1. Distributed Processing, Client/Server and Clusters
Chapter 16

2. Client/Server Computing
Client machines:
single-user PCs or workstations that provide a highly user-friendly interface to the end user
Each server provides a set of shared user services to the clients
The server enables many clients to share access to the same database and enables the use of a high-performance computer system to manage the database

3. Client/Server Applications
Client and server platforms/OS may be different
These lower-level differences are irrelevant as long as a client and server share the same communications protocols (ex: TCP/IP) and support the same applications
Actual functions performed by the application can be split up between client and server in a way that optimizes the use of resources
Optimize the ability of users to perform various tasks and to cooperate with one another using shared resources
Heavy emphasis on providing a user-friendly Graphical User Interface (GUI) on the client side (presentation services layer)

4. Generic Client/Server Architecture

5. Database Applications
One of the most common families of client/server applications
The server is a database server responsible for maintaining the database
Interaction between client and server is in the form of transactions
the client makes a database request and receives a database response
A variety of different client applications can use the same database server; all using the same interface/protocol

6. Client/Server Architecture for Database Applications
e.g. SQL: Structured Query Language

7. Client/Server Database Usage Example:
think of an application in which we need to compute the mean of the ages of a certain population and the search criteria returns 300K records
 heavy network traffic
To optimize performance: server can be equipped with application logic for performing data analysis (computation of mean).
 Split-up the application logic

8. Client/Server Interaction Yet another example:
think of an application in which we need to search for a person named Jo Smith, born in 1980, whose SSN starts with 123 …….
If initial query results in 100K possible records, the server may just indicate that without sending the records.
Then search can be narrowed down and the # of possible records is reduced drastically.
After a few iterations we may receive the desired record.

9. Classes of Client/Server Applications
Host-based (dumb terminal)
not true client/server computing
traditional mainframe environment
Server-based (thin client)
server does all the processing
User(client) workstation provides a graphical user interface

10. Classes of Client/Server Applications
Fat client models
Takes advantage of desktop power and can serve large number of clients
Cooperative
application processing is performed in an optimized fashion
complex to set up and maintain but
greater user productivity gains and greater network efficiency
Client-based
Most common client/server model
all application processing done at the client
data validation routines and other database logic function are done at the server
Some of the more sophisticated database logic functions are housed on the client side
It enables the user to employ applications tailored to local needs

11. Three-Tier Client/Server Architecture
Application software distributed among three types of machines
User machine
thin client
Middle-tier server
Gateway
Converts protocols
Map from one type of database query to another
Merge/integrate results from different data sources
Assumes both roles:
server & client
Backend server
Legacy applications

12. File Cache Consistency
File caches hold recently accessed file records
Cache consistency problem:
Caches are consistent when they contain exact copies for remote data
Simple solution: File-locking prevents simultaneous access to a file
Complicated approach: allow multiple read but one write access; when there is a write, mark the file as non-cacheable

13. Middleware
Lack of standards for client/server models makes it difficult to implement an integrated, multivendor, enterprise-wide client/server configuration
Middleware: Set of tools that provide a uniform means and style of access to system resources across different platforms. Goal: to enable an application or user at a client to access a variety of services on servers without being concerned about differences among them
Provides standard programming interfaces/protocols that sit between the application above and the communications software+OS below.
Capability to hide the complexities and disparities of different network protocols and OS
Enable programmers to build applications that look and feel the same with little effort
Enable programmers to use the same method to access data

14. LOGICAL VIEW OF MIDDLEWARE
Middleware which cuts across all client and server platforms, is responsible for routing client requests to the appropriate server.
SOA (Service-Oriented Architecture): Services with well-defined interfaces are shared by different departments.
Standardized interfaces are used to enable service modules to communicate with one another and to enable client applications to communicate with service modules.
The most popular interface is the use of XML (Extensible Markup Language) over HTTP (Hypertext Transfer Protocol), known as Web services. SOAs are also implemented using other standards, such as CORBA (Common Object Request Broker Architecture).

15. Distributed Message Passing
Middleware products are typically based on one of two underlying mechanisms:
Message-passing or RPC (Remote procedure calls)

16. Message-passing schemes
Reliable
Guarantees delivery if possible - Not necessary to let the sending process know that the message was delivered
Unreliable
Send the message out into the communication network without reporting success or failure - Reduces complexity and overhead
Blocking
Send does not return control to the sending process until the message has been transmitted
OR does not return control until an acknowledgment is received
Receive does not return until a message has been placed in the allocated buffer
Nonblocking
Process is not suspended as a result of a Send or a Receive
Efficient and flexible
Difficult to debug

17. Clusters Clusters Compared to SMP
Alternative to symmetric multiprocessing (SMP)
Group of interconnected, whole computers working together as a unified computing resource
illusion is one machine
system can run on its own
Clusters Compared to SMP
SMP is easier to manage and configure
SMP takes up less space and draws less power
Clusters are better for incremental and absolute scalability
Add new systems in small increments
Can have dozens of machines each of which is a multiprocessor
Clusters are superior in terms of availability
Failure of one node does not mean loss of service
Clusters have superior price/performance

18. Beowulf and Linux Clusters
Mass market commodity components (No custom components)
A dedicated, private network (LAN or WAN or internetworked combination)
Easy replication from multiple vendors
Scalable I/O
A freely available software base
Returning the design and improvements to the community

19. Issues on Clusters Failure management Load balancing
Highly available vs. fault-tolerant clusters
Highly available clusters offers a high probability that all resources will be in service
Fault-tolerant cluster ensures that all resources are always available (use of redundant disks/processors etc.)
Load balancing
When a new computer is added to the cluster, the load-balancing facility should automatically include this computer in scheduling applications
Parallelizing Computation
Parallelizing compiler
Parallelized application

20. Parallelizing Computation
Parallelizing compiler
determines, at compile time, which parts of an application can be executed in parallel
performance depends on the nature of the problem and how well the compiler is designed
Parallelized application
the programmer writes the application from the outset to run on a cluster and uses message passing to move data, as required, between cluster nodes
this places a high burden on the programmer but may be the best approach for exploiting clusters for some applications
In some cases, effective use of a cluster requires executing software from a single application in parallel.
Three general approaches to the problem:
Parallelizing compiler:
A parallelizing compiler determines, at compile time, which parts of an application can be executed in parallel.
These are then split off to be assigned to different computers in the cluster.
Performance depends on the nature of the problem and how well the compiler is designed.
Parallelized application:
The programmer writes the application from the outset to run on a cluster and uses message passing to move data, as required, between cluster nodes.
This places a high burden on the programmer but may be the best approach for exploiting clusters for some applications.
Parametric computing:
This approach can be used if the essence of the application is an algorithm or program that must be executed a large number of times, each time with a different set of starting conditions or parameters.
Parametric computing
this approach can be used if the essence of the application is an algorithm or program that must be executed a large number of times, each time with a different set of starting conditions or parameters
for this approach to be effective, parametric processing tools are needed to organize, run, and manage the jobs in an orderly manner