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PRESSURE BASED ROUTING PROTOCOL FOR UNDERWATER WIRELESS SENSOR NETWORKS: A SURVEY
Khasawneh, Ahmad,Bin Abd Latiff, Muhammad Shafie,Chizari, Hassan,Tariq, MoeenUddin,Bamatraf, Abdullah Korean Society for Internet Information 2015 KSII Transactions on Internet and Information Syst Vol.9 No.2
Underwater wireless sensor networks (UWSNs) are similar to the terrestrial sensor networks. Nevertheless, there are different characteristics among them such as low battery power, limited bandwidth and high variable propagation delay. One of the common major problems in UWSNs is determining an efficient and reliable routing between the source node and the destination node. Therefore, researchers tend to design efficient protocols with consideration of the different characteristics of underwater communication. Furthermore, many routing protocols have been proposed and these protocols may be classified as location-based and location-free routing protocols. Pressure-based routing protocols are a subcategory of the location-free routing protocols. This paper focuses on reviewing the pressure-based routing protocols that may further be classified into non-void avoidance protocols and void avoidance protocols. Moreover, non-void avoidance protocols have been classified into single factor based and multi factor based routing protocols. Finally, this paper provides a comparison between these protocols based on their features, performance and simulation parameters and the paper concludes with some future works on which further study can be conducted.
( Syed Mubarak Ali ),( Imran Ghani ),( Muhammad Shafie Abd Latiff ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.1
In this modern era of technology and information, e-learning approach has become an integral part of teaching and learning using modern technologies. There are different variations or classification of e-learning approaches. One of notable approaches is Personal Learning Environment (PLE). In a PLE system, the contents are presented to the user in a personalized manner (according to the user`s needs and wants). The problem arises when a new user enters the system, and due to the lack of information about the new user`s needs and wants, the system fails to recommend him/her the personalized e-learning contents accurately. This phenomenon is known as cold-start problem. In order to address this issue, existing researches propose different approaches for recommendation such as preference profile, user ratings and tagging recommendations. In this research paper, the implementation of a novel interaction-based approach is presented. The interaction-based approach improves the recommendation accuracy for the new-user cold-start problem by integrating preferences profile and tagging recommendation and utilizing the interaction among users and system. This research work takes leverage of the interaction of a new user with the PLE system and generates recommendation for the new user, both implicitly and explicitly, thus solving new-user cold-start problem. The result shows the improvement of 31.57% in Precision, 18.29% in Recall and 8.8% in F1-measure.