ABSTRACT
Reducing
the communication energy is essential to facilitate the growth of emerging
mobile applications. In this paper, we introduce signal strength into
location-based applications to reduce the energy consumption of mobile devices
for data reception. First, we model the problem of data fetch scheduling, with
the objective of minimizing the energy required to fetch location-based
information without impacting the application’s semantics adversely. To solve
the fundamental problem, we propose a dynamic-programming algorithm and prove
its optimality in terms of energy savings. Then, we perform post optimal
analysis to explore the tolerance of the algorithm to signal strength
fluctuations. Finally, based on the algorithm, we consider implementation
issues. We have also developed a virtual tour system integrated with existing
Web applications to validate the practicability of the proposed concept. The
results of experiments conducted based on real-world case studies are very
encouraging and demonstrate the applicability of the proposed algorithm toward
signal strength fluctuations.
AIM
The
aim of this paper is propose a dynamic-programming algorithm and prove its
optimality in terms of energy savings.
SCOPE
The
scope of this paper is perform post optimal analysis to explore the tolerance
of the algorithm to signal strength fluctuations
EXISTING SYSTEM
EXISTING SYSTEM
Many
existing approaches leverage the complementary characteristics of WiFi and
3Gi.e., WiFi to improve energy efficiency, and 3G to maintain ubiquitous connectivity.
Recently, it has been observed that signal strength has a direct impact on the
communication energy consumption. The communication energy per bit when the
signal is weak could be as much as six times more than that when the signal is
strong . This phenomenon has proved evident in both WiFi and 3G . The reason for such a phenomenon
results mainly from the adaptive modulation and power control employed in
wireless network systems. Based on the observation, it could be promising to
exploit signal strength information to reduce the communication energy of
mobile devices. However, the challenge is how to exploit this observation to
gain energy efficiency. In particular, signal strength may fluctuate with time
due to multipath fading, so attention has to be paid to the impact of signal
fluctuations on the practicability of the proposed approaches in real-world
environments.
DISADVANTAGES
· The
problem of data fetches scheduling, with the objective of minimizing the energy
required to fetch location-based information without impacting the
application’s semantics adversely.
· Reducing
the communication energy
PROPOSED SYSTEM
In
this project, propose a dynamic-programming algorithm to solve the fundamental
problem. The solution involves scheduling the fetching of location-based
information at appropriate locations so as to minimize the total energy
consumption. We prove that the algorithm is optimal in terms of energy savings.
Third, we perform post optimal analysis to explore how the algorithm responds
to signal strength fluctuations, especially the fluctuation range within which
the derived solution remains optimal or feasible. The analysis helps to
understand the impact of signal fluctuations on the practicability of this new
concept in real-world environments. Fourth, we discuss technical implementation
issues that arise when introducing signal strength into location-based
applications for energy savings. Fifth, we conducted a series of experiments in
Taipei City, Taiwan, for real-world case studies. The results show that an
Android smart phone of HTC EVO 3D can achieve a significant energy reduction
when accessing location-based applications. Finally, we discuss the limitations
of our work and highlight issues that require further investigation. The
concept, once proved practicable and embraced gradually, could be extended and
applied to other variants of location-based applications based on the knowledge
learned from this work.
ADVANTAGES
· Smartphone
can achieve energy savings of 46%–70% and 35%–60% for pedestrian users along
the two routes,
· The
algorithm can tolerate signal strength fluctuations very well when the objects
along a route is sparse.
SYSTEM CONFIGURATION
HARDWARE REQUIREMENTS:-
· Processor - Pentium –III
·
Speed - 1.1 Ghz
·
RAM - 256 MB(min)
·
Hard
Disk - 20 GB
·
Floppy
Drive - 1.44 MB
·
Key
Board - Standard Windows Keyboard
·
Mouse - Two or Three Button Mouse
·
Monitor -
SVGA
SOFTWARE REQUIREMENTS:-
·
Operating
System :Android OS
·
Front
End : JAVA
·
Database
: SqLite
·
Tool :Eclipse
REFERENCES
Pi-Cheng
Hsiu, Chih-Chuan
Cheng “Extend Your Journey: Considering Signal Strength and Fluctuation in
Location-Based Applications” IEEE/ACM Transactions on Networking,
Volume:23, Issue: 2 February
2014.
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