Tuesday, 20 October 2015
Extend Your Journey: Considering Signal Strength and Fluctuation in Location-Based Applications
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.
The aim of this paper is propose a dynamic-programming algorithm and prove its optimality in terms of energy savings.
The scope of this paper is perform post optimal analysis to explore the tolerance of the algorithm to signal strength fluctuations
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.
· 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
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.
· 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.
· 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
· Operating System :Android OS
· Front End : JAVA
· Database : SqLite
· Tool :Eclipse
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.