Wireless Distributed Computing on the Android Platform
| dc.contributor.author | Karra, Kiran | en |
| dc.contributor.committeechair | Clancy, Thomas Charles III | en |
| dc.contributor.committeemember | Reed, Jeffrey H. | en |
| dc.contributor.committeemember | White, Christopher Jules | en |
| dc.contributor.department | Electrical and Computer Engineering | en |
| dc.date.accessioned | 2014-03-14T20:46:14Z | en |
| dc.date.adate | 2012-10-23 | en |
| dc.date.available | 2014-03-14T20:46:14Z | en |
| dc.date.issued | 2012-09-27 | en |
| dc.date.rdate | 2012-10-23 | en |
| dc.date.sdate | 2012-10-01 | en |
| dc.description.abstract | The last couple of years have seen an explosive growth in smartphone sales. Additionally, the computational power of modern smartphones has been increasing at a high rate. For example, the popular iPhone 4S has a 1 GHz processor with 512 MB of RAM [5]. Other popular smartphones such as the Samsung Galaxy Nexus S also have similar specications. These smartphones are as powerful as desktop computers of the 2005 era, and the tight integration of many dierent hardware chipsets in these mobile devices makes for a unique mobile platform that can be exploited for capabilities other than traditional uses of a phone, such as talk and text [4]. In this work, the concept using smartphones that run the Android operating system for distributed computing over a wireless mesh network is explored. This is also known as wireless distributed computing (WDC). The complexities of WDC on mobile devices are different from traditional distributed computing because of, among other things, the unreliable wireless communications channel and the limited power available to each computing node. This thesis develops the theoretical foundations for WDC. A mathematical model representing the total amount of resources required to distribute a task with WDC is developed. It is shown that given a task that is distributable, under certain conditions, there exists a theoretical minimum amount of resources that can be used in order to perform a task using WDC. Finally, the WDC architecture is developed, an Android App implementation of the WDC architecture is tested, and it is shown in a practical application that using WDC to perform a task provides a performance increase over processing the job locally on the Android OS. | en |
| dc.description.degree | Master of Science | en |
| dc.identifier.other | etd-10012012-214953 | en |
| dc.identifier.sourceurl | http://scholar.lib.vt.edu/theses/available/etd-10012012-214953/ | en |
| dc.identifier.uri | http://hdl.handle.net/10919/35256 | en |
| dc.publisher | Virginia Tech | en |
| dc.relation.haspart | Karra_K_T_2012.pdf | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | android | en |
| dc.subject | mesh networks | en |
| dc.subject | wireless distributed computing | en |
| dc.title | Wireless Distributed Computing on the Android Platform | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Electrical and Computer Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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