Welcome!

Java IoT Authors: Pat Romanski, Elizabeth White, Mano Marks, Jim Hansen, David Sprott

Related Topics: Java IoT

Java IoT: Article

Using Space-Based Programming for Loosely Coupled Distributed Systems

Using Space-Based Programming for Loosely Coupled Distributed Systems

One of the problems of highly distributed systems is figuring out how systems discover each other. After all, the whole point of having systems distributed is to allow flexible and perhaps even dynamic configurations to maximize system performance and availability. How do these distributed components of one system or multiple systems discover each other? And once they're discovered how do we allow enough flexibility, such as rediscovery, to allow their fail-safe operation?

Space-based programming may provide us with a good answer to these questions and more. In this article I'll describe what a space is and how it can be used to mitigate some of the issues mentioned above. And I've included a technique to convert an ordinary message queue into a space.

What Is a Space?
Conventional distributed tools rely on passing messages between processes (asynchronous communication) or invoking methods on remote objects (synchronous communication). A space is an extension of the asynchronous communication model in which two processes are not passing messages to one another. In fact, the processes are totally unaware of each other.

In Figure 1, Process 1 places a message into the space. Process 2, which has been waiting for this type of message, takes the message out of the space and processes it. Based on the results, it places another message into the space. Process 3, which has been waiting for this type of message, takes the message out of the space.

Following are highlights of the preceding discussion:

  1. The space may contain different types of messages. In fact, I used the term message for clarity. These messages are actually just "things" (the message may be an object, an XML document or anything else that the space allows to be put in it). In Figure 1 the different shapes in the space illustrate the different types of messages.
  2. The three processes involved have no knowledge of one another. All they know is that they put a message in a space and get a message out of the space.
  3. As in the message-passing scenario, we aren't limited to two processes communicating asynchronously, but rather any number of processes communicating via a common space. This allows the creation of loosely coupled systems that can be highly distributed and extremely flexible, and can provide high availability and dynamic load balancing.
Let's look at a more specific example this time. A common encryption method is the use of "one-way" functions, which take an input and, like any other function, generate an output. The distinguishing feature of such functions is that it's extremely difficult to compute the input that was given to the function to get the output (i.e., to compute the inverse of the function); hence, the term one-way function. Instead of trying to figure out the inverse of the function to get the input required for the given output, an easier way may be to take all possible inputs and compute the output for each one. When we get an output that matches the one we have, we've found the right "input." But this can be extremely time consuming given the vast number of possible inputs.

Assume that passwords can't be more than four characters in length and only alphanumeric ASCII characters are used. This gives us 14,776,336 possible passwords (624). Using the brute force technique to break the password, assume that the main program breaks the input set into 16 pieces and puts each piece – along with the encrypted password – in the space. The password-breaking programs watch the space for such pieces and each available program immediately grabs a piece and starts working. The programs continue until no more such pieces are available or until the password has been broken. If the password is broken, the breaking program puts the solution in the space, which is picked up by the main program.

The main program then proceeds to pick up the remaining pieces, since it has already found the solution it needs. The program never knew how many password-breaking programs were available, nor did it know where they were located. The password-breaking programs had no knowledge about one another or about the main program. If there were 16 password-breaking programs available, and each one was on a separate machine, we would've had 16 machines working on breaking the password simultaneously!

No change to any configuration of the system is required to add new password-breaking programs. This is why spaces are so good for fault tolerance, load balancing and scalability.

As you can see, spaces provide an extremely powerful concept/mechanism to decouple cooperating or dependent systems. The concept of a space isn't new, however. Tuple spaces were first described in 1982 in the context of a programming language called Linda. Linda consisted of tuples, which were collections of data grouped together, and the tuple space, which was the shared blackboard from which applications could place and retrieve tuples. The concept never gained much popularity outside of academia, however. Today spaces may be an elegant solution to many of the traditional distributed computing dilemmas. In recognition of this fact, JavaSoft has created its own implementation of the space concept, JavaSpaces, and IBM has created TSpaces, which is much more functional and complex than JavaSpaces. (We won't discuss IBM's TSpaces in this article.)

We're now in a position to describe some of the key characteristics of a space:

  • Spaces provide shared access: A space provides a network-accessible "shared memory" that can be accessed by many shared remote/local processes concurrently. The space handles all issues regarding concurrent access, allowing the processes to focus on the task at hand. At the very least, spaces provide processes with the ability to place and retrieve "things." Some spaces also provide the ability to read/peek at things (i.e., to get the thing without actually removing it from the space, thus allowing other processes to access it as well).
  • Spaces are persistent: A space provides reliable storage for processes to place "things." These "things" may outlive the processes that created them. It also allows the dependent/cooperating processes to work together even when they have nonoverlapping life cycles, and boosts the fault tolerance and high-availability capability of distributed systems.
  • Spaces are associative. Associative lookup allows processes to "find" the "things" they're interested in. As many processes may be using/sharing the same space, many different "things" may be in the space. It's important for processes to be able to get the "things" they require without having to filter out the "noise" themselves. This is possible because spaces allow processes to define filters/templates that instruct/direct the space to "find" the right "things" for that process.
These are just a few key characteristics of spaces. Many commercial space implementations, such as the ones from JavaSoft and IBM, have additional characteristics such as the ability to perform "transacted" operations on the space.

JavaSoft's Implementation: JavaSpaces
JavaSpaces technology, a new realization of the tuple spaces concept described above, is an implementation that's available free from JavaSoft. JavaSpaces is built on top of another complex technology, Jini, a Java-based technology that allows any device to become network aware. Jini provides a complex yet elegant programming model that realizes the Jini team's vision of "network anything, anytime, anywhere."

The goal of JavaSpaces is to provide what might be thought of as a file system for objects. Like other JavaSoft APIs, JavaSpaces provides a simple yet powerful set of features to developers. As I see it, however, JavaSpaces has four drawbacks:

  1. The implementation of JavaSpaces is complex to install.
  2. The fact that it builds on top of Jini makes it a little too heavy, especially if there are no plans to use Jini elsewhere in the project.
  3. JavaSpaces relies on Java RMI, the suitability of which for highly scalable commercial applications is a topic of debate among many software gurus.
  4. JavaSpaces works only with serializable Java objects.
Creating Your Own Space Implementation
Even though commercial implementations of spaces are available in the market, there are several reasons to create your own. If you work in a start-up company, budget constraints may be a big reason. Also, the functionality offered by a commercial implementation may be too much for the job at hand. Not only may this result in a larger learning curve, it may even slow down your application due to the sheer size of the memory footprint. Finally, it's always fun to create your own implementation.

At Online Insight we decided to create our own implementation. The primary reasons for our decision were our limited set of requirements and the extremely lightweight implementation we required to achieve our scalability and performance goals.

Our requirements can be summarized as follows:

  1. The space must support shared access.
  2. The space must be persistent.
  3. The space must provide the ability to specify a filtering template.
  4. The space must allow one "thing" to be accessed by only one process/application at a time (i.e., we don't support the "read" operation).
  5. The space must perform and scale well under load.
  6. The space must be accessible to other CORBA objects.
  7. The space must not impose a limitation on what you can put in it (unlike JavaSpaces, for example).
  8. The space must not impose size limitations on what you can put in it (the underlying hardware, however, may impose a limitation).
Note that the first three requirements are, in addition, key characteristics of a space.

Java Message Service
At the time we were evaluating message queue–type software – specifically, Java Message Service (JMS) implementations – we realized that we could build our space facility on top of one of these queues.

JMS is an API for accessing enterprise-messaging systems from Java programs. It defines a common set of enterprise-messaging concepts and facilities, and attempts to minimize the set of concepts a Java language programmer must learn to use, including enterprise-messaging products such as IBM MQSeries. JMS also strives to maximize the portability of messaging applications. It doesn't, however, address load balancing/fault tolerance, error notification, administration of the message queue or security issues. These are all message queue vendor–specific and outside the domain of the JMS.

By using message queues that expose a JMS interface, we allow ourselves the flexibility to switch vendors of message queues if we discover that the selected one doesn't meet our scalability requirements. This separation of implementation from interface is an important design pattern (see the Bridge design pattern in Design Patterns by Gamma et al., published by Addison-Wesley). Since each JMS implementation has its own unique way of getting the initial connection factory, we defined a Java interface with one method, "getConnectionFactory", which returns the initial connection factory.

Each space is configured through a properties file. One property in this file is the fully qualified name of the class that implements this interface. There is one such class for each JMS implementation supported by the space. For example, we created one class for Sun's Java Message Queue and one for Progress Software's SonicMQ. By doing this, changing the underlying message queue used by the space is simply a matter of changing the name of the Java class in the properties file for the space. Therefore, if one vendor's message queue doesn't live up to our expectations, we can quickly switch to another.

The space implementation itself is a CORBA object that has the following interface:

interface Space
{
void write(in ByteStream blob) raises (SpaceException);
ByteStream take() raises (SpaceException);
void write_filter(in ByteStream blob, in FilterSeq f)
raises (SpaceException);
ByteStream take_filter(in FilterSeq f) raises (SpaceException);
ByteStream take_filter_as_string(in string f)
raises (SpaceException);

void shutdown();
};

The type ByteStream simply evaluates to a stream of bytes. Hence, anything that can be represented as a stream of bytes, such as a CORBA object IOR, a serialized Java object or an XML document, can be stored in the space and retrieved.

Each space instance has three properties: a name, a property that indicates if this instance of the space is persistent and a property that indicates if this instance of the space allows filters. The reason there are properties to turn the persistence and filtering off is purely for performance.

Not all spaces in our application domain are required to be persistent, in which case persistence is a performance bottleneck because it involves writing out to a database or similar storage mechanism. Similarly, if filtering isn't required, it's a performance bottleneck. As mentioned above, each space is configured through a properties file,which has the property indicating the space name, the persistence status (on/off) and the filtering status (on/off) of the space.

An example of the properties file used in configuring the space is shown below:

SpaceName=MySpace
AllowFilter=true
Persistent=true

# The factory to use to get the initial Connection Factory
SpaceFactory=SonicMQSpaceFactoryImpl

The "SpaceName" property is the name of the space, "AllowFilter" is a boolean property where true means the space turns filter support on and "Persistent" is a boolean property where true means the space turns persistence on. "SpaceFactory" is set to the fully qualified name of the class that allows us to get the initial connection factory from the message queue. In the foregoing example, this property is set to a class that works with SonicMQ implementation.

During start-up each space installs itself in the CORBA Name Service using its name property as the binding name and in the CORBA Trader Service with the name, persistence and filter properties. Thus interested applications/processes can find a space by using a well-known name from the CORBA Name Service or the space properties from the CORBA Trader Service. For example, an application that wants filtering but isn't interested in persistence can indicate these requirements to the CORBA Trader Service, which will then provide the application with a list of CORBA space references that match these requirements. The application may then choose one from that list based on some further screening.

Our implementation of the space gains all its persistence and filtering capabilities from the underlying messaging queue provider. Our space is the only client of the message queue. In our implementation the only purpose the message queue serves is as a high-quality storage/retrieval mechanism that also provides filtering capabilities. We aren't relying on the queuing facilities per se.

Each method of the CORBA interface is detailed below:

  • write: This method is called by an application when it wants to put a stream of bytes into the space and doesn't want to attach filtering properties to the stream.
  • write_filter: This method is used by an application when it wants to put a stream of bytes into the space and wants to attach filtering properties to the stream. The type FilterSeq evaluates to an array of filters that are attached to that bytestream. A filter is a name-value pair. Hence, a FilterSeq is an array of name value pairs.
  • take: This method is called by an application when it wants to retrieve a stream of bytes from the space. No filtering is performed since none is specified.
  • take_filter: This method is called by an application when it wants to retrieve a stream of bytes from the space. However, in this case a FilterSeq is provided. For a match to occur, the bytestream must have a subset of the filters provided in the method call, and the value of each filter attached to the bytestream must match the value for the corresponding filter in the method call.
  • take_filter_as_string: This method is called by an application when it wants to retrieve a stream of bytes from the space. In this case a string that specifies the exact filter is provided. For a match to occur, the filter properties attached to the bytestream must satisfy the filter string provided in the method call. This method is used when the filtering conditions can't be specified as a FilterSeq.
  • shutdown: This method is called to shut down the space. The shutdown is clean, which means the registration with the Name Service and the Trader Service is removed.
The space implements all methods in the interface as synchronized. Furthermore, the take implementations are nonblocking, that is, if there's nothing to take, the method returns with nothing.

Conclusion
Distributed applications can be notoriously difficult to design, build and debug. The distributed environment introduces many complexities that aren't present when writing stand-alone applications. Some of these challenges are network latency, synchronization and concurrency, and partial failure.

Space-based programming, although not a silver bullet, is an excellent concept that can lead to an elegant solution to these problems. It takes us one step closer to achieving our goals in a distributed system, namely those of scalability, high availability, loose coupling and performance. It also helps us face the challenges mentioned above. Best of all, you don't have to buy an expensive implementation to get started with this excellent concept. It's fairly easy to create a homegrown implementation that satisfies your requirements...and it's fun, too!

Resources

  1. Linda Group: www.cs.yale.edu/HTML/YALE/CS/Linda/linda.html
  2. JavaSpaces homepage: www.javasoft.com/products/javaspaces/
  3. IBM, TSpaces: www.almaden.ibm.com/cs/TSpaces/
  4. Carriero, N.J. (1987). "Implementation of Tuple Space Machines," PhD thesis, Yale University, Department of Computer Science.
  5. Segall, E.J. (1993). "Tuple Space Operations: Multiple-Key Search, Online Matching and Wait-Free Synchronization," PhD thesis, Rutgers University, Department of Computer Science.
  6. Gul, A., et al. "ActorSpaces: An Open Distributed Programming Paradigm," University of Illinois at Urbana-Champaign, ULIUENG-92-1846.

More Stories By Tarak Modi

Tarak Modi, a certified Java programmer, is a lead systems architect at Online Insight where he's responsible for setting, directing, and implementing the vision and strategy of the company's product line from a technical and architectural perspective. Tarak has worked with Java, C++, and technologies such as EJB, Corba, and DCOM, and holds a BS in EE, an MS in computer engineering, and an MBA with a concentration in IS.

Comments (0)

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.


@ThingsExpo Stories
More and more brands have jumped on the IoT bandwagon. We have an excess of wearables – activity trackers, smartwatches, smart glasses and sneakers, and more that track seemingly endless datapoints. However, most consumers have no idea what “IoT” means. Creating more wearables that track data shouldn't be the aim of brands; delivering meaningful, tangible relevance to their users should be. We're in a period in which the IoT pendulum is still swinging. Initially, it swung toward "smart for smart...
The WebRTC Summit New York, to be held June 6-8, 2017, at the Javits Center in New York City, NY, announces that its Call for Papers is now open. Topics include all aspects of improving IT delivery by eliminating waste through automated business models leveraging cloud technologies. WebRTC Summit is co-located with 20th International Cloud Expo and @ThingsExpo. WebRTC is the future of browser-to-browser communications, and continues to make inroads into the traditional, difficult, plug-in web co...
"A lot of times people will come to us and have a very diverse set of requirements or very customized need and we'll help them to implement it in a fashion that you can't just buy off of the shelf," explained Nick Rose, CTO of Enzu, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Buzzword alert: Microservices and IoT at a DevOps conference? What could possibly go wrong? In this Power Panel at DevOps Summit, moderated by Jason Bloomberg, the leading expert on architecting agility for the enterprise and president of Intellyx, panelists peeled away the buzz and discuss the important architectural principles behind implementing IoT solutions for the enterprise. As remote IoT devices and sensors become increasingly intelligent, they become part of our distributed cloud enviro...
SYS-CON Events announced today that MobiDev, a client-oriented software development company, will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place June 6-8, 2017, at the Javits Center in New York City, NY, and the 21st International Cloud Expo®, which will take place October 31-November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. MobiDev is a software company that develops and delivers turn-key mobile apps, websites, web services, and complex softw...
With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo 2016 in New York. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be! Internet of @ThingsExpo, taking place June 6-8, 2017, at the Javits Center in New York City, New York, is co-located with 20th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry p...
The security needs of IoT environments require a strong, proven approach to maintain security, trust and privacy in their ecosystem. Assurance and protection of device identity, secure data encryption and authentication are the key security challenges organizations are trying to address when integrating IoT devices. This holds true for IoT applications in a wide range of industries, for example, healthcare, consumer devices, and manufacturing. In his session at @ThingsExpo, Lancen LaChance, vic...
Who are you? How do you introduce yourself? Do you use a name, or do you greet a friend by the last four digits of his social security number? Assuming you don’t, why are we content to associate our identity with 10 random digits assigned by our phone company? Identity is an issue that affects everyone, but as individuals we don’t spend a lot of time thinking about it. In his session at @ThingsExpo, Ben Klang, Founder & President of Mojo Lingo, discussed the impact of technology on identity. Sho...
Manufacturers are embracing the Industrial Internet the same way consumers are leveraging Fitbits – to improve overall health and wellness. Both can provide consistent measurement, visibility, and suggest performance improvements customized to help reach goals. Fitbit users can view real-time data and make adjustments to increase their activity. In his session at @ThingsExpo, Mark Bernardo Professional Services Leader, Americas, at GE Digital, discussed how leveraging the Industrial Internet and...
What are the new priorities for the connected business? First: businesses need to think differently about the types of connections they will need to make – these span well beyond the traditional app to app into more modern forms of integration including SaaS integrations, mobile integrations, APIs, device integration and Big Data integration. It’s important these are unified together vs. doing them all piecemeal. Second, these types of connections need to be simple to design, adapt and configure...
IoT generates lots of temporal data. But how do you unlock its value? You need to discover patterns that are repeatable in vast quantities of data, understand their meaning, and implement scalable monitoring across multiple data streams in order to monetize the discoveries and insights. Motif discovery and deep learning platforms are emerging to visualize sensor data, to search for patterns and to build application that can monitor real time streams efficiently. In his session at @ThingsExpo, ...
A critical component of any IoT project is what to do with all the data being generated. This data needs to be captured, processed, structured, and stored in a way to facilitate different kinds of queries. Traditional data warehouse and analytical systems are mature technologies that can be used to handle certain kinds of queries, but they are not always well suited to many problems, particularly when there is a need for real-time insights.
WebRTC is about the data channel as much as about video and audio conferencing. However, basically all commercial WebRTC applications have been built with a focus on audio and video. The handling of “data” has been limited to text chat and file download – all other data sharing seems to end with screensharing. What is holding back a more intensive use of peer-to-peer data? In her session at @ThingsExpo, Dr Silvia Pfeiffer, WebRTC Applications Team Lead at National ICT Australia, looked at differ...
"ReadyTalk is an audio and web video conferencing provider. We've really come to embrace WebRTC as the platform for our future of technology," explained Dan Cunningham, CTO of ReadyTalk, in this SYS-CON.tv interview at WebRTC Summit at 19th Cloud Expo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
In his General Session at 16th Cloud Expo, David Shacochis, host of The Hybrid IT Files podcast and Vice President at CenturyLink, investigated three key trends of the “gigabit economy" though the story of a Fortune 500 communications company in transformation. Narrating how multi-modal hybrid IT, service automation, and agile delivery all intersect, he will cover the role of storytelling and empathy in achieving strategic alignment between the enterprise and its information technology.
Growth hacking is common for startups to make unheard-of progress in building their business. Career Hacks can help Geek Girls and those who support them (yes, that's you too, Dad!) to excel in this typically male-dominated world. Get ready to learn the facts: Is there a bias against women in the tech / developer communities? Why are women 50% of the workforce, but hold only 24% of the STEM or IT positions? Some beginnings of what to do about it! In her Day 2 Keynote at 17th Cloud Expo, Sandy Ca...
You have great SaaS business app ideas. You want to turn your idea quickly into a functional and engaging proof of concept. You need to be able to modify it to meet customers' needs, and you need to deliver a complete and secure SaaS application. How could you achieve all the above and yet avoid unforeseen IT requirements that add unnecessary cost and complexity? You also want your app to be responsive in any device at any time. In his session at 19th Cloud Expo, Mark Allen, General Manager of...
Web Real-Time Communication APIs have quickly revolutionized what browsers are capable of. In addition to video and audio streams, we can now bi-directionally send arbitrary data over WebRTC's PeerConnection Data Channels. With the advent of Progressive Web Apps and new hardware APIs such as WebBluetooh and WebUSB, we can finally enable users to stitch together the Internet of Things directly from their browsers while communicating privately and securely in a decentralized way.
Providing secure, mobile access to sensitive data sets is a critical element in realizing the full potential of cloud computing. However, large data caches remain inaccessible to edge devices for reasons of security, size, format or limited viewing capabilities. Medical imaging, computer aided design and seismic interpretation are just a few examples of industries facing this challenge. Rather than fighting for incremental gains by pulling these datasets to edge devices, we need to embrace the i...
Internet of @ThingsExpo, taking place June 6-8, 2017 at the Javits Center in New York City, New York, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @ThingsExpo New York Call for Papers is now open.