Wireless Sensor Networks, Data Collection Study

Wireless sensor network usually consists of large number of sensor nodes with self-organized manner. And data gathering is one of the most fundamental and important operations in sensor networks. Sensor nodes sample local environment, and transmit the results to base station through the multi-hop routing, even to the remote user. Currently, the power for sensor node is supplied by dry battery or fastener battery. So it is a challenging task to design energy-efficient data gathering protocols for wireless sensor networks. Moreover, low delay is a typical QoS requirement in wireless sensor networks, that's because low-delay data gathering can help to capture the abnormity in the monitoring area in time. Also, it is important to avoid the disaster and to decrease the loss of the disaster.This dissertation mainly studies the energy-delay-aware data gathering problems: coverage-preserving gathering gathering-oriented node placement and interference-free transmission scheduling. Finally, we develop a fire monitoring system with sensor networks based on the correlative research results.The problem of coverage-preserving data gathering is to study the trade-off and optimization between the density of the active nodes and the transmission range between the nodes. In the dense network, it will produce the redundant data, thus wasting much energy. And the node's transmission range becomes longer in sparse network, which results in mass transmission cost. Hence, this dissertation first defines the coverage-preserving data gathering problem, which mainly selects a certain number of nodes to construct an energy-efficient tree while preserving the original coverage. This problem can be formalized into integer linear programming, and we present a heuristic algorithm, CPDG, to solve this problem. Simulation results show that CPDG can greatly improve the performance of the network. For example, it can conserve about 30% energy cost compared with famous PEDAP algorithm. To extend the network lifetime, an impro- ved algorithm, BCPDG, mainly constructs the tree based on the remainder energy on each node when some nodes use their batteries up, thus can balance the energy cost among all nodes and extend the network lifetime.In gathering-oriented placement problem, m data source nodes and base station are fixed in a given area, and how to efficiently place n relaying nodes to minimize the total energy consumption. This dissertation first designs an efficient placement algorithm for linear model, and presents a vector-based node placement algorithm for the planar network model. That is, a novel vector-based placement algorithm is used to calculate the positions of the relay nodes to reach an energy-efficient deployment for wireless sensor network which contains fixed source nodes and certain number of relay nodes. The experimental results illustrate that the network deployed by our algorithm saves 50% energy of that deployed by regular algorithm when the ratio of source- and relay-number is 1:2. As in practical application systems, the numbers of nodes are often limited because of the cost, so our algorithm is of significant importance to construct low cost WSNs application system.Many applications, such as emergent succor and fire monitoring, etc, require that the nodes can report the data to the user in lower delay. Thus, it is necessary to study energy-delay-aware data gathering problem. This dissertation presents an energy-delay-efficient data gathering algorithm (SODG), which takes the transmission interference into considerations. This algorithm is fully distributed and localized, for it is only depending on one-hop neighbors' information. To minimize the delay, the algorithm permits the parallel transmission, thus it is difficult to avoid the interference among the nodes. We first construct Gabriel graph with local information, and build up data gathering tree on the Gabriel graph. It can conserve the energy when transmission on the Gabriel graph, because this avoids the longer transmission range. What's more, parallel transmissions can minimize the delay. The experimental results show that our algorithm is energy-delay-efficient. Especially, SODG algorithm can conserve 64% energy compared with PEGASIS algorithm, and decrease 80% delay compared with ring- based gathering protocols.Based on the research on the data gathering problem and combined with the practical requirements, we develop a fire monitoring prototype system. This dissertation also introduces the system architecture, the functional modules of the system and key energy-conserve technologies on the different layers of the protocol stack. Now, this system is in the phase of debugging in the real environment.The contributions and novelties of this dissertation are as following:It is the first time that this dissertation presents coverage-preserving data gathering scheme, which studies the trade-off between the node density and transmission range. And the dissertation designs two energy-efficient data gathering algorithms, CPDG and BCPDG.For node placement problem, this dissertation designs a novel Vector-based algorithm to place the nodes efficiently. And the experiments show its efficiency. For real-time data gathering problem, we design a distributed and localized algorithm to schedule the nodes' transmissions, so as to achieve low delay and low energy cost.The dissertation explores the data gathering problem through computational geometry, which can be extended to solve other problems in the field of sensor network.More than the theoretical research, this dissertation describes a fire monitoring system based on wireless sensor networks. Now, we have finished the prototype system on MicaZ platform, which contains about 30 sensor nodes.