Version-1 (March-April 2016)
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| Paper Type | : | Research Paper |
| Title | : | A Rapid and Reliable Receiver for Warning Delivery in Vehicular Ad-Hoc Networks |
| Country | : | India |
| Authors | : | Anseena A S || Shameem Ansar A |
Abstract: Vehicular ad-hoc networks (VANETs) are known for highly mobile and frequently disconnected characteristics. To improve safety, a warning message in VANETs should be delivered both reliably and urgently. In the existing solution, we make consensus of receiver by assigning rank, and the best forwarder is selected by distance to the centroid of the neighbors in need of message. The proposed work aims at overcoming the above limitations.........
[1] Junliang Liu 1,2, Zheng Yangi, 2, and Ivan Stojmenovic1, 3 "Receiver Consensus : On-Time Warning Delivery For Vehicular
Ad-Hoc Network" July 2013.
[2] S. Biswas, R. Tatchikou, and F. Dion, `` Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic
safety,'' IEEE Commun. Mag., vol. 44, no. 1, pp. 74_82, Jan. 2006.
[3] N. Wisitpongphan, O. Tonguz, J. S. Parikh, P. Mudalige, F. Bai, and V. Sadekar ``Broadcast storm mitigation techniques in vehicular
ad hoc networks,'' IEEE Wireless Commun., vol. 14, no. 6, pp. 84_94, Dec. 2007.
[4] S. Olariu and M. Weigle, Vehicular Networks: From Theory to Practice. Cleveland, OH, USA: CRC, 2009.
[5] M.-T. Sun, W.-C. Feng, T.-H. Lai, K. Yamada, H. Okada, and K. Fujimura ``GPS-based message broadcast for adaptive inter-vehicle
communications,'' in Proc. IEEE Veh. Technol. Co nf., Sep. 2000, pp. 2685_2692.
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| Paper Type | : | Research Paper |
| Title | : | A Novel Framework for Dependable Cloud Computing |
| Country | : | Nigeria |
| Authors | : | Dr. Roy Joel Ureigho || Edje Abel || Felix Elugwu |
Abstract: The cloud computing is one technology that has taken the computing world by storm with potent opportunities that are so tempting to ignore. Yet many are skeptical about its adoption because of the many problems that came with internet usage. The belief is that since cloud computing is an offshoot of internet, there are possibilities of multifaceted problems possibly inherited from Internet....
Keywords: cloud computing, dependable cloud computing, internet, securityg
[1]. R. Sailer,E. Valdez, T. Jaeger, et al., sHype: Secure hypervisor approach to trusted virtualized systems,RC23511, IBM, Yorktown Heights, NY 2005. (On-line:http://www.research.ibm.com/secure_systems_department/projects/hypervisor.)
[2]. N. Santos, K.Gummand, and R. Rodrigues, Towards trusted cloud computing,In: Workshop on hot topics in cloud computing, San Diego, CA, 2009.
[3]. M. Jensen, J. Schwenk, N. Gruschka. and L. Iacono, On technical security issues in cloud computing,In: IEEE International Conference on Cloud Computing (CLOUD-II 2009), Bangalore, India, September 2009, 109-116.
[4]. F.J. Krautheim, Building trust into utility cloud computing, doctoral diss., University of Maryland, Baltimore County, Baltimore, MD, 2010.
[5]. R.K.L. Ko, P. Jagadpramana, M. Mowbray, S. Pearson, M. Kirchberg, Q. Liang, B. S. Lee, TrustCloud: A framework for accountability and trust in cloud computing. HP Laboratories HPL-2011-38, 2011.
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| Paper Type | : | Research Paper |
| Title | : | Recommender Systems to Address New User Cold-Start Problem with User Side Information |
| Country | : | India |
| Authors | : | M. Sunitha || Dr. T. Adilakshmi |
Abstract: Due to exponential growth of Internet, users are facing the problem of Information overloading. Recommender Systems (RS) serve as an indispensible tool to solve information overloading problem. Due to their great commercial value, recommender systems have also been successfully deployed in industry, such as product recommendation at Amazon, music recommendation at iTunes, movie recommendation at Netflix, etc.....
Keywords: Information Overloading, collaborative filtering, recommender system, Social Network, Social matrix.
[1]. Jovian Lin, Kazunari Sugiyama, Min-Yen Kan, Tat-Seng Chua, Addressing Cold-Start in App Recommendation: Latent User Models Constructed from Twitter Followers, SIGIR'13, July 28–August 1, 2013, Dublin, Ireland
[2]. Daqiang Zhang, Qin Zou, Haoyi Xiong, CRUC: Cold-start Recommendations Using Collaborative Filtering in Internet of Things, Elsevier ESEP, 9-10 December 2011, Singapore
[3]. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, Eds., Recommender systems handbook. Springer US, October 2011
[4]. Xiwang Yang, Yang Guo, Yong Liu,Bayesian-Inference-Based Recommendation in Online Social Networks, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24, NO. 4, APRIL 2013
[5]. Ko-Jen Hsiao, Alex Kulesza, and Alfred O. Hero,Social Collaborative Retrieval, arXiv:1404.2342v1 [cs.IR] 9 Apr 2014