IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Framework for Classifying Indonesian News Curator in TwitterTELKOMNIKA JOURNAL
News curators in twitter are a user, which is interested in following, spreading, giving feedback of
recent popular articles. There are two kinds of this user, news curator as human user and news aggregator
as bot user. In prior works about news curator, the classification system built using followers, URL,
mention and re-tweet feature. However, there are limited prior works for classifying Indonesian News
Curator in twitter and still hard for labeling data involve just two features: followers and URL. In this paper,
we proposed a framework for classifying Indonesian news curator in twitter using Naïve Bayes Classifier
(NBC) and added features such as location, bio profile, and common tweet. Another purpose for analyzing
the influential features of certain class, so it’s make easier for labeling data of this role in the future.
Examination result using percentage split as evaluating system produced 87% accuracy. The most
influential features for news curator are followers, bio profile, mention and re-tweet. For news aggregator
class are followers, location, and URL. The rest just common tweet feature for not both class. We
implemented Feature Subset Selection (FSS) for increasing system performance and avoiding the over
fitting data, it has produced 92.90% accuracy.
We discuss the operation of bit-torrent, the framework behind its working nature and have listed the proposed modifications to deal with performance issues, research challenges and factors to be considered while implementing bit-torrent in a P2P social network. Bit torrent
has been slowly migrating from its conventional public file
sharing role to a social network. In todays world, recognition of having a more distributed and decentralized social network has grown largely among people. We have presented a paradigm for the design of bit-torrent style sharing feature in P2P social network.
Detecting Spambot as an Antispam Technique for Web Internet BBSijsrd.com
Spam which is one of the most popular and also the most relevant topic that needs to be understood in the current scenario. Everyone whether it may be a small child or an old person are using emails everyday all around the world. The scenario which we are seeing is that almost no one is aware or in simple sentence they do not know what actually the spam is and what they will do in their systems. Spam in general means unsolicited or unwanted mails. Botnets are considered one of the main source of the spam. Botnet means the group of software's called bots and the function of these bots is to run on several compromised computers autonomously and automatically. The main objective of this paper is to detect such a bot or spambots for the Bulletin Board System (BBS). BBS is a computer that is running software that allows users to leave a message and access information of general interest. Originally BBSes were accessed only over a phone line using a modem, but nowadays some BBSes allowed access via a Telnet, packet switched network, or packet radio connection. The main methodology that we are going to focus is on Behavioural-based Spam Detection (BSD) method. Behavioral-based Spam Detector (BSD) combines several behaviours of the spam bots at different stages including the behaviour of spam preparation before the spam session when the spammers search for an open relay SMTP service to send e-mails through, and the behaviour of spammers while connecting to the mail server. Detecting the abnormal behaviour produced by the spam activities gives a high rate of suspicion on the existence of bots.
A Framework for Classifying Indonesian News Curator in TwitterTELKOMNIKA JOURNAL
News curators in twitter are a user, which is interested in following, spreading, giving feedback of
recent popular articles. There are two kinds of this user, news curator as human user and news aggregator
as bot user. In prior works about news curator, the classification system built using followers, URL,
mention and re-tweet feature. However, there are limited prior works for classifying Indonesian News
Curator in twitter and still hard for labeling data involve just two features: followers and URL. In this paper,
we proposed a framework for classifying Indonesian news curator in twitter using Naïve Bayes Classifier
(NBC) and added features such as location, bio profile, and common tweet. Another purpose for analyzing
the influential features of certain class, so it’s make easier for labeling data of this role in the future.
Examination result using percentage split as evaluating system produced 87% accuracy. The most
influential features for news curator are followers, bio profile, mention and re-tweet. For news aggregator
class are followers, location, and URL. The rest just common tweet feature for not both class. We
implemented Feature Subset Selection (FSS) for increasing system performance and avoiding the over
fitting data, it has produced 92.90% accuracy.
We discuss the operation of bit-torrent, the framework behind its working nature and have listed the proposed modifications to deal with performance issues, research challenges and factors to be considered while implementing bit-torrent in a P2P social network. Bit torrent
has been slowly migrating from its conventional public file
sharing role to a social network. In todays world, recognition of having a more distributed and decentralized social network has grown largely among people. We have presented a paradigm for the design of bit-torrent style sharing feature in P2P social network.
Detecting Spambot as an Antispam Technique for Web Internet BBSijsrd.com
Spam which is one of the most popular and also the most relevant topic that needs to be understood in the current scenario. Everyone whether it may be a small child or an old person are using emails everyday all around the world. The scenario which we are seeing is that almost no one is aware or in simple sentence they do not know what actually the spam is and what they will do in their systems. Spam in general means unsolicited or unwanted mails. Botnets are considered one of the main source of the spam. Botnet means the group of software's called bots and the function of these bots is to run on several compromised computers autonomously and automatically. The main objective of this paper is to detect such a bot or spambots for the Bulletin Board System (BBS). BBS is a computer that is running software that allows users to leave a message and access information of general interest. Originally BBSes were accessed only over a phone line using a modem, but nowadays some BBSes allowed access via a Telnet, packet switched network, or packet radio connection. The main methodology that we are going to focus is on Behavioural-based Spam Detection (BSD) method. Behavioral-based Spam Detector (BSD) combines several behaviours of the spam bots at different stages including the behaviour of spam preparation before the spam session when the spammers search for an open relay SMTP service to send e-mails through, and the behaviour of spammers while connecting to the mail server. Detecting the abnormal behaviour produced by the spam activities gives a high rate of suspicion on the existence of bots.
Tecxipio 10 facts about p2p file sharing network usage in chinaTECXIPIO GmbH
For this latest TECXIPIO infographic, we’ve gathered data for 10 noteworthy file sharing trends in China. Analyses of P2P file sharing network usage generate data that give unique insights into consumer preferences and different target markets. With this analysis, we provide an in-depth look at what’s popular among users of P2P file sharing networks in China.
This file sharing analysis for the People’s Republic of China is based on activity in P2P file sharing networks during the first six months of 2017.
Bowling Alone and Trust Decline in Social Network SitesPaolo Massa
In this paper we analyze the community of a social network site, Advogato. The peculiar characteristics of Advogato is that users can explicitly express weighted trust relationships among themselves. We conduct a longitudinal analysis of the trust network over a time period of 4 years, exploring the community as it grew from a knit circle of 300 users to an society of almost 6500 individuals. We report the changes over time of standard indexes in social network analysis such as clustering and degrees of separation. We then focus on specific measures about trust such as reciprocity and changes over time of average trust. A decline in trust is observed as the community grows. Following what we believe to be the first empirical analysis of trust evolution over time in a real community, we conclude suggesting how the availability of data about human relationships in social network sites is opening up the possibility of monitoring changes in trust in real time. In order to foster this research line, we released the datasets and the code we used in our analysis.
Twet is an application that offers search by pattern popular social sites like Twitter, Flickr or Youtube for the latest related content. In order to make the search more efficient we use the WordNet thesaurus to enlarge the search pattern by adding synonyms. Using Bing Maps, it searches for the location of the photos.
Asymmetric Social Proximity Based Private Matching Protocols for Online Socia...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Authors: Vacharasintopchai, Thiti and Nguyen-Huu, Phong
Issue Date: 11-Dec-2009
Type: Article
Series/Report no.: Proc. 2nd International Conference on Robotics, Informatics, and Intelligent Technology (RIIT2009);
Abstract: Social networks offer incredible opportunities for users to create contents and share their experiences. The number of users joining these social networks has been rising dramatically. However, in a social network several users may share the same name. This causes name ambiguity in which search engine returns homogeneous search results for each queried name. To solve this problem we propose an approach to improve search results for finding friends within a large social network by using friendships among users as our backbone feature. Our approach finds most ranked seeds by using PageRank algorithm before computing approximate shortest path in a directed graph. We also retrieve real data from the social network Twitter to verify our approach. Results show that our approach outperforms the SeedBase approach which selects seeds randomly with large margin.
URI: http://dspace.siu.ac.th/handle/1532/718
2013 NodeXL Social Media Network AnalysisMarc Smith
Social media network analysis and visualization with NodeXL - the network overview discovery and exploration add-in for Excel. Map Twitter, Facebook, email, blogs, and the web with a point and click interface within the familiar spreadsheet.
An introduction in the world of Social Network Analysis and a view on how this may help learning networks. History, data collection and several analysis techniques are shown.
A survey of Stemming Algorithms for Information Retrievaliosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Tecxipio 10 facts about p2p file sharing network usage in chinaTECXIPIO GmbH
For this latest TECXIPIO infographic, we’ve gathered data for 10 noteworthy file sharing trends in China. Analyses of P2P file sharing network usage generate data that give unique insights into consumer preferences and different target markets. With this analysis, we provide an in-depth look at what’s popular among users of P2P file sharing networks in China.
This file sharing analysis for the People’s Republic of China is based on activity in P2P file sharing networks during the first six months of 2017.
Bowling Alone and Trust Decline in Social Network SitesPaolo Massa
In this paper we analyze the community of a social network site, Advogato. The peculiar characteristics of Advogato is that users can explicitly express weighted trust relationships among themselves. We conduct a longitudinal analysis of the trust network over a time period of 4 years, exploring the community as it grew from a knit circle of 300 users to an society of almost 6500 individuals. We report the changes over time of standard indexes in social network analysis such as clustering and degrees of separation. We then focus on specific measures about trust such as reciprocity and changes over time of average trust. A decline in trust is observed as the community grows. Following what we believe to be the first empirical analysis of trust evolution over time in a real community, we conclude suggesting how the availability of data about human relationships in social network sites is opening up the possibility of monitoring changes in trust in real time. In order to foster this research line, we released the datasets and the code we used in our analysis.
Twet is an application that offers search by pattern popular social sites like Twitter, Flickr or Youtube for the latest related content. In order to make the search more efficient we use the WordNet thesaurus to enlarge the search pattern by adding synonyms. Using Bing Maps, it searches for the location of the photos.
Asymmetric Social Proximity Based Private Matching Protocols for Online Socia...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Authors: Vacharasintopchai, Thiti and Nguyen-Huu, Phong
Issue Date: 11-Dec-2009
Type: Article
Series/Report no.: Proc. 2nd International Conference on Robotics, Informatics, and Intelligent Technology (RIIT2009);
Abstract: Social networks offer incredible opportunities for users to create contents and share their experiences. The number of users joining these social networks has been rising dramatically. However, in a social network several users may share the same name. This causes name ambiguity in which search engine returns homogeneous search results for each queried name. To solve this problem we propose an approach to improve search results for finding friends within a large social network by using friendships among users as our backbone feature. Our approach finds most ranked seeds by using PageRank algorithm before computing approximate shortest path in a directed graph. We also retrieve real data from the social network Twitter to verify our approach. Results show that our approach outperforms the SeedBase approach which selects seeds randomly with large margin.
URI: http://dspace.siu.ac.th/handle/1532/718
2013 NodeXL Social Media Network AnalysisMarc Smith
Social media network analysis and visualization with NodeXL - the network overview discovery and exploration add-in for Excel. Map Twitter, Facebook, email, blogs, and the web with a point and click interface within the familiar spreadsheet.
An introduction in the world of Social Network Analysis and a view on how this may help learning networks. History, data collection and several analysis techniques are shown.
A survey of Stemming Algorithms for Information Retrievaliosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Najnowsze technologie i narzędzia wykorzystywane w procesie kształtowania ma...Marcin Czajka
Najnowsze technologie i narzędzia wykorzystywane w procesie kształtowania marki pracodawcy | Employer Branding Management Summit 2013. Zbiór case studies, część przykładów kampanii zrealizowanych przez GravityAd - social communication.
Social Media & Mobile.
Studies on Effect of Waveguide Dimensions on Resonant Frequency of Shunt Tee ...iosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Business innovatie moeten altijd in de cloud. Niet als technologisch concept maar vanuit community denken. Een paar bouwstenen voor innovaties bij ondernemingen:
1. let op beginselen van duurzaamheid. Een groeiende groep mensen verwacht innovaties die duurzaam zijn
2. hou rekening met communities die vloeibaar zijn, complexiteit van de maatschappij en onzekerheid bij mensen
3. klanten op de eerste plek (en niet shareholders). Als de innovatie de klant niet op de erste plek zet, kent de klant wel een andere voor de dienstverlening.
Hoe overleef je in de digitale maatschappij: afleren en aanleren, klein is het nieuwe groot
Guidelines to implement the "Healthy Lifestyle Community", from the International Federation of Red Cross and Red Crescent Societies.
How-to step guide to use the digital ecosystem for Non Communicable Diseases prevention, advocacy and networking with people from and outside the Red Cross Red Crescent Movement.
Strategy for job application on VSO.
Objective: to design a plan to recruit 200 volunteers in 1 month, given the VSO social media channels current status. Estimate a budget and planning accordingly.
Taller de Social Media, orientado a las organizaciones sin fines de lucro, para aprender nociones básicas y principales de la gestión de Redes Sociales, enfocado hacia las campañas con causa y de recolección.
Workshop on Social Media strategies for non-profit organisations, in order to showcase basic and essential principles on social networks management, with focus on charitable causes and crowdfunding.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE ISM 2008: Kalman Graffi: A Distributed Platform for Multimedia CommunitiesKalman Graffi
Online community platforms and multimedia content delivery are merging in recent years. Current platforms like Facebook and YouTube are client-server based which result in high administration costs for the provider. In contrast to that peer-to-peer systems offer scalability and low costs, but are limited in their functionality. In this paper we present a framework for peer-to-peer based multimedia online communities.We identified the key challenges for this new application of the peer-to-peer paradigm and built a plugin based, easily extendible and multifunctional framework. Further, we identified distributed linked lists as valuable data structure to implement the user profiles, friend lists, groups, photo albums and more. Our framework aims at providing the functionality of common online community platforms combined with the multimedia delivery capabilities of modern peer-to-peer systems, e.g. direct multimedia delivery and access to a distributed multimedia pool.
A Cooperative Peer Clustering Scheme for Unstructured Peer-to-Peer Systemsijp2p
This paper proposes a peer clustering scheme for unstructured Peer-to-Peer (P2P) systems. The proposed
scheme consists of an identification of critical links, local reconfiguration of incident links, and a
retaliation rule. The simulation result indicates that the proposed scheme improves the performance of
previous schemes and that a peer taking a cooperative action will receive a higher profit than selfish peers
A Cooperative Peer Clustering Scheme for Unstructured Peer-to-Peer Systemsijp2p
This paper proposes a peer clustering scheme for unstructured Peer-to-Peer (P2P) systems. The proposed
scheme consists of an identification of critical links, local reconfiguration of incident links, and a
retaliation rule. The simulation result indicates that the proposed scheme improves the performance of
previous schemes and that a peer taking a cooperative action will receive a higher profit than selfish peers.
A Cooperative Peer Clustering Scheme for Unstructured Peer-to-Peer Systemsijp2p
This paper proposes a peer clustering scheme for unstructured Peer-to-Peer (P2P) systems. The proposed
scheme consists of an identification of critical links, local reconfiguration of incident links, and a
retaliation rule. The simulation result indicates that the proposed scheme improves the performance of
previous schemes and that a peer taking a cooperative action will receive a higher profit than selfish peers.
A Cooperative Peer Clustering Scheme for Unstructured Peer-to-Peer Systemsijp2p
This paper proposes a peer clustering scheme for unstructured Peer-to-Peer (P2P) systems. The proposed
scheme consists of an identification of critical links, local reconfiguration of incident links, and a
retaliation rule. The simulation result indicates that the proposed scheme improves the performance of
previous schemes and that a peer taking a cooperative action will receive a higher profit than selfish peers.
A Cooperative Peer Clustering Scheme for Unstructured Peer-to-Peer Systemsijp2p
This paper proposes a peer clustering scheme for unstructured Peer-to-Peer (P2P) systems. The proposed
scheme consists of an identification of critical links, local reconfiguration of incident links, and a
retaliation rule. The simulation result indicates that the proposed scheme improves the performance of
previous schemes and that a peer taking a cooperative action will receive a higher profit than selfish peers.
A Cooperative Peer Clustering Scheme for Unstructured Peer-to-Peer Systemsijp2p
This paper proposes a peer clustering scheme for unstructured Peer-to-Peer (P2P) systems. The proposed
scheme consists of an identification of critical links, local reconfiguration of incident links, and a
retaliation rule. The simulation result indicates that the proposed scheme improves the performance of
previous schemes and that a peer taking a cooperative action will receive a higher profit than selfish peers.
A study of index poisoning in peer topeerIJCI JOURNAL
P2P file sharing systems are the most popular forms of file sharing to date. Its client-server architecture
attains faster file transfers, however with its peer anonymity and lack of authentication it has become a
gold mine for malicious attacks. One of the leading sources of disruptions in the P2P file sharing systems is
the index poisoning attacks. This attack seeks to corrupt the indexes used to reference files available for
download in P2P systems with false data. In order to protect the users from these attacks it is important to
find solutions to eliminate or mitigate the effects of index poisoning attacks. This paper will analyze index
poisoning attacks, their uses and solutions proposed to defend against them.
Alluding Communities in Social Networking Websites using Enhanced Quasi-cliqu...IJMTST Journal
Social media is attracting global crowd rapidly. In websites such as Facebook, twitter etc one can share, view, like posts, such as images, videos, texts. Users also interact with each other. Communities are part of few such social networking websites. In a community people can learn more about their area of interest, share information on those topics, discuss about their perspectives etc. This paper recommends how community can be suggested to a user based on enhanced quasi clique technique.
Prometheus: User-Controlled P2P Social Data Management for Socially-aware App...Nicolas Kourtellis
Recent Internet applications, such as online social networks and user-generated content sharing, produce an unprecedented amount of social information, which is further augmented by location or collocation data collected from mobile phones. Unfortunately, this wealth of social information is fragmented across many different proprietary applications. Combined, it could provide a more accurate representation of the social world, and it could enable a whole new set of socially-aware applications. We introduce Prometheus, a peer-to-peer service that collects and man- ages social information from multiple sources and implements a set of social inference functions while enforcing user-defined access control poli- cies. Prometheus is socially-aware: it allows users to select peers that manage their social information based on social trust and exploits naturally- formed social groups for improved performance. We tested our Prometheus prototype on PlanetLab and built a mobile social application to test the performance of its social inference functions under real-time constraints. We showed that the social-based mapping of users onto peers improves the service response time and high service availability is achieved with low overhead.
Prometheus: User-Controlled P2P Social Data Management for Socially-aware Applications. Nicolas Kourtellis, Joshua Finnis, Paul Anderson, Jeremy Blackburn, Cristian Borcea, Adriana Iamnitchi. ACM/IFIP/USENIX 11th International Middleware Conference, 2010
EFFECTIVE TOPOLOGY-AWARE PEER SELECTION IN UNSTRUCTURED PEER-TO-PEER SYSTEMSijp2p
Peer-to-Peer systems form logical overlay networks on top of the Internet. Essentially, peers randomly
choose logical neighbours without any knowledge about underlying physical topology. This may cause
inefficient communications among peers. This topology mismatch problem may result in poor
performance and scalability for Peer-to-Peer systems. A possible way to improve the performance of
Peer-to-Peer systems is the overlay network construction based on the knowledge of the physical network
topology. In this paper, we will propose the use of the “Record Route” and “Timestamp” options
supported in the IP protocol to explore the paths between peers. By the topology-aware peer selection,
our approach outperforms traditional P2P systems using random peer selection. Our approach only
incurs a low overhead and can be deployed easily in various P2P systems.
EFFECTIVE TOPOLOGY-AWARE PEER SELECTION IN UNSTRUCTURED PEER-TO-PEER SYSTEMSijp2p
Peer-to-Peer systems form logical overlay networks on top of the Internet. Essentially, peers randomly
choose logical neighbours without any knowledge about underlying physical topology. This may cause
inefficient communications among peers. This topology mismatch problem may result in poor
performance and scalability for Peer-to-Peer systems. A possible way to improve the performance of
Peer-to-Peer systems is the overlay network construction based on the knowledge of the physical network
topology. In this paper, we will propose the use of the “Record Route” and “Timestamp” options
supported in the IP protocol to explore the paths between peers. By the topology-aware peer selection,
our approach outperforms traditional P2P systems using random peer selection. Our approach only
incurs a low overhead and can be deployed easily in various P2P systems.
EFFECTIVE TOPOLOGY-AWARE PEER SELECTION IN UNSTRUCTURED PEER-TO-PEER SYSTEMS ijp2p
Peer-to-Peer systems form logical overlay networks on top of the Internet. Essentially, peers randomly choose logical neighbours without any knowledge about underlying physical topology. This may cause inefficient communications among peers. This topology mismatch problem may result in poor performance and scalability for Peer-to-Peer systems. A possible way to improve the performance of Peer-to-Peer systems is the overlay network construction based on the knowledge of the physical network topology. In this paper, we will propose the use of the “Record Route” and “Timestamp” options supported in the IP protocol to explore the paths between peers. By the topology-aware peer selection, our approach outperforms traditional P2P systems using random peer selection. Our approach only incurs a low overhead and can be deployed easily in various P2P systems.
FUTURE OF PEER-TO-PEER TECHNOLOGY WITH THE RISE OF CLOUD COMPUTINGijp2p
Peer-to-Peer (P2P) networking emerged as a disruptive business model displacing the server based
networks within a point in time.P2P technologies are on the edge of becoming all-purpose in developing
several applications for social networking. In the past seventeen years, research on P2P computing and
systems has received enormous amount of attention in the areas of academia and the industry. P2P rose to
triumphant profit-making systems in the internet. It represents the best incarnation of the end to end
argument, the frequently disputed design philosophies that guided the design of the internet. The doubting
factor then is why is research on P2P computing now fading from the spotlight and suffering a nose dive
fall as dramatic as its rise to its popularity. This paper is going to capture a quick look at past results in
peer-to-peer computing with focus on understanding what led to its rise, what contributed to its commercial
success and what has led to its lack of interest. The insight of this paper introduces cloud computing as a
paradigm to peer-to-peer computing.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
An Examination of Effectuation Dimension as Financing Practice of Small and M...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Does Goods and Services Tax (GST) Leads to Indian Economic Development?iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Childhood Factors that influence success in later lifeiosrjce
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Socio Media Connect: A Social Profile based P2P Network
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 2, Ver. VI (Mar – Apr. 2015), PP 61-67
www.iosrjournals.org
DOI: 10.9790/0661-17266167 www.iosrjournals.org 61 | Page
Socio Media Connect: A Social Profile based P2P Network
Chirag Jain1
,Hardeepsingh Jethra2
, Rishikesh Pange3
, Vinil Jain4
, S.C.Shrawne5
1
(VeermataJijabai Technological Institute, India)
2
(VeermataJijabai Technological Institute, India)
3
(VeermataJijabai Technological Institute, India)
4
(VeermataJijabai Technological Institute, India)
5
(VeermataJijabai Technological Institute, India)
Abstract: It is observed that users tend to like and follow a particular type music/movies based on their social
interests. Users like music of particular artists, album; movies/TV shows of a particular actor, director, genre,
etc. Generally, peer-to-peer networks do not use this vital information to perform effective search using the
metadata of media files. This information can be used to create social profile of users and cluster the peers
based on their interests as reflected in the social profiles. This clustering of users over a peer-to-peer network
will help in finding the users their interested files more easily. Also, peer-to-peer networks usually flood the
entire network to search a particular file. But, due to clustering of peers based on their social interest, there is
no need to flood the entire network to find a particular file, as most of the times the required file will be found in
the cluster itself, which will in turn reduce the network overhead. We simulated this system using JXTA to
connect the peers after clustering over P2P network. The peers with similar social profiles were connected via a
common communication channel and therefore the results were better than the normal P2P network.
Keywords: clustering,media, peer-to-peer, sharing, similarity
I. Introduction
Peer-to-peer networks have become very important in today’s world and hence, it is really important to
improve the efficiency of the P2P network for finding and receiving files. If a peer wants to search for a file, it
requests all its neighbours for the file. If none of the neighbours have the requested file, then all the neighbours
ask their neighbours. This process continues till the file is found in the network or all the peers in the network
are requested for the file. This results in flooding of the entire P2P network. Because the peers with similar
interests are not directly connected in a normal P2P network, they have a broader search window. In
SocioMediaConnect, we aim to tackle this problem. The media files such as music, movies and TV shows
contain important information such as genre, actors, artists, etc.
Example: Inception (Movie)
Title: Inception- Genre: Action, Mystery, Sci-Fi; Director: Christopher Nolan; Writer: Christopher Nolan;
Actors: Leonardo DiCaprio, Joseph Gordon-Levitt, Tom Hardy; Language: English, Japanese, French
This information can be compiled into a file, what we call the social profile of the user. The social
profile is built from all the files that the user shares with the peer-to-peer network.
II. Outline of Socio Media Connect
Our proposed work, SocioMediaConnect will have a peer-to-peer network with social profiling of each
user, where users will be able to search objects by the semantic attributes of the multimedia files. Peers with
similar interests are clustered to form a group. If the similarity quotient of the group and the new peer falls
within the threshold then the peer is added to the group with highest similarity quotient. Since, the interested
people will be directly connected by the network, the time required to find and retrieve resources will be much
lesser. SocioMediaConnect will search for a given resource first amongst the people (neighbours) with matching
similar profile and then if the resource is not found our system will flood the entire peer-to-peer network with
search query, thus making the search window narrower. Moreover, most of the times, no separate channel is
required for transferring file between peers because neighbouring peers are directly connected by common
channel. This gives SocioMediaConnect a major advantage over common peer-to-peer networks. In
SocioMediaConnect, peers mimic how people form social network and how they query, based on their interests.
Whenever a new resource is downloaded from neighbouring peers, its metadata will be generated and integrated
with previous metadata. The pipes used for communication between peers use secure cannel for communication,
which uses public key encryption, to prevent loss of data or its modification and also prevents against other
possible security thefts.
SocioMediaConnect will feature two kinds of peers:
2. Socio Media Connect: A Social Profile based P2P Network
DOI: 10.9790/0661-17266167 www.iosrjournals.org 62 | Page
Member peer
Admin peer
III. Proposed Work
The system consists of many groups with each group having members with similar interests in music,
movies and series. Each member of SMC has its own social profile based on the music, movies and series
interests of the user. Since the peers with interested file are directly connected with a common channel, the peer
won’t have to flood the entire P2P network with the search query. As a result the TTL (Time to Live) value of
the packets will be reduced, thereby reducing the overhead of the entire P2P network.
The admin of each group behaves as a dual peer viz. admin and member. Admin peer, in addition to
activities performed by the member peer, also performs activities such as maintaining the group vector, member
list of all peers in the group, list of different groups present in SMC, sending group vector to new peer added to
SMC, periodically maintains the status of all peers within the group. All peers have a unique username in order
to avoid conflict. Also group names are unique.
Algorithm 1-To update the group vector after a new peer is added to the group:
1. Read the social profile of the new peer.
2. Create a List_Peer<Name, Value> of all the tags in the profile
3. Create a List_Group<Name, Value> of all the tags in the group vector
4. For each entry in the List_Peer
a. If Name exists in List_Group
i. Add entry.value to corresponding List_Group entry
b. Else create new entry in List_Group for the current tag and update the attributes
5. Write List_Group<Name,Value> to group vector
Group Vector:
Each group has its own group vector which is maintained by the admin. Initially, when the only
member of the group is the admin, the vector of the admin is itself the group vector. As peers with same
interests are added to the group, the group vector keeps on updating. Group Vector is stored in xml format. As a
result, the group vector is the essential component in forming the groups of matching profiles. Whenever a peer
downloads a new file from SMC, the peer generates new tags corresponding to the new file to temp.xml and
periodically sends it to the admin. Admin updates the group vector whenever it receives such a file. Admins
runs the same algorithm whenever it receives a new profile or temp.xml
Attribute file:
This file will be generated by the system when the peer joins a group. This file helps the peer to decide
which group to j
oin the next time it comes online. It stores the following information: Type of peer, Group Name, Peer
ID of Admin
Figure 1: social profile format
3. Socio Media Connect: A Social Profile based P2P Network
DOI: 10.9790/0661-17266167 www.iosrjournals.org 63 | Page
Working of SMC with an example:
Figure 2: New peer enters system
Consider a P2P network with 3 groups--Group1, Group2, and Group3 (as shown above). Group1 has 3
members, Group2 has 4 members and Group3 has 3 members. All group admins are connected via a common
group. When a new peer joins SMC, it first selects a unique username after communicating with the name
server. SMC creates 3 folder (Music, Movies and Series) in the peer’s home directory. SMC places all the
movies, music and series files it wants to share and also wants them in its social profile in these files. SMC starts
building the social profile of the peer, after the peer is done adding files to the directories. After building the
social profile, SMC initially adds the new peer to a common group containing all the admins. New peer sends a
“hello” message to all the admins via the common group channel. New peer also sends some other information
necessary for P2P communication. In response, all admins reply by sending their group vectors which will be
analysed by the new peer to find matching interest. The new peer will run profile matching algorithm in order
to find a group with similar interest. The algorithm returns for each group-no of matches and the average score.
New Peer will sort the output. The peer then selects the group with maximum no of matches and least average
score.
Figure 3: Group formation based on social profiles
New Peer Group1 Group2 Group3
Music Score 1.41 1.28 1.39
Movie Score 1.31 1.12 1.4
Series Score 1.33 1.5 1.41
(Average Score, No of matches) (1.35,3) (1.3,2) (1.4,3)
4. Socio Media Connect: A Social Profile based P2P Network
DOI: 10.9790/0661-17266167 www.iosrjournals.org 64 | Page
If these values fall within the threshold, then the peer will be added to this group. Otherwise the peer
will have to form a new group and becomes the admin. According to the profile matching algorithm, the new
peer joins the Group1 because all number of matches is maximum for group1 (music, movie and series score is
below threshold) and average score is the least. New Peer sends a message to the admin ofgroup1 saying it
wants to join group1 along with its own social profile. Admin of group1 then adds the new peer to group1,
updates the group vector with the tags of new peer. Admin also sends a new member list to all the members of
the group indicating that a new peer has joined. After joining the group, the new peer can request the file list
of any member in the group. Since all the members have similar interest the peer can expect to find a file of its
interest easily. The search queries of the peer will be first sent only to the members of the group so as to reduce
the network overhead.
Important Algorithms designed and implemented for SMC:
Algorithm -To add new peer to SocioMediaConnect:
1. Peer joins Socio Media Connect
2. Choose unique peer name
3. Build social profile after files has been added
4. Add peer to Admin group and wait for 15 seconds
5. For each advertisement received
a. Extract profile
b. Run matching algorithm
6. Sort all profiles by similarity
7. If similarity under threshold
a. Add peer to group
b. Add peer tags to group vector
c. start member peer
8. Else
a. Create new peer group
b. Start Admin peer
9. Create attr.txt file
After this algorithm finishes, a new peer will either be added to a group or a new group will be created. This
algorithm also creates the attribute file.
Algorithm 2. Build Social profile
1. Create File List
2. For each file in File List
a. If FileType == Audio
i. Extract Tags using JAudioTagger
b. Else If FileType == Video
i. Extract file name
ii. Run GuessIt to get qualified name
iii. Query OMDB API to get movies/series information
iv. Extract tags from json array
c. Add tags to peername_Profile.xml
This algorithm will be initiated once the new peer has selected a unique username and placed the files
in shared folders. The output of this algorithm is the social profile of the peer. Social profile of the peer is an
xml file where there is a separate tag for each tag extracted from the file and its value is equal to the number of
objects by that tag. Initially an empty List<Name, Value> is created. Whenever a new tag is extracted from the
file, it is searched inside the list to check if already exists. If found then, its value is incremented by one, else a
new entry is created in the list <name, 1>
Algorithm 3. Match Social Profiles
1. Get all group vectors
2. For each vector
a. Extract vector
b. Apply cosine function between group vector and peer vector
c. Check movies, music and series weights
d. If all weights < Threshold
i. Add to List
5. Socio Media Connect: A Social Profile based P2P Network
DOI: 10.9790/0661-17266167 www.iosrjournals.org 65 | Page
Cosine Function:
For each social profile, we initially create 3 vectors each for music, movies and series. These vectors contain the
weight of each tag which is calculated as follows:
weight of tag =
no. of objects by that tag
Totalno. of objects
For comparing two social profiles, we require two sets of such vectors which are as follows:
Vector1music = <wt1, wt2, wt3, … wtn1>
Vector1movies = <wt1, wt2, wt3, … wtn2>
Vector1series = <wt1, wt2, wt3, … wtn3>
Vector2music = <wt1, wt2, wt3, … wtm1>
Vector2movies = <wt1, wt2, wt3, … wtm2>
Vector2series = <wt1, wt2, wt3, … wtm3>
The similarity between two social profiles is calculated using inverse of cosine function. As a result, similarity is
in the range [1,∞], where,
1 indicates completely matching social profiles
1
cos (0)
∞ indicates completely different social profiles
1
cos (90)
Similarity is calculated as follows:
Similaritymusic=
𝟏
𝐕𝐞𝐜𝐭𝐨𝐫𝟏𝐦𝐮𝐬𝐢𝐜 .𝐕𝐞𝐜𝐭𝐨𝐫𝟐𝐦𝐮𝐬𝐢𝐜
|𝐕𝐞𝐜𝐭𝐨𝟏𝐦𝐮𝐬𝐢𝐜| .|𝐕𝐞𝐜𝐭𝐨𝐫𝟐𝐦𝐮𝐬𝐢𝐜|
Similaritymovies=
𝟏
𝐕𝐞𝐜𝐭𝐨𝐫𝟏𝐦𝐨𝐯𝐢𝐞𝐬 .𝐕𝐞𝐜𝐭𝐨𝐫𝟐𝐦𝐨𝐯𝐢𝐞𝐬
|𝐕𝐞𝐜𝐭𝐨𝐫𝟏𝐦𝐨𝐯𝐢𝐞𝐬| .|𝐕𝐞𝐜𝐭𝐨𝐫𝟐𝐦𝐨𝐯𝐢𝐞𝐬|
Similarityseries=
𝟏
𝐕𝐞𝐜𝐭𝐨𝐫𝟏𝐬𝐞𝐫𝐢𝐞𝐬 .𝐕𝐞𝐜𝐭𝐨𝐫𝟐𝐬𝐞𝐫𝐢𝐞𝐬
|𝐕𝐞𝐜𝐭𝐨𝐫𝟏𝐬𝐞𝐫𝐢𝐞𝐬| .|𝐕𝐞𝐜𝐭𝐨𝐫𝟐𝐬𝐞𝐫𝐢𝐞𝐬|
Similarity=
𝐒𝐢𝐦𝐢𝐥𝐚𝐫𝐢𝐭𝐲(𝐦𝐮𝐬𝐢𝐜) + 𝐒𝐢𝐦𝐢𝐥𝐚𝐫𝐢𝐭𝐲(𝐦𝐨𝐯𝐢𝐞𝐬 )+ 𝐒𝐢𝐦𝐢𝐥𝐚𝐫𝐢𝐭𝐲(𝐬𝐞𝐫𝐢𝐞𝐬)
𝟑
Algorithm 4. Search for Resources
1. Peer submits search query
2. Send query to all group members
3. Wait for results from peers
4. If result is received
a. Send result to requested peer
b. Show result in GUI
5. else if user selects advanced query
i. send query to all admins
ii. match peer’s group profile with other admin’s group profiles
iii. if result found
1. send result to peer
2. show result in GUI
3. end the process
6. Show no result found
IV. Simulation Environment
We used JXTA to form P2P network. JXTA is set of protocols that can be implemented using their own
technology to establish P2P connections with other peers using identical technologies or different
implementations of JXTA. We used JXSE 2.6 which is JAVA implementation of JXTA
In order to extract tags from music files we used JAudioTagger which is the Audio Tagging library used for
tagging data in Audio files
In order to extract tags from movie/series files we used OMDB API which is a free web service to obtain
movie information
6. Socio Media Connect: A Social Profile based P2P Network
DOI: 10.9790/0661-17266167 www.iosrjournals.org 66 | Page
In order to speed up process of building profile we used ThreadPool
In a P2P network, any peer can tap and listen to communicate on between any two peers which can cause
security issues. In our simulation , we used JXTA UnicastSecurePipe which automatically encrypts and
decrypts messages and also shares public key certificates with peers
While clustering threshold for cosine function used was 1/cos (30)
Each peer generated around 3000-10000 tags depending on the number of files it possesses
V. Performance Evaluation
Figure 4: Performance evaluation
Following Observation were made:
1. We Simulated SocioMediaConnect using 100 peers. The average time required for retrieving the search
results without clustering is 149.9 milliseconds whereas the average time required for retrieving the search
results with clustering is 92.1 milliseconds. Hence, the time required is considerably less for clustered
network.
2. The search time increases linearly as new peers are added to the P2P network in both the cases (with and
without clustering), but the overall performance of SocioMediaConnect is always better than a normal P2P
network.
3. The time required for advanced search in SocioMediaConnect is greater, but the probability of performing
advanced search is very low. Advanced search is only performed when the peer does not find the requested
resource in the peer group. As a result, advanced search does not degrade the overall performance of
SocioMediaConnect and hence the overall output is much better than a normal P2P network.
VI. Conclusion
In this paper, we proposed a method for clustering peers over a P2P network based on the social
interests of the peers. With this method, we found that peers will be able find resources of their interests easily
from their neighbouring peers present in the same group. Also, we improved the search efficiency in the P2P
network by searching only in the peer group because the probability of finding the requested resource was very
high in the same group. This resulted in a narrower such window and considerably lesser network congestion.
Moreover, there was no need to flood the entire network to find the required resources. Network overhead was
also considerably reduced and also lesser number of messages were exchanged between peers.
SocioMediaConnect can be easily integrated with any existing P2P system
References
[1]. Kate Ching-Ju Lin, Chun-Po Wang, Cheng-Fu Chou, and LeanaGolubchik, “SocioNet: A Social-Based Multimedia Access System
for Unstructured P2P Networks”
[2]. Ching-Ju Lin, Shuo-Chan Tsai, Yi-Ting Chang and Cheng-Fu Chou, “Enabling Keyword Search and Similarity Search in Small-
World-based P2P Systems”
[3]. Practical JXTA,Cracking the P2P puzzle DawningStreamsInc
[4]. JXTA in a Nutshell, O’Reilly
[5]. OMDB API, http://omdbapi.com/
[6]. JAudioTagger,http://www.jthink.net/jaudiotagger/
7. Socio Media Connect: A Social Profile based P2P Network
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[7]. GuessIT, https://github.com/wackou/guessit
[8]. Clustering Techniques, http://www.ise.bgu.ac.il/faculty/liorr/hbchap15.pdf
[9]. JXSE-2.6, https://jxse.kenai.com/
[10]. Cosine Similarity Function, http://en.wikipedia.org/wiki/Cosine_similarity