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High-rise structure monitoring with elevator-assisted wireless sensor networking: design, optimization, and case study

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Abstract

Wireless sensor networks have been widely suggested to be used in cyber-physical systems for structural health monitoring. However, for nowadays high-rise structures (e.g., the Guangzhou New TV Tower, peaking at 600 m above ground), the extensive vertical dimension creates enormous challenges toward sensor data collection, beyond those addressed in state-of-the-art mote-like systems. One example is data transmission from sensor nodes to the base station. Given the long span of the civil structures, neither a strategy of long-range one-hop data transmission nor short-range hop-by-hop communication is cost-efficient. In this paper, we propose EleSense, a novel high-rise structure monitoring framework that uses elevators to assist data collection. In EleSense, an elevator is attached with the base station and collects data when it moves to serve passengers; as such, the communication distance can be effectively reduced. To maximize the benefit, we formulate the problem as a cross-layer optimization problem and propose a centralized algorithm to solve it optimally. We further propose a distributed implementation to accommodate the hardware capability of sensor nodes and address other practical issues. Through extensive simulations, we show that EleSense has achieved a significant throughput gain over the case without elevators and a straightforward 802.11 MAC scheme without cross-layer optimization. Our distributed implementation in EleSense performs only marginally worse (<1%) than the centralized optimal algorithm. Moreover, EleSense can greatly reduce the communication costs while maintaining good fairness and reliability. Our case study with real experiments and data sets on the Guangzhou New TV Tower further validates the effectiveness of EleSense.

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Notes

  1. http://www.cse.polyu.edu.hk/benchmark/.

  2. Note that to the best of our knowledge, in civil applications, data aggregation in the intermediate nodes is not practical for the time being (for background on civil data evaluation, one may refer to [6]).

  3. Note that the random way point mobility model is only used for generating elevator movements. Although as discussed later in Sect. 8 that EleSense can naturally work on any mobility model that can predict future elevator movements, here the random way point mobility model is not used for elevator movement prediction.

  4. A link is considered good if it can reliably transmit a data packet within one time unit.

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Acknowledgements

This research is partly supported by a Start-up Grant from the University of Mississippi, an NSF I/UCRC Grant (1539990), an Industrial Canada Technology Demonstration Program (TDP) grant, an NSERC Discovery Grant, and an E.W.R. Steacie Memorial Fellowship.

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Correspondence to Feng Wang.

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A preliminary version of this paper appeared in IEEE INFOCOM’12.

Appendix: Design of evaluation function

Appendix: Design of evaluation function

In EleSense, we use the following evaluation function for a vertex \(v_{M,t}\) with \(M=(m_0,m_1,\ldots ,m_n)\):

$$\begin{aligned} Eval(v_{M, t})= & {} \min \limits _{t<t' \le t_{pause}} \left( CC(t')\right. \\&\left. + \max \left( q(t'-t), TC(t')\right) \right) \text {,} \end{aligned}$$

where \(t_{pause}\) is the finish time of the latest known elevator movement (since then the elevator is assumed to pause), \(CC(t')\) is the communication cost and \(TC(t')\) is the time cost for all the remaining packets to be delivered to the base station.

Since the elevator may move during the time of \([t,t']\), we define \(E\text {-}MAX(t')\) and \(E\text {-}MIN(t')\) as the highest and lowest locations that the elevator appears during this period. Figure 3 shows an illustration. Sensor nodes are then divided into three sets, namely, “Direct”, “Above” and “Below”. The Direct set contains those sensor nodes with chances to directly send data packets to the base station. And the Above set includes those higher than \(E\text {-}MAX(t')\) and needing others to help relay the packets; the Below set is similar to the Above set except that its sensor nodes are lower than \(E\text {-}MIN(t')\). The communication cost \(CC(t')\) is thus computed as

$$\begin{aligned} CC(t')=\, & {} p \cdot \sum _{i=1}^{n} m_i \cdot \left( I_{[s_i \in Direct]} \right. \\&+\, HOP(s_i, E\text {-}MAX(t')) \cdot I_{[s_i \in Above]} \\&\left. +\, HOP(s_i, E\text {-}MIN(t')) \cdot I_{[s_i \in Below]} \right) \text { ,} \end{aligned}$$

where HOP(ab) is the minimum hop count from a to b. The time cost \(TC(t')\) can be further computed as

$$\begin{aligned} TC(t')= \,& {} TC_{Direct}(t') + TC_{Relay}(t') \text {,} \end{aligned}$$

where \(TC_{Direct}(t')\) is the time cost for the packets that can be directly transmitted from a sensor node to the base station and \(TC_{Relay}(t')\) is the time cost for the packets that have to be relayed to reach the base station. \(TC_{Direct}(t')\) is calculated by

$$\begin{aligned} TC_{Direct}(t') = q \cdot \sum \limits _{i=1}^{n} m_i \cdot I_{[s_i \in Direct]} \text { .} \end{aligned}$$

And \(TC_{Relay}(t')\) is computed by

$$\begin{aligned} TC_{Relay}(t')=\, & {} \max \left( TC_{Above}(t')+TC_{E\text {-}MAX}(t'),\right. \\&\left. TC_{Below}(t')+TC_{E\text {-}MIN}(t') \right) \text { ,} \end{aligned}$$

where \(TC_{E\text {-}MAX}(t')\) and \(TC_{E\text {-}MIN}(t')\) are computed by q times the durations taken by the elevator to achieve \(E\text {-}MAX(t')\) and \(E\text {-}MIN(t')\), respectively. \(TC_{Above}(t')\) is the time cost for the packets at the sensor nodes in the Above set to be relayed to the base station (at \(E\text {-}MAX(t')\)). If we put the packets by the increasing order of their hop distances to the base station, it is easy to find out that when the first packet goes towards the base station, the later packets can just follow it back-to-back like a pipeline, \(TC_{Above}(t')\) is then computed as q times the sum of the duration taken by the first packet to reach the base station and the time units equal to two times of the remaining packet number (since a sensor node can not send and receive data packets within the same time unit). \(TC_{Below}(t')\) is computed by a similar way. As the base station may receive packets alternatively from both directions (from the Above set as well as from the Below set), we take the maximum (including the time for the elevator to move to the corresponding location) for the final value of \(TC_{Relay}(t')\).

It is worth noting that since the evaluation function does not consider the time costs to hold transmissions to avoid the interferences of wireless links, its value in fact serves as a lower bound of the actual weight costs. Thus to further reduce the number of visited vertices, during the local search we also cut down a search branch if the sum of its evaluation function value and its current total weight is already greater than the currently found minimum total weight to the last row.

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Wang, F., Wang, D. & Liu, J. High-rise structure monitoring with elevator-assisted wireless sensor networking: design, optimization, and case study. Wireless Netw 25, 29–47 (2019). https://doi.org/10.1007/s11276-017-1539-5

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