A Dual Framework and Algorithms for Targeted Online Data Delivery
A
Dual Framework and Algorithms for Targeted Online Data Delivery
Abstract:
A
variety of emerging online data delivery applications challenge existing
techniques for data delivery to human users, applications, or middleware that
are accessing data from multiple autonomous servers. In this paper, we develop
a framework for formalizing and comparing pull-based solutions and present dual
optimization approaches. The first approach, most commonly used nowadays,
maximizes user utility under the strict setting of meeting a priori constraints
on the usage of system resources. We present an alternative and more flexible
approach that maximizes user utility by satisfying all users. It does this
while minimizing the usage of system resources. We discuss the benefits of this
latter approach and develop an adaptive monitoring solution Satisfy User
Profiles(SUPs). Through formal analysis, we identify sufficient optimality
conditions for SUP. Using real (RSS feeds) and synthetic traces, we empirically
analyze the behavior of SUP under varying conditions. Our experiments show that
we can achieve a high degree of satisfaction of user utility when the
estimations of SUP closely estimate the real event stream, and has the
potential to save a significant amount of system resources. We further show
that SUP can exploit feedback to improve user utility with only a moderate increase
in resource utilization.
Existing System:
·
Most commonly used nowadays, maximizes
user utility under the strict setting of meeting a priori constraints on the
usage of system resources.
·
Currently, the burden of when to probe
an RSS resource lies with the client.
Although RSS providers use a
Time-To-Live (TTL) measure to suggest a probing schedule.
·
Due to heavy workloads that may be
imposed by client probes (especially on popular Web feed providers such as
CNN), about 80 percent of the feeds have an average size smaller than 10 KB,
suggesting that items are promptly removed from the feeds. These statistics on
refresh frequency and volatility illustrate the challenge faced by a proxy in
satisfying user needs.
Proposed System:
·
We develop a framework for formalizing
and comparing pull-based solutions and present dual optimization approaches.
·
Minimizing the number of probes to
sources is important for pull-based applications to conserve resources and
improve scalability.
·
Solutions that can adapt to changes in
source behavior are also important due to the difficulty of predicting when
updates occur. In this paper, we have addressed these challenges.
·
We have addressed these challenges
through the use of a new formalism of a dual optimization problem, reversing
the roles of user utility and system resources.
·
We have formally shown that SUP is optimal
for OptMon2 and under certain restrictions can be optimal for OptMon1 as well.
·
We have empirically shown, using RSS
data traces as well as synthetic data, that SUP can satisfy user profiles and
capture more updates compared to existing policies.
·
SUP is adaptive and can dynamically change
monitoring schedules.
KEYWORDS:
Generic Technology Keywords: Database,
User Interface, Programming
Specific Technology Keywords: C#.Net,
ASP.Net, MS SqlServer-08
Project Keywords: Presentation, Business Object, Data Access Layer
SDLC Keywords: Analysis, Design, Code, Testing, Implementation, Maintenance
SYSTEM
CONFIGURATION
HARDWARE
CONFIGURATION
S.NO
|
HARDWARE
|
CONFIGURATIONS
|
1
|
Operating System
|
Windows 2000 & XP
|
2
|
RAM
|
1GB
|
3
|
Processor (with Speed)
|
Intel
Pentium IV (3.0 GHz) and Upwards
|
4
|
Hard Disk Size
|
40 GB and above
|
5
|
Monitor
|
15’ CRT
|
SOFTWARE
CONFIGURATION
S.NO
|
SOFTWARE
|
CONFIGURATIONS
|
1
|
Platform
|
Microsoft Visual Studio
|
2
|
Framework
|
.Net Framework 4.0
|
3
|
Language
|
C#.Net
|
4
|
Front End
|
Asp.Net (WCF)
|
5
|
Back End
|
SQL Server 2008
|
Categories:
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