Recovery Point Objective Research Articles

Approaches to Disaster Recovery in Cloud Databases: A Comparative Analysis of Current Mechanisms

Disaster recovery (DR) is a critical aspect of maintaining the availability, integrity, and continuity of cloud databases, which store and manage vast amounts of mission-critical data. With the increasing reliance on cloud platforms for business operations, organizations must implement effective disaster recovery mechanisms to safeguard against data loss, downtime, and system failures. This paper presents a comparative analysis of current disaster recovery approaches in cloud databases, examining the strengths and weaknesses of various strategies, including backup and restore, data replication, and automated failover systems. We evaluate how these mechanisms are applied in different cloud models (public, private, and hybrid), considering factors such as recovery time objectives (RTO), recovery point objectives (RPO), cost, and scalability. The paper also discusses emerging technologies and trends in cloud DR, such as real-time data synchronization, machine learning-based predictive recovery, and multi-cloud disaster recovery solutions. Additionally, the role of cloud service providers’ Service Level Agreements (SLAs) in defining DR expectations is analyzed. By comparing the advantages and limitations of these mechanisms, this paper provides insights into how organizations can select the most appropriate DR strategy based on their specific business needs and risk tolerance. The study concludes by offering recommendations for optimizing disaster recovery plans in cloud environments to ensure business continuity and data protection in the face of unexpected disruptions.

Comprehensive data security and compliance framework for SMEs

Small and Medium-sized Enterprises (SMEs) are increasingly relying on cloud platforms to support critical business operations, making effective disaster recovery (DR) strategies essential for ensuring business continuity. This review proposes a robust disaster recovery framework tailored for SMEs, designed to minimize downtime and data loss in the event of a system failure, cyberattack, or natural disaster. The framework integrates advanced cloud technologies to create a cost-effective, scalable solution that aligns with the resource constraints of SMEs while providing enterprise-grade resilience. Key components of the disaster recovery framework include cloud-based data replication, automated backup solutions, and geo-redundant storage to ensure that data is continuously available and recoverable. This model employs real-time data synchronization and incremental backups to minimize Recovery Point Objectives (RPO), ensuring that critical data is not lost during an unexpected outage. Additionally, the framework leverages automated failover mechanisms to achieve low Recovery Time Objectives (RTO), allowing businesses to restore operations quickly after an interruption. Cloud orchestration tools such as AWS Elastic Disaster Recovery or Azure Site Recovery are utilized to automate disaster recovery processes, reducing manual intervention and improving the speed of recovery. The framework also incorporates regular testing of disaster recovery plans, using simulation tools to identify weaknesses and optimize response times. For SMEs, cost-effectiveness and ease of management are crucial. The framework emphasizes a pay-as-you-go model for cloud resources, allowing businesses to scale their disaster recovery solutions as they grow without incurring excessive upfront costs. By providing continuous monitoring and proactive threat detection, this disaster recovery framework ensures that SMEs can maintain uninterrupted business operations on cloud platforms, thereby enhancing resilience and mitigating the financial and operational risks associated with data loss and system downtime.

A Techno-Business Platform to Improve Customer Experience Following the Brand Crisis Recovery: A B2B Perspective.

A platform is a business model that allows business-to-business (B2B) participants to connect, interacts, create and exchange value. B2B exploits social media for brand building and branding is vulnerable to attacks, which leads to a brand crisis. B2B should characterise such crisis and respond proportionally to avert damage to social listening (SL). To diminish damages, the solution is to measure customer experience (CX), especially in a crisis situation. The study proposes an analytics-enabled customer experience (AeCX) platform for emotion detection in social media and measures CX after recovering from such crisis, by exploring recovery time objective (RTO), recovery point objective (RPO), techno-business features (TBF), SL and perceived risk (PR). A quantitative research methodology is used on primary data collected from 302 B2B participants. The study reveals improvement in CX and the results provide evidence that social media channels and the TBF of AeCX have become important.

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

Evaluating and modelling solutions for disaster recovery

Systems outages can have disastrous effects on businesses such as data loss, customer dissatisfaction, and subsequent revenue loss. Disaster recovery (DR) solutions have been adopted by companies to minimise the effects of these outages. However, the selection of an optimal DR solution is difficult since there does not exist a single solution that suits the requirement of every company (e.g., availability and costs). In this paper, we propose an integrated model-experiment approach to evaluate DR solutions. We perform experiments in different real-world DR solutions and propose analytic models to evaluate these solutions regarding DR key-metrics: steady-state availability, recovery time objective (RTO), recovery point objective (RPO), downtime, and costs. The results reveal that DR solutions can significantly improve availability and minimise costs. Also, a sensitivity analysis identifies the parameters that most affect the RPO and RTO of the DR adopted solutions.

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.

Assessing the resilience of an IT portfolio

One of the goals of the business impact analysis (BIA) process is to establish recovery objectives. Having established recovery objectives, the next step is to assess whether one’s IT portfolio can actually meet those objectives. Unfortunately, there is no well-defined and prescriptive process for this. This article describes a model that can be customised and applied in any organisation to take an IT-centric view to assessing resilience capabilities. The first stage of this process is to gather IT-specific data, either through a questionnaire or by querying the configuration management database directly. The next step is to leverage a set of scoring rubrics in order to assess the capabilities of each application with respect to meeting recovery point objectives, recovery time objectives and service-level targets, as well as the strength of staffing, documentation and disaster recovery plans. The output of the model is a composite score for each application (based upon an aggregate capability score and a weighting factor) that identifies those services in the IT portfolio with the greatest gaps in their capabilities (ie those services in greatest need of remediation). The logic of the model can either be built with spreadsheets or automated through business continuity management planning platforms.

A High‐Performance Hierarchical Snapshot Scheme for Hybrid Storage Systems

With the increased snapshot operations (creation or deletion), the performance of storage system will degrade severely whether in Copy on write (COW) or Redirect on write (ROW). This paper presents a novel snapshot scheme which could use of storage resources effectively and keep the historical data accurately for SSDHDD-hybrid storage system. SSD (source volume) stores all the active data and executes read/write operations without responding to snapshot operations. In contrast, HDDs (snapshot volume) store the writing data sequentially in the form of logs and are responsible for backup and snapshot operations. In this way, the hybrid storage system can get the high throughput power via SSD even the snapshot functions are active and HDDs can keep pace with the high Input/Output operations per second (IOPS) capability of the SSD. Logs are combined and kept in a separate image volume by the controller. So, fine-grained Recovery point objective (RPO) and good Recovery time objective (RTO) can be achieved. Experiment results show that the prototype can achieve excellent I/O performance while snapshot operations are active and consume a few extra storage space.

Developing a two-step fuzzy cost–benefit analysis for strategies to continuity management and disaster recovery

Continuation of organizations’ key processes in the aftermath of disasters plays an important role in the different businesses. The business continuity management (BCM) is a new concept which has attracted a lot of attention in the last decade and the most renowned organizations in the world use BCM as an effective precautionary approach to mitigate the consequences of disasters and making them resilient against disruptions. Alongside BCM, insuring and outsourcing are two other ways for coping with disasters. This study presents a novel framework for analyzing these three strategies (i.e. BCM, outsourcing and insuring) by which the best one can be selected according to the organization’s characteristics and relevant data. Furthermore, the study aims to elaborate on the interrelationships between the organization’s desirable continuity level in terms of recovery time objective (RTO) and recovery point objective (RPO) indicators, and the chosen approach to response disastrous situations. For this, all of the cost and benefits of each approach are considered and based on the type of organization for which a cost–benefit analysis is done. Economic factors such as the current and the future values as well as inflation rate are taken into account to select the best possible response strategy. As there is inherent uncertainty in input data, this study proposes a fuzzy based method to capture the impreciseness of data in the form of triangular fuzzy numbers. The proposed methodology is implemented on a numerical example to show its applicability.

A real-time data backup model and methods based on peer-to-peer network

Real–time backup data transmission over the internet can guarantee system availability using the self–organisation features of the internet during a disaster. We present a real–time disaster recovery backup model based on peer–to–peer (P2P) streaming with considering the reliability and security. The key metrics, which are recovery time objective (RTO), recovery point objective (RPO), and predicted channel delay of the P2P disaster recovery backup model, were analysed. Then the backup methods were described based on a P2P network, which consists of a node–joining mechanism, data sending and receiving mechanism, etc. To ensure transport channel redundancy, we designed a node conflict resolution algorithm. We also optimised the algorithm in terms of node distance, historical information, useless nodes traffic, etc. Finally, simulation experiments were conducted. Compared with a backup method using a leased line, the methods can avoid the conflict between fixed bandwidth and dynamic changes in backup data size and the single point of failure of a leased line.

Multi-site data distribution for disaster recovery—A planning framework

In this paper, we present DDP-DR: a Data Distribution Planner for Disaster Recovery. DDP-DR provides an optimal way of backing-up critical business data into data centers (DCs) across several Geographic locations. DDP-DR provides a plan for replication of backup data across potentially large number of data centers so that (i) the client data is recoverable in the event of catastrophic failure at one or more data centers (disaster recovery) and, (ii) the client data is replicated and distributed in an optimal way taking into consideration major business criteria such as cost of storage, protection level against site failures, and other business and operational parameters like recovery point objective (RPO), and recovery time objective (RTO). The planner uses Erasure Coding (EC) to divide and codify data chunks into fragments and distribute the fragments across DR sites or storage zones so that failure of one or more site / zone can be tolerated and data can be regenerated. We describe data distribution planning approaches for both single customer and multiple customer scenarios.

Optimal strategic decision for disaster recovery

Sustained data availability, accuracy, security, and updating of financial transactions are critical for banking business services. The significance of 24 × 365 hour service availability with accurate and secured data is the business comparative and competitive advantages. Choosing the right IT contingency planning (ITCP) for disaster recovery (DR) insures business continuity and optimizes banking investment. This research investigates the essential fundamental requirements of each banking business unit and concentrates the mapping of business criticality to DR readiness by assessing recovery time objective (RTO) and recovery point objective (RPO) to guarantee business continuity under a maximum tolerable period of disruption (MTPD). The DR strategy model proposed the optimization strategy for choosing the right pattern of disaster recovery solution for each business unit requirements with decision-making information supports.

Consequential Analysis of Information System Criticality in a Healthcare Organization

Implementation of information technology (IT) in healthcare has increased with little attention paid to the consequences of system failures. This qualitative study assesses the organizational understanding of IT vulnerabilities, the potential consequences of failure and system recovery capabilities within a large healthcare facility. Fifty nine percent (59%) of identified software applications were rated mission critical by participants, 46% were medium impact and 1 application was a non-factor. Downtime procedures were in place for only 39% of applications with 30% of those deemed “mission-critical” lacking downtime procedures. Expected recovery time objectives (RTO) and recovery point objectives (RPO) for users were not consistent with those projected by the IT department. A sub-analysis of the emergency department showed a high percentage of mission critical software but only 36% had downtime procedures. Continued inattention to the risks and hazards associated with widely disseminated IT within healthcare represents a continuing and little discussed vulnerability.

When disaster strikes, manage IT (disaster recovery)

IT people often end up wearing the disaster recovery hat, so they should ensure that robust DR management abilities are among their skillsets. Business continuity is a vast - even overwhelming - subject which mainly has been taken under the wing of the IT department. At its most basic level it encompasses everything involved in keeping a business up and running during a 'disaster' - or, depending on your business requirements, everything involved in getting the business operational within a set period of time after a disaster. This will help to determine what level of protection is required, and may help in determining some realistic recovery time objectives (RTOs) and recovery point objectives (RPOs).