• List of Articles Ranking

      • Open Access Article

        1 - A Unicast Tree-Based Data Gathering Protocol for Delay Tolerant Mobile Sensor Networks
        Zeynab Mottaginia Ali Ghaffari
        The Delay Tolerant Mobile Sensor Networks (DTMSNs) distinguish themselves from conventional sensor networks by means of some features such as loose connectivity, node mobility, and delay tolerability. It needs to be acknowledged that traditional end-to-end routing proto Full Text
        The Delay Tolerant Mobile Sensor Networks (DTMSNs) distinguish themselves from conventional sensor networks by means of some features such as loose connectivity, node mobility, and delay tolerability. It needs to be acknowledged that traditional end-to-end routing protocols cannot be applied usefully in such challenging network conditions because of intermittent connections and/or long delays. Hence, this research is intended to propose a Unicast Tree-based Data Gathering protocol (UTDG) to resolve this problem. A UTDG includes 3 phases: tree formation phase, data collection and data transmission phase, and finally the updating phase. The proposed protocol constructs a tree in each community on the basis of transmission ranking, contact probability and the link expiration time. The selection of the next-hop node is based on the tree structure rather than forwarding the message to the neighbor node directly. Each node unicasts the data to its parent in the related community, and the root of the tree successively sends the data to the sink node. The authors contend, based on the simulation results of the study, that the proposed protocol can gain significantly higher message delivery rates with lower transmission overhead and also lower delay in data delivery than the other existing DTMSNs routing protocols in some applications. Manuscript Document
      • Open Access Article

        2 - The Surfer Model with a Hybrid Approach to Ranking the Web Pages
        Javad Paksima - -
        Users who seek results pertaining to their queries are at the first place. To meet users’ needs, thousands of webpages must be ranked. This requires an efficient algorithm to place the relevant webpages at first ranks. Regarding information retrieval, it is highly impor Full Text
        Users who seek results pertaining to their queries are at the first place. To meet users’ needs, thousands of webpages must be ranked. This requires an efficient algorithm to place the relevant webpages at first ranks. Regarding information retrieval, it is highly important to design a ranking algorithm to provide the results pertaining to user’s query due to the great deal of information on the World Wide Web. In this paper, a ranking method is proposed with a hybrid approach, which considers the content and connections of pages. The proposed model is a smart surfer that passes or hops from the current page to one of the externally linked pages with respect to their content. A probability, which is obtained using the learning automata along with content and links to pages, is used to select a webpage to hop. For a transition to another page, the content of pages linked to it are used. As the surfer moves about the pages, the PageRank score of a page is recursively calculated. Two standard datasets named TD2003 and TD2004 were used to evaluate and investigate the proposed method. They are the subsets of dataset LETOR3. The results indicated the superior performance of the proposed approach over other methods introduced in this area. Manuscript Document