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SMART SHIFT ADAPTIVE FLASH TECHNOLOGY

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SMART SHIFT ADAPTIVE FLASH TECHNOLOGY

ORDINARY APPLICATION

Published

date

Filed on 27 October 2024

Abstract

To increase performance and prolong battery life, Smart Shift Adaptive Flash is utilized in consumer electronics such as laptops, smartphones, and tablets. By optimizing data storage, it ensures optimum power usage and increases device responsiveness. As a result, apps run more smoothly and boot up faster. This technology is essential for managing massive information and high-intensity workloads in data centers and enterprise settings. It guarantees servers' long-term dependability, fast data access, and economical power consumption. Mission-critical applications that demand endurance and performance are supported by the technology. This adaptive flash technology is used by cloud service providers to effectively handle enormous volumes of data while lowering storage expenses. It guarantees dependability across dispersed cloud systems and speeds up data access times. It is therefore perfect for high-demand cloud storage services and virtualized systems. Adaptive flash technology improves loading times and lowers in-game latency on gaming consoles. It facilitates the management of sizable game files and offers speedier data access for processing in real time. In demanding gaming conditions, the technology guarantees improved performance and more fluid gameplay. The technology is utilized in IoT devices and automotive systems where dependable and quick data access is crucial. It drives linked IoT devices, sophisticated infotainment systems, and apps for autonomous driving. It is appropriate for crucial, data-driven automotive applications due to its improved dependability and efficient power consumption.

Patent Information

Application ID202441081907
Invention FieldCOMPUTER SCIENCE
Date of Application27/10/2024
Publication Number44/2024

Inventors

NameAddressCountryNationality
Dr. R. RaviProfessor, Department of Computer Science and Engineering, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. M. R. KaviyaIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. S. Lakshmi PooraniIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. M. C. Madhu VarshaIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. M. MaharajaIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. N. NithyashriIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627 003, Tamil Nadu, IndiaIndiaIndia
Ms. C. K. NivedhaIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. A. Renisha Julin KethsiaIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. G. SanthiyaIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. R. Seetha LakshmiIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. S. M. Shanmugha LakshmiIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. M. Shifana MariamIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. V. Siva ShanthiIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. J. SunmithalakshmiIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. P. Vel VignasennIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. S. VishnupriyaIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Ms. S. SabreenIIst year IT, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. R. S. Akaash AbishekIIst year MECH, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. S. E. VishwaaIIst year CS&BS, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. P. KarthickIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. P. Afran SyedIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. A. SubramanianIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. S. VigneshIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. S. AnwarIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia
Mr. A. John AmicsIIst year CSE, Cyberforensics Applied Lab Student, Francis Xavier Engineering College, Vannarpettai, Tirunelveli – 627003, Tamil Nadu, IndiaIndiaIndia

Applicants

NameAddressCountryNationality
FRANCIS XAVIER ENGINEERING COLLEGEVannarpettai, Tirunelveli - 627003, Tamil Nadu, IndiaIndiaIndia

Specification

Description:Field of invention:
The invention relates to data storage technologies, particularly adaptive memory systems and flash storage management. This technology aims to optimize non-volatile memory, such as flash memory, by dynamically adapting to changing data demands, ambient conditions, and performance requirements. It includes intelligent data management algorithms that adapt to changing usage patterns, power efficiency requirements, and performance expectations.
Objective of invention:
Smart Shift adaptable Flash Technology aims to provide an intelligent, adaptable memory management system that improves flash storage performance, durability, and power economy based on real-time data utilization and environmental conditions. It promises to improve performance by dynamically altering read/write speeds, reducing latency, and increasing memory longevity by intelligently dispersing wear among memory cells.
The technology also aims to enhance power efficiency by switching operations to low-power modes when high performance is not required, making it perfect for portable and embedded systems. It also prioritizes data quality through dynamic error correction and recovery operations while responding to various workload types, optimizing for a wide range of applications from consumer devices to enterprise storage. Scalability is another important consideration,
Ensuring that the technology can be used in a variety of businesses, from small devices to huge data centre Overall, the goal is to provide a smart, adaptable flash memory solution that strikes a balance between high performance, power efficiency, and long-term reliability.
Detailed description:
TempFlash Adaptive Technology addresses the requirement for adaptive heating systems in both domestic and commercial contexts by providing a state-of-the-art option for accurate and effective temperature control across a variety of applications.



Identified problem:
The issues mentioned for Smart Shift Adaptive Flash Technology focus around the difficulties that typical flash memory systems have in optimizing performance, power economy, and lifespan. Flash memory has a finite number of write/erase cycles, which causes premature degradation, particularly in high-write situations such as data centre and heavily used consumer devices. Furthermore, present systems frequently waste energy by failing to flexibly shift to low-demand conditions, which is especially troublesome for battery-powered devices. Flash memory performance can also vary due to changes in data access patterns or environmental factors like as temperature, which can reduce performance and raise the chance of data mistakes. Furthermore, many systems lack the ability to adapt to new applications, which limits their efficacy across industries. As a result, a more intelligent and adaptable approach to flash memory management is required to ensure consistent performance, lower power consumption, longer memory lifespan, and dependable data integrity over a wide range of operating situations and use cases.
Proposed Solution:
The proposed answer is the creation of Smart Shift Adaptive Flash Technology, a dynamic and intelligent memory management system that addresses the limitations of standard flash memory. This technology adjusts in real time to maximize flash memory performance, power consumption, and durability in response to workload demands, environmental conditions, and device-specific requirements.
Dynamic Performance Adjustment: The system analyses and modifies flash memory operations in real time, switching between high-performance and low-power modes based on the amount of data access. This allows for quicker read/write speeds during peak demand while conserving energy during periods of low activity.
Intelligent Wear-Leveling: To address flash memory's short lifespan, the technology employs advanced wear-leveling algorithms that distribute data equally across memory cells. This prevents localized wear and dramatically extends memory duration by minimizing load on individual cells.

Adaptive Power Management: By dynamically regulating power consumption based on workload and usage patterns, the system saves energy during idle periods while efficiently managing power-hungry processes. This makes it ideal for portable, battery-powered devices such as cellphones and IoT devices.
Error Detection and Correction: The technology includes powerful error detection and correction algorithms that dynamically adjust to the condition of the memory cells and environmental conditions, assuring data dependability even as the flash memory ages or functions in harsh settings.
Block diagram:


Block description 1:
The Smart Shift Adaptive Flash Technology comprises several interconnected components, each essential for optimizing flash memory performance and reliability. At its core is the Flash Memory Array, utilizing NAND and NOR flash chips for non-volatile data storage. NAND flash offers high density and speed, making it suitable for SSDs, while NOR flash enables quick access for embedded systems. The Microcontroller/Processor acts as the central control unit, executing adaptive algorithms and managing interactions with the flash memory based on real-time input from various components.





Product diagram :


Hardware setup:

Micro Controller:
Smart Shift Adaptive Flash Technology, typically used in flash storage solutions, focuses on optimizing data storage and retrieval performance through adaptive algorithms and efficient memory usage. Though hardware setups can vary depending on the specific application of the technology, a typical hardware configuration supporting such technology might involve the following components:
Processor (CPU):
A powerful multi-core CPU (such as AMD Ryzen or Intel Core i7) to manage the real-time decision-making algorithms and adaptive data processing.
Flash Memory (NAND Flash):
Single-level cell (SLC), multi-level cell (MLC), or triple-level cell (TLC) NAND flash technology are the three types of NAND flash chips. To optimize performance and longevity, the adaptive flash management algorithms modify the way data is written to various memory layers.
A common option for SSDs, 3D NAND Flash provides improved performance and durability because of its stacked construction.

Memory Controller:
A flash controller that controls memory cell wear leveling and data distribution. In order to modify the way data is written, read, and transferred between the various layers of flash memory, adaptive algorithms are frequently incorporated in this controller.
DRAM Cache:
By temporarily storing frequently accessed data, a DRAM module serves as a buffer/cache for read/write operations, enhancing performance.
By serving as a bridge between the CPU and the flash memory, the DRAM cache in SSDs typically enhances I/O speed and lowers latency.
Interface:
Compared to SATA, the PCIe/NVMe interface offers faster data transfer speeds. SSDs that make use of adaptive technology frequently include the PCIe interface.
Despite being slower than PCIe, the SATA interface is still utilized in legacy systems and more cost-conscious configurations.

Firmware/Software Layer:
Wear leveling, garbage collection, error correction code (ECC), and Smart Shift Adaptive Flash techniques are implemented by this firmware. These technologies optimize performance, provide error-free data storage, and dynamically manage data placement.
Cooling System:
Advanced cooling, including heat sinks or active cooling fans, may be necessary for high-performance systems that use Smart Shift Adaptive Flash Technology in order to disperse heat produced by high-speed processes.
The implementation of Smart Shift Adaptive Flash Technology, which improves the flash memory's longevity and performance, is made possible by this hardware configuration.
The implementation of Smart Shift Adaptive Flash Technology, which improves the flash memory's longevity and performance, is made possible by this hardware configuration.


Working model:


Software Setup:

Operating System Support:
Flash memory and sophisticated storage management must be supported by the operating system. Linux (such as Ubuntu and CentOS) is a popular option because of its adaptability and support for SSD and NVMe. Flash storage configurations for consumers and businesses also frequently employ Windows (e.g., Windows 10, Server). Flash storage optimizations are specific to macOS. Drivers are integrated into every operating system to effectively manage adaptive flash technology.
Firmware:
The flash memory controller's firmware is essential for data management and extending the device's life. In order to avoid early failure, it manages crucial functions including wear leveling, which distributes writes uniformly across memory cells. In order to improve write performance, garbage collection moves and erases data blocks, consolidating vacant space. Errors in data access are found and corrected by error correction codes (ECC). Additionally, firmware uses adaptive algorithms to dynamically balance endurance and performance.
Enhanced File Systems:
Performance is increased by selecting a file system made for flash storage. F2FS, which is optimized for flash memory in Linux, lessens wear and write amplification. Additionally popular are ext4 and Btrfs, the latter of which provides capabilities like data scrubbing and SSD RAID support. APFS, which is tailored for SSD storage and increases speed and efficiency, is used by macOS. NTFS and ReFS, which are used by Windows, can manage SSDs but might not be as well-suited for adaptive flash technology.
APIs and drivers:
To control how the OS and flash memory interact, drivers and APIs are necessary. Low-latency read/write operations are made possible by NVMe drivers, which give SSDs quick communication. Custom vendor drivers are used by certain systems to maximize the functionality of Smart Shift Adaptive Flash. Because they let the SSD know which blocks are no longer being used, TRIM/DISCARD operations are crucial for preserving flash storage performance. Higher-level software and developers can access sophisticated storage functions through APIs. For predictive maintenance, SMART monitoring monitors the condition of the gadget.
Tools for Management:
In order to track and improve SSD performance, manufacturers frequently offer proprietary management tools. Examples include Intel SSD Toolbox and Samsung Magician, which provide services including firmware updates, disk health monitoring, and performance diagnostics. Smartmontools and other open-source solutions enable Linux users to assess the SSD's health. The optimal operation of the Smart Shift algorithms and other adaptive technologies is guaranteed by these instruments. They also give users information about storage performance and data usage.
Monitoring Performance:
The effects of Smart Shift Adaptive Flash technology on system performance can be evaluated and optimized with the use of performance monitoring tools. I/O profilers that evaluate input/output performance and offer information on read/write speeds and latency include iostat and fio. It is possible to set up telemetry tools like Prometheus and Grafana to collect comprehensive data about SSD longevity, health, and usage. Dashboards for real-time monitoring show these insights. In order to effectively utilize the technology, monitoring aids in the identification of bottlenecks and the optimization of system setup.




Arrangement Setup: , Claims:1. By dynamically controlling data placement, Smart Shift Adaptive Flash Technology maximizes read/write processes. This makes it perfect for real-time applications since it lowers latency and speeds up data access. It guarantees the best possible responsiveness, particularly in settings with a lot of storage, such as databases and high-speed data processing.

2. By reducing needless write cycles and leveling wear, the technology prolongs the life of flash memory. It avoids early memory failure by dividing writes evenly among cells. It is perfect for crucial enterprise applications because of its adaptive algorithms and trash collection, which further improve durability.

3. The technique aids in power conservation by streamlining memory access and cutting down on pointless activities. It minimizes energy consumption during low-intensity operations by adjusting performance according to demand. This lowers power usage, prolongs battery life, and lowers data center energy expenses.

4. Proactive error management and enhanced data reliability error correction codes (ECC) guarantee that data is safe and undamaged. In order to prevent corruption, the system moves data from failing cells and keeps an eye on memory health. Long-term data reliability is ensured by early detection of possible faults using SMART monitoring.

5. This technology can be used in a variety of settings, ranging from huge enterprise systems to consumer gadgets. Both high-performance processes, such as database management and cloud storage, and low-intensity jobs can be handled by it. Because of its adaptability, it may be used in a wide range of applications, simplifying cross-platform storage solutions.

Documents

NameDate
202441081907-COMPLETE SPECIFICATION [27-10-2024(online)].pdf27/10/2024
202441081907-FORM 1 [27-10-2024(online)].pdf27/10/2024
202441081907-FORM-9 [27-10-2024(online)].pdf27/10/2024
202441081907-POWER OF AUTHORITY [27-10-2024(online)].pdf27/10/2024

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