Internet Of Things Perception Layer Modeling And Fast Scheduling Method Research And Application

Internet of things (IoT) perception layer is the bottom layer in IoT architecture, itoccupies important position. This dissertation researches on IoT perception layer behaviormodeling method and fast scheduling method and application, which has important academicvalue and practical significance for promoting manufacture information technology,networked intelligent measurement and control technology development and application. Theresearch work is supported by High-level Talents Project of Guangdong higher school (letter[2010] No.79), Industrial Research Project of Guangdong Science and TechnologyDepartment (2009B010900045), and2012Guangdong-Hong Kong Key Area Major Project(2012A090200005).The research progress of related content at home and abroad includingmixed logical system MLD modeling, scheduling algorithm research progress, deadlockproblem with scheduling, etc. is reviewed to decide research contents of this paper. Researchwork includes several aspects as follows:This paper first studys IoT perception platform layer behavior MLD modeling method.Three basic nodes including sensor node, controlled node, coordinating node are used todescribe system application scenario, nodes’ internal information flow mechanism areabstracted by automata.. It realizes that the whole structure of IoT perception layer isexpressed clearly under multi-terminal, multi-tasking, multi-mode, the layer structure anddynamic behavior are described visually and normalized. MLD modeling method is used withIoT perception layer whole measurement and control behavior in information acquisition,scheduling, execution decisions between two states in three state automatically evolutionmodel is converted to MLD model, and IoT perception measurement and control processbehavior expression is deduced. IoT perception layer measurement and control processbehavior is described by state variables and input variables and auxiliary variables, thecontinuous dynamic feature, logical rules and operation constraints are integrated into stateequation with mixed integer inequality constraints.It can can grasp system process, systemoperation constraints, the qualitative knowledge and other factors on a macro level, it lays aimportant foundation for measurement and control system coordination optimization.Based on the MLD modeling, this paper studys perception layer scheduling planning method and performance optimization strategy. Based on IoT perception layer MLD modeland automaton scheduling model transformation analysis, it can realize the whole IoTperception layer MLD model and automatic scheduling model transformation. IoT perceptionlayer fast scheduling mechanism is proposed based on hierarchical automata. Global taskscheduling and control automata model, local scheduling automaton model are studied in themechanism. Systems at different levels can use independent scheduling policy and realize thatthe perception layer runs orderly, reliably and quickly. VOSM system hierarchical automatascheduling strategy is studied by UPPAAL simulation tool, results show that the performanceof VOSM system according to classic serial working mechanism not using the scheduler ispoor performance indicators and deadlocks may occur,while using hierarchical automatascheduling strategy, the performance index improved significantly. Furthermore, perceptionlayer performance optimization method is studied based on the deadlock problem. Themathematics expression is deduced for task and resource distribution characteristics when adeadlock occurs in perception layer. Time constraints and mathematical expression areestablished for deadlock detectors including global deadlock, data acquisition deadlock,parameter computing local deadlock. Genetic algorithm (GA) is used to quickly reliefdeadlock and ensure the cost is minimum when multitask stuck in a deadlock in perceptionlayer.According to the dynamic adaptability of task scheduling problem in perception layer, thispaper studys IoT perception layer information dynamic scheduling strategy. Implementationarchitecture of perception layer information dynamic scheduling method under data priority(DP-PIDSM) is put forward. Information service classification method based on theDPQ-EDF is adopted to realize sensor data sent to the coordinator according to the priority ofthe emergency degree to sensor data. Information scheduling method based on PP-WRR isput forward, it guarantee high priority queues can be served in high probability and lowpriority queues are served in low probability. Perception layer dynamic scheduling methodunder energy limit (EL-PSISM) is put forward. According to problems of how to save energyand meet the sensor nodes update rate, decision coefficient Cs_iis used to schedule nodessleep or not. Intelligent sensor node information scheduling model is built by MLD method,Simulation based on OPNET for DP-PIDSM and EL-PIDSM，parallel scheduling for30and 48sensor nodes respectively, the results shows that, DPQ-EDF information serviceclassification and PP-WRR information dynamic scheduling methods relative to the SPalgorithm, WRR algorithm, when packet scheduling process average delay is0.03s,0.01s, thedeadline index is increased by23.2%,7.3%respectively. Sleep scheduling and informationcommunication scheduling strategy, compared with not take EL-PIDSM scheduling methods,it can save energy50.4%when information loss coefficient is0.148. It reflects feasibility andeffectiveness of the model EL-PIDSM.To test the application effect of the method, the paper discusses the application of IoTperception layer scheduling method in vehicle operation safe state motoring (VOSM)platform. According to VOSM system architecture based on IoT, the system informationscheduling optimization model is researched and the time constraints for scheduling moduleare set up and their physical meaning is discussed. VOSM system fast scheduling and datapriority experiments show the practicability, effectiveness with IoT fast schedulingtechnology.