| Summary: | 博士 === 國立臺灣大學 === 電機工程學研究所 === 97 === Data management system in transient networks, such as Mobile Ad hoc NETworks (MANETs), sensor networks, and vehicular networks, is essential to allow users to analyze/reason a physical phenomenon by issuing queries. Traditional query processing techniques used by the database systems may not be adequate for transient networks as in these networks, the topology of nodes (or stations) is highly dynamic; and the capability of each node is limited by energy, bandwidth, and computing power. In this dissertation, we study how to achieve energy efficient data management in transient networks. Our study covers different aspects of query processing, including the query processing algorithms, the underlying network protocols to execute the algorithms, and their interworking.
The problem finding K-Nearest Neighbors (KNN) is one of the major topic in data management. In transient networks (especially mobile sensor networks), energy conservation should be done along with query processing. Current KNN algorithms require certain kind of indexing support. This index could be either a centralized spatial index or an in-network data structure that is distributed over the sensor nodes. Creation and maintenance of these index structures, to reflect the network dynamics due to sensor node mobility, may result in long query response time and low battery efficiency, thus limiting their practical use. In Chapter 2, we propose a novel algorithm called Density-aware Itinerary KNN query processing (DIKNN) that is more suitable for transient networks. DIKNN avoids the cost of index maintenance by combining the query dissemination and response collection in an itinerary.
In Chapter 3, we look down to MAC layer to study the energy conservation issue in transient networks. Although Quorum-based Power Saving (QPS) protocols have been proposed for ad hoc networks (e.g., IEEE 802.11 ad hoc mode) to increase energy efficiency and prolong the operational time of mobile stations, these protocols assign to each station a cycle pattern that specifies when the station should wake up (to transmit/receive data) and sleep (to save battery power). In all existing QPS protocols, the cycle length is either identical for all stations or is restricted to certain numbers (e.g. squares or primes). These restrictions on cycle length limit the practical use of QPS protocols in transient networks as each individual station may want to select a cycle length that is best suited for its own need (in terms of remaining battery power, tolerable packet delay, and drop ratio). We propose the notion of Hyper Quorum System (HQS)---a generalization of QPS that allows for arbitrary cycle lengths, and therefore tailorable energy conservation effect on each station.
Based on the results in Chapters 2 and 3, in Chapter 4 we investigate how query processing algorithms at Application layer and energy conservation protocols at MAC layer can interwork with each other. We take in to account the clustering techniques at Network layer, which is common in Mobile Ad Hoc Networks (MANETs) to ensure the scalability and efficiency of various communication protocols, and propose an Asymmetric Cyclic Quorum (ACQ) system that is able to give further energy conservation by letting the MAC acknowledge the requirements from upper layers. In Chapter 5, we further extend the concept of ACQ to the vehicular networks and propose DSRC-AA that is suitable for highly dynamic networks requiring very short packet transmission delay.
We conduct extensive simulations over our studies. Simulation results show that DIKNN, ACQ/DSRC-AA, and HQS can achieve significant improvement in energy conservation at Application, Network, and MAC layers respectively in handling queries while preserving user-tolerable latency and query result accuracy.
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