Abstract
| Original language | Undefined |
|---|---|
| Title of host publication | 7th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2011 |
| Place of Publication | Wuhan |
| Publisher | IEEE |
| Pages | 237-244 |
| Number of pages | 8 |
| ISBN (Print) | 2160-4886 |
| DOIs | |
| Publication status | Published - 10 Oct 2011 |
Publication series
| Name | |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 2160-4886 |
Keywords
- METIS-285063
- Context-aware connectivity management
- IR-79532
- BSS-Neurotechnology and cellular engineering
- EWI-21389
- virtual social community
- network context data
Cite this
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Towards a feasible social-based methodology to manage wireless connectivity context data. / Rigolin Ferreira Lopes, R.; van Beijnum, Bernhard J.F.; dos Santos Moreira, Edson.
7th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2011. Wuhan : IEEE, 2011. p. 237-244.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Towards a feasible social-based methodology to manage wireless connectivity context data
AU - Rigolin Ferreira Lopes, R.
AU - van Beijnum, Bernhard J.F.
AU - dos Santos Moreira, Edson
N1 - QoS , context-aware connectivity management , feasible social-based methodology , handoff mechanisms , location-based social media , mobility management , mobility predictors , power consumption , wireless connectivity context data , wireless connectivity islands
PY - 2011/10/10
Y1 - 2011/10/10
N2 - Wireless connectivity context data is composed by date, time, geographical localization, and QoS metrics, to cite the most common. These data are employed, in a particular way, by fundamental techniques for context-aware connectivity management, e.g. mobility predictors, handoff mechanisms and mobility management. For instance, mobility and QoS predictors use, as input, previous georeferenced network context data. Normally, context data are available in hardly updated databases with considerable size. In this paper, we propose a social-based methodology to allow mobile users collaborate to discover wireless connectivity islands. The methodology is composed by methods to gather, combine, summarize and share context data inside the users' social circles. We, also, designed a schema to mashup context data with location-based social media. It is result of a prototyping effort and we focus the discussion on its feasibility and limitations in terms of storage size, power consumption and QoS metrics
AB - Wireless connectivity context data is composed by date, time, geographical localization, and QoS metrics, to cite the most common. These data are employed, in a particular way, by fundamental techniques for context-aware connectivity management, e.g. mobility predictors, handoff mechanisms and mobility management. For instance, mobility and QoS predictors use, as input, previous georeferenced network context data. Normally, context data are available in hardly updated databases with considerable size. In this paper, we propose a social-based methodology to allow mobile users collaborate to discover wireless connectivity islands. The methodology is composed by methods to gather, combine, summarize and share context data inside the users' social circles. We, also, designed a schema to mashup context data with location-based social media. It is result of a prototyping effort and we focus the discussion on its feasibility and limitations in terms of storage size, power consumption and QoS metrics
KW - METIS-285063
KW - Context-aware connectivity management
KW - IR-79532
KW - BSS-Neurotechnology and cellular engineering
KW - EWI-21389
KW - virtual social community
KW - network context data
U2 - 10.1109/WiMOB.2011.6085398
DO - 10.1109/WiMOB.2011.6085398
M3 - Conference contribution
SN - 2160-4886
SP - 237
EP - 244
BT - 7th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2011
PB - IEEE
CY - Wuhan
ER -