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The job of the distribution grid planner has become more challenging in recent years. Three interrelated forces are contributing to this situation.

1. The proliferation of applications to connect distributed energy resources (DERs). From storage (behind/before the meter), rooftop solar, electric vehicle (EV) chargers, to the sensors and communication technologies that enable smart cities, we face unprecedented demands on the distribution grid. The interaction effects can be quite complex, and the feasibility of any DER must be examined carefully to maintain grid reliability. However, current approaches to feasibility studies have not scaled at the same pace as DER applications, creating a backlog that frustrates solution providers, their customers, and policymakers who wish to enable a grid that is resilient, green, accessible and cost-effective. This is a serious impediment to grid modernization and the roll-out of the Internet of Things at the city and national level.

2. Data. The fundamental inputs to DER feasibility studies include diverse sets of data such as geolocation information, asset type, circuit loads, traffic patterns, solar insulation patterns, and socio-demographic data. Some of these data are located within the governing organization, however most of these datasets are often not integrated or interoperable, either because of legacy formats and technologies, or as mandated by policy as a security measure (or some combination). The result is a fractured information landscape that requires the grid planner to access multiple databases in series. Even with fairly routine feasibility studies, the time to assemble data sets needed to begin an assessment can be prohibitive on the order of a day or more per project. Beyond this, there may be additional datasets that exist outside of the control of the grid planner that may be useful for current and future decision making. These data, mixed with distribution system operator (DSO) collected data, may offer valuable insights especially as interacting services become required, this comes with substantial risk and caveats.

3. Data security, data governance and privacy. Grid data is highly sensitive, and has been traditionally contained in specialized servers, most often on premises. Such data does not readily lend itself to comingling with outside sources, given security protocols and data policies. Furthermore, any data that could be used to infer personally identifiable information either directly or via derivative metadata, such as census data, maintenance personnel data, location or other kinds of behavioral information must be handled with appropriate privacy protocols. The general approach has been to have a bias against using additional datasets and related assessment algorithms given the high barrier to secure and safe data sharing. What this does is diminish the possibility to experiment with better assessment tools for current feasibility studies, or to look beyond such studies to develop data-driven predictions on how the grid should evolve. The issues of data governance are compounded by national and international privacy laws like the EUs GDPR, which set severe penalties on enterprises that violate personal data rights. This is fundamentally a digital rights management problem.

In response to these challenges, German utility innogy SE (which owns Westnetz, the largest DSO in Germany), created DigiKoo, an automated grid information access platform that gives DSOs and other customers the ability to easily and securely access and share data within their organizations and beyond. At the heart of DigiKoo are a set trusted intermediary web services that securely store and manage disparate data sets in a fashion that complies with national privacy and data management laws, consumer protection frameworks and enterprise policies that the respective dataset owners specify. DigiKoo does this by using Intertrust Modulus, a data rights management platform built by Intertrust Technologies Corp, innogys close partner. DigiKoo provides a trusted analytics framework on top of Modulus curated datasets that allows for private and secure computation that gives planners the ability to quickly assess future scenarios that may affect the grid.

At its core the DigiKoo platform combines data virtualization and data governance with machine learning and physics-based power flow models. In addition, it provides software developers with a rich data and technology ecosystem that enables them to develop solutions and applications without requiring accessing DSOs directly. This enable efficient and quick application development and a route to market.

Data virtualization refers to a data management process that copes with the various data formats, software and operating systems, the result of which provides an error-free, and consistent view of all underlying data. This is important when multiple legacy systems within a company need to be accessed, which are not readily compatible, or when attempting to access data across companies where such challenges could be even more pronounced.

Data governance, or governance, is the process of ensuring the right entities gain access to the right data in the right context. This is done within DigiKoo by creating and enforcing fine-grained digital rules for managing access to data based on polices that DigiKoo and its partners define or program in the system. Governance takes place in a protected processing environment that ensures that the rights management occurs in a secure and predictable way. DigiKoo implements data governance using the Intertrust Modulus platform, which provides rights management capabilities that allow fine grain data control of data items, implementation of privacy and data policy and blind-analysis of data sets. Modulus not only allows for context-specific data management, but also for multi-party data analysis in a way that protects the data in a manner consistent with the data owners wishes.

The DigiKoo analytics framework provides several standardized applications that includes a product that identifies the cost optimal installation location of private electric vehicle charging stations, using a combination of powerflow data, socioeconomic data and geo-locational data of garages. The German government has allocated US$1 billion of support to upgrade garage infrastructure and this application can help to allocate these subsidies. A solar and storage application identifies the potential for rooftop solar at the circuit-level, while providing the likelihood of growth patterns and related grid impacts based on affinity measures of distributed generation and other sources. From a data quality perspective, the DigiKoo platform can visualize on a map where existing technical documentation may be incorrect and offer how to correct such mistakes.

DigiKoo continues to experiment and build its offerings through pilot projects. However, the current results are promising: the average time to complete a feasibility study for various DERs has been reduced from an average of 10 hours to 5 minutes. As utilities around the world adopt data-driven technologies to enhance planning in a world of smart cities and progressively more connected infrastructure, tools like DigiKoo will become as essential as volt meters in grid planning; this is especially true in counties with strict privacy regimes and in places where competing utilities must collaborate to provide planners with common data-driven interfaces to do their jobs.

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Once-Reticent Utilities Accelerating Move to the Cloud - Transmission & Distribution World

Cisco Systems is losing two high-ranking executives as its former CIO as well as data center sales leader prepare to leave the company.

Guillermo Diaz Jr., Cisco's current senior vice president of customer transformation since February and former chief information officer since 2015, is leaving the company in February 2020, according to an internal email viewed first by The Information. Frank Palumbo, senior vice president of global data center sales, is also leaving.

A spokesperson for Cisco confirmed the planned departures to CRN on Friday. CRN has reached out to Palumbo for comment. Diaz referred comment back to Cisco.

[Related: AWS, Cisco Easing Pain Into The Cloud' With AWS Outposts Support, SD-WAN Tie-Ins]

Palumbo, Cisco's senior vice president of global data center sales, is reportedly joining Pensando Systems, an edge computing startup founded by ex-Cisco engineers and backed by former Cisco Chairman and CEO John Chambers, The Information reported on Friday. Palumbo worked at Cisco for 27 years.

Chambers ripped the sheet off Pensando Systems, his stealth software firm in October that develops hardware and software that lets companies run their servers more efficiently, particularly in the cloud. The company, which includes several high-profile ex-Cisco engineers such as Mario Mazzola, Prem Jain, Luca Cafiero and Soni Jiandani, is taking aim at AWS with its offerings.

Diaz, who has spent nearly two decades at Cisco, has been leading the firm's Customer Transformation business since he cleared out of the CIO seat in February. Cisco brought in Jacqueline Guichelaar, formerly chief information officer at Thomson Reuters, as its CIO in February.

The departures come on the heels of Cisco revealing plans to restructure several business units, including its cloud business and enterprise and data center networking segments to better position itself against competitors, the company said in an internal email in November.

Specifically, Cisco's enterprise networking and data center networking units are being combined. Cisco is also renaming its existing cloud computing business to Cloud Strategy and Compute and expanding the segment to include server products.

The San Jose, Calif.-based networking giant also reassigned several of its department leaders as a result of the restructure. Dave Ward, Cisco's chief technology officer of engineering and chief architect, is stepping down to take a new role inside the company. Roland Acra, senior vice president and general manager of Ciscos Data Center business unit, will be his replacement. The soon-to-be combined enterprise and data center networking unit will be led by Cisco's Senior Vice President and General Manager of enterprise networking, Scott Harrell. Liz Centoni, a 19-year Cisco veteran and current senior vice president and general manager of IoT for the tech giant, will now lead Cisco's new Cloud Strategy and Compute business unit. Cloud computing's former leader, Kip Compton, is moving to Ciscos Networking and Security Business group, Cisco said.

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Cisco Down Two Execs As One Reportedly Jumps To John Chambers-Backed Pensando - CRN: The Biggest Tech News For Partners And The IT Channel

Qualcomm generally uses its annual Snapdragon Tech Summit in Maui to unveil next-generation mobile processors and related technologies, which it accomplished with major new Snapdragon 865/765 and 3D Sonic Max dual-fingerprint scanner reveals today. But the bigger theme of the event is demonstrating real-world use cases for the companys new 5G AI chips that will drive consumer demand for next-generation smartphones and devices.

Even though 5G data services are still in their earliest days, uptake from OEMs, carriers, and consumers has already been encouraging stronger than 4G, by all accounts. Leading the events first-day keynote, Qualcomm president Cristiano Amon noted that over 230 5G devices are already either launched or in development, a staggering number given that networks are still in the process of launching worldwide. Nicki Palmer, chief product development officer for top U.S. carrier Verizon, said that the company is already selling seven 5G devices, whereas at the same time in 4Gs lifecycle, it offered only one.

Early real-world 5G use cases include considerably higher-resolution and faster streaming videos, cloud gaming, and facilitating next-generation user-created content, such as enhancing the presence of 3D imagery and high resolution 360-degree videos. Qualcomm also expects 5G will have a growing role in mixed reality experiences, including enabling virtual presence for teleconferencing and facilitating responsive augmented reality.

Going forward, Amon suggested that the separate domains of 5G and AI will be linked, noting that 5G cellular technologies will enable massive, low-latency data transfers between mobile devices and nearby edge cloud servers quantities and types of data that will require AI as a processing intermediary. Amonpredicted that 5G and AI will soon lead to a complete convergence of on-device apps with cloud services, effectively eliminating the present gap between a mobile devices own hardware and the computing resources it can marshal.

5G will bring to you a reliable, always-on connection to the cloud, he said, which can be trusted to expand persistently connected devices with virtually unlimited storage and on-demand cloud services. Rather than relying on the devices to supply the processing horsepower for apps, theyll draw significantly and seamlessly on cloud services distributed intelligence bringing about an age of intelligent cloud connectivity.

So far, the company is bullish on its 5G prospects, expecting to see 1.4 billion 5G smartphone shipments by 2022. Of course, the legwork to get devices into the marketplace is being undertaken by OEMs such as Motorola, Oppo, Xiaomi, and HMD/Nokia, each of which committed during the event to offering devices based on the new Snapdragon processors in 2020. While none of the companies offered specifics on its new devices, Xiaomi alone promised over 10 new 5G smartphones in the coming year. Qualcomm says that it has developed two- and three-chip modular platforms for its new Snapdragon offerings, and will offer OEMs similar options to spark the development of Snapdragon-based wearables and IoT devices.

Carriers will also be a major part of the picture, and uptake is positive so far. Amon said that the company expects 200 million 5G subscribers by the end of next year, and 2.8 billion 5G connections by 2025, aided by large numbers of network launches across the globe over the next two years. Without naming T-Mobile specifically, Amon embraced that companys forward-thinking strategy of combining low, medium, and high frequency spectrums to create blanket, true 5G, and performance 5G service layers, noting that carriers will use dynamic spectrum sharing to transition their networks from 4G to 5G while continuing to serve both types of users.

Verizons Palmer also highlighted the 5G R&D work currently being undertaken at its five separate 5G Labs, which she noted was focused on developing use cases and bolstering hundreds of companies with creative 5G ideas.She also claimed a new worlds first, saying that Verizon has just become the first carrier to offer 5G on a beach, regrettably underscoring the companys odd 5G launch strategy of covering only small segments of select cities with short-distance millimeter wave 5G towers. The company has promised to offer 5G data service in parts of 30 markets by the end of 2019, up from fewer than 20 plus some NFL stadiums today.

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Qualcomms Snapdragon Tech Summit focuses on 5G AI chips and use cases - VentureBeat

It is easy to be enticed by the features and flexibility of VMware Cloud on AWS, but it is also important to consider the migration challenges that come with a move from an on-premises data center to AWS.

VMware Cloud on AWS is a hybrid cloud service that can extend an enterprise's on-premises VMware environment to Amazon's public cloud. It was developed jointly by AWS and VMware, but VMware sells and operates the service. While a number of tools and scripts exist to help you move workloads to this service, a VMware-to-AWS migration is no simple task. Let's go through a few key VMware Cloud on AWS migration challenges and how you can work through them.

Before you start a VMware Cloud on AWS migration, understand that you won't accumulate cost savings overnight. Moving infrastructure and applications requires careful planning, so organizations should prepare for the costs and complexity accordingly. You'll also have to spend to keep dual environments running and staff working throughout the process.

To manage these costs, undertake traditional maintenance, such as cleaning up servers and handling OS and application patching, before a single workload moves offsite. Make a checklist and physically check off each server as it goes through the optimization process. This should also include rightsizing of both CPU and memory resources. While VMware Cloud on AWS resources can scale almost indefinitely, your budget cannot.

Network configurations are one of the first AWS migration challenges an enterprise will face, regardless of how deeply embedded a workload is in its existing architecture. IT teams should consider VMware Hybrid Cloud Extension (HCX) as a means to simplify this process.

HCX is a network migration toolset in VMware Cloud that starts with WAN optimization, compression and deduplication. Important for VM migration, HCX can stretch your Layer 2 networks for easier VM relocation. HCX also provides a few critical tools to save time and money. For example, HCX won't make you re-platform or change workload IP addresses -- a huge relief for application teams.

Bypassing the normal 250 Mbps bandwidth for live vMotion of a virtual machine -- to migration speeds closer to 100 Mbps -- helps users with slower internet connections. VMware HCX requires some additional network configuration steps to transition from one environment to another and accommodate the seamless transition, but the WAN optimization, Layer 2 stretching and other capabilities are huge advantages that can make up for those efforts.

Once your network framework is set, you'll need decide whether to do a forklift migration or a rebuild in the cloud. Both migration approaches have advantages and challenges in terms of cost, complexity and turnaround time.

If you choose to rebuild, you can keep your existing applications up and running while you replicate them in the cloud. A rebuild likely produces a smaller footprint in your cloud because it's optimized for that environment. You can remove legacy installations, update patching and have a fresh start in usage for a more stable, better performing platform. However, rebuilding takes a lot of time and work to complete. So, while the end result might be cleaner, the effort and costs involved could be prohibitive.

This leaves you with a forklift -- or lift and shift -- migration. Now, it could be a live vMotion migration or it could be a cold migration with minimal outages. The key here is you're not making changes to the workloads themselves. But, moving them as is into VMware Cloud on AWS would be a huge mistake.

Even though you have bought a cloud environment with multiple hosts and have all these resources dedicated to it, you still need to clean up and optimize your workloads before moving them into VMware Cloud on AWS, as you would any cloud platform. This includes the cleanup of server C drives of temporary files and systems from patch installations, along with runaway server profiles and downloads folders. If workloads are not cleaned up, you can easily double a server's storage footprint when it moves to the cloud.

In addition, you will still have to get the workloads into your VMware Cloud on AWS environment. Even VMware's HCX WAN optimization technology can't fix bad storage habits such as keeping installation ISO files and downloads on server desktops.

Regardless of the migration model you choose, incorrect sizing issues and other bad habits won't get magically fixed when you move workloads to VMware Cloud on AWS. Misconfigurations and excess files will ultimately cost more money if you don't address them upfront. You need to have as clean an environment as possible if you want a successful VMware Cloud on AWS migration.

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Overcome these VMware Cloud on AWS migration challenges - TechTarget

Bitcoin Ichimoku Analysis: When to buy Bitcoin? Today Im using the Ichimoku cloud analysis for BTC price Prediction to find out if NOW is a good time to buy Bitcoin. That is if you believe Bitcoin is the right asset to invest in and suits your unique risk tolerance.

Once youve watched the video, let me know what you about the Bitcoin price forecast. Are you investing in Bitcoin? Is now a good time to buy Bitcoin? Or would you rather wait or the BTC price to drop further?

I look at the markets based on my signatureInvest Diva Diamond Analysis (IDDA)and combine it with the Ichimoku Kinko Hyo strategy development technique including indications from theIchimoku cloud. The IDDA looks at investment strategies from 5 points: technicals, fundamentals, sentiment, capital, and overall.

Created by a pseudonymous developer (or developers) using the pseudonym Satoshi Nakamoto, Bitcoin gave birth to the multibillion-dollar cryptocurrency industry. The blockchain technology supports Bitcoin and the decentralization movement. Although many projects have tried to replicate Bitcoins success by creating coins that are far more scalable and advanced on the technological level, Bitcoin has remained the most dominant cryptocurrency on the market. Its main use-case has been shifting, though. People started to consider it as a store of value (digital gold) rather than a payment currency. And that is primarily due to its high domination, large liquidity, and generally lower volatility in relation to other cryptocurrencies.

There is still an ongoing debate in the space about whether Bitcoin should be considered a medium of exchange or a store of value. In its whitepaper Bitcoin was designed as a peer-to-peer version of electronic cash. The global cash market accounts for about $36.8 trillion of physical money and could increase to $90.4 trillion if we also include money held in easily accessible accounts. BTC is the native currency of Bitcoin the blockchain. Its main application within the ecosystem is to serve as a reward instrument for miners who are adding blocks to the blockchain. Miners are paid through a combination of Bitcoins block reward and transaction fees.

According to the Simetri research, as the number one cryptocurrency, Bitcoin continues to be the driving force behind the crypto economy. Its influence over the overall market is undeniable, while its prospects for development look promising. Its ecosystem is evolving, with many projects that enhance its functionality as well as scalability.

The Lightning Network alone has seen significant growth since the last year, in terms of both network capacity and merchant adoption. The interest from institutional investors also has been significant. The appearance of necessary infrastructure that will allow investment in Bitcoin through regulated and well-structured investment vehicles, will attract even more smart money into the crypto economy. Therefore it seems likely that Bitcoin can become a store of value asset, and attract institutional money into its ecosystem.

This will make bitcoin even more dominant in the crypto economy and will support and stabilize its value proposition. Due to its strong market position and overall ecosystem expansion, Bitcoin receives an A- from Semitri research:

BitcoinIchimoku cloudAnalysis indicates mixed signals across different time frames in terms of BTC price prediction. On one hand, on the daily chart, the BTC/USD pair has crossed below the Ichimoku cloud and testing to break below the 61% Fibonacci retracement level of 7,362. A break below this level could open doors for further drops towards the key support level of $6,000.

On the other hand, on the monthly chart, the pair is being supported by the monthly Ichimoku cloud. we wont know until January 2020 if this support is going to hold the pair from further drops.

So when is a good time to buy Bitcoin?

Watch the video to find out, and let me know what you think.

Disclaimer Trading in the financial markets involves a risk of loss and you should only trade the money you can afford to lose.

This article was originally published on InvestDiva.com.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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Bitcoin Ichimoku Cloud Analysis BTC Price Prediction When To Buy Bitcoin? - Nasdaq