|By Tarak Modi||
|October 1, 2000 12:00 AM EDT||
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:
- 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.
- 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.
- 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.
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.
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:
- The implementation of JavaSpaces is complex to install.
- 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.
- JavaSpaces relies on Java RMI, the suitability of which for highly scalable commercial applications is a topic of debate among many software gurus.
- JavaSpaces works only with serializable Java objects.
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:
- The space must support shared access.
- The space must be persistent.
- The space must provide the ability to specify a filtering template.
- 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).
- The space must perform and scale well under load.
- The space must be accessible to other CORBA objects.
- The space must not impose a limitation on what you can put in it (unlike JavaSpaces, for example).
- The space must not impose size limitations on what you can put in it (the underlying hardware, however, may impose a limitation).
Java Message Service
At the time we were evaluating message queuetype 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 vendorspecific 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:
void write(in ByteStream blob) raises (SpaceException);
ByteStream take() raises (SpaceException);
void write_filter(in ByteStream blob, in FilterSeq f)
ByteStream take_filter(in FilterSeq f) raises (SpaceException);
ByteStream take_filter_as_string(in string f)
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=MySpaceThe "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.
# The factory to use to get the initial Connection Factory
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.
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!
- Linda Group: www.cs.yale.edu/HTML/YALE/CS/Linda/linda.html
- JavaSpaces homepage: www.javasoft.com/products/javaspaces/
- IBM, TSpaces: www.almaden.ibm.com/cs/TSpaces/
- Carriero, N.J. (1987). "Implementation of Tuple Space Machines," PhD thesis, Yale University, Department of Computer Science.
- Segall, E.J. (1993). "Tuple Space Operations: Multiple-Key Search, Online Matching and Wait-Free Synchronization," PhD thesis, Rutgers University, Department of Computer Science.
- Gul, A., et al. "ActorSpaces: An Open Distributed Programming Paradigm," University of Illinois at Urbana-Champaign, ULIUENG-92-1846.
The explosion of connected devices / sensors is creating an ever-expanding set of new and valuable data. In parallel the emerging capability of Big Data technologies to store, access, analyze, and react to this data is producing changes in business models under the umbrella of the Internet of Things (IoT). In particular within the Insurance industry, IoT appears positioned to enable deep changes by altering relationships between insurers, distributors, and the insured. In his session at @ThingsExpo, Michael Sick, a Senior Manager and Big Data Architect within Ernst and Young's Financial Servi...
Feb. 28, 2015 12:00 PM EST Reads: 1,089
SYS-CON Events announced today that Open Data Centers (ODC), a carrier-neutral colocation provider, will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place June 9-11, 2015, at the Javits Center in New York City, NY. Open Data Centers is a carrier-neutral data center operator in New Jersey and New York City offering alternative connectivity options for carriers, service providers and enterprise customers.
Feb. 28, 2015 12:00 PM EST Reads: 1,804
When it comes to the Internet of Things, hooking up will get you only so far. If you want customers to commit, you need to go beyond simply connecting products. You need to use the devices themselves to transform how you engage with every customer and how you manage the entire product lifecycle. In his session at @ThingsExpo, Sean Lorenz, Technical Product Manager for Xively at LogMeIn, will show how “product relationship management” can help you leverage your connected devices and the data they generate about customer usage and product performance to deliver extremely compelling and reliabl...
Feb. 28, 2015 12:00 PM EST Reads: 1,212
The IoT market is projected to be $1.9 trillion tidal wave that’s bigger than the combined market for smartphones, tablets and PCs. While IoT is widely discussed, what not being talked about are the monetization opportunities that are created from ubiquitous connectivity and the ensuing avalanche of data. While we cannot foresee every service that the IoT will enable, we should future-proof operations by preparing to monetize them with extremely agile systems.
Feb. 28, 2015 11:00 AM EST Reads: 1,126
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. Learn about IoT, Big Data and deployments processing massive data volumes from wearables, utilities and other machines.
Feb. 28, 2015 11:00 AM EST Reads: 983
SYS-CON Events announced today that CodeFutures, a leading supplier of database performance tools, has been named a “Sponsor” of SYS-CON's 16th International Cloud Expo®, which will take place on June 9–11, 2015, at the Javits Center in New York, NY. CodeFutures is an independent software vendor focused on providing tools that deliver database performance tools that increase productivity during database development and increase database performance and scalability during production.
Feb. 28, 2015 11:00 AM EST Reads: 2,396
Feb. 28, 2015 10:30 AM EST Reads: 2,374
“In the past year we've seen a lot of stabilization of WebRTC. You can now use it in production with a far greater degree of certainty. A lot of the real developments in the past year have been in things like the data channel, which will enable a whole new type of application," explained Peter Dunkley, Technical Director at Acision, in this SYS-CON.tv interview at @ThingsExpo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Feb. 28, 2015 10:00 AM EST Reads: 3,192
SYS-CON Events announced today that Intelligent Systems Services will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Established in 1994, Intelligent Systems Services Inc. is located near Washington, DC, with representatives and partners nationwide. ISS’s well-established track record is based on the continuous pursuit of excellence in designing, implementing and supporting nationwide clients’ mission-critical systems. ISS has completed many successful projects in Healthcare, Commercial, Manufacturing, ...
Feb. 28, 2015 10:00 AM EST Reads: 1,144
PubNub on Monday has announced that it is partnering with IBM to bring its sophisticated real-time data streaming and messaging capabilities to Bluemix, IBM’s cloud development platform. “Today’s app and connected devices require an always-on connection, but building a secure, scalable solution from the ground up is time consuming, resource intensive, and error-prone,” said Todd Greene, CEO of PubNub. “PubNub enables web, mobile and IoT developers building apps on IBM Bluemix to quickly add scalable realtime functionality with minimal effort and cost.”
Feb. 28, 2015 10:00 AM EST Reads: 4,596
The major cloud platforms defy a simple, side-by-side analysis. Each of the major IaaS public-cloud platforms offers their own unique strengths and functionality. Options for on-site private cloud are diverse as well, and must be designed and deployed while taking existing legacy architecture and infrastructure into account. Then the reality is that most enterprises are embarking on a hybrid cloud strategy and programs. In this Power Panel at 15th Cloud Expo (http://www.CloudComputingExpo.com), moderated by Ashar Baig, Research Director, Cloud, at Gigaom Research, Nate Gordon, Director of T...
Feb. 28, 2015 10:00 AM EST Reads: 3,948
Sensor-enabled things are becoming more commonplace, precursors to a larger and more complex framework that most consider the ultimate promise of the IoT: things connecting, interacting, sharing, storing, and over time perhaps learning and predicting based on habits, behaviors, location, preferences, purchases and more. In his session at @ThingsExpo, Tom Wesselman, Director of Communications Ecosystem Architecture at Plantronics, will examine the still nascent IoT as it is coalescing, including what it is today, what it might ultimately be, the role of wearable tech, and technology gaps stil...
Feb. 28, 2015 09:45 AM EST Reads: 712
DevOps tends to focus on the relationship between Dev and Ops, putting an emphasis on the ops and application infrastructure. But that’s changing with microservices architectures. In her session at DevOps Summit, Lori MacVittie, Evangelist for F5 Networks, will focus on how microservices are changing the underlying architectures needed to scale, secure and deliver applications based on highly distributed (micro) services and why that means an expansion into “the network” for DevOps.
Feb. 28, 2015 09:15 AM EST Reads: 1,179
With several hundred implementations of IoT-enabled solutions in the past 12 months alone, this session will focus on experience over the art of the possible. Many can only imagine the most advanced telematics platform ever deployed, supporting millions of customers, producing tens of thousands events or GBs per trip, and hundreds of TBs per month. With the ability to support a billion sensor events per second, over 30PB of warm data for analytics, and hundreds of PBs for an data analytics archive, in his session at @ThingsExpo, Jim Kaskade, Vice President and General Manager, Big Data & Ana...
Feb. 28, 2015 09:00 AM EST Reads: 1,180
For years, we’ve relied too heavily on individual network functions or simplistic cloud controllers. However, they are no longer enough for today’s modern cloud data center. Businesses need a comprehensive platform architecture in order to deliver a complete networking suite for IoT environment based on OpenStack. In his session at @ThingsExpo, Dhiraj Sehgal from PLUMgrid will discuss what a holistic networking solution should really entail, and how to build a complete platform that is scalable, secure, agile and automated.
Feb. 28, 2015 09:00 AM EST Reads: 2,269
We’re no longer looking to the future for the IoT wave. It’s no longer a distant dream but a reality that has arrived. It’s now time to make sure the industry is in alignment to meet the IoT growing pains – cooperate and collaborate as well as innovate. In his session at @ThingsExpo, Jim Hunter, Chief Scientist & Technology Evangelist at Greenwave Systems, will examine the key ingredients to IoT success and identify solutions to challenges the industry is facing. The deep industry expertise behind this presentation will provide attendees with a leading edge view of rapidly emerging IoT oppor...
Feb. 28, 2015 09:00 AM EST Reads: 2,783
In the consumer IoT, everything is new, and the IT world of bits and bytes holds sway. But industrial and commercial realms encompass operational technology (OT) that has been around for 25 or 50 years. This grittier, pre-IP, more hands-on world has much to gain from Industrial IoT (IIoT) applications and principles. But adding sensors and wireless connectivity won’t work in environments that demand unwavering reliability and performance. In his session at @ThingsExpo, Ron Sege, CEO of Echelon, will discuss how as enterprise IT embraces other IoT-related technology trends, enterprises with i...
Feb. 28, 2015 09:00 AM EST Reads: 2,076
Feb. 28, 2015 09:00 AM EST Reads: 1,214
The Internet of Things (IoT) is causing data centers to become radically decentralized and atomized within a new paradigm known as “fog computing.” To support IoT applications, such as connected cars and smart grids, data centers' core functions will be decentralized out to the network's edges and endpoints (aka “fogs”). As this trend takes hold, Big Data analytics platforms will focus on high-volume log analysis (aka “logs”) and rely heavily on cognitive-computing algorithms (aka “cogs”) to make sense of it all.
Feb. 28, 2015 09:00 AM EST Reads: 959
The Internet of Everything (IoE) brings together people, process, data and things to make networked connections more relevant and valuable than ever before – transforming information into knowledge and knowledge into wisdom. IoE creates new capabilities, richer experiences, and unprecedented opportunities to improve business and government operations, decision making and mission support capabilities. In his session at @ThingsExpo, Gary Hall, Chief Technology Officer, Federal Defense at Cisco Systems, will break down the core capabilities of IoT in multiple settings and expand upon IoE for bo...
Feb. 28, 2015 09:00 AM EST Reads: 1,042