Welcome!

Java Authors: Pat Romanski, Yeshim Deniz, Liz McMillan, Carmen Gonzalez, Yakov Fain

Related Topics: Java

Java: Article

Java Programming: The Java Async IO Package

Fast, scalable IO for sockets and files

The Async IO package is designed to provide fast and scalable input/output (IO) for Java applications using sockets and files. It provides an alternative to the original synchronous IO classes available in the java.io and java.net packages, where scalability is limited by the inherent "one thread per IO object" design. It also provides an alternative to the New IO package (java.nio), where performance and scalability are limited by the polling design of the select() method.

As its name implies, the Async IO package provides asynchronous IO operations, where the application requests an IO operation from the system, the operation is executed by the system asynchronously from the application, and the system then informs the application when the operation is complete. The Async IO package supports a number of styles of application programming and gives the application designer considerable freedom in the management of the number of threads used to handle IO operations and also in the design of the components that handle the asynchronous notifications.

Why Java Applications Need the Async IO Package
The question "Why do Java applications need the Async IO package?" can be answered in two words: performance and scalability.

Performance and scalability are key attributes of the IO system for IO-intensive applications. IO-intensive applications are typically, although not exclusively, server-side applications. Server-side applications are characterized by the need to handle many network connections to many clients and also by the need to access many files to serve requests from those clients. The existing standard Java facilities for handling network connections and files do not serve the needs of server-side applications adequately. The java.io and java.net packages provide synchronous IO capabilities, which require a one-thread-per-IO-connection style of design, which limits scalability since running thousands of threads on a server imposes significant overhead on the operating system. The New IO package, java.nio, addresses the scalability issue of the one-thread-per-IO-connection design, but the New IO select() mechanism limits performance.

Current operating systems, such as Windows, AIX and Linux, provide facilities for fast, scalable IO based on the use of asynchronous notifications of IO operations taking place in the operating system layers. For example, Windows and AIX have IO Completion Ports, while Linux has the sys_epoll facility. The Async IO package aims to make these fast and scalable IO facilities available to Java applications through a package that provides IO capabilities linked to an asynchronous style of programming.

The current version of the Async IO package, com.ibm.io.async, is designed as an extension to the Java 2 Standard Edition 1.4, which can in principle be provided on any hardware and software platform. The platforms currently supported by the package include Windows, AIX, Linux, and Solaris.

Elements of the Async IO Package
The major elements of the Async IO package are the classes AsyncFileChannel, AsyncSocketChannel, and AsyncServerSocketChannel. The channels represent asynchronous versions of files, sockets, and server sockets. These fundamental classes are designed to be similar in naming and in operation to the channel classes of the New IO package. Good news for Java programmers familiar with the New IO package.

AsyncFileChannels and AsyncSocketChannels provide asynchronous read and write methods against the underlying file or socket. An asynchronous operation is a request to the system to perform the operation, where the method returns immediately to the calling application regardless of whether the operation has taken place or not. Instead of providing a return value that gives information about the operation, such as the number of bytes read/written, asynchronous read and write operations return objects that implement the IAsyncFuture interface.

The IAsyncFuture interface is another important component of the Async IO package. First an IAsyncFuture represents the state of the asynchronous operation - most important, whether the operation has completed or not. Second, the IAsyncFuture provides methods that return the result of the operation once it has completed. An IAsyncFuture can throw exceptions as well as the normal outcome of the operation, if something goes wrong during the operation.

The application uses one of three methods to find out whether a particular operation has completed:

  • Polling: Calls the isCompleted() method of the IAsyncFuture, which returns true once the operation is complete
  • Blocking: Uses the waitForCompletion() method of the IAsyncFuture, which can be used either to wait for a specified period or to wait indefinitely for the operation to complete
  • Callback: Uses the addCompletionListener() method of the IAsyncFuture, so the application can register a method that's called back by the system when the operation completes
Which method an application uses to find out about the completion of an operation is driven by the overall design of the application, although the most truly "asynchronous" designs would tend to use the callback method. If an application uses the callback method, the thread that requests the IO operation carries on to do more work, while the callback is normally handled on a separate thread.

Data Formats Supported by Asynchronous Read and Write Operations
The read and write operations supplied by the Async IO package use the ByteBuffer class to hold the data. This class is the same as the one used in the New IO package. One difference between the Async IO package and the New IO package is that the ByteBuffers used for the Async IO package must be Direct ByteBuffers. Direct ByteBuffers have the memory for their content allocated in native memory outside the Java Heap. This provides better performance for IO operations since the operating system code can access the data in the buffer memory directly, without the need for copying.

ByteBuffers can be viewed as buffers supporting other primitive types, such as Int, Float, or Char, using methods such as bytebuffer.asIntBuffer(). ByteBuffers also have a series of methods that support the reading and writing of primitive types at arbitrary locations in the ByteBuffer using methods like bytebuffer.putLong( index, aLong).

Simple Examples of Async IO Read and Write Operations
Listing 1 shows the use of an AsyncSocketChannel as a client socket that involves connecting the socket to a remote server and then performing a read operation. In this example, the blocking style is used to wait for asynchronous operations to complete.

Listing 2 is a program fragment that shows the use of a callback to receive the notification of the completion of an asynchronous operation. This fragment shows just some of the methods of a class that is handling socket IO. It's assumed that an AsyncSocketChannel has already been opened and connected, that a direct ByteBuffer is available, and that an object named "state" tracks the state of the IO.

When the IO operation is requested (channel.read( ... )) an IAsyncFuture is returned. The next step is to give the IAsyncFuture a callback method by calling the addCompletionListener( ... ) method. The callback method gets called when the operation completes. The callback method is the futureCompleted( ... ) method that forms part of a class that implements the ICompletionListener interface.

In this example, the class with the callback is the same as the class that makes the read request (so "this" is used as the first parameter in the addCompletionListener method). The signature of the futureCompleted ( ... ) method is fixed: its parameters are an IAsyncFuture object that represents the operation and, second, an object that holds the application state, which is associated with the IAsync-Future through the addCompletion-Listener( ... ) method where it forms the second parameter (in this example, we use the object called "state").

The futureCompleted( ... ) method is called when the operation completes. It is possible that the operation is complete before the completion listener is added to the future. If this happens, the futureCompleted( ... ) method is called directly from the addCompletionListener( ... ) method, without any delay.

The futureCompleted( ... ) method receives the future object relating to the completed operation, plus the application state object.

Beyond the Basics: Multi Read/Write Operations and Timeouts
The previous sections described the basic functions available as part of the Java Async IO package. The package also supplies more advanced interfaces for asynchronous IO. The first advanced interface supplies the capability to perform read and write operations using multiple buffers for the data. The second advanced interface provides a time-out on the asynchronous IO operation.

Both the multi read/write operations and the time-out facility are provided by the AsyncSocketChannelHelper and AsyncFileChannelHelper classes. This is done to keep the interface to the Async-FileChannel and AsyncSocketChannel classes as straightforward as possible.

Create an AsyncSocketChannelHelper object by wrapping an existing AsyncSocketChannel. An AsyncFileChannelHelper is created by wrapping an existing AsyncFileChannel object. All operations on the channel helper object apply to the underlying asynchronous channel.

The multi read/write operations take ByteBuffer arrays as input and return IAsyncMultiFuture objects. IAsyncMultiFuture objects differ from IAsyncFuture objects only in that they have a getBuffers() method that returns the ByteBuffer arrays involved in the operation in place of the getBuffer() method, which relates to the single buffer read/write operations. The multi read/write operations are useful for applications that need to send or receive data that's best handled by multiple buffers, perhaps where different elements of the data are handled by different application components (see Listing 3).

The time-out operations provided by the AsyncSocketChannelHelper and AsyncFileChannelHelper classes are versions of the basic read and write operations that have a time-out period applied to them. The basic read and write operations of asynchronous channels can in principle take forever to complete. This is particularly a problem for an application that uses the callback technique to get notified that the operation is complete, since the callback might never get called if the operation does not complete. The use of the time-out versions of the operations guarantees that the IAsyncFuture will complete when the time-out expires, even if the underlying read/write operation does not complete. If the time-out expires, the IAsyncFuture completes with an AsyncTimeoutException. In addition, the underlying operation is cancelled (equivalent to invoking the IAsyncFuture cancel(future) method).

Note that using the time-out versions of read and write are different from using the IAsyncFuture waitForCompletion( timeout ) method (see Listing 4). waitForCompletion provides a time-out for the wait on the completion of the IAsyncFuture. If this time-out expires, control is returned to the application, but the IAsyncFuture is not completed and the underlying read/write operation is still underway. By contrast, if the time-out expires on the AsyncChannelHelper read/write methods, the IAsyncFuture is completed (with an AsyncTimeoutException) and the underlying operation is cancelled.

An important point about operations that time out is that the state of the channel is left indeterminate. Once an operation is cancelled, it's unlikely that the channel can be used again and the safe option is for the application to close the channel.

Asynchronous IO Thread Management
If you write an application program that uses the callback method to get notifications that asynchronous IO operations have completed, you need to understand which Java threads are used to run the callbacks. The threads used to run the callbacks will run application code. If your application code needs the threads to have any special characteristics, such as specific context information or security settings, this could cause problems for your application code unless your application carefully controls the actual threads that are used to run the callbacks.

The threading design of the Async IO package is outlined in Figure 1. Applications make requests to the package for Async IO operations. The requests are passed to the operating system's IO functions. When the operations complete, notifications of their completion are passed back to the Async IO package and are initially held in an IO Completion Queue. The Async IO package has a set of one or more Java threads that it uses to process the notifications in the IO Completion Queue. Notifications are taken from the Completion Queue, and the IAsyncFuture related to the operation is marked as completed. If a Callback Listener has been registered on the IAsyncFuture, the Callback Listener method is called. Once the CallBack Listener method finishes, the thread returns to the Async IO package and is used to process other notifications from the Completion Queue.

By default, the Async IO package uses its own Result Thread Manager to manage the threads that handle the callbacks. It allocates a number of threads, typically equal to the number of processors on the system. These threads are vanilla Java threads with no special characteristics. However, the application can control the threads in one of two ways.

The application can override the default Result Thread Manager by calling the setResultThreadManager(IResult-ThreadManager) method of the Abstract- AsyncChannel class. The application must supply its own manager class that implements the IResultThreadManager interface, which defines the full life cycle for threads used by the Async IO package. The IResultThreadManager interface provides control over the policies applied to the result threads, including the timing of creation and destruction, the minimum and maximum numbers of threads, plus the technique used for creation and destruction of the threads.

Alternatively, the application can use the default IResultThreadManager implementation provided by the Async IO package, but control the nature of the threads used to handle results and callbacks. This is done by supplying the default IResultThreadManager implementation with an application-defined IThreadPool object, by calling the set-ThreadPool( IThreadPool ) method on the IResultThreadManager. This allows the application to control the nature of the threads used in the Result Thread Manager. For example, application data can be attached to the thread or specific security settings applied to the thread, or the threads used in the IResultThreadManager can be cached by the IThreadPool.

Performance
Performance is one of the important reasons for using the Async IO package. How does its performance stack up against the original synchronous Java IO and also against the New IO package?

Performance is a complex issue, but a simple test provides some guidance. The test uses Socket IO with multiple clients communicating with a single server. Each client performs repeated operations, writing 256 bytes to the server and reading a 2,048 byte response from the server. For the test, the clients are always the same code, but three variations of the server code are used:

  • Synchronous Server, using the original Java IO classes
  • New IO Server, using the New IO classes
  • Asynchronous IO Server, using the Async IO package
The server code is as similar as possible, but the differences implied by the different programming models of the IO packages are built into the code. Most notably, the threading design of the Synchronous Server is one-thread-per-client, while the number of threads used for the New IO and Asynchronous Server is determined by the number of processors on the server system and is much smaller than the number of clients. An important feature of the server code is that the caches of the common objects used by the server code are used as much as possible - notably the ByteBuffers (in all three cases) and the threads (in the case of the Sync Server). This is done to reduce the startup times as much as possible for each socket; this reflects a common practice for typical server designs.

We ran the tests with a Windows 2000 single processor server system and a Windows Server 2003 four-way system running the clients, connected via a 100Mb Ethernet network, with varying numbers of client sockets each performing a connect followed by 50 read/write cycles with the server. The results are shown in Table 1, which provides the data for the average time in microseconds to complete each read/write cycle, quoted with and without the startup time included. The startup time is the time taken for the client socket to connect to the server before any data is transmitted.

(If you're surprised that the four-way server system is used to drive the client side for this test, it's used to ensure that the very large number of clients can be created successfully.)

The last two cases involve running with a number of inactive client sockets, which are connected to the server but are not transmitting any data during the test. This is more typical of a real Web server. These inactive sockets are a load for the server to handle alongside the active sockets.

This shows the Async IO, New IO, and Sync servers are all similar in terms of average times in lightly loaded situations. The failure of the Sync server to handle the case of 7,000 total clients shows its limitations in terms of scalability. The figures for the New IO server show that the performance suffers as the number of clients rise. In particular the New IO server shows a marked rise in the overhead for starting up new connections as the number of connections rises. The Async IO server manages to achieve reasonably stable performance right through the range tested, both for startup time and for the read/write cycle time.

These simple tests show that the Async IO package is able to deliver on its promise of performance and scalability and can form part of the solution for server applications intended to handle many thousands of clients.

Pitfalls to Avoid
As with the use of any API, there are some aspects of the Async IO API that you need to think about to avoid problems.

You need to be careful with the use of the ByteBuffers that are used in the read and write methods of asynchronous channels. Because the IO operations occur asynchronously, there is the potential for the Async IO package to use the ByteBuffers at the same time as the application code. The rule to follow in order to avoid trouble is that the application code should not access the ByteBuffers from the time that an asynchronous read or write operation is requested until the point that the Async IO package signals that the operation is complete. Any attempt by the application to access the ByteBuffers before the operation is complete could cause unpredictable results.

Asynchronous channels provide facilities for the cancellation of asynchronous IO operations. These include the explicit cancel() method available on the futures returned by operations on asynchronous channels, and also the implicit cancellation that takes place as part of the time-out of an IO operation on an AsyncSocketChannelHelper or AsyncFileChannelHelper. If an operation is cancelled, the under-lying channel (file or socket) is left in an indeterminate state. Because of this, your application should not attempt to perform any more operations on the channel once cancellation has occurred. The best thing to do is to close the channel as soon as possible.

The performance of read and write operations using Async IO is designed to be as close as possible to the performance of equivalent synchronous IO operations. However, there is some extra overhead involved in running an asynchronous operation compared with a synchronous operation, associated with setting up and executing the asynchronous notifications. The implication of this is that asynchronous reads and writes involving very small packets of data (i.e., a few bytes only) are going to have a significantly higher overhead than synchronous equivalents. You should take this into account when designing your application to use Async IO.

Summary
The Java Async IO package provides valuable facilities for fast, scalable Socket and File IO, which are an alternative to the use of java.io and java.nio facilities in client-side and server-side applications. The package also assists the program design by providing an event-driven interface for IO operations that is simple to use.

Resources

  • The C10K Problem Page contains a comprehensive discussion of the need for fast, scalable IO for servers and the facilities available to provide this on various systems: www.kegel.com/c10k.html
  • Pattern-Oriented Software Architecture: www.cs.wustl.edu/~schmidt/POSA/
  • New IO APIs have a full description of the standard Java New IO package: http://java.sun.com/j2se/1.4.2/docs/guide/nio/index.html
  • Download the Async IO package to try out in your applications: www.alphaworks.ibm.com/tech/aio4j
  • More Stories By Mike Edwards

    Dr. Mike Edwards is a strategic planner in the IBM Java Technologies group in Hursley, England. He is responsible for technical planning for future IBM products including the IBM Java SDKs and for Web services–related products. Before working on Async IO, Mike was involved in the planning of Java SDK 1.4.0 and was a member of the Expert Group for JSR 059, which defined the specification for J2SE 1.4.0 and JSR 051, which created the New IO package. Mike received his PhD in Elementary Particle Physics from Birmingham University.

    More Stories By Tim Ellison

    Tim Ellison is a senior software engineer and strategic planner in the emerging technologies team at IBM Hursley Java Technologies group. He has contributed to the implementation of Smalltalk, IBM VisualAge Micro Edition, Eclipse, and the Java SDK over a period of 20 years. His interests are in new ways to apply object technology to difficult problems.

    Comments (7) View Comments

    Share your thoughts on this story.

    Add your comment
    You must be signed in to add a comment. Sign-in | Register

    In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


    Most Recent Comments
    Mike Edwards 10/26/04 10:55:01 AM EDT

    Paul,

    Please email me directly if you would like to discuss your question about NIO in more detail - I'd prefer to keep this discussion thread dedicated to Async IO.

    Yours, Mike.

    Paul 10/25/04 10:38:17 AM EDT

    Mike:

    Your article is great! I used NIO for a socket server, could you help me out a qustion?

    NIO send message by Byte between client and server, I got many samples with it to delever string message acting as HTTP server. HOw can I deliver and parse the message wrapped in an object instead of only string? could you give me some clues or any samples?

    Regards,

    Thanks you very much.

    Paul

    [email protected]

    Mike Edwards 10/25/04 08:27:39 AM EDT

    Bret,

    Your question about why NIO performs less well than the original synchronous IO is an interesting one.

    Fundamentally, NIO is less about performance and more about scalability. Synchronous IO demands one thread per socket and most operating systems limit the number of threads. New IO allows many sockets per thread and so allows a much greater number of sockets per application. The figures in our article show this lack of scalability of synchronous IO.

    In terms of performance, New IO has to do the same read and write calls to the operating system that are done by synchronous IO. However, New IO requires the use of the Selector and the management of the key sets - this is an overhead. Synchronous IO by contrast has the overhead of thread switching between the many threads. At low numbers of sockets, the difference in the overheads is not significant, except that the setup time for putting a new channel into the Selector makes New IO slower to add a new channel (note: our code caches the threads used by synchronous IO). At high number of sockets, the time to insert a channel into the Selector climbs as does the time to do the Select operation, due to the data structures used to hold the select list. Thread switch time does not increase as much - so making New IO performance look worse at high numbers of sockets.

    We shall look to make our performance test code available on the AIO4J site, so that you can take a look at how the server code compares between Sync IO, New IO and AIO4J.

    Yours, Mike.

    Bret Hansen 10/23/04 12:17:20 PM EDT

    So your test shows that the nio package is slower than the original synchronous API.

    Can you explain why? I haven't looked at your code yet.

    Bret

    Mike Edwards 10/13/04 03:11:59 AM EDT

    Csaba,
    Glad that you were able to find the tables & images. The online version of the article is not laid out anywhere near as well as the "original" article in the print version - which you can see if you get the PDF download of the October JDJ.

    Yours, Mike.

    Csaba 10/12/04 05:12:32 AM EDT

    Nevermind, found it...

    Csaba 10/12/04 05:10:31 AM EDT

    Where are the tables/images for this article ? I was really interested in that comparison chart, but couldn't find the link...

    @ThingsExpo Stories
    SYS-CON Events announced today that Red Hat, the world's leading provider of open source solutions, will exhibit at Internet of @ThingsExpo, which will take place on November 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA. Red Hat is the world's leading provider of open source software solutions, using a community-powered approach to reliable and high-performing cloud, Linux, middleware, storage and virtualization technologies. Red Hat also offers award-winning support, training, and consulting services. As the connective hub in a global network of enterprises, partners, a...
    SYS-CON Events announced today that Matrix.org has been named “Silver Sponsor” of Internet of @ThingsExpo, which will take place on November 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA. Matrix is an ambitious new open standard for open, distributed, real-time communication over IP. It defines a new approach for interoperable Instant Messaging and VoIP based on pragmatic HTTP APIs and WebRTC, and provides open source reference implementations to showcase and bootstrap the new standard. Our focus is on simplicity, security, and supporting the fullest feature set.

    SUNNYVALE, Calif., Oct. 20, 2014 /PRNewswire/ -- Spansion Inc. (NYSE: CODE), a global leader in embedded systems, today added 96 new products to the Spansion® FM4 Family of flexible microcontrollers (MCUs). Based on the ARM® Cortex®-M4F core, the new MCUs boast a 200 MHz operating frequency and support a diverse set of on-chip peripherals for enhanced human machine interfaces (HMIs) and machine-to-machine (M2M) communications. The rich set of periphera...

    Predicted by Gartner to add $1.9 trillion to the global economy by 2020, the Internet of Everything (IoE) is based on the idea that devices, systems and services will connect in simple, transparent ways, enabling seamless interactions among devices across brands and sectors. As this vision unfolds, it is clear that no single company can accomplish the level of interoperability required to support the horizontal aspects of the IoE. The AllSeen Alliance, announced in December 2013, was formed with the goal to advance IoE adoption and innovation in the connected home, healthcare, education, aut...
    The Internet of Things (IoT) is making everything it touches smarter – smart devices, smart cars and smart cities. And lucky us, we’re just beginning to reap the benefits as we work toward a networked society. However, this technology-driven innovation is impacting more than just individuals. The IoT has an environmental impact as well, which brings us to the theme of this month’s #IoTuesday Twitter chat. The ability to remove inefficiencies through connected objects is driving change throughout every sector, including waste management. BigBelly Solar, located just outside of Boston, is trans...
    The only place to be June 9-11 is Cloud Expo & @ThingsExpo 2015 East at the Javits Center in New York City. Join us there as delegates from all over the world come to listen to and engage with speakers & sponsors from the leading Cloud Computing, IoT & Big Data companies. Cloud Expo & @ThingsExpo are the leading events covering the booming market of Cloud Computing, IoT & Big Data for the enterprise. Speakers from all over the world will be hand-picked for their ability to explore the economic strategies that utility/cloud computing provides. Whether public, private, or in a hybrid form, clo...
    Software AG helps organizations transform into Digital Enterprises, so they can differentiate from competitors and better engage customers, partners and employees. Using the Software AG Suite, companies can close the gap between business and IT to create digital systems of differentiation that drive front-line agility. We offer four on-ramps to the Digital Enterprise: alignment through collaborative process analysis; transformation through portfolio management; agility through process automation and integration; and visibility through intelligent business operations and big data.
    The Transparent Cloud-computing Consortium (abbreviation: T-Cloud Consortium) will conduct research activities into changes in the computing model as a result of collaboration between "device" and "cloud" and the creation of new value and markets through organic data processing High speed and high quality networks, and dramatic improvements in computer processing capabilities, have greatly changed the nature of applications and made the storing and processing of data on the network commonplace.
    Be Among the First 100 to Attend & Receive a Smart Beacon. The Physical Web is an open web project within the Chrome team at Google. Scott Jenson leads a team that is working to leverage the scalability and openness of the web to talk to smart devices. The Physical Web uses bluetooth low energy beacons to broadcast an URL wirelessly using an open protocol. Nearby devices can find all URLs in the room, rank them and let the user pick one from a list. Each device is, in effect, a gateway to a web page. This unlocks entirely new use cases so devices can offer tiny bits of information or simple i...
    Things are being built upon cloud foundations to transform organizations. This CEO Power Panel at 15th Cloud Expo, moderated by Roger Strukhoff, Cloud Expo and @ThingsExpo conference chair, will address the big issues involving these technologies and, more important, the results they will achieve. How important are public, private, and hybrid cloud to the enterprise? How does one define Big Data? And how is the IoT tying all this together?
    The Internet of Things (IoT) is going to require a new way of thinking and of developing software for speed, security and innovation. This requires IT leaders to balance business as usual while anticipating for the next market and technology trends. Cloud provides the right IT asset portfolio to help today’s IT leaders manage the old and prepare for the new. Today the cloud conversation is evolving from private and public to hybrid. This session will provide use cases and insights to reinforce the value of the network in helping organizations to maximize their company’s cloud experience.
    TechCrunch reported that "Berlin-based relayr, maker of the WunderBar, an Internet of Things (IoT) hardware dev kit which resembles a chunky chocolate bar, has closed a $2.3 million seed round, from unnamed U.S. and Switzerland-based investors. The startup had previously raised a €250,000 friend and family round, and had been on track to close a €500,000 seed earlier this year — but received a higher funding offer from a different set of investors, which is the $2.3M round it’s reporting."
    The Industrial Internet revolution is now underway, enabled by connected machines and billions of devices that communicate and collaborate. The massive amounts of Big Data requiring real-time analysis is flooding legacy IT systems and giving way to cloud environments that can handle the unpredictable workloads. Yet many barriers remain until we can fully realize the opportunities and benefits from the convergence of machines and devices with Big Data and the cloud, including interoperability, data security and privacy.
    All major researchers estimate there will be tens of billions devices - computers, smartphones, tablets, and sensors - connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. Over the summer Gartner released its much anticipated annual Hype Cycle report and the big news is that Internet of Things has now replaced Big Data as the most hyped technology. Indeed, we're hearing more and more about this fascinating new technological paradigm. Every other IT news item seems to be about IoT and its implications on the future of digital busines...
    Cultural, regulatory, environmental, political and economic (CREPE) conditions over the past decade are creating cross-industry solution spaces that require processes and technologies from both the Internet of Things (IoT), and Data Management and Analytics (DMA). These solution spaces are evolving into Sensor Analytics Ecosystems (SAE) that represent significant new opportunities for organizations of all types. Public Utilities throughout the world, providing electricity, natural gas and water, are pursuing SmartGrid initiatives that represent one of the more mature examples of SAE. We have s...
    The Internet of Things needs an entirely new security model, or does it? Can we save some old and tested controls for the latest emerging and different technology environments? In his session at Internet of @ThingsExpo, Davi Ottenheimer, EMC Senior Director of Trust, will review hands-on lessons with IoT devices and reveal privacy options and a new risk balance you might not expect.
    IoT is still a vague buzzword for many people. In his session at Internet of @ThingsExpo, Mike Kavis, Vice President & Principal Cloud Architect at Cloud Technology Partners, will discuss the business value of IoT that goes far beyond the general public's perception that IoT is all about wearables and home consumer services. The presentation will also discuss how IoT is perceived by investors and how venture capitalist access this space. Other topics to discuss are barriers to success, what is new, what is old, and what the future may hold.
    Swiss innovators dizmo Inc. launches its ground-breaking software, which turns any digital surface into an immersive platform. The dizmo platform seamlessly connects digital and physical objects in the home and at the workplace. Dizmo breaks down traditional boundaries between device, operating systems, apps and software, transforming the way users work, play and live. It supports orchestration and collaboration in an unparalleled way enabling any data to instantaneously be accessed on any surface, anywhere and made interactive. Dizmo brings fantasies as seen in Sci-fi movies such as Iro...
    There’s Big Data, then there’s really Big Data from the Internet of Things. IoT is evolving to include many data possibilities like new types of event, log and network data. The volumes are enormous, generating tens of billions of logs per day, which raise data challenges. Early IoT deployments are relying heavily on both the cloud and managed service providers to navigate these challenges. In her session at 6th Big Data Expo®, Hannah Smalltree, Director at Treasure Data, to discuss how IoT, Big Data and deployments are processing massive data volumes from wearables, utilities and other mach...
    This Internet of Nouns trend is still in the early stages and many of our already connected gadgets do provide human benefits over the typical infotainment. Internet of Things or IoT. You know, where everyday objects have software, chips, and sensors to capture data and report back. Household items like refrigerators, toilets and thermostats along with clothing, cars and soon, the entire home will be connected. Many of these devices provide actionable data - or just fun entertainment - so people can make decisions about whatever is being monitored. It can also help save lives.