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Sensifi: a Wireless Sensing System for Ultra-High-Rate Applications Sensifi: A Wireless Sensing System for Ultra-High-Rate Applications Chia-Chi Li, Vikram K. Ramanna, Daniel Webber, Cole Hunter, Tyler Hack, and Behnam Dezfouli∗ Internet of Things Research Lab, Santa Clara University, USA fcli1, vramanna, dwebber, chunter, thack, [email protected] Abstract—Wireless Sensor Networks (WSNs) are being used in various applications such as structural health monitoring and industrial control. Since energy efficiency is one of the major design factors, the existing WSNs primarily rely on low-power, low-rate wireless technologies such as 802.15.4 and Bluetooth. In this paper, by proposing Sensifi, we strive to tackle the challenges of developing ultra-high-rate WSNs based on the 802.11 (WiFi) standard. As an illustrative structural health monitoring application, we consider spacecraft vibration test and identify system design requirements and challenges. Our main contributions are as follows. First, we propose packet encoding methods to reduce the overhead of assigning accurate timestamps to samples. Second, we propose energy efficiency methods to enhance the system’s lifetime. Third, to enhance sampling rate and mitigate sampling rate instability, we reduce the overhead of processing outgoing packets through the network stack. Fourth, we study and reduce the delay of processing time synchronization packets through the network stack. Fifth, we propose a low-power node design particularly targeting vibration monitoring. Sixth, we use our node design to empirically evaluate energy efficiency, sampling rate, and data rate. We leave large-scale evaluations as future work. Index Terms—Sensing, 802.11, WiFi, Low-Power, RTOS, Packet Processing, Vibration Test. F 1 INTRODUCTION a large number of wired accelerometers (more than 200), The reductions in the cost and energy consumption of simultaneously sampled by expensive, high-performance microprocessors, wireless transceivers and sensors have Data Acquisition (DAQ) modules [11]. The large number facilitated the development of Wireless Sensor Networks of nodes and the high sampling rate (around 50 kHz) (WSNs) for Structural Health Monitoring (SHM) as well result in generating a massive amount of data that must as applications such as Process Automation (PA), Factory be collected from the structure. This results in a disar- Automation (FA), and medical monitoring [1]–[5]. WSNs ray of wired connections that make installing and de- are being used in SHM applications to monitor spacecraft, bugging these sensors an excessively laborious and time- aerial vehicles, high-rise buildings, dams, highways, and consuming process. In addition to the setup difficulties, bridges [2], [6]–[8]. In these applications, sensor nodes the extra weight applied to the spacecraft by the cables collect information such as acceleration, ambient vibration, can skew vibrational measurement results [12]. The cables load, and stress at sampling frequencies usually above also introduce electrostatic noise that affects data collection 100 Hz [9]. The replacement of cables with wireless links accuracy. reduces design, deployment, and maintenance costs. Also, Besides satisfying the high sampling rate required by arXiv:2012.14635v2 [cs.NI] 20 Jun 2021 wireless links offer higher reliability compared to cables these applications, the additional system requirements are: that are subject to wear and tear. (i) liveness: collecting data from all the nodes while sam- In this paper, we use the term ultra-high-rate to refer pling is in progress, (ii) scalability: live data collection from to the systems whose data transmission rate is in the a large number of nodes (e.g., more than 200 in spacecraft range of few hundreds of Mbps to a few Gbps. The monitoring), (iii) energy efficiency: the nodes’ longevity ultra-high-rate of communication is the result of high- must satisfy the duration requirement of the experiment, rate, high-resolution sampling. Applications such as FA, (iv) accuracy: accurate timestamps must be assigned to Power Systems Automation (PSA), and Power Electronics the samples, and (v) reliability: lossless collection of raw Control (PEC) are representative of ultra-high-rate sce- samples is required. Unfortunately, the existing systems do narios [10]. A prominent example of SHM is spacecraft not address these requirements. We highlight design chal- vibration monitoring. These tests are performed to analyze lenges and the shortcomings of existing systems as follows. a spacecraft’s mechanical durability against the launch’s First, considering the energy limitations of sensor nodes, powerful vibrational forces. These tests are conducted with 802.15.4 and 802.15.1 are the primary wireless technologies used in existing works [13]. Consider a node collecting ∗Corresponding Author. 12-bit samples at 50 ksps. This node needs to communi- 1 cate at 600 kbps, excluding the overhead of the samples’ application scenario, the proposed methods and configu- timestamps; hence, the 250 kbps data rate provided by the rations can be used to achieve the desired energy-delay 802.15.4 standard is less than the communication demand tradeoff. Third (§6), we show that preparing and processing of one node. Similarly, the wireless technologies used in outgoing packets by the network stacks introduce a non- current industrial networks, such as WirelessHART [14], negligible delay that must be minimized to increase sam- WIA-PA [15], ISA 100 [16], WSAN-FA/IO-Link [17], and pling rate and stability. Our work reveals that bypassing WISA [18] cannot be used for ultra-high-rate sensing appli- transport layer processing is essential to minimize the cations. Second, the liveness requirement is not satisfied if effect of packet processing on sampling rate, and this samples are stored in the main memory or a memory card bypassing also translates into the higher performance of and then transferred whenever the user requests for data timestamp encoding. Fourth (§7), we present a thorough delivery [19]–[22]. For example, spacecraft vibration tests study of time synchronization and identify the challenges require live response monitoring, identifying malfunction- caused by network stack complexity. We place the time ing nodes, and making adjustments to the test configura- synchronization function in the 802.11 subsystem, between tion parameters. Besides, frequent placement and removal the packet decoding logic and driver, and confirm that of nodes in hard-to-access areas are not desirable. Third, the maximum error is bounded by 0:25 µs. Fifth (§8), we compression and in-network processing methods are lossy present a modular, low-power node design. This node is and cannot be used in scenarios where raw data collec- capable of collecting 16-bit samples at rates up to 500 ksps. tion is required to implement various data analysis meth- Therefore, it enables us to measure sampling rate varia- ods [7], [23]. Furthermore, the compression level provided tions, study the impact of packet processing on the sam- by these methods is not enough to adapt low-rate wire- pling rate, and evaluate energy consumption. Compared less technologies for ultra-high-rate applications. Also, the with the existing works that rely on TinyOS [7], [24], [25], high processing overhead of these compression algorithms Linux [26]–[28], or theoretical performance analysis [29], causes a considerable interruption in sample collection. [30], our hardware platform supports the two widely-used Fourth, variations of inter-sample delay make assigning Real-Time Operating Systems (RTOSes) targeting resource- accurate timestamps to samples more challenging, and constrained devices: FreeRTOS [31], [32] and ThreadX [33], achieving sampling rate stability is particularly difficult [34]. Also, we use the network stacks available for these in ultra-high-rate applications. Running additional tasks RTOSes, namely, LwIP [35], NetX [36], and NetXDuo [37]. on the processor causes interruptions of sample collection Therefore, a unique aspect of our work is identifying and and variations of the sampling rate. Therefore, the effect of tackling the underlying challenges of using these tools for running additional tasks, such as packet processing and developing ultra-high-rate applications. Sixth (§9), using wireless transmission, must be minimized. The existing our node design, we empirically evaluate various aspects work has identified this challenge; however, they do not of the system and demonstrate the performance enhance- offer a comprehensive evaluation or mitigation of these ments achieved with the proposed methods. However, we problems [20], [24]. leave large-scale throughput evaluation of the system as In this paper, we propose Sensifi, a system based on future work. The methods proposed in this paper can 802.11 (WiFi) standard for ultra-high-rate sensing appli- be employed for developing WSN systems for applica- cations. Towards tackling the underlying challenges of tions such as PA, FA, Building Automation System (BAS), developing this system, the main contributions of this paper intra-vehicle communication, and Wireless Avionics Intra- are as follows: First (§4), we show that assigning accurate Communications (WAIC). timestamps (sub µs accuracy) to samples introduces a significant overhead− and wastes precious payload bytes 2 SAMPLE APPLICATION SCENARIO and wireless communication bandwidth. Considering the distribution of inter-sample intervals, we propose three Although the proposed system can be used in various encoding methods to reduce payload overhead. These ultra-high-rate sensing
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