Disaster Recovery System Research Articles

Efficient and robust disaster recovery system using cloud-based algorithms with data integrity

Incorporating cloud-based algorithms for disaster recovery (DR), it explores data replication, failover, virtual machine (VM) migration, and consistency algorithms. These algorithms play a pivotal role in safeguarding data and system continuity during unforeseen disruptions. Data replication ensures redundancy, failover algorithms swiftly transition to backup resources, VM migration facilitates resource optimization, and consistency algorithms maintain data integrity. Leveraging cloud technology enhances the effectiveness of these algorithms, providing robust DR solutions critical for business continuity in today's digital landscape. The recent growth in popularity of internet services on a massive scale has also raised the demand for stable underpinnings. Despite the fact that DR for big data is frequently overlooked in security research, the majority of existing approaches use a narrow, endpoint-centric approach. The significance of DR strategies has grown as cloud storage has become the norm for more data. But traditional cloud-centric DR techniques may be expensive, thus less expensive alternatives are being sought. There is persistent concern in the information technology (IT) community about whether or not cloud service providers (CPs) can guarantee data and service continuity in the event of a disaster.

PERAN PEMERINTAH DAERAH DALAM PENGURANGAN RISIKO BENCANA MELALUI PENINGKATAN KETAHANAN BENCANA DAERAH DI KABUPATEN TANAH BUMBU

Exploitation of natural resources triggers a decrease in the carrying capacity and capacity of the environment and results in climate change and various kinds of disasters. The objectives of this research are Analyzing the role of the Regional Government in implementing the Regional Resilience Index Improvement Program; Analyzing the inhibiting factors of the Regional Resilience Index improvement that has been carried out by the Tanah Bumbu Regency Government; Determining the priority scale of the Regional Disaster Resilience Improvement Program. Data analysis used in this study is Calculating the percentage of indicator achievement based on the Technical Guidelines for the Regional Resilience Index Assessment Tool, Descriptive analysis of inhibiting factors in increasing the Regional Disaster Resilience Index (71 Indicators) to stakeholders through interviews, Creating a priority scale matrix to determine recommendations. Determination of the priority scale matrix is based on Minimum Service Standards and ranking of relevant stakeholders. The results of research on the role and inhibiting factors of the Tanah Bumbu district government in increasing the Regional Resilience Index are Indicators implemented in the priority of Strengthening Policies and Institutions by 60.00%. Indicators implemented in the priority of Risk Assessment and Integrated Planning amounted to 75.00%. Indicators implemented in the Information System Development, Training and Logistics priority by 69.23%. Indicators implemented in the priority of Thematic Handling of Disaster Prone Areas amounted to 80.00%. Indicators implemented in the priority of Increasing the Effectiveness of Disaster Prevention and Mitigation by 70.00%. Indicators implemented in the priority of Strengthening Disaster Preparedness and Emergency Management by 55.00%. Indicators implemented in the Disaster Recovery System Development priority of 75.00%.

The mPOC Framework: An Autonomous Outbreak Prediction and Monitoring Platform Based on Wearable IoMT Approach

This paper presents the mHealth Predictive Outbreak for COVID-19 (mPOC) framework, an autonomous platform based on wearable Internet of Medical Things (IoMT) devices for outbreak prediction and monitoring. It utilizes real-time physiological and environmental data to assess user risk. The framework incorporates the analysis of psychological and user-centric data, adopting a combination of top-down and bottom-up approaches. The mPOC mechanism utilizes the bidirectional Mobile Health (mHealth) Disaster Recovery System (mDRS) and employs an intelligent algorithm to calculate the Predictive Exposure Index (PEI) and Deterioration Risk Index (DRI). These indices trigger warnings to users based on adaptive threshold criteria and provide updates to the Outbreak Tracking Center (OTC). This paper provides a comprehensive description and analysis of the framework’s mechanisms and algorithms, complemented by the performance accuracy evaluation. By leveraging wearable IoMT devices, the mPOC framework showcases its potential in disease prevention and control during pandemics, offering timely alerts and vital information to healthcare professionals and individuals to mitigate outbreaks’ impact.

Wellbeing in disaster recovery: Understanding where systems get stuck

Disasters effectively break the ability of a community to operate effectively and create a serious challenge to both individual and community wellbeing. We analyse longer-term recovery as a system that enables community members to regain and retain material and subjective wellbeing. In this paper we posit that wellbeing needs to be understood as an important emergent property of a disaster recovery system. However, in certain cases wellbeing does not occur and the recovery system has become “stuck”. We apply a systems traps lens to a well-known recovery effort where wellbeing did not emerge equitably or sufficiently to show where and how the system got stuck. We present three system traps that severely hindered wellbeing emergence following the Canterbury earthquakes. From this we suggest system traps are a useful analytical tool for those undertaking disaster recovery seeking to better support the development of wellbeing. We conclude that applying a systems traps lens to long-term recovery systems in general, and wellbeing in particular helps to both identify where challenges are located and how to address them.

Long-term housing recovery among Mexican immigrants: How service providers navigate racialized anti-immigrant disaster recovery policies

Disasters are increasing in frequency and intensity. Much of the current disaster literature adopts a social vulnerability perspective, which considers how political, social, and economic factors influence pre-disaster preparation and post-disaster recovery. Even with this focus, however, there remains a dearth of literature on immigrant populations and their long-term recovery trajectories. This paper applies a racial formation framework to a disaster context. I seek to show how service providers from community-based organizations (CBOs) navigate racialized anti-immigrant disaster recovery policies to help the Mexican immigrant community in Houston, Texas with their long-term housing recovery after Hurricane Harvey. I conducted semi-structured interviews and ethnographic observations with service providers from CBOs located in Houston that serve this population with post-disaster housing. I argue that the disaster recovery system is comprised of racial structures and racialized anti-immigrant policies, passively and actively limiting the access to resources for the Mexican immigrant community. I found that to challenge the racial structures and racialized anti-immigrant policies of the disaster recovery system, service providers assist the community through direct assistance to Mexican immigrants excluded from other programs; collaboration with other organizations to combine limited resources; helping the community navigate racialized anti-immigrant bureaucracy; and building trust by embedding themselves in the victimized community. However, findings also show that these organizations face significant challenges in conducting their work. This research brings a much-needed theoretical expansion of race and racialization theories to disaster research.

PENGURANGAN RISIKO BENCANA BERBASIS DESTANA DI DESA GLAGAHARJO DALAM MEWUJUDKAN KETAHANAN WILAYAH KABUPATEN SLEMAN

Glagaharjo Village is a one of the villages in Sleman Regency that is a Disaster Resilient Village (DRV). This study aims to analyze the implementation of disaster risk reduction based on disaster resilient village in Glagaharjo Village and its implications for regional resilience in Sleman Regency. Using a qualitative method with an exploratory approach, the research was conducted from May 2021 - January 2022 in Glagaharjo Village, Cangkringan District, Sleman Regency. Interviews, documentation, and observation with analytical techniques using the Miles, Huberman and Saldana model were used as the data collection techniques. The result of this research shows that disaster risk reduction based on disaster resilient village in Glagaharjo Village has successfully met the criteria to become a Major Disaster Resilient Village by getting a score of 98/112. Consequently, the program has fulfilled the Astagatra aspect and has positive implications for regional resilience in Sleman Regency, as it supports 6 of 7 priorities for regional resilience, namely: (1) strengthening policies and institutions, (2) risk assessment and integrated planning, (3) developing information systems, training and logistics, (4) handling thematic areas prone to disasters, (5) disaster emergency preparedness and handling, and (6) development of disaster recovery system.

A failure detection method of remote disaster recovery and backup system

Failure detection is one of the basic functions of building a reliable disaster recovery backup system. Aiming at the application-level disaster recovery backup failure detection problem, this paper analyzes the remote disaster recovery center architecture and failure detection hierarchy, and predicts the arrival time of cross-domain heartbeat information through the back propagation neural network based on particle swarm optimization (PSO-BP). When the actual timeout is reached, the active Auxiliary Detection (AD) is used to improve the correctness of failure detection, and finally the effectiveness of method PSO-BP-AD is verified through simulation.

A Study on How to Build a Disaster Recovery System that can Minimize Recovery Time Objective(RTO) and Recovery Point Objective(RPO) to Ensure Business Continuity

A Study on How to Build a Disaster Recovery System that can Minimize Recovery Time Objective(RTO) and Recovery Point Objective(RPO) to Ensure Business Continuity

A Novel Hash Chain-Based Data Availability Monitoring Method for Off-site Disaster Recovery Architecture

With the rapid development of mobile Internet, there is a higher demand for the real-time, reliability and availability of information systems and to prevent the possible systemic risks of information systems, various business consistency standards and regulatory guidelines have been published, such as Recovery Time Object (RTO) and Recovery Point Object (RPO). Some of the current related researches focus on the standards, methods, management tools and technical frameworks of business consistency, while others study the data consistency algorithms in the cases of large data, cloud computing and distributed storage. However, few researchers have studied on how to monitor the data consistency and RPO of production-disaster recovery, and what architecture and technology should be applied in the monitoring. Moreover, in some information systems, due to the complex structures and distributions of data, it is difficult for traditional methods to quickly detect and accurately locate the first error data. Besides, due to the separation of production data center (PDC) and disaster recovery data center (DRDC), it is difficult to calculate the data difference and RPO between the two centers. This paper first discusses the architecture of remote distributed DRDCs. The architecture can make the disaster recovery (DR) system always online and the data always readable, and support the real-time monitoring of data availability, consistency as well as other related indicators, in this way to make DRDC out-of-the-box in disasters. Second, inspired by blockchain, this paper proposes a method to realize real-time monitoring of data consistency and RTO by building hash chains for PDC and DRDC. Third, this paper evaluates the hash chain operations from the algorithm time complexity, the data consistency, and the validity of RPO monitoring algorithms and since DR system is actually a kind of distributed system, the proposed approach can also be applied to the data consistency detection and data difference monitoring in other distributed systems.

Design of Reliable Disaster Recovery System through Integrated Server Redundancy

Even before the September 11 terrorist attacks in the United States in 2001, information systems prepared against disasters in Korea were extremely weak. However, as various domestic and foreign accident cases have occurred, it is recognized that preparations for this are necessary. Accordingly, at present, each institution has prepared and implemented various backup policies to protect the institution's information and data in case of disaster. Therefore, in this paper, we conducted a study to design a more stable and efficient disaster recovery system by building redundancy for server operating in integrated data center. To do this, we analyzed the redundancy design for the integrated disaster recovery server and designed the overall system configuration. Also, the design results were analyzed by testing web server redundancy and switch redundancy. In this paper, the proposed design method for stabilization and efficiency of disaster recovery system is the redundant construction of integrated server and switch. In other words, the disaster recovery system was composed of active storage and standby storage, and data stabilization was promoted through real-time replication of each other. In the existing disaster recovery system, there is a problem in stabilizing replication because there is no monitoring system for internal replication between storage arrays. To solve this problem, we designed a system that replicates all data in active storage to standby storage in real time and monitors the replication status. Therefore, introducing service conversion automation from the main system, which is the method designed in this paper, to the disaster recovery system, improves the stability and reliability of the service of the local governments, so that it is possible to operate a more efficient and advanced disaster recovery system.

Interface Mode Assignment Method for Self‐Reconstruction of Wireless Mesh Networks Based on IEEE 802.11 Infrastructure‐Mode

The key features of computer networks available for a disaster situation are reliable, fault tolerance, and self‐configurable. Therefore, using a wireless mesh network for disaster prevention and recovery system has gained much attention from the research community in the last decades. In addition, from the practical aspects of the network infrastructures of the disaster system, we should assume the core capabilities such as wireless connectivity in a wide range, ease of use, and low cost so on. In this paper, we propose an interface mode assignment method for reconstructing a route from an isolated router to a gateway (GW) router in a wireless mesh network based on IEEE 802.11 infrastructure mode after a disaster occurrence. The proposed method assigns an adequate mode to each interface in an isolated router to recover the network reachability in a distributed manner. Simulation results show the effectiveness of the proposed method via two different scenarios. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Scalable, near-zero loss disaster recovery for distributed data stores

This paper presents a new Disaster Recovery (DR) system, called Slogger, that differs from prior works in two principle ways: (i) Slogger enables DR for a linearizable distributed data store, and (ii) Slogger adopts the continuous backup approach that strives to maintain a tiny lag on the backup site relative to the primary site, thereby restricting the data loss window, due to disasters, to milliseconds. These goals pose a significant set of challenges related to consistency of the backup site's state, failures, and scalability. Slogger employs a combination of asynchronous log replication, intra-data center synchronized clocks, pipelining, batching, and a novel watermark service to address these challenges. Furthermore, Slogger is designed to be deployable as an "add-on" module in an existing distributed data store with few modifications to the original code base. Our evaluation, conducted on Slogger extensions to a 32-sharded version of LogCabin, an open source key-value store, shows that Slogger maintains a very small data loss window of 14.2 milliseconds which is near the optimal value in our evaluation setup. Moreover, Slogger reduces the length of the data loss window by 50% compared to incremental snapshotting technique without having any performance penalty on the primary data store. Furthermore, our experiments demonstrate that Slogger achieves our other goals of scalability, fault tolerance, and efficient failover to the backup data store when a disaster is declared at the primary data store.

User-Centric Cyber Disaster Recovery as a Service

In a world of interdependent economies and online transactions, a large volume of data hosted on the cyberspace a daily bases. Cyber threats and attacks are steadily increasing. Most time, these threats and attacks are targeted at service providers but service users are greatly affected by the attacks due to their vulnerability level. When disasters knockdown the infrastructures of a single service provider, it will have ripple effects on thousands of innocent service users. Therefore, service users need more than ever to prepare for major crises targeted at their service providers. To cope with this trends, every service user requires an independent business continuity plan (BCP) or disaster recovery plan (DRP) and data backup policy which falls within their cost constraints while achieving the target recovery requirements in terms of recovery time objective (RTO) and recovery point objective (RPO). The aim of this paper is to develop a model for a user-centric disaster recovery system to enable service users to independently develop their data backup policies that best suits their remote databases, and host same as a cloud service deployable on public cloud for users to subscribe to and be billed on pay-as-you-go billing model. The system developed is highly compatible with MYSQL, MSSQL and Oracle databases. A combination of Dynamic System Development Methodology (DSDM) and Object- Oriented Analysis and Design Methodology (OOADM) were used to design the system while Java Enterprise Edition (JEE) is used to develop the system. The encryption and compression mechanisms of the system were tested with various sizes of backup files ranging from 64 Kb to 20Mb and several performance metrics such as (1) Encryption time; (2) Compression size; (3) CPU clock cycles and battery power are compared and analysed with some well-known encryption and compression algorithms.

Rescue: Wireless power-enabled communication architecture for earthquake rescue operations

In a natural disaster such as an earthquake, it is vital to know the number of people trapped under the ruins. To address this problem, we propose RESCUE — wiREless backScattering CommUnication-based disastEr recovery system. RESCUE is composed of special Radio-frequency identification (RFID) readers and sensors that are used to determine the total number of people under the ruins. Passive wireless sensor nodes are placed inside the building during construction and are equipped with a camera that is activated during an earthquake. After the earthquake, communication to the passive tags of sensors is achieved by wireless power transfer from a reader located outside the ruins. Tags harvest this energy and send the image data stored by the camera. We also design an antenna structure to maximize simultaneous wireless information and power transfer (SWIPT) for devices under ruins. We analyze the communication channel between reader and sensors and derive a channel model over ruins. Furthermore, we obtain the results of experimental study where we validate the derived channel model. Results show that RESCUE can collect the desired data in a relatively short time, and hence, is a promising disaster recovery system architecture.

Android - Based Disaster Recovery System: Leveraging Hardware Controls for Emergency Data Recovery and Communication

Android - Based Disaster Recovery System: Leveraging Hardware Controls for Emergency Data Recovery and Communication

The role of data and information exchanges in transport system disaster recovery: A New Zealand case study

The Mw7.8 earthquake on 14 November 2016 near Kaikōura, New Zealand had major impacts on the country's transport system. Road, rail and port infrastructure was damaged, creating substantial disruption for transport operators, residents, tourists, and business owners across several regions. During the response and recovery phases, a large amount of information and data associated with the transport system was generated, managed, analysed, and exchanged within and between organisations to assist decision making.In this paper, we characterise how the transport system, infrastructure, and supply chain responded and adapted to earthquake-related disruptions and examine the flow and use of information in post-disaster (response and recovery) decision making across all transport modes. We present key findings from a post-earthquake assessment with the aim of improving information and data exchanges and related decision making in the transport sector during future events. This research commenced a year after the earthquake and involved 35 different stakeholder groups.Many information exchanges were effective, enabling the transport system to respond and adapt successfully, and allowing the continued mobility of users and goods. Organisations responding to transport disruptions drew on existing data sources in new ways, collected novel datasets, and leveraged relationships to manage information exchanges. There is, however, scope for improvement to reduce barriers to information exchanges and enhance post-disruption data usage between the numerous organisations involved in transport recovery. This may include improved clarity on organisational boundaries and an enhanced role for coordinators to act as single points of contact for transport sectors.

Optimizing Git for handling database backups: findings and insights from another 6,000 hours of experimentation

This is the second in a series of papers detailing results from on-going investigations of using Git - a distributed source control system - as a database backup and disaster recovery tool. The first paper, published early 2017 after 2,000 hours of data processing and simulations, warns that the default configuration of Git is unsuitable for database backups, but also shares configuration tweaks that make it safe and more space-efficient than zipped .sql archives - as low as only 1% of the storage space needed by .sql archives. This second paper focuses on optimization, looking specifically to identify which configuration tweaks and factors affect the reliability, scalability and efficiency of a Git-based database backup and disaster recovery system. Critical insights regarding the reliability and scalability of a Git-based database backup system were found after 6,000 hours of experimentation, centered around the problem of configuring Git to be able to handle .sql files measured in gigabytes.

Mobile Health Personal-to-Wide Area Network Disaster Management Paradigm

As full-scale natural disasters unfold, telecommunication infrastructures and services are among the most impacted, halting the necessary communications to and from the disaster zones, including the humanitarian operators and the people in need. The temporary relief can be achieved by establishing infrastructureless (ad-hoc) wireless networks; however, ad-hoc networks, instead of providing direct services to the end-users and affected people, provide direct connectivity to the localized service providers, which indirectly cover end-users. From a range of services provided by the humanitarian operators, healthcare has by far the top priority, which is the focus of this paper, through the utilization of smartphones in a Mobile Health (mHealth) perspective, which is an emerging concept in the smart-city paradigm for monitoring and tracking end-user health conditions. This paper covers the disaster management paradigm based on a novel bidirectional mHealth disaster recovery system and its protocol design and associated implications.

The Solution of Disaster Recovery System on Cloud Computing Environment

As the number of cases of cloud environment development in the financial industry has increased, cases of disaster recovery system in the financial industry are increasing. However, the establishment of the cloud environment for the main tasks in the financial industry is being restricted or limited in the cloud environment due to the security restriction regulation on the personal information and the financial business information. Unlike the establishment of a disaster recovery system for a general enterprise cloud environment, the financial industry of the cloud environment has a wide range of personal information security and protection regulations, and there are many limitations according to the respective country. Therefore, it is necessary to consider the existing one in constructing the disaster recovery system of the cloud environment in the financial industry. This research analyzes the solution and technology trends for existing cloud disaster recovery system, and extracts the problems of existing cloud disaster recovery system. In addition, the financial business classification criteria based on the services to be provided in the cloud environment, and determine the scope of introduction of the legacy system and the cloud system according to the cloud business classification standard are defined in this paper. In the standard of financial service to be provided in the cloud environment, the classification standard of the financial business is newly defined based on the range of influence of the personal information and the service continuity of the financial service from the core/context theory. Lastly disaster recovery system in cloud environment for financial business services is defined.

A Study on Information System and Disaster Recovery System for Business Continuity

A Study on Information System and Disaster Recovery System for Business Continuity