National Repository of Grey Literature 4 records found  Search took 0.02 seconds. 
Communication node Localization Techniques in Wireless Sensor Networks
Pekárek, Jan ; Kubánková, Anna (referee) ; Šimek, Milan (advisor)
The bachelor´s thesis describes wireless sensor networks and communication protocols. Below this thesis contains basic algorithms for localization techniques communication nodes in wireless sensor networks. These basic algorithms are classified by methods. The bachelor´s thesis values algorithms by their advantages or disadvantages for usage in the suggested localization algorithm. In this thesis is solved a new simulating programme J-SIM, peruse separate package that are useful in the wireles sensor networks. In J-SIM is created a sensor network and models separate communication nodes. Models communication nodes are created separately for sensor nodes and target nodes. For localization algorithm is created program in the programming language Java which run results from simulating programme J-SIM. Programme J-SIM, simulation created by virtue of Tcl script and final programme are applied to CD.
Reduction of position estimate error in incremental localization techniques
Pekárek, Jan ; Morávek, Patrik (referee) ; Šimek, Milan (advisor)
The diploma thesis describes localization of communications nodes in the Wireless Sensor Networks. This thesis contains basic algorithms for localization sensor's nodes as are Map-Growing and ABC (Assumption Based Coordinates). Then is chosen acceptable algorithm for simulation on random sensor networks. For research these problems is used software MATLAB. For a given the university's environment are researched appropriate algorithms with possible optimalization algorithms. The result of diploma thesis is a localization algorithm with initial multilateration system and this system is located in the center sensor's network. As algorithm IMap4-Growing (Improved Map4-Growing) with optimization, which uses optimization distance between sensors and radio range. In the diploma thesis is simulated optimalization algorithm Mass-Spring.
Communication node Localization Techniques in Wireless Sensor Networks
Pekárek, Jan ; Kubánková, Anna (referee) ; Šimek, Milan (advisor)
The bachelor´s thesis describes wireless sensor networks and communication protocols. Below this thesis contains basic algorithms for localization techniques communication nodes in wireless sensor networks. These basic algorithms are classified by methods. The bachelor´s thesis values algorithms by their advantages or disadvantages for usage in the suggested localization algorithm. In this thesis is solved a new simulating programme J-SIM, peruse separate package that are useful in the wireles sensor networks. In J-SIM is created a sensor network and models separate communication nodes. Models communication nodes are created separately for sensor nodes and target nodes. For localization algorithm is created program in the programming language Java which run results from simulating programme J-SIM. Programme J-SIM, simulation created by virtue of Tcl script and final programme are applied to CD.
Reduction of position estimate error in incremental localization techniques
Pekárek, Jan ; Morávek, Patrik (referee) ; Šimek, Milan (advisor)
The diploma thesis describes localization of communications nodes in the Wireless Sensor Networks. This thesis contains basic algorithms for localization sensor's nodes as are Map-Growing and ABC (Assumption Based Coordinates). Then is chosen acceptable algorithm for simulation on random sensor networks. For research these problems is used software MATLAB. For a given the university's environment are researched appropriate algorithms with possible optimalization algorithms. The result of diploma thesis is a localization algorithm with initial multilateration system and this system is located in the center sensor's network. As algorithm IMap4-Growing (Improved Map4-Growing) with optimization, which uses optimization distance between sensors and radio range. In the diploma thesis is simulated optimalization algorithm Mass-Spring.

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