Utilize signal traces from others a crowdsourcing perspective of energy saving in cellular data communication +91-9994232214,8144199666, ieeeprojectchennai@gmail.com, www.projectsieee.com, www.ieee-projects-chennai.com IEEE PROJECTS 2015-2016 ----------------------------------- Contact:+91-9994232214,+91-8144199666 Email:ieeeprojectchennai@gmail.com Support: ------------- Projects Code Documentation PPT Projects Video File Projects Explanation Teamviewer Support

1. Utilize Signal Traces from Others? A Crowd sourcing Perspective of
Energy Saving in Cellular Data Communication
Abstract:
With the tremendous growth in wireless network deployment and
increasing use of mobile devices, e.g., smart phones and tablets, improving
energy efficiency in such devices, especially with communication driven
workloads, is critical to providing a satisfactory user experience. Studies
show that signal strength plays an important role on energy consumption
of cellular data communications. While energy consumption can be
minimized by accurately predicting signal strengths and reacting to it in
real time, the dynamic nature of wireless environments makes signal
strengths highly unpredictable. In this paper, after analyzing in detail the
signal strength variation and its impact on energy consumption, we
propose to use crowd sourcing approach to optimize mobile devices’
energy efficiency by utilizing signal strength traces reported/shared by
other users/devices in cellular networks. Via a comprehensive
measurement study, we observe that signal strength traces collected from
different devices are pseudo identical, and they even exhibit similar
threshold-based behaviors in the relationship between signal strength and
device power consumption. Based on our observations, we propose a
predictive scheduling algorithm that: (i) selects the right set of signal

2. strength traces based on its location, (ii) applies a filter to smooth out signal
strengths and hide abrupt changes, (iii) digitizes the signal strength to
“good" and “bad" areas, and (iv) schedules transmissions based on power-
throughput characteristics to optimize the transmission energy efficiency.
To demonstrate the efficacy of the proposed algorithms, we prototype the
Crowd sourcing-based predicative scheduling algorithm on Android-based
smart phones. Our experiment results from real-life driving tests
demonstrate that, by leveraging others’ signal traces, mobile devices can
save energy up to 35% compared to the conventional opportunistic
scheduling, i.e., schedule transmissions only based on instantaneous
channel conditions.
Existing System:
Variations between strong and weak signal areas are large enough to pose
significant energy impact on mobile devices when running network driven
applications, as we show clearly in this paper.
As more and more people are increasingly connected to the Internet, crowd
sourcing stands out as an effective approach to either decrease cost for
certain tasks or to enable usage scenarios that are impossible otherwise.
The basic principle behind crowd sourcing is that it utilizes collective
intelligence from the crowd to solve a specific problem, e.g., reporting
news events. In this paper, we propose to use crowd sourcing approach to
obtain signal strength information and save energy for cellular data
communications.
Proposed System:

3. We aim to answer the questions mentioned above through a
comprehensive experimental study and evaluate the benefit via a
prototype implementation. We select High-Speed Packet Access (HSPA)
network for the measurement study, since it is currently the dominant
network for cellular data communications.
Six Android platforms are used to analyze their respective relationships of
signal strength vs. power consumption and signal strength vs. network
throughput.
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• RAM : 256 Mb.
Software Requirements:
• Operating system : - Windows XP.
• Front End : - JSP
• Back End : - SQL Server

4. Software Requirements:
• Operating system : - Windows XP.
• Front End : - .Net
• Back End : - SQL Server