Name
Abstract | ||
|---|---|---|
Smartphones now become an indispensable part of our daily life. However, their continuing operations consume lots of battery energy. For example, a fully-charged smartphone usually cannot support its continuing operation for a whole day. A fundamental problem related to this energy issue is how to prolong the smartphone lifetime so that it can last as long as possible to meet its user needs. Wireless energy transfer has been demonstrated as a promising technique to address this challenge. In this paper, we study the smartphone charging problem, using wireless chargers deployed on public commuters, e.g., subway trains, to charge energy-critical smartphones when their users take subway trains to work or go home. Since the residual energy of different smartphones are significantly different, the charging satisfactions of different users are essentially different too. In this paper we formulate this charging problem as a novel optimization problem that allocates limited wireless chargers on subway trains to charge energy-critical smartphones such that the overall charging satisfaction of mobile users is maximized, for a given monitoring period (e.g., one day). Specifically, we first devise a 1 over 3-approximation algorithm if the travel trajectory of each smartphone user in the monitoring period is given; otherwise, we devise an online algorithm dealing with dynamic energy-critical smartphone charging requests. We finally evaluate the performance of the proposed algorithms through experimental simulations with a real dataset of subway-taking in San Francisco. The experimental results show that the proposed algorithms are very promising, and 93.9% of energy-critical user smartphones can be satisfactorily charged in one-day monitoring period. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/PCCC.2015.7410303 | IPCCC |
Keywords | Field | DocType |
public commuters,wireless energy transfer,battery energy,smartphone lifetime,smartphone charging problem,energy-critical smartphones,1/2-approximation algorithm,online algorithm,smartphone charging requests,San Francisco,energy-critical user smartphones | Online algorithm,Wireless,Residual energy,Computer science,Computer network,Real-time computing,Battery energy,Energy transfer,Train,Optimization problem,Trajectory | Conference |
ISSN | Citations | PageRank |
1097-2641 | 1 | 0.36 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenzheng Xu | 1 | 315 | 21.18 |
| Weifa Liang | 2 | 1676 | 134.75 |
| Su Hu | 3 | 4 | 1.12 |
| Xiaola Lin | 4 | 1099 | 78.09 |
| Jian Peng | 5 | 59 | 11.21 |