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GLOBALSOFT TECHNOLOGIES 
IEEE PROJECTS & SOFTWARE DEVELOPMENTS 
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE 
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS 
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmai l.com 
Converged Architecture for Broadcast and 
Multicast 
Services in Heterogeneous Network 
Abstract:- 
MBMS provides point-to-multipoint (p-t-m) radio bearers 
and multicast support in the cellular network to support the streaming and file 
download services. This paper proposes a converged architecture for broadcast and 
multicast services in a heterogeneous network. To support the broadcast/multicast 
services in the long-term evolution (LTE) network, the standard enhances 
multimedia broadcast multicast service (MBMS). In the broadcast network, digital 
video broadcasting for handhelds (DVB-H) is the standard for broadcasting IP data 
services to user equipment (UE). Accordingly, the converged LTE and DVB-H 
network can be used to service the broadcast/multicast services. To employ the 
converged network, additional entities are required for the contents management, 
electronic service guide (ESG) management and resource management. Therefore, 
we propose several logical entities to fulfill functionality from the above 
mentioned issues. The proposed logical entities are as follows: an integrated
contents server, an integrated ESG server and an integrated management server. 
We also present several scenarios for implementing the converged architecture and 
compare the advantage of each scenario. Service providers can exploit the 
converged architecture according to preference and equipped devices. This study is 
of particular interest to the service providers because it provides the service 
providers with an insight of the various scenarios to make the converged 
architecture for broadcast/multicast service. 
Existing System 
 On top of these generic elements, we build an intuitive, fuzzy-based query 
evaluation mechanism that supports the service matchmaking process by 
employing and appropriately combining existing similarity metrics. 
 Structured network is organized in such a way that data items are located 
at specific nodes in the network, and those nodes maintain some state 
information to enable efficient retrieval of data. 
 Structured nodes are not efficient and flexible enough for applications 
where nodes join or leave the network frequently. 
 The Sequential Algorithm is used which increases the latency of the 
project. 
 Since the nodes are selected sequentially, if any node gets disconnected, 
the exact answer is not received. And identification of the disconnected 
node becomes tedious and sometimes impossible. 
Disadvantage 
 In the DVB-H network, the radio resource will be wasted if only a few users 
request the same content. And also, LTE network can serve restricted users 
because the available radio resource is limited.
 Therefore, the approach about the converged network is needed to exploit a 
complementary management. 
 we tackle the problems that arise upon service discovery, when users need to 
search for operations delivered by services of different types 
Proposed System 
 The proposed approach is based on the premise that service discovery 
should be orthogonal to the various service models and technologies. 
 The various proposed approaches only partially address the discovery of 
heterogeneous services, mainly because they were not fundamentally 
designed to do so. 
 The proposed matchmaker quantifies the similarity of an offered service 
operation with respect to a given request, while weights are used to 
differentiate the search criteria priorities 
 A converged architecture was proposed for an integrated network between 
LTE and DVB-H network 
 The proposed logical entities are as follows: an integrated contents server, 
an integrated ESG server and an integrated management server. 
 We also present several scenarios for implementing the converged 
architecture and compare the advantage of each scenario. 
Advantage
 The proposed a multiannotator approach to automatically constructing an 
annotation wrapper for annotating the search result records retrieved from any 
given web database. 
 Each of these annotators exploits one type of features for annotation and our 
experimental results show that each of the annotators is useful and they together 
are capable of generating high quality annotation. 
 We can join the nodes at random times and depart without a prior notification. 
HARDWARE REQUIREMENTS : 
 Hard disk : 500 GB 
 RAM : 512 MB 
 Processor Speed : 3.00GHz 
 Processor : Pentium IV Processor 
SOFTWARE REQUIREMENTS : 
 Front End : VS .NET 2010 
 Code Behind : C#.net 
 Back End : SQL SERVER 2005

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2014 IEEE DOTNET DATA MINING PROJECT Supporting privacy-protection-in-persona...
 
2014 IEEE DOTNET DATA MINING PROJECT Similarity preserving snippet based visu...
2014 IEEE DOTNET DATA MINING PROJECT Similarity preserving snippet based visu...2014 IEEE DOTNET DATA MINING PROJECT Similarity preserving snippet based visu...
2014 IEEE DOTNET DATA MINING PROJECT Similarity preserving snippet based visu...
 
2014 IEEE DOTNET DATA MINING PROJECT Product aspect-ranking-and--its-applicat...
2014 IEEE DOTNET DATA MINING PROJECT Product aspect-ranking-and--its-applicat...2014 IEEE DOTNET DATA MINING PROJECT Product aspect-ranking-and--its-applicat...
2014 IEEE DOTNET DATA MINING PROJECT Product aspect-ranking-and--its-applicat...
 
2014 IEEE DOTNET DATA MINING PROJECT Mining statistically significant co loca...
2014 IEEE DOTNET DATA MINING PROJECT Mining statistically significant co loca...2014 IEEE DOTNET DATA MINING PROJECT Mining statistically significant co loca...
2014 IEEE DOTNET DATA MINING PROJECT Mining statistically significant co loca...
 
2014 IEEE DOTNET DATA MINING PROJECT Lars an-efficient-and-scalable-location-...
2014 IEEE DOTNET DATA MINING PROJECT Lars an-efficient-and-scalable-location-...2014 IEEE DOTNET DATA MINING PROJECT Lars an-efficient-and-scalable-location-...
2014 IEEE DOTNET DATA MINING PROJECT Lars an-efficient-and-scalable-location-...
 
2014 IEEE DOTNET DATA MINING PROJECT Data mining with big data
2014 IEEE DOTNET DATA MINING PROJECT Data mining with big data2014 IEEE DOTNET DATA MINING PROJECT Data mining with big data
2014 IEEE DOTNET DATA MINING PROJECT Data mining with big data
 
2014 IEEE DOTNET DATA MINING PROJECT Anonymous query processing in road networks
2014 IEEE DOTNET DATA MINING PROJECT Anonymous query processing in road networks2014 IEEE DOTNET DATA MINING PROJECT Anonymous query processing in road networks
2014 IEEE DOTNET DATA MINING PROJECT Anonymous query processing in road networks
 
2014 IEEE DOTNET DATA MINING PROJECT Ai and opinion mining
2014 IEEE DOTNET DATA MINING PROJECT Ai and opinion mining2014 IEEE DOTNET DATA MINING PROJECT Ai and opinion mining
2014 IEEE DOTNET DATA MINING PROJECT Ai and opinion mining
 
2014 IEEE DOTNET DATA MINING PROJECT A probabilistic approach to string trans...
2014 IEEE DOTNET DATA MINING PROJECT A probabilistic approach to string trans...2014 IEEE DOTNET DATA MINING PROJECT A probabilistic approach to string trans...
2014 IEEE DOTNET DATA MINING PROJECT A probabilistic approach to string trans...
 
2014 IEEE DOTNET DATA MINING PROJECT A novel model for mining association rul...
2014 IEEE DOTNET DATA MINING PROJECT A novel model for mining association rul...2014 IEEE DOTNET DATA MINING PROJECT A novel model for mining association rul...
2014 IEEE DOTNET DATA MINING PROJECT A novel model for mining association rul...
 
2014 IEEE JAVA DATA MINING PROJECT Xs path navigation on xml schemas made easy
2014 IEEE JAVA DATA MINING PROJECT Xs path navigation on xml schemas made easy2014 IEEE JAVA DATA MINING PROJECT Xs path navigation on xml schemas made easy
2014 IEEE JAVA DATA MINING PROJECT Xs path navigation on xml schemas made easy
 
2014 IEEE JAVA DATA MINING PROJECT Web image re ranking using query-specific ...
2014 IEEE JAVA DATA MINING PROJECT Web image re ranking using query-specific ...2014 IEEE JAVA DATA MINING PROJECT Web image re ranking using query-specific ...
2014 IEEE JAVA DATA MINING PROJECT Web image re ranking using query-specific ...
 
2014 IEEE JAVA DATA MINING PROJECT Shortest path computing in relational dbms
2014 IEEE JAVA DATA MINING PROJECT Shortest path computing in relational dbms2014 IEEE JAVA DATA MINING PROJECT Shortest path computing in relational dbms
2014 IEEE JAVA DATA MINING PROJECT Shortest path computing in relational dbms
 
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
2014 IEEE JAVA DATA MINING PROJECT Security evaluation of pattern classifiers...
 
2014 IEEE JAVA DATA MINING PROJECT Secure outsourced attribute based signatures
2014 IEEE JAVA DATA MINING PROJECT Secure outsourced attribute based signatures2014 IEEE JAVA DATA MINING PROJECT Secure outsourced attribute based signatures
2014 IEEE JAVA DATA MINING PROJECT Secure outsourced attribute based signatures
 
2014 IEEE JAVA DATA MINING PROJECT Secure mining of association rules in hori...
2014 IEEE JAVA DATA MINING PROJECT Secure mining of association rules in hori...2014 IEEE JAVA DATA MINING PROJECT Secure mining of association rules in hori...
2014 IEEE JAVA DATA MINING PROJECT Secure mining of association rules in hori...
 
2014 IEEE JAVA DATA MINING PROJECT Searching dimension incomplete databases
2014 IEEE JAVA DATA MINING PROJECT Searching dimension incomplete databases2014 IEEE JAVA DATA MINING PROJECT Searching dimension incomplete databases
2014 IEEE JAVA DATA MINING PROJECT Searching dimension incomplete databases
 
2014 IEEE JAVA DATA MINING PROJECT Privacy preserving and content-protecting ...
2014 IEEE JAVA DATA MINING PROJECT Privacy preserving and content-protecting ...2014 IEEE JAVA DATA MINING PROJECT Privacy preserving and content-protecting ...
2014 IEEE JAVA DATA MINING PROJECT Privacy preserving and content-protecting ...
 

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2014 IEEE DOTNET DATA MINING PROJECT Converged architecture for broadcast and multicast services in heterogeneous network

  • 1. GLOBALSOFT TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmai l.com Converged Architecture for Broadcast and Multicast Services in Heterogeneous Network Abstract:- MBMS provides point-to-multipoint (p-t-m) radio bearers and multicast support in the cellular network to support the streaming and file download services. This paper proposes a converged architecture for broadcast and multicast services in a heterogeneous network. To support the broadcast/multicast services in the long-term evolution (LTE) network, the standard enhances multimedia broadcast multicast service (MBMS). In the broadcast network, digital video broadcasting for handhelds (DVB-H) is the standard for broadcasting IP data services to user equipment (UE). Accordingly, the converged LTE and DVB-H network can be used to service the broadcast/multicast services. To employ the converged network, additional entities are required for the contents management, electronic service guide (ESG) management and resource management. Therefore, we propose several logical entities to fulfill functionality from the above mentioned issues. The proposed logical entities are as follows: an integrated
  • 2. contents server, an integrated ESG server and an integrated management server. We also present several scenarios for implementing the converged architecture and compare the advantage of each scenario. Service providers can exploit the converged architecture according to preference and equipped devices. This study is of particular interest to the service providers because it provides the service providers with an insight of the various scenarios to make the converged architecture for broadcast/multicast service. Existing System  On top of these generic elements, we build an intuitive, fuzzy-based query evaluation mechanism that supports the service matchmaking process by employing and appropriately combining existing similarity metrics.  Structured network is organized in such a way that data items are located at specific nodes in the network, and those nodes maintain some state information to enable efficient retrieval of data.  Structured nodes are not efficient and flexible enough for applications where nodes join or leave the network frequently.  The Sequential Algorithm is used which increases the latency of the project.  Since the nodes are selected sequentially, if any node gets disconnected, the exact answer is not received. And identification of the disconnected node becomes tedious and sometimes impossible. Disadvantage  In the DVB-H network, the radio resource will be wasted if only a few users request the same content. And also, LTE network can serve restricted users because the available radio resource is limited.
  • 3.  Therefore, the approach about the converged network is needed to exploit a complementary management.  we tackle the problems that arise upon service discovery, when users need to search for operations delivered by services of different types Proposed System  The proposed approach is based on the premise that service discovery should be orthogonal to the various service models and technologies.  The various proposed approaches only partially address the discovery of heterogeneous services, mainly because they were not fundamentally designed to do so.  The proposed matchmaker quantifies the similarity of an offered service operation with respect to a given request, while weights are used to differentiate the search criteria priorities  A converged architecture was proposed for an integrated network between LTE and DVB-H network  The proposed logical entities are as follows: an integrated contents server, an integrated ESG server and an integrated management server.  We also present several scenarios for implementing the converged architecture and compare the advantage of each scenario. Advantage
  • 4.  The proposed a multiannotator approach to automatically constructing an annotation wrapper for annotating the search result records retrieved from any given web database.  Each of these annotators exploits one type of features for annotation and our experimental results show that each of the annotators is useful and they together are capable of generating high quality annotation.  We can join the nodes at random times and depart without a prior notification. HARDWARE REQUIREMENTS :  Hard disk : 500 GB  RAM : 512 MB  Processor Speed : 3.00GHz  Processor : Pentium IV Processor SOFTWARE REQUIREMENTS :  Front End : VS .NET 2010  Code Behind : C#.net  Back End : SQL SERVER 2005