Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/226793
Title: Distributed TDMA Scheduling in Tree based Wireless Sensor Networks with Multiple Data Attributes and Multiple Sinks
Researcher: Vasavada, Tejas Mukeshbhai
Guide(s): Srivastava, Sanjay
Keywords: Engineering and Technology,Computer Science,Computer Science Artificial Intelligence
University: Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT)
Completed Date: 2018
Abstract: Data collection is an important application of wireless sensor networks. Sensors are newlinedeployed in given region of interest. They sense physical quantity like temperature, newlinepressure, solar radiation, speed and many others. One or more sinks are also deployed in the network along with sensor nodes. The sensor nodes send sensed data to the sink(s). This operation is known as converge cast operation. Once nodes are deployed, logical tree is formed. Every node identi_es its parent node to transmit data towards sink. As TDMA (Time Division Multiple Access) completely prevents collisions, it is preferred over CSMA (Carrier Sense Multiple Access). The next step after tree formation is to assign time slot to every node of the tree. A node transmits only during the assigned slot. Once tree formation and scheduling is done, data transfer from sensors to sink takes place. We have proposed an algorithm known as SLBMHT (Schedule Length Balancing for Multi-sink HeTerogeneous Networks). It is an extension of SLBMHM. The proposed algorithm is capable of balancing schedule lengths no matter whether imbalance is caused due to di_erence in density or di_erence in heterogeneity. It is also evaluated through simulations. It is found that the SLBMHT algorithm results in maximum upto 56% reduction in schedule length di_erence, maximum upto 20% reduction in overall schedule length and 2% to 17% reduction in energy consumption per TDMA frame during data transfer phase. It results in maximum 7% more energy consumption during control phase. As control phase does not take place very frequently, increase in energy consumption during control phase can be balanced by reduction in energy consumption during data x phase. As a result, network lifetime is going to increase. newline newline
Pagination: xv, 137p.
URI: http://hdl.handle.net/10603/226793
Appears in Departments:Department of Information and Communication Technology

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01_title.pdfAttached File78.46 kBAdobe PDFView/Open
02_declaration and certificate.pdf62.78 kBAdobe PDFView/Open
03_acknowledgements.pdf48.94 kBAdobe PDFView/Open
04_table of contents.pdf89.5 kBAdobe PDFView/Open
05_abstract.pdf95.9 kBAdobe PDFView/Open
06_list of principal symbols and acronyms.pdf69.12 kBAdobe PDFView/Open
07_list of tables and figures.pdf64.58 kBAdobe PDFView/Open
08_chapter 1.pdf199.35 kBAdobe PDFView/Open
09_chapter 2.pdf391.95 kBAdobe PDFView/Open
10_chapter 3.pdf119.29 kBAdobe PDFView/Open
11_chapter 4.pdf353.77 kBAdobe PDFView/Open
12_chapter 5.pdf666.61 kBAdobe PDFView/Open
13_chapter 6.pdf741.73 kBAdobe PDFView/Open
14_chapter 7.pdf89.7 kBAdobe PDFView/Open
15_chapter 8.pdf85.47 kBAdobe PDFView/Open
16_references.pdf80.14 kBAdobe PDFView/Open
17_appendix.pdf121.17 kBAdobe PDFView/Open


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