based on Ceph. The results show that, compared with Basic-Pyramid (BP), the recovery time of AFTP code is reduced by 8%-64%, and compared with the commonly used classic block codes, the recovery time of AFTP code is reduced by 11%-52%.

Synchronous subnanosecond clock and data recovery for optically switched data centres using clock phase caching

The rapid growth in the amount of data being transferred within data centres, combined with the slowdown in Moore’s Law, creates challenges for the future scalability of electronically switched data-centre networks. Optical switches could offer a future-proof alternative, and photonic integration platforms have been demonstrated with nanosecond-scale optical switching times. End-to-end switching time is, however, currently limited by the clock and data recovery time, which typically takes microseconds, removing the benefits of nanosecond optical switching. Here we show that a clock phase caching technique can provide clock and data recovery times of under 625 ps (16 symbols at 25.6 Gb s−1). Our approach uses the measurement and storage of clock phase values in a synchronized network to simplify clock and data recovery versus conventional asynchronous approaches. We demonstrate the capabilities of our technique using a real-time prototype with commercial transceivers and validate its resilience against temperature variation and clock jitter. A clock synchronization method, which is based on optical clock distribution and clock phase caching, can provide subnanosecond clock and data recovery times for fast optical switching in large-scale data centre networks using off-the-shelf commercial transceivers.

Link Recovery Scheme for Multi-Point mmWave Communications

Directional transmission in millimeter wave (mmWave) communications results in prolonged access times. This is attributed to the increased number of conducted measurements to determine optimum beam directions at the mobile station (MS) and base station (BS) that return the highest received signal levels. Additionally, once these beams are determined and links are established for data-planes, then blockage effects and outages make these links more vulnerable to link failures, resulting in communications drops. Hence, dynamic and fast recovery schemes are required to maintain communications sessions following the beam access stage. In this paper, a novel recovery access scheme is proposed for multi-point mmWave communications based on fog access points (AP). Namely, the scheme leverages diversity and network coding techniques to achieve near-instantaneous recovery times, without the need for beam scanning. The scheme features near-instantaneous data recovery times and efficient power consumption as compared to traditional recovery methods.

Merkle Hash Tree with Hash based Digital Signature for Cloud Data Confidentiality and Security

It provides efficient processing power, an unbelievable computation speed and a wide array of stage space.Basically, the cloud computing transfer the huge volume of data on the different cloud servers which is maintained by the different kinds of cloud providers and this process help to remove the physical data’s possession even though user are the data owners. This extraordinary element coordinates to raise the innumerable new security disadvantages which have not been surely known obviously. Consequently, in this paper present a novel methodology for secure cloud information stockpiling with the assistance of Merkle Hash Tree (MHT) with hash based advanced mark to give trustworthiness and protection of redistributed information in cloud using private key security approach. Additionally, in this work use theAdvanced Encryption Standard (AES) for conforming the data confidentiality and data security before the data is stored into the cloud. The simulation results show the better results in term of Data Recovery Time, Processing time, and efficiency respectively

Security and Privacy of Data in Cloud Computing

The cloud computing paradigm is being used because there is no need to setup additional IT infrastructure such as hardware and software, its low up-front cost. Security and privacy of data is important in day to today life especially for applications that uses cloud computing such as social media. Customer information that is stored at Cloud is crucial that needs to be protected against potential intruders. There is threat to maintain the data in transit and data at cloud due to different possible attacks. Due to this there is growing need of privacy and security of data. In this paper, the privacy and issues, privacy preservation techniques are addressed. In addition to this, in order to protect the data, the secret sharing algorithm is implemented and analyzed. The shamir’s secret sharing (k,n) algorithm is used to split the data into n partial shares which can be distributed in cloud. The user collects at least k partial shares to reconstruct the complete data. It is observed that if the file size is increased, the data recovery time is also increased. The paper concludes with privacy preservation guidelines.

Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoT

QoS-aware big data analysis is critical in Information-Centric Internet of Things (IC-IoT) system to support various applications like smart city, smart grid, smart health, intelligent transportation systems, and so on. The employment of non-volatile memory (NVM) in cloud or edge system provides good opportunity to improve quality of data analysis tasks. However, we have to face the data recovery problem led by NVM failure due to the limited write endurance. In this paper, we investigate the data recovery problem for QoS guarantee and system robustness, followed by proposing a rarity-aware data recovery algorithm. The core idea is to establish the rarity indicator to evaluate the replica distribution and service requirement comprehensively. With this idea, we give the lost replicas with distinguishing priority and eliminate the unnecessary replicas. Then, the data replicas are recovered stage by stage to guarantee QoS and provide system robustness. From our extensive experiments and simulations, it is shown that the proposed algorithm has significant performance improvement on QoS and robustness than the traditional direct data recovery method. Besides, the algorithm gives an acceptable data recovery time.

FTLADS: Object-Logging Based Fault-Tolerant Big Data Transfer System Using Layout Aware Data Scheduling

Layout-Aware Data Scheduler (LADS) data transfer tool, identifies and addresses the issues that lead to congestion on the path of an end-to-end data transfer in the terabit network environments. It exploits the underlying storage layout at each endpoint to maximize throughput without negatively impacting the performance of shared storage resources for other users. LADS can avoid congested storage elements within the shared storage resource, improving input/output bandwidth, and hence the data transfer rates across the high speed networks. However, absence of FT (fault tolerance) support in LADS results in data re-transmission overhead along with the possible integrity issues upon errors. In this paper, we propose object based logging methods to avoid transmitting the objects which are successfully written to Parallel File System (PFS) at the sink end. Depending on the number of logger files created, for the whole dataset, we classified our fault tolerance mechanisms into three different categories: File logger, Transaction logger and Universal logger. Also, to address space overhead of these object based logging mechanisms, we have proposed different methods of populating logger files with the information of the completed objects. We have evaluated the data transfer performance and recovery time overhead of the proposed object based logging fault tolerant mechanisms on LADS data transfer tool. Our experimental results show that, LADS in conjunction with proposed object based fault tolerance mechanisms exhibit an overhead of less than 1% with respect to data transfer time and total recovery time overhead is around 10% of total data transfer time at any fault point.

Study on the relationship between uncertainty in illness and recovery quality in patients with breast tumor

Objective To investigate the relationship between uncertainty in illness and recovery quality. Methods A cross sectional study was conducted from June to December 2015. The Chinese version Mishel Uncertainty in Illness Scale was used to assess uncertainty in illness of 168 patients with unconfirmed breast tumor undergoing general anesthesia. The following datarecovery time, time stay in postanesthesiacar unit, modified Observer′s Assessment of Alertness/Sedation Scale score etc were recorded. Results The breast tumor patients had a medium degree of illness uncertainty (81.11±12.57) points. Educational background, marital status, family medical history, the severity of disease affect scores of illness uncertainty (P<0.05 or 0.01). Uncertainty in illnesswas negative correlated with recovery quality (P<0.05 or 0.01). Conclusions Uncertainty in illness of patients isrelated to recovery quality. Nursesshould instruct breast tumor patients to manage symptoms to decrease uncertainty in illness. Key words: Breast neoplasm; Illness uncertainty; Quality of recovery

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.

A Reed-Solomon Based Method to Improve Message Delivery in Delay Tolerant Networks

Delay and Disruption Tolerant Networks are made up of mobile wireless nodes which may experience major message delivery restrictions. Such restrictions are the result of intermittent connectivity and scattered topology. Within these networks, messages can be detained for long periods of time or never be delivered. Existing solutions that purport improved message delivery rates modify routing protocols to perform integrity verification with each hop, resulting in routing overhead and, very often, unnecessary processing costs. This article proposes a scheme, named EMCOD, which decreases message delivery delay, while minimally increasing the processing overheads. To achieve this, EMCOD uses data encoding and interleaving to create messages. The original data is reassembled from some of the messages received, without the need to wait for all messages to be received. In scenarios subject to long delays and/or significant packet loss rates, it is possible to reduce original data recovery times by more than 50%. The processing overhead resulting from the encoding procedures is offset by the data recovery capabilities, which effectively decreases network overheads by more than 60%, in the same scenarios. EMCOD modifies the Bundle Layer, without interfering with the remaining layers, making it possible to route the messages through nodes that do not implement the proposed scheme.

Intelli-restore as an instantaneous approach for reduced data recovery time

Due to the competitive and regulatory pressures and the high demands and dependence placed on data, there is need for higher data availability and a faster means of recovering the data in case it becomes corrupted or lost. Based on results provided on the reasons behind the long / high data recovery times by Kenyan SMEs this paper provides a solution that reduces the data recovery time. In order to solve the problem of high data recovery times, an instantaneous data recovery strategy based on an existing Continuous Data Protection (CDP) architecture is introduced as an important component of a well-rounded backup and recovery strategy. CDP is a disk based backup solution which ensures that data is retrieved at a much faster rate during recovery. The solution presented in this paper could help organizations adopt or complement existing data recovery strategies.

Continuous Data Protection as a Strategy for Reduced Data Recovery Time

This paper presents the reasons behind the long / high data recovery times by Kenyan Firms and provides a solution that reduces the data backup for recovery time. It was found that the time taken to recover data was reasonably high because of the type of media that was used for backing up data: the magnetic data tape. In order to solve the problem of high data recovery times, Continuous Data Protection (CDP) is introduced as an important component of a well-rounded backup and recovery strategy to complement the existing backup strategy as CDP is a disk based backup solution which ensures that data is retrieved at a much faster rate. The findings presented in this paper could help researchers design a strategy for instanteneous data recovery based on Continuous Data protection.