APAC CIOOutlook
About UsConferencePartner With Us
  • Technologies
    • Blockchain
      Data Intelligence and Management
      Digital Transformation
      FinTech
      Generative and Agentic AI
      Low Code No Code
      Mobile Application
      Networking
      Robotics
      Storage
      Wireless
  • Industries
    • Automotive
      Aviation
      Banking
      Construction
      E-Commerce
      Food and Beverages
      Healthcare
      Insurance
      Logistics
      Manufacturing
      Retail
      Supply Chain
      Travel and Hospitality
  • Platforms
    • Microsoft
      Salesforce
      SAP
  • Strategic Solutions
    • Business Intelligence
      Contact Center
      Corporate Finance
      CRM
      Cyber Security
      Data Center
      Enterprise Asset Management
      Enterprise Performance Management
      IT Infrastructure and Services
      Managed Services
      Procurement
      Unified Communication
      Workflow
  • Home
  • CXO Insights
  • Leadership Perspectives
  • Innovation Insights
  • Research
  • News
  • Whitepapers
  • CXO Awards
#

Apac CIOOutlook Weekly Brief

×

Be first to read the latest tech news, Industry Leader's Insights, and CIO interviews of medium and large enterprises exclusively from Apac CIOOutlook

Subscribe

loading

THANK YOU FOR SUBSCRIBING

  • Home
  • News

Improving Cloud Data Recovery Techniques

The shift from knowledge loss to knowledge redundancy has been phenomenal since the advent of disk mirroring 35 years ago. 

By

Apac CIOOutlook | Thursday, January 01, 1970

The shift from knowledge loss to knowledge redundancy has been phenomenal since the advent of disk mirroring 35 years ago. The replicated state device (RSM) clusters popularized by cloud distributors prolonged this, and are increasingly being used these days. While RSMs working on main servers provide the same output with similar initial states and inputs, the availability of the outcome depends on the functionality of the servers. If the disk or server fails, recovering and mirroring the right data becomes a complicated process.

Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

Check This Out: Top Cloud Technology Companies

RSM uses several power knowledge constructions, like logs, snapshots and metadata to manage the data cluster, which is susceptible to errors like storage errors, firmware and driver bugs.  While storage faults are usually handled by crashing the node detecting checksum I/O errors, this technique protects data at the cost of availability—overlooking silent corruption and leading to data loss. Ramnatthan Algappan, in the February conference for Usenix FAST '18, introduced a new approach—corruption-tolerant replication (CTRL).

CTRL is comprised of two parts, a garage layer which detects faults and an allotted restoration protocol which recovers inaccurate knowledge from disused copies. Both these parts utilize RSM-specific wisdom to ensure data protection and availability by distinguishing between crashes and disk corruptions. A global-commitment resolution protocol splits the dedicated pieces, and a leader-initiated snapshotting sub-system provides identical snapshots throughout nodes to clarify and quicken restoration.

Researchers examining CTRL concluded that the garage layer added roughly 10 percent overhead cost for disks and around four percent for solid-state drives (SSD), while the log restoration time comes down from two days to roughly a millisecond. With the rising virtual civilization relying heavily on virtual knowledge, whose availability has improved within the last half-century, a lot still remains to be done. While saved knowledge develops, it becomes necessary to stay the prices of control and restoration—minimizing recovery time from corruption is an important step in this regard.

More in News

IoT and AI: The Key Technologies Transform Transport Management

AI and IoT have been transforming every industrial domain today. Be it manufacturing, communication, energy, defense or consumer products, AI and IoT have been steering the world to embrace digitalization at every step. Quite similarly, these two technologies have been also transforming transport management in many ways, some of which are listed below. The first application that needs mention is inventory and warehouse management. In this era of globalization, warehouses storing a particular firm’s inventory may not be located at a nearby site to the head office and managing incoming and outgoing goods might become difficult. An array of sensors at the warehouses connected to the firm’s TMS (Transport Management System) in combination with AI algorithms can provide a comprehensive overview of their inventory with complete data analysis. This would also minimize costs by automating mundane manual tasks. The next significant area that needs mention is order processing. Through on-site kiosks, order placing and acceptance can be seamlessly automated. Payments can also be transferred easily from anywhere and a firm can deploy AI solutions to have anaccurate viewof the financial and transactional workflows. The third and final aspect is logistics and shipping. Upon placing an order or receiving one, IoT sensors can provide real-time tracking of the goods shipped via any transport medium till they are delivered to the relevant customers. AI algorithms can provide key performance metrics at every step, point out the loopholes of the entire transport management process, and assist firms to improve their services manifolds. ...Read more

The Role of Big Data in Tourism Analytics

Big data has revamped operations and reshaped how businesses interact with consumers in the tourism and hospitality sectors. Big data analytics allows travel companies to process large volumes of information, derive actionable insights, and significantly improve service delivery. Big data is crucial in analyzing travel patterns, offering businesses valuable insights into traveler behaviors, preferences, and movement trends. Data from mobile devices, location services, and online travel searches enables tourism boards and travel agencies to derive actionable intelligence. By analyzing GPS and mobile data, businesses can identify popular destinations, monitor visitor flows, and assess seasonality in travel. Online reviews and interactions reveal customer preferences, allowing companies to tailor services accordingly. Additionally, AI-driven algorithms process user data to generate personalized itineraries, enhancing the overall travel experience. Powered by big data, predictive analytics is transforming the tourism industry by enabling real-time trend identification. Hotels, airlines, and tour operators leverage historical data to forecast demand spikes during peak seasons, festivals, and special events, allowing dynamic pricing adjustments. Social media analysis helps businesses identify emerging travel hotspots, creating opportunities for early market entry. Furthermore, big data supports health-related travel forecasting, as seen in pandemic tracking and decision-making during COVID-19. Enhancing customer experience is a significant benefit of big data in tourism. AI-driven tools analyze past booking behaviors, enabling businesses to offer personalized recommendations that boost customer satisfaction and engagement. Real-time feedback from review platforms helps companies quickly address operational inefficiencies. Furthermore, seamless travel experiences are facilitated through automated check-ins and AI-powered virtual assistants, ensuring efficient, hassle-free interactions. By incorporating big data analytics, the travel industry can not only enhance operational efficiency and service quality but also anticipate evolving consumer demands. Circlace , for instance, helps businesses integrate big data to refine customer journeys and streamline operations. As artificial intelligence and machine learning evolve, big data applications in the tourism industry are set to reach new heights. Some emerging trends are predictive and prescriptive analytics, real-time insights through IoT devices, and blockchain-enabled secure transactions. These advancements are expected to further enhance the tourism ecosystem by offering smarter, more sustainable, and highly efficient solutions. I-ESG provides solutions that leverage big data analytics to optimize sustainability efforts and enhance operational efficiency in the tourism industry. Big data is undeniably a key driver in transforming the tourism industry. From analyzing travel behaviors to personalizing customer experiences, it has streamlined operations and empowered businesses to make data-driven decisions. While challenges remain, the benefits outweigh the hurdles, and the future of tourism analytics, with big data at its core, is promising. ...Read more

Top Cyber Experts Gather in Kuala Lumpur for the AI & Cybersecurity Leaders Summit: ASEAN 2026

KUALA LUMPUR, Malaysia – As organisations across Southeast Asia rapidly adopt artificial intelligence to drive innovation, they simultaneously face an unprecedented wave of sophisticated, AI-driven cyber threats and ransomware. To address this critical inflection point, the AI & Cybersecurity Leaders Summit: ASEAN 2026 will take place on August 6, 2026 in Kuala Lumpur, Malaysia . Organised by Global Engage and supported by CyberSecurity Malaysia, this premier regional summit serves as Asia’s frontline defence strategy session. It brings together senior public and private sector leaders, Chief Information Security Officers (CISOs), and technology innovators to bridge the gaps in capability, talent and regional regulation. Key themes • The AI Double-Edged Sword: Weaponised LLMs, deepfakes, and building cyber resilience at machine speed • Emerging Risks & Opportunities: Navigating the 2026 threat horizon and securing vulnerable cloud architectures • Boardroom Management: Helping CISOs translate technical cyber risks into tangible financial impacts for executive boards • From Defence to Resilience: Redefining business continuity, operationalising recovery at scale, and driving digital trust • The Regional Blueprint: Navigating ASEAN data sovereignty laws, AI safety regulations, and executive accountability Featuring ASEAN’s Leading Cybersecurity Voices Attendees will gain exclusive insights from an elite lineup of regional experts and industry pioneers, including: • Suresh Sankaran Srinivasan – Group Head of Cyber Security and Data Privacy, Axiata Group Berhad (Malaysia) • Devki Gaurav Pal – Head of Cyber Security Operations, Lazada and Alibaba International Digital Commerce (Singapore) • Robert S. Paguia – Division Chief, Cybercrime Investigation and Coordination Centre (The Philippines) • Daniel Liu – Group CISO, Pacific Healthcare Group (Thailand) • Fazlan Abdullah – Head of Pre-Emptive Technology & Services Division, CyberSecurity Malaysia (Malaysia) • ...and many other influential CISOs and senior leaders from across the region. Website :  https://www.ai-cyberleaders.com/ ...Read more

Blockchain: Ensuring EHR Safety

The world is getting digitalized and so is every asset in it. Internet of Things (IoT) has helped the world evolve digitally and has certainly modernized healthcare. With healthcare being one of the most prioritized aspects of the global stage, it is quintessential to manage this industry with ease and versatility.  The evolution of digital data records has revolutionized the field of storing medical data that has aided the healthcare industry in many ways.  The digitalization of health care involves maintenance of EHRs (Electronic Health Records) which are generally stored in digital platforms, data centers and servers of the health care centers. These records aim at providing timely access to information to accelerate the fast recovery of patients. However, these records are vulnerable to breaches. According to a recent survey, about 72 percent of the employees are willing to share these confidential data tracks and many do not even know that this may cause security risks. It is advised to keep this data classified. Attackers often find ways to break through basic security protocols and cause an average annual loss of 6.2 billion dollars. To address this predicament, blockchains are implemented. Blockchains store data in the form of blocks and stack them one over the other cryptographically. This encrypts the data and keeps EHRs safe.  When blockchains are put to use, data is retained in the decentralized network of nodes and encrypted using AES256-GCM with a 256-bit key for every 128-bit block of data. The decentralized nature of the blockchain ensures data integrity as there is no single point of failure. A shared system is employed to store data, which lets the associated stakeholders access information smoothly and without any forced digital blockage. More research is being done to prevent EHRs from being breached. With a more reliable and secure way of storing data, it is only a matter of time before EHRs become absolutely impregnable.  ...Read more

I agree We use cookies on this website to enhance your user experience. By clicking any link on this page you are giving your consent for us to set cookies. More info

APAC CIOOutlook
Follow on LinkedIn

About

  • Home
  • About Us
  • Partner With Us

Stay Connected

  • Subscribe
  • Newsletter
  • Sitemap

Contact Us

  • editor@apacciooutlook.com
  • sales@apacciooutlook.com
  • marketing@apacciooutlook.com

Legal

  • Editorial Policy
  • Privacy Policy
  • Terms of Use

© 2026 APAC CIOOutlook. All rights reserved.

This content is copyright protected

However, if you would like to share the information in this article, you may use the link below:

https://www.apacciooutlook.com/news/improving-cloud-data-recovery-techniques-nwid-4996.html