Cross-Layer Analysis of the End-to-End Delay
Distribution in Wireless Sensor Networks
Abstract:
Emerging applications of wireless sensor networks (WSNs) require real-time quality-of-service
(QoS) guarantees to be provided by the network. Due to the nondeterministic impacts of the
wireless channel and queuing mechanisms, probabilistic analysis of QoS is essential. One important
metric of QoS in WSNs is the probability distribution of the end-to-end delay. Compared to other
widely used delay performance metrics such as the mean delay, delay variance, and worst-case
delay, the delay distribution can be used to obtain the probability to meet a specific deadline for
QoS-based communication in WSNs. To investigate the end-to-end delay distribution, in this paper,
a comprehensive cross-layer analysis framework, which employs a stochastic queuing model in
realistic channel environments, is developed. This framework is generic and can be parameterized
for a wide variety of MAC protocols and routing protocols. Case studies with the CSMA/CAMAC
protocol and an any cast protocol are conducted to illustrate how the developed framework can
analytically predict the distribution of the end-to-end delay. Extensive test-bed experiments and
simulations are performed to validate the accuracy of the framework for both deterministic and
random deployments. Moreover, the effects of various network parameters on the distribution of
end-to-end delay are investigated through the developed framework. To the best of our knowledge,
this is the first work that provides a generic, probabilistic cross-layer analysis of end-to-end delay
in WSNs.
Introduction:
WIRELESS sensor networks (WSNs) have been utilized in many applications as both a
connectivity infrastructure and a distributed data generation network due to their
Ubiquitous and flexible nature [6]. Increasingly, a large number of WSN applications
require real-time quality-of-service (Quos) guarantees [5]. Such QoS requirements usually
depend on two common parameters: timing and reliability. In this paper, we focus on the
probability distribution of the end-to-end delay in WSNs. Characterization of the end-toend delay distributions fundamental for real-time communication applications with
probabilistic QoS guarantees. Indeed, the cumulative distribution function (cdf) of the
delay for a given deadline can be used as a probabilistic metric for reliability and
timeliness.
Existing System:
Emerging applications of wireless sensor networks (WSNs) require real-time quality-ofservice (QoS) guarantees to be provided by the network. Due to the non deterministic
Impacts of the wireless channel and queuing mechanisms, probabilistic analysis of QoS
Is essential. One important metric of QoS in WSNs is the probability distribution of the
end-to-end delay. Compared to other widely used delay performance metrics such as the
mean delay, delay variance, and worst-case delay, the delay distribution can be used to
obtain the probability to meet a specific deadline for QoS-based communication in WSNs.
Proposed System:
To investigate the end-to-end delay distribution, in this paper, a comprehensive cross-layer
analysis framework, which employs a stochastic queuing model in realistic channel
environments, is developed. This framework is generic and can be parameterized for a
wide variety of MAC protocols and routing protocols.
Modules:
*Sensor.
*Client.
*server.
Sensor:
A sensor is a technological device or biological organ that detects, or senses, a signal or physical
condition and chemical compounds.
Software requirements:
 VS .NET 2008
 C#

Windows XP.
HARDWARE REQUIREMENTS:
 Hard disk
:
40 GB
 RAM
:
512mb
 Processor
:
Pentium IV
 Monitor
:
17” Color monitor
SYSTEM ANALYSIS
This system deals with the problem of Network Traffic. It also
solves the major problem faced due to this network traffic and cost effectiveness.
Actually we won’t take care of size of data that we used to send to the receiver
we just attach the document and send it to our receiver. But causes lot of
problems in the network. It not only affect our side but also for other user who
depends on that particular network.
We have concentrate more on the network side because once
the network gets down everyone of the user will be troubled. So our project gives
the some rules to the user regarding the size of data. The Administrator may
dynamically be able to change the size of data regarding to the network traffic
that’s it.
About the Organization
KRESTTECHNOLOGIES
An ISO 9001: 2000 Certified Company
KREST TECHNOLOGIES is an ISO 9001: 2000 certified was established in 2005 for course design,
conduct and placement guidance. Based in Hyderabad, we are offering High Application Oriented
Training with 100% Placement Assistance & Lateral Placements. Krest provides academic projects in
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Data warehousing, .Net, C# and Java/J2EE as well as develops its own range of quality Embedded
Products.
Krest has always been on top of the players in this profession. Krest has successfully powered itself in
training thousands of students and professionals. The teaching philosophy deployed, thrives to create indepth knowledge about the subject at hand. We believe that depth is an essential ingredient to achieve
heights in training and development. Students from KREST TECHNOLOGIES have proved the point by
their work in the fast paced industry world.
Every bit of that hard earned knowledge came as a result of years of highly specialized work and contact
with thousands of people
We are old in that the experiences of our senior staff are almost unmatched in their knowledge of the
subjects being addressed at our conferences and speaking engagements.
PROJECTS: Crest have sound backing of our resources for the effectual execution of academic projects.
Our technical expertise along with working knowledge has made us a responsible organization in the
eyes of our valued clients. Thus, we are recognized to be one of the most trusted institutes offering
Advance Training, PROJECTS for students.
Krest provides academic final year projects of M.Tech, MS, B.E. / B.Tech, MCA & Msc in the streams of:





Embedded
Fingerprint & Smartcard based
Digital signal processing
Power Electronics,
Fuzzy and Neural Networks



IEEE Projects
.Net/C#.Net, Linux
Java/J2EE
Data Warehousing
Wireless Communication( ZigBee, Bluetooth, GSM, RF,IR)
Thanks & Best Regards
VEERU.K
Chief Executive Officer ( C.E.O )
Krest Technologies
Mobile: 9000404185
System Communications
Instrumentation
Digital Image Processing
Power Systems
VLSI( Verilog and VHDL)