Abstract
Wireless integrated sensor networks, which include collecting, managing data and communication, are used more and more widely for their low cost and convenient deployment. Nowadays the research concerning each aspect of sensor networks is fairly active. Data Aggregation mechanism is one of the key problems in sensor networks. By considering the data transmission delay and overall network energy efficiency, this chapter develops a game-theoretic model of real-time reliable aggregation (RA-G) mechanism for wireless sensor networks. Based on the study of related literatures, first of all in this chapter, the research status of WSN, the system architecture, the characteristics, and the critical technologies are summarized, current typical routing algorithms of WSN are classified and introduced one by one. Taking the implicit collaborative imperative for sensors to achieve overall network objectives (accomplish real-time collection tasks effectively) subject to individual resource consumption into account, this paper proposes a game-theoretic model of reliable data aggregation architecture in wireless sensor networks, defines a multi-tier data aggregation architecture in which semantic based aggregation and average computation aggregation is performed in sensor-level and node-level aggregation respectively. All nodes that detect the same target join the same logic group. Each selected group leader uses game-theoretic model which tradeoffs between energy dissipation and data transmission delay to determine the degree of aggregation. To meet the real-time constraints and balance the energy consumption between nodes, a decision-making model based on game theory which takes delay compensation into account is proposed in the data-relaying stage. The simulation results show that the use of reliable data aggregation architecture can reduce the total transmission overhead of WSN, make the network more energy-efficient and prolong the lifetime of sensor network. On the other hand, the game-theoretic model used in group-level aggregation and data-relaying stage balance the tradeoffs between the energy dissipation and the timeliness of data transmission; therefore, also RA-G data aggregation mechanism is reliable.
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