2012
DOI: 10.4304/jnw.7.4.699-706
|View full text |Cite
|
Sign up to set email alerts
|

Performance Analysis of a Novel LBS Application Using MBMS&TPEG in 3G Mobile Networks

Abstract: Location-based services (LBS) provide content that is dynamically customized according to the user's location. These services are commonly delivered to mobile devices. Due to wireless bandwidth limit, broadcasting based transmission technology is one of main methods to provide dynamic real-time information or public emergency for commercial LBS applications. Multimedia Broadcast and Multicast Services (MBMS) is a broadcasting service offered via existing GSM and UMTS cellular networks. MBMS has the major benef… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2013
2013
2015
2015

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 8 publications
(3 citation statements)
references
References 4 publications
(5 reference statements)
0
3
0
Order By: Relevance
“…Studies [3] [7] utilizes data locality in VMs to improve the performance. Study [4] builds a model that defines metrics to analyze the data allocation problem. Study [7] proposes a MapReduce framework on virtual machine which takes full advantage of data locality, virtual machine live migration and checkpoint.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Studies [3] [7] utilizes data locality in VMs to improve the performance. Study [4] builds a model that defines metrics to analyze the data allocation problem. Study [7] proposes a MapReduce framework on virtual machine which takes full advantage of data locality, virtual machine live migration and checkpoint.…”
Section: Related Workmentioning
confidence: 99%
“…Hadoop, which is the most popular open-sourced MapReduce framework implementation, is used by Amazon, Adobe, Ebay, Facebook, IBM, Last.fm, Twitter, CMU and ETH etc. almost 150 corporations and research center [4].…”
Section: Introductionmentioning
confidence: 99%
“…Support vector machines (SVM) theory is a machine learning method based on the statistical learning theory [11,12,13]. By learning algorithm, SVM can automatically find those support vectors which have greater ability to distinguish classifications, construct classifier, and maximize the interval between classes, thus it has better promotion and higher classification accuracy [2,14,15]. In the classification study of remote sensing image, application of SVM classification do not need data dimensionality reduction, and has high performance in algorithm's convergence, training speed and classification accuracy [16,17].…”
Section: Introductionmentioning
confidence: 99%