Corba Interview Preparation Guide

CORBAs goal is to address interoperability at various levels. There is a history to this.
In the early versions of CORBA, interoperability between platforms and programming languages was addressed. This included the standardization of IDL and the mapping of IDL to a programming language. While a client and server developed with the same vendors ORB could talk to one another, a client and server developed with different vendors? ORBs were not likely to interoperate.
CORBA 2.0 introduced interoperability between different ORB vendors. This resulted from the introduction of a standard wire protocol called General Inter-ORB Protocol (GIOP), and the incarnation for GIOP for the internet, known as Internet Inter-ORB Protocol (IIOP). So CORBA 2.0 compliant ORBs will interoperate. This means a client using ORB vendor A can talk to a server using ORB vendor B.
Interoperability is actually a broader issue than just have ORB vendor A talking to ORB vendor B. Fuller interoperability means that various services interoperate. For example, while a CORBA object can talk to a DCOM object via a protocol bridge, can the CORBA Transaction Service talk to the Microsoft Transaction Service to have a seamless transaction between systems? This broader interoperability at the service level is being addressed now.

Yes, but we can fake it pretty easily.
While CORBA does support a deferred synchronous request/response, it does not directly support distributed requests with a callback driven response. A callback driven response allows an application to perform an operation on a distributed object, associate a callback with the response, continue with other processing. When the server responds, the associated callback is automatically executed within the original caller?s application.

There are a number of ways to tune CORBA applications for better performance. Remember that distribution should only be used if a reason to do so exists. Distribution does not make sense for the sake of distribution. If distribution does not serve a purpose then it should be avoided. Avoiding excessive distribution can result in better performance. Care should be taken when introducing distribution into an applications object model. IDL interfaces can be tuned to minimize network latency. Invoking remote operations requires transmitting data across the network. Network performance is typically optimized by ensuring adequate bandwidth. Once the required bandwidth is achieved raw network performance cannot be increased. One key to tuning an IDL interface is to reduce the number of network transfers that need to occur. Calling an operation that returns 100 bytes might take 5 milliseconds. Calling an operation that returns 200 bytes of data might take around 6 milliseconds. Calling 2 operations that return 100 bytes might take a total of 10 milliseconds. One key to tuning IDL operations is to avoid implementing several get operations and to combine them into a single get operation which returns the appropriate combination of data. Caching results of remote operations can avoid network overhead associated with calling the same remote methods more than once. Many applications can perform remote operations upon startup rather than during normal usage. Users are often more willing to wait at startup time rather than during application usage. Many performance problems are associated with serialization and blocking conditions. For example, Let us assume that clients will be making remote operations to a single server. A single client?s request causes the server to block for a extended period of time, the entire client community might have to wait. Make sure that multiple distributed operations are not becoming serialized within a single server process. Utilize multiple server processes or threaded servers instead.

CORBA does not directly support distributed reference counting. This was a conscious decision on the part of its designers. While CORBA does not directly support reference counting, it is possible to build reference counting into a particular distributed object architecture. This can be done through an explicit session management facility which can be exposed through factories or other remote interfaces. While it is possible to design reference counting into an application, it is the burden of the application designer/developer to ensure that such an approach is implemented correctly.

No, it is infrastructure. Which is good because the history of high-level? one size fits all? architectures hasn't been very good, has it?
CORBA provides low level request/response communication. It also provides general services that are implemented on top of request/response communication. The actual architecture used within a given application is not defined by CORBA. CORBA leaves these decisions up the application architect.

There are several different common architectures that can be used within multi-threaded CORBA servers. A server process needs the ability to process CORBA messages. These messages are processed by one or more threads, as determined by the application architecture. The CORBA specification does not specifically address threading capabilities within CORBA compliant ORBs. An ORB vendor is free to support only single-threaded application or to support multi-threaded applications. If the ORB does support the development of multi-threaded applications, the ORB might only support a subset of the threading models listed below. Significant threading code might still need to be developed to achieve one of the models. For example, the ORB vendor might support a set of application hooks (i.e., interceptors or filters) and allow you to implement threading code with the native OS thread API. On the other hand, the ORB product might provide a built-in feature so no custom thread development needs to be done. The CORBA specification does not address this issue. When you consider different threading models, it is important to consider what kind of concurrency is desired. While it may be advantageous that two or more threads can be concurrent, it may also be disadvantageous. Also, the resources consumed by idle or active threads, and also the resources consumed for thread creation and deletion, need to be considered. Thread-Per-Request: With this architecture, the CORBA server ensures that each incoming message is processed in its own thread. This means that multiple requests will be processed concurrently. There are concurrency issues. If two or more requests (threads) are using the same object, then some form of concurrency control (locking) is needed. Also, if two or more requests (threads) are from the same client, then perhaps the requests should be serialized instead of allowed to execute concurrently. Thread-Per-Client: With this architecture, the CORBA server ensures that each incoming message from a distinct client is processed in its own thread. This is similar to Thread-Per-Request except multiple requests from the same client are serialized. Requests from distinct clients are concurrent. The way that one client is distinguished from another is an interesting problem. Typically, this is done by looking a the network connection and determining that the clients are the same or different. The server needs the ability to monitor client connections and the inception and termination of this connections (typically at a network level, not an application level). Thread-Per-Server-Object: With this architecture, the CORBA server ensures that each object in the server gets it own thread of execution. This means that multiple requests will be processed concurrently provided they are using different objects. Multiple requests using the same object are serialized. There are concurrency issues, and some locking strategy is needed. Also, deadlock is very possible. It may be that threading or locking at each object is too fine a grain, and a more appropriate choice is putting the thread/lock boundary around a group of coordinating objects. For each of the above threading architectures, the required server threads can be either created on demand or recycled through a thread pool. The advantage of creating threads on demand is that an arbitrary number of threads can be supported. A thread is created, used, and then reaped. The Thread-Per-Request model would create/reap a thread for each request; the Thread-Per-Client model would create/reap a thread for each client connection; the Thread-Per-Server-Object model would create/reap a thread for each CORBA object instantiated in the server. Thread creation and reaping has some cost, which may be large or small depending on the operating system thread support. A thread pool is an alternative to creating threads on demand. In this approach, a fixed number of threads are created and cycled in turn to meet the demand for threads. If the demand for threads exceeds the pool size, then further requests for threads are blocked until one of the existing threads is recycled. This approach has the advantage of capping the server resources.

Client-side CORBA applications might require multi-threading to allow it to perform other tasks while it is waiting for a synchronous remote invocation to return. It might desire this functionality for several different reasons.
A client application might wish to leverage the static request/response style of invocation but achieve some degree of asynchronous communication. Perhaps the client wishes to perform several synchronous invocations within their own application threads. This would allow a client to obtain results from several remote servers more quickly. There are several reasons the use of multi-threading might be preferred over the use of DII. DII might be complicate application source code. Application polling associated with the deferred synchronous invocation might result in a performance bottleneck.
A client-side CORBA application might need to respond to events such as incoming invocations, connect requests, or GUI events (mouse clicks, etc.) CORBA products that support only blocking style remote invocations will be unable to process any of these events. This would mean that a client-side application would be unable to respond to GUI events for the duration of any remote CORBA invocations. This is not an issue for short duration invocations but becomes a problem for longer invocations or in failure or time-out situations. Performing remote invocations within dedicated threads can avoid this issue.

Different CORBA implementations can vary significantly in performance. Good implementations should be fairly similar since network performance defines the maximum achievable performance characteristics. Network latency does represent the significant portion of distributed invocation latency.

The CORBA specification does not currently address multi-threaded architectures. Provided that the CORBA product is thread safe, threaded CORBA applications can be developed. CORBA clients and servers can both be multi-threaded. Daemon processes provided with CORBA products may be implemented as multi-threaded servers by the CORBA vendor. Different multi-threaded models or multi-threaded architectures may be supported by a particular CORBA product. A particular ORB may provide frameworks to simplify the development of multi-threaded CORBA applications.

CORBA is the acronym for Common Object Request Broker Architecture, OMG's open, vendor-independent architecture and infrastructure that computer applications use to work together over networks. Using the standard protocol IIOP, a CORBA-based program from any vendor, on almost any computer, operating system, programming language, and network, can interoperate with a CORBA-based program from the same or another vendor, on almost any other computer, operating system, programming language, and network.