To make MNAC works efficiently in a UAN, it is crucial to guarantee that both the source and the mirror node have identical data to send. In this section, I design a MAC protocol, called MNA-MAC to achieve this goal.
4.2.4.1 Spatially-correlated observation
In most of sensor networks, in order to detect the target events reliably, sensors in the immediate vicinity are deployed to observe highly correlated data. After the data fusion, the probability of a false detection from any single sensor node could be considerably reduced through the collaborative sensing. Therefore, the data collected by the sensors are spatially-correlated [68].
In the last ten years, people have leveraged the feature of spatial correlation to improve the performance of MAC protocols for a sensor network [68–70]. The main idea of these protocols are saving energy and reducing the collision probability among packets by suppressing the transmission opportunities among correlated observations. More specifically, due to the spatial correlation, neighboring nodes in a sensor network are most likely aware of the same event, hence a MAC protocol could select only a portion of nodes to report their sensing results. With this strategy, a network can reduce its traffic load and extend its lifetime dramatically.
Different from existing researches, I utilize the property of spatial correlation for a completely different purpose — maintain the identity of the data collected by the source node and the mirror node. To achieve this, in MNAC I always select a mirror
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node from the observation correlation area of a source node to guarantee that they have the same sensing data to transmit.
How to divide the correlation area dynamically in a complex underwater environ- ment, however, is a challenge. Particularly, the correlation region in a UAN may change with the time, e.g., when tracking a moving target or measuring the water temperature from different seasons. In this situation, a network should be capable of re-identify the correlation area in a varying environment for appropriate mirror node selection. Next, I introduce how to implement this function in MNA-MAC.
4.2.4.2 Assumptions
Here, I assume the network is static5 and non-synchronized. All nodes use a single channel for control message and data packet transmissions. I further assume that each sensor node knows the distance to its nearby buoys, which could be measured at the initial stage of the network through the classic two-way handshake method [71]. Similar distance measurement approach has been successfully tested in the sea experiment [72]. Furthermore, I suppose that surface nodes realize whether a sensor node is in their overlapping coverage area or not by sending test packets. If a sensor node hears test packets from different buoys, then it is in an overlapping coverage area of neighboring buoys; otherwise, it belongs to a single buoy.
Finally, I assume that surface nodes cannot hear the acoustic signals from each other, a transmission of one buoy thus will not disrupt the data reception of another. This assumption is based on the fact that surface nodes usually use the RF modem for internode communications [73], and thus the distance among neighboring buoys could be longer than the rage of acoustic communications.
5
The random drift of sensor nodes with the ocean current may result in a mismatch of the phase and the amplitude, especially the phase, between the source signal and the mirror signal, effects of which have been studied in Section 4.2.3.
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4.2.4.3 Protocol description
MNA-MAC consists of two stages for the correlation area detection and re-identification, respectively. In the first stage, each buoy divides sensor nodes in its coverage range into different clusters based on the cross-correlation coefficient among the collected data. In the second stage, the buoy involves new nodes into or removes old ones from a cluster with the variation of environments to re-identify the correlation area. Next, I introduce these two stages in detail.
Correlation area detection : In this stage, since the surface node has little knowl- edge regarding the correlation area of a network, it cannot select the mirror node rashly; otherwise, the data collected by the source and the mirror node may have some differ- ences, resulting in a packet collision at both the protected receiver and the intended receiver. Therefore, a surface node in this stage considers each acoustic node as an independent one, and then applies a conventional underwater MAC protocol for the data transmission [74, 75].
Each time when a surface node receives the data from sensor nodes, it measures the similarity among these data by calculating their cross-correlation coefficients. If the coefficient among any data packets over a certain threshold, the buoy divides the corresponding nodes into the same correlation area, and then groups them into the same cluster. This process will repeat several times for a reliable clustering.
Correlation area re-identification : In this stage, a source node sends out an RTS packet to reserve the channel before its data transmission. Once a buoy received the RTS, it first checks whether the source node is in an overlapping area of its neigh- boring buoys or not. If yes, the buoy selects a node from the cluster of the source node as a mirror node, and sends a CTS and an assist-to-send (ASTS) message to the source and the mirror node, respectively. Otherwise , the buoy simply replies with a CTS message to the source node, since its transmission would not disrupt other buoys.
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The CTS and ASTS packets attach the time information to tell the source and the mirror node how long they should wait for the following data transmission, respectively. Using the scenario depicted in Fig. 4.11 as an example, when node A and A0 receive CTS and ASTS from buoy S2, they are requested to wait for tA wait and tA0wait secs,
respectively, before their data transmission. Therefore, we have
tA0 wait− tA wait+dA 0S 2 − dAS2 c + tAST S= τ ∗ A0, (4.29) where dA0S
2 and dA0S2 are the distances from nodes A
0 and A to buoy S
2, respec-
tively; tAST S is the transmission time of an ASTS packet, and τA∗0 is the optimal delay
expressed in (4.22) to create a strong destructive interference. Let
Twait, τA∗0− tAST S+ dAS2 − dA0S2 c , (4.30) then we obtain tA0wait = Twait, Twait> 0, 0, otherwise, (4.31) and tA wait = Twait, Twait≤ 0, 0, otherwise. (4.32)
After a successful data reception, the buoy replies with an acknowledgement (ACK) message for a reliable communication.
Other nodes that do not win the contention for the following data transmission will enter the receive model. They overhear the packet sent from the winner and compare it with their local data. If a node collected the same data with the one it overheard, it discards the local data to avoid a redundant transmission; otherwise, it sends an RTS message to initiate a new round of communication after hearing ACK for the current winner.
Each time when a buoy receives data from the sensor nodes, it calculates the cross- correlation coefficients among them, and then classifies the nodes into different clusters.
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In this way, each buoy could re-identify correlation area in a varying environment and maintain the identity of the data from the source and the mirror node.