Smartphone traffic characteristics and context dependencies
| dc.contributor.advisor | Eager, Derek | en_US |
| dc.contributor.advisor | Stanley, Kevin G. | en_US |
| dc.contributor.committeeMember | Kusalik, Anthony J. | en_US |
| dc.contributor.committeeMember | Makaroff, Dwight | en_US |
| dc.contributor.committeeMember | Dinh, Anh v. | en_US |
| dc.creator | Kaisar, Shahriar | en_US |
| dc.date.accessioned | 2013-01-03T22:28:09Z | |
| dc.date.available | 2013-01-03T22:28:09Z | |
| dc.date.created | 2012-01 | en_US |
| dc.date.issued | 2012-01-19 | en_US |
| dc.date.submitted | January 2012 | en_US |
| dc.description.abstract | Smartphone traffic contributes a considerable amount to Internet traffic. The increasing popularity of smartphones in recent reports suggests that smartphone traffic has been growing 10 times faster than traffic generated from fixed networks. However, little is known about the characteristics of smartphone traffic. A few recent studies have analyzed smartphone traffic and given some insight into its characteristics. However, many questions remain inadequately answered. This thesis analyzes traffic characteristics and explores some important issues related to smartphone traffic. An application on the Android platform was developed to capture network traffic. A user study was then conducted where 39 participants were given HTC Magic phones with data collection applications installed for 37 days. The collected data was analyzed to understand the workload characteristics of smartphone traffic and study the relationship between participant contexts and smartphone usage. The collected dataset suggests that even in a small group of participants a variety of very different smartphone usage patterns occur. Participants accessed different types of Internet content at different times and under different circumstances. Differences between the usage of Wi-Fi and cellular networks for individual participants are observed. Download-intensive activities occurred more frequently over Wi-Fi networks. Dependencies between smartphone usage and context (where they are, who they are with, at what time, and over which physical interface) are investigated in this work. Strong location dependencies on an aggregate and individual user level are found. Potential relationships between times of the day and access patterns are investigated. A time-of-day dependent access pattern is observed for some participants. Potential relationships between movement and proximity to other users and smartphone usage are also investigated. The collected data suggests that moving participants used map applications more. Participants generated more traffic and primarily downloaded apps when they were alone. The analyses performed in this thesis improve basic understanding and knowledge of smartphone use in different scenarios. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10388/ETD-2012-01-284 | en_US |
| dc.language.iso | eng | en_US |
| dc.subject | smartphone traffic | en_US |
| dc.subject | context dependency | en_US |
| dc.subject | location dependency | en_US |
| dc.subject | time of day dependency | en_US |
| dc.subject | cellular network | en_US |
| dc.subject | Wi-Fi network | en_US |
| dc.subject | proximity dependency | en_US |
| dc.subject | heterogeneity | en_US |
| dc.title | Smartphone traffic characteristics and context dependencies | en_US |
| dc.type.genre | Thesis | en_US |
| dc.type.material | text | en_US |
| thesis.degree.department | Computer Science | en_US |
| thesis.degree.discipline | Computer Science | en_US |
| thesis.degree.grantor | University of Saskatchewan | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Science (M.Sc.) | en_US |