Technology Trends predicted in 2020

IEEE Computer Society (IEEE CS) tech experts present what they believe will be the most widely adopted technology trends in 2020.

The topmost technology trends predicted to reach adoption in 2020 are:

  1. Non-volatile memory (NVM) products, interfaces and applications. 

The NVM Express (NVMe) describes it as “an open collection of standards and information to fully expose the benefits of nonvolatile memory in all types of computing environments from mobile to data center. NVMe is designed from the ground up to deliver high bandwidth and low latency storage access for current and future NVM technologies.”NVMe is an interface specification for connecting storage to servers via the PCI Express bus. In basic terms, it is a faster way for SSDs to communicate with their host systems. It helps to overcome the bottleneck that occurred when very fast flash was connected to systems via the SAS or SATA connections that were originally designed for HDDs (Hard disk drives).

 NVMe over Fabric connects SSDs to networks. NVM Express (NVMe) SSDs will replace SATA ( Serial ATA) and SAS SSDs within the next few years, and NVMe-oF(NVMe Over Fabrics )  will be the dominant network storage protocol in five years. Flash memories uses two technologies – NAND and NOR. Flash memory are used in modern PC and modems which can be easily updated when necessary. NOR flash provides high-speed random access, reading and writing data in specific memory locations; it can retrieve as little as a single byte. NAND flash reads and writes sequentially at high speed, handling data in small blocks, however it is slower on read when compared to NOR. NAND Flash Memory is widely used NVM. NVMe enables NAND tiering technologies and programming functions that increase endurance, enable computational storage, and allow more memory-like access to data.  Emerging memory technologies such as MRAM (Magnetic RAM), ReRAM (Resistive RAMs , RRAM, and Memristor being the most common name) and PCM (also called PRAM, Phase-Change Memory ) technology will provide future higher performance NVMe devices.
  • Digital twins, including cognitive twins. 

digital twin is a virtual model of a process, product or service. This pairing or bridging of the virtual and physical worlds allows analysis of data and monitoring of systems to avoid problems before they even occur, prevent downtime, develop new opportunities and even plan for the future by using simulations. Industry is using digital twins to deliver more accurate, intelligent and engaging interactions.They are an exact replica of something in the physical world. It provides data-driven representations of physical systems using IoT sensors and analytics. Digital twins offer engineers virtual tools for managing assets and resources while improving performance. Companies develop digital twins by attaching sensors to their products and equipment in order to monitor systems and model system dynamics. More than a blueprint or schematic, it  combines a real-time simulation of system dynamics with a set of executive controls. Serving as both an interactive simulation and a set of administrative tools, digital twins manage facilities, systems, and machines, while gathering data to drive performance.

Digital twins are data-driven learning systems.They combine data from human experts with machine intelligence to drive the evolution of work in new and unexplored ways. By detecting anomalies and automating repair processes, they can model and simulate entire procedures and processes. Most importantly, the technology enables firms to anticipate problems and prevent mistakes before they occur.Digital twins consist of three components: A data model , a set of analytics or algorithms and a set of executive controls. A key feature of any IoT implementation, this technology enables companies to simulate processes and improve operations over time. Manufacturers tend to use digital twin technology to improve operations such as plant processes and machine performance in order to optimize supply chains. Digital twins are a reality in the manufacturing industry, and major IoT platforms, like Siemens MindSphere, are supporting them. They have also become a widespread tool in complex system operations; railways and power plants have been used in cities since Jan 2019. Cognitive digital twins are in the early stages of trial and experimentation. In one example, a digital twin of an aircraft’s engine enables pilots to monitor the health of an engine in real time. Using digital twin technology to manage entire factories, companies like Siemens are simulating and testing systems at the level of individual machines. General Electric has built digital twins of jet engine components that predict their remaining life and the optimum maintenance intervals.

Summing up ….

NVMe (Non-volatile memory Express) is an interface specification for connecting storage to servers via the PCI Express bus. In basic terms, it is a faster way for SSDs to communicate with their host systems. It helps to overcome the bottleneck that occurred when very fast flash was connected to systems via the SAS or SATA connections that were originally designed for HDDs (Hard disk drives). NVMe over Fabric(NVMe-oF) connects SSDs to networks. A digital twin is a virtual model of a process, product or service.They are data driven learning systems.

Kindly refer the below link to know further :

https://www.enterprisestorageforum.com/storage-hardware/nvme-5-key-facts-about-nonvolatile-memory-express.html