## 1 Introduction  
Civil structures are constantly affected by diverse forms of external forces and environmental influences during their life-time. The potential for error or oversight in their initial design and construction, negligence of the user, or other factors cannot be excluded from discussions regarding the structure's long-term stability and safety and, therefore, to prevent large-scale damage or accidents,systematic management plans and countermeasures should be prepared in advance. As a part of such efforts, research into structural health monitoring (SHM) systems was begun earnestly by the construction field in the 1990s to evaluate the condition and detect damage to civil structures in real-time. Major large bridges are a key focus of the application efforts of SHM [1; 2; 3; 4; 5; 6]. Currently, since existing SHM systems build upon existing wired measuring systems, it is expensive to expand the measuring channels and maintain and manage the very large response data sets obtained. Since long-term measurement is required for accurate SHM, new systems should outclass existing systems. Recently, measurement and monitoring technologies using wireless sensor networks (WSNs) have attracted attention [7; 8; 9; 10], and application examples using WSNs in various fields have also been introduced [11; 12; 13; 14; 15; 16; 17; 18]. In the construction field, [PERSON] et al. [19] and [PERSON] et al. [20] developed a smart SHM (S-SHM), in which WSNs are newly incorporated into SHM systems. For these systems, the cost of building the system is reduced and the CPU and memory are embedded in the sensor, so that by RF networking, simple preprocessing of the measured signal is possible. It is feasible to install the sensor in limited-access or dangerous environments not accessible by existing wired measuring systems. [PERSON] et al. [21] and [PERSON] et al. [22] developed the Imote2, a wireless sensor node that uses the concepts of S-SHM, and performed substantial research, including health monitoring and structural evaluation, on a full-scale bridge. [PERSON] et al. [23] developed another wireless sensor node, Narada, by adapting a self-recharging method using solar panels and an inter-sensor node sub-networking scheme to obtain more stable data compared to existing S-SHM systems, applying the node to the Carquinez Bridge in California, USA. In these studies, the S-SHM systems configured using individual wireless sensor nodes improve the economic feasibility of installation and obtain better efficiency in terms of the system configuration, operation, and management, compared to existing wire-based SHM systems [24]. It is highly important for SHM of civil structures to be able to measure an accurate dynamic acceleration response of the structure in real-time. Generally, since the measurement of the dynamic response of a structure requires a large amount of data via each channel compared to a simple static response, building and managing systems that can capture and analyze these data can vastly increase costs. The S-SHM systems previously developed, which use wireless sensor nodes, are limited in their performance once the number of input channels is increased, due to the significant increase in the data acquisition rate and the corresponding necessary storage capacity [20; 22]. Optimum performance can be obtained by configuring the wireless sensor node at the level of a high-performance PC to improve the data processing speed and storage capacity. Furthermore, although diverse wireless communication methods (e.g., Bluetooth, Zigbee, Wi-Fi) are currently used, each one of them has weaknesses and strengths with respect to factors such as the limits of their communication distance, speed, and the number of expanded channels. However, if the initial volume of the raw data from the structure can be reduced, these fundamental limitations of existing wireless communication technologies can be overcome.