30-09-2012, 04:54 PM
hai i need ppt for fast data collection in tree based wireless sensor networks
30-09-2012, 04:54 PM
hai i need ppt for fast data collection in tree based wireless sensor networks
22-08-2013, 02:38 PM
Fast data collection in tree based wireless sensor networks
Fast data collection.docx (Size: 46.49 KB / Downloads: 104) Introduction Convergecast namely the collection of data from a set of sensors toward a common sink over a tree- based routing topology, is a fundamental operation in wireless sensor networks (WSNs). In many applications, it is crucial to provide a guarantee on the delivery time as well as increase the rate of such data collection. For instance, in safety and mission-critical applications where sensor nodes are deployed to detect oil/gas leak or structural damage, the actuators and controllers need to receive data from all the sensors within a specific deadline, failure of which might lead to unpredictable and catastrophic events. This falls under the category of one-shot data collection. On the other hand, applications such as permafrost monitoring require periodic and fast data delivery over long periods of time, which falls under the category of continuous data collection. For periodic traffic, it is well known that contention-free medium access control (MAC) protocols such as Time Division Multiple Access (TDMA) are better fit for fast data collection, since they can eliminate collisions and retransmissions and provide guarantee on the completion time as opposed to contention-based protocols [1]. However, the problem of constructing conflict-free (interference-free) TDMA schedules even under the simple graph-based interference model has been proved to be NP-complete. In this work, we consider a TDMA framework and design polynomial-time heuristics to minimize the schedule length for both types of convergecast. We also find lower bounds on the achievable schedule lengths and compare the performance of our heuristics with these bounds. We start by identifying the primary limiting factors of fast data collection, which are: 1) interference in the wireless medium, 2) half-duplex transceivers on the sensor nodes, and 3) topology of the network. Then, we explore a number of different techniques that provide a hierarchy of successive improvements, the simplest among which is an interference-aware, minimum-length TDMA scheduling that enables spatial reuse. To achieve further improvement, we combine transmission power control with scheduling, and use multiple frequency channels to enable more concurrent transmissions. Literature survey: According to Valter Crescenzi, Giansalvatore Mecca and Paolo Merialdo, “Road Runner: Towards Automatic Data Extraction from Large Web Sites”, Extracting data from HTML sites through the use of automatically generated wrappers. To automate the wrapper generation and the data extraction process, the paper develops a novel technique to compare HTML pages and generate a wrapper based on their similarities and differences. Experimental results on real-life data-intensive Web sites confirm the feasibility of the approach. According to Deng CAI, Shipeng Yu, Ji-Rong Wen and Wei-Ying Ma, “Extracting Structure for Web Pages based on Visual Representation” Content A new web content structure based on visual representation is proposed in this paper. Many web applications such as information retrieval, information extraction and automatic page adaptation can benefit from this structure. This paper presents an automatic top-down, tag-tree independent approach to detect web content structure. It simulates how a user understands web layout structure based on his visual perception. Comparing to other existing techniques, our approach is independent to underlying documentation representation such as HTML and works well even when the HTML structure is far different from layout structure. Experiments show satisfactory results. According to Chia-Hui Chang, “Automatic Information Extraction from Semi-Structured Web pages” The World Wide Web is now undeniably the richest and most dense source of information, yet its structure makes it difficult to make use of that information in a systematic way. Existing system Existing work had the objective of minimizing the completion time of converge casts. However, none of the previous work discussed the effect of multi-channel scheduling together with the comparisons of different channel assignment techniques and the impact of routing trees and none considered the problems of aggregated and raw converge cast, which represent two extreme cases of data collection. Proposed system Fast data collection with the goal to minimize the schedule length for aggregated converge cast has been studied by us in, and also by others in, we experimentally investigated the impact of transmission power control and multiple frequency channels on the schedule length Our present work is different from the above in that we evaluate transmission power control under realistic settings and compute lower bounds on the schedule length for tree networks with algorithms to achieve these bounds. We also compare the efficiency of different channel assignment methods and interference Models and propose schemes for constructing specific routing tree topologies that enhance the data collection rate for both aggregated and raw-data converge cast. Conclusions We studied fast converge cast in WSN where nodes communicate using a TDMA protocol to minimize the schedule length. We addressed the fundamental limitations due to interference and half-duplex transceivers on the nodes and explored techniques to overcome the same. We found that while transmission power control helps in reducing the schedule length, multiple channels are more effective. We also observed that node-based (RBCA) and link-based (JFTSS) channel assignment schemes are more efficient in terms of eliminating interference as compared to assigning different channels on different branches of the tree (TMCP). |
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