A simulation framework to ensure data consistency in sensor networks

K-REx Repository

Show simple item record

dc.contributor.author Shah, Nikhil Jeevanlal
dc.date.accessioned 2008-01-11T15:49:51Z
dc.date.available 2008-01-11T15:49:51Z
dc.date.issued 2008-01-11T15:49:51Z
dc.identifier.uri http://hdl.handle.net/2097/541
dc.description.abstract The objective of this project is to address the problem of data consistency in sensor network applications. An application may involve data being gathered from several sources to be delivered to multiple sinks, resulting in multiple data streams with several sources and sinks for each stream. There may be several inter-stream constraints to be satisfied in order to ensure data consistency. In this report, we model this problem as that of variable sharing between the components in an application, and propose a framework for implementing variable sharing in a distributed sensor network. In this framework, we define the notion of variable sharing in component based systems. We allow the application designer to specify data consistency constraints in an application. Given an application, we implement a tool to identify various types of shared variables in an application. Given the shared variables and the data consistency constraints, we provide an infrastructure to implement the shared variables. This infrastructure has tools to synthesize the code to be deployed on each of the nodes in the physical topology. The infrastructure has been built for the TinyOS platform. We have evaluated the framework using several examples using the TOSSIM simulator. en
dc.language.iso en_US en
dc.publisher Kansas State University en
dc.subject Sensor Networks en
dc.subject Data Consistency en
dc.subject Atomic Consistency en
dc.subject Causal Consistency en
dc.title A simulation framework to ensure data consistency in sensor networks en
dc.type Report en
dc.description.degree Master of Science en
dc.description.level Masters en
dc.description.department Department of Computing and Information Sciences en
dc.description.advisor Gurdip Singh en
dc.subject.umi Computer Science (0984) en
dc.date.published 2008 en
dc.date.graduationmonth May en


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search K-REx


Advanced Search

Browse

My Account

Statistics








Center for the

Advancement of Digital

Scholarship

118 Hale Library

Manhattan KS 66506


(785) 532-7444

cads@k-state.edu