Research On Key Technologies For WSN-based Information Broadcast System

Wireless sensor network has becoming a hot research topic recently. It combines research areas like the microelectronic manufacture, sensing technology, theories of wireless communication, and embed technologies. In order to make full use of the power from monitoring and collection of WSN, and take advantages of the monitoring data, the WSN should be integrated with other theories and technologies. Among the related areas, distributed information broadcast system is one of those techniques which are closely connected with WSN. The monitoring data collected by WSN will be the basis of information broadcast system that manages, makes policy and controls the whole WSN and its data. This dissertation carries out the research work in the design of WSN-based information broadcast system and focuses on the related core theories and algorithms.This dissertation discusses the following problems:data collection&restoration in WSN, data propagation, and data update&schedule in large-scale hierarchical information broadcast system.Also, this dissertation proposes the event-triggered based subscription model, and then proposes a novel message oriented publish/subscribe broadcast system named EventX to cater to the features of sensor networks and its applications. According to type and time interval, EventX implements an algorithm to analyze and decompose compound subscription. After that, another weight information based greed algorithm is introduced for the low-energy state of nodes. Simulation results show that the EventX is suitable to reduce communication overhead and prolong the lifetime of sensor networks.Considering the continuing advances in sensor networks and application design, it's important to improve information availability in a class of delay-tolerant sensor network applications according to the scarce resources and sensor energy. This dissertation points out the design objective and introduces the system architecture of RealStore—a framework for providing in-network storage service in sensor environments, and defines the information storing cooperation zone as well as its zone manager in RealStore. RealStore implements an algorithm to store and extract information based on network coding theory in cooperation zone. Simulation test results show that the RealStore is capable to improve information availability efficiently.In the data server layer, existing event-matching algorithms are not very efficient, especially for interval range predicates and overlapping predicates in subscriptions. So this dissertation discusses the above challenge and proposes a dynamic and fast event matching algorithm called SGEM. SGEM algorithm can well support range predicates or overlapping predicates and provides single and composite event matching. It groups the subscriptions by the predicates and dynamically identifies appropriate number of groups considering different statistical distributions of subscriptions at run time. Also, we present an experimental evaluation and compare its performance with existing algorithms. The experiment results show that SGEM can significantly reduce the evaluation cost and guarantees the scalability with respect to the number of subscriptions as well as the number of predicates and events.This dissertation research updates propagation using broadcast delivery method in hierarchical data broadcast systems with a high rate of updates at the primary server and a high rate of data requests at the secondary servers. Updates are propagated from hierarchical data servers to single-item on-demand data requests from a population of data consumers. Three algorithms that combine update propagation with data broadcast scheduling in hierarchical data broadcast systems with a high rate of updates at the primary server and a high rate of data requests at the secondary servers are proposed named:RU, RU+ESI and PF algorithm. The proposed algorithms are functions of the rates of consumer requests and of data updates to increase data freshness and decrease consumers wait time. At the secondary servers, two implementations of the decision maker component of the proposed algorithms (i.e., LWF and RxW) are provided to demonstrate the versatility of the proposed algorithms. The experimental results show that the proposed algorithms are stable under various update arrival rates as well as consumers' request rates.Considering the challenges of scheduling items for broadcast by data servers in response to data consumers' multiple-item queries. This dissertation introduces the item selection approach, MLWF—a new data scheduling algorithm that adapts dynamic changes in the queue of pending queries. MLWF schedules a data item to meet the following conditions for broadcast:the item has a high frequency of occurrence among the pending queries, the total wait time of the queries in which the item occurs is large, and the broadcast of the item will cause a large number of queries to be completely satisfied. MLWF uses a normalized weight factor to give a higher priority to the broadcast of a data item that will cause the largest number of pending queries to be fully (or almost fully) answered. MLWF is compared with a generalization of LWF, Round Robin and FSO, All the experiment results show that MLWF performs better than LWF, FSO, and Round Robin in terms of consumers' average wait time.In the last section, a summary has been given for all the proposed research contents. The innovative points are summarized. Also, the further work has been discussed.