Name
Abstract | ||
|---|---|---|
\With rapid increases in demand for mobile data, mobile network operators are trying to expand wireless network capacity by deploying WiFi hotspots to offload their mobile traffic. However, these network-centric methods usually do not fulfill interests of mobile users (MUs). MUs consider many problems to decide whether to offload their traffic to a complementary WiFi network. In this paper, we study the WiFi offloading problem from MU's perspective by considering delay-tolerance of traffic, monetary cost, energy consumption as well as the availability of MU's mobility pattern. We first formulate the WiFi offloading problem as a finite-horizon discrete-time Markov decision process (FDTMDP) with known MU's mobility pattern and propose a dynamic programming based offloading algorithm. Since MU's mobility pattern may not be known in advance, we then propose a reinforcement learning based offloading algorithm, which can work well with unknown MU's mobility pattern. Extensive simulations are conducted to validate our proposed offloading algorithms. |
Year | Venue | Keywords |
|---|---|---|
2016 | Asia-Pacific Network Operations and Management Symposium-APNOMS | WiFi,mobile data offloading,reinforcement learning,energy-aware |
Field | DocType | ISSN |
Mobile computing,Wireless network,Computer science,Mobile data offloading,Markov decision process,Computer network,Small cell,Cellular network,Mobile broadband,Reinforcement learning,Distributed computing | Conference | 2576-8565 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Zhang | 1 | 59 | 12.03 |
| Bo Gu | 2 | 33 | 15.79 |
| Zhi Liu | 3 | 241 | 32.87 |
| Kyoko Yamori | 4 | 59 | 16.35 |
| Yoshiaki Tanaka | 5 | 49 | 14.72 |