Optimal Client-Server Assignment for
Internet Distributed Systems
ABSTRACT:
We investigate an underlying mathematical model and
algorithms for optimizing the performance of a class of distributed systems
over the Internet. Such a system consists of a large number of clients who
communicate with each other indirectly via a number of intermediate servers.
Optimizing the overall performance of such a system then can be formulated as a
client-server assignment problem whose aim is to assign the clients to the
servers in such a way to satisfy some prespecified requirements on the
communication cost and load balancing. We show that 1) the total communication
load and load balancing are two opposing metrics, and consequently, their
tradeoff is inherent in this class of distributed systems; 2) in general,
finding the optimal client-server assignment for some prespecified requirements
on the total load and load balancing is NP-hard, and therefore; 3) we propose a
heuristic via relaxed convex optimization for finding the approximate solution.
Our simulation results indicate that the proposed algorithm produces superior
performance than other heuristics, including the popular Normalized Cuts
algorithm.
EXISTING SYSTEM:
A typical distributed system consists of
a mix of servers and clients. The servers are more computational and resource
powerful than the clients. A classical example of such systems is e-mail. When
a client A sends an e-mail to another client B, A does not send the e-mail
directly to B. Instead, A sends its message to its e-mail server which has been
previously assigned to handle all the e-mails to and from A. This server relays
A’s e-mail to another server which has been previously assigned to handle
e-mails for B. B then reads A’s e-mail by downloading the e-mail from its
server. Importantly, the e-mail servers communicate with each other on behalf
of their clients. The main advantage of this architecture is specialization, in
the sense that the powerful dedicated e-mail servers release their clients from
the responsibility associated with many tasks including processing and storing
e-mails, and thus making e-mail applications more scalable. A more interesting
scenario is the Instant Messaging System (IMS). An IMS allows real time
text-based communication between two or more participants over the Internet.
Each IMS client is associated with an IMS server which handles all the instant
messages for its clients. Similar to e-mail servers, IMS servers relay instant
messages to each other on behalf on their clients. In an IMS that uses the XMPP
(Jabber) protocol such as Google Talk, clients can be assigned to servers
independent of their organizations.
DISADVANTAGES
OF EXISTING SYSTEM:
We use multiple servers; we also need to balance the
communication load among the servers for the following reasons:
v If
one server is overloaded, we need to add another server to distribute the load,
which is economically inefficient and usually increases the overall
communication load
v As
a heavily loaded server typically exhibits a low performance, we would like to
avoid the situation.
v To
minimize the amount of total communication load, assigning all clients to one
server is optimal. However, it is impossible due to overloading and completely
loses the load balance. Simple load balancing does not usually take account of
reducing the overall communication load.
PROPOSED SYSTEM:
In the proposed system the primary
contribution is a heuristic algorithm via relaxed convex optimization that
takes a given communication pattern among the clients as an input, and produces
an approximately optimal client-server assignment for a prespecified tradeoff
between load balance and communication cost. we must strike a balance between
reducing the overall communication load and increasing the load fairness among
the servers, i.e., the load balance.
ADVANTAGES
OF PROPOSED SYSTEM:
The advantages of the proposed system have follows:
ü The
two groups have different number of servers, a server within a group with fewer
servers will likely to have a higher load than a server in the group with more
servers. This reduces the load balance.
ü We
describe a number of emerging applications that have the potential to benefit
from the client-server assignment problem.
SYSTEM ARCHITECTURE:
ALGORITHMS USED:
SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
ü Processor - Pentium –IV
ü Speed - 1.1
Ghz
ü RAM - 256
MB(min)
ü Hard Disk -
20 GB
ü Key Board -
Standard Windows Keyboard
ü Mouse - Two
or Three Button Mouse
ü Monitor - SVGA
SOFTWARE CONFIGURATION:-
ü Operating System : Windows XP
ü Programming Language :
JAVA
ü Java Version :
JDK 1.6 & above.
REFERENCE:
Hiroshi Nishida, Member, IEEE, and Thinh
Nguyen, Member, IEEE-“Optimal Client-Server Assignment for Internet Distributed
Systems”-IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24, NO. 3,
MARCH 2013.