Optical waves do not suffer from such high attenuation but are affected by scattering. Moreover, transmission of optical signals requires high precision in pointing the narrow laser beams. The traditional approach for ocean-bottom or ocean column monitoring is to deploy underwater sensors that record data during the monitoring mission, and then recover the instruments.
This approach has the following disadvantages: Real time monitoring is not possible. This is critical especially in surveillance or in environmental monitoring applications such as seismic monitoring. The recorded data cannot be accessed until the instruments are recovered, which may happen several months after the beginning of the monitoring mission.
No interaction is possible between onshore control systems and the monitoring instruments. This impedes any adaptive tuning of the instruments, nor is it possible to reconfigure the system after particular events occur.
Sensor deployment guide
If failures or misconfigurations occur , it may not be possible to detect them before the instruments are recovered. This can easily lead to the complete failure of a monitoring mission. The amount of data that can be recorded during the monitoring mission by every sensor is limited by the capacity of the onboard storage devices memories, hard disks, etc. Therefore, there is a need to deploy underwater networks that will enable real time monitoring of selected ocean areas, remote configuration and interaction with onshore human operators.
This can be obtained by connecting underwater instruments by means of wireless links based on acoustic communication. Many researchers are currently engaged in developing networking solutions for terrestrial wireless ad hoc and sensor networks. Although there exist many recently developed network protocols for wireless sensor networks, the unique characteristics of the underwater acoustic communication channel, such as limited bandwidth capacity and variable delays, require for very efficient and reliable new data communication protocols.
The six-component tuple is defined as follows:. Observe the channel state via b and the award value returned to the system when the action a is taken under the state s. For easy description, the superscript indicates the time and subscript indicates the set state.
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No superscript and subscript indicates the variant at the present time. For interactions between the MDP model based on the belief state and underwater acoustic channel, refer to Fig. As presented in Fig. The influences of states on the observation is changed to the influence of observations on the belief state. The interaction between MDP model and underwater acoustic channel based on internal belief state. The uncertainty of the underwater sensor network environment and the extended sensor network life shall be considered in the MDP decision of the belief state space.
In Eq. Channel occupancy is predicted according to the present belief state and actions, in order to reasonably perceive the belief state and connection action in the next cycle. For easy description, the underwater acoustic sensor network is comprised of n randomly distributed underwater acoustic sensor nodes, which is represented as G V , E. V indicates the set of sensor nodes, and E represents the edge set. Each underwater acoustic sensor node corresponds to one 3D coordinate x , y , z in the 3D space, and the communication radius of these nodes is R. Definition 3 The distance between two nodes, s u and s v , in the Euclidean space is described as follows:.
The underwater acoustic sensor node is under the half duplex operation mode, namely, the node is only the transmission or receiving node at the time t. In the communication radius R , if multiple transmission nodes send data to one receiving node, the receiving node shall reasonably schedule the channel slot to reduce channel access conflictions. The time axis of the receiving nodes is averagely divided into n slots. The transmission node transmits data packets in the time slot allocated under the obtained channel use privilege.
The action state a n,t of the transmission node s n is divided into the silent state and busy state. The transmission node s n receives the confirmation message ACK and no confirmation message NAK observation values for free or busy receiving channels.
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The node states are partially observable. Therefore, the channel access conditions at a slot depends on the present state of each node and the historical observation value. It is assumed that the size of each data packet is r bits. In Eqs. The state transition probability depends on the final observation values and present node state in the belief state space MDP system. In order to improve the network channel utilization rate and extend network survival life, the transmission node with the high link quality shall be first selected for the transmission data packets.
The nodes with higher residual energy shall be selected to forward data, in order to avoid the excessive consumption of some nodes.
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One target for optimizing channel scheduling is to obtain the maximal award scheduling strategy. The channel scheduling target function calculated by Eqs. The set of transmission node s i is Sset , and the receiving node is s j. Sset comprises of the adjacent nodes of s i. Read s i in Sset in order to set the reading node as s n.
When the receiving node s j is free, s n sends control packet RT to s j. Remove s n from Sset. Output the queue q i , which is the scheduling sequence of the channels used by the transmission node. Obtain the scheduling sequence q i of the channel, according to the transmission node and transmit data packets in the allocated slots.
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After transmission, the state of the channel used by the node is predicted according to link quality, residual energy, and belief state space. NS3 was simulated and analyzed. The performance of the MAC protocol was evaluated using Aqua-sim as the simulator, and the sensor node was made to work under half duplex mode.
The sensor node can move at random in any direction. For parameter setting, refer to the reference [ 14 ]. The network throughput, energy consumption and success rate of transmission data were used as the reference parameters in the simulation analysis. The correlation among the network throughput, data packet transmission rate, and node quantity of the three different MAC protocols was compared. The network throughput of the three MAC protocols is proportional to the transmission rate of the data packet refer to Fig. When the transmission rate of the data packet reaches 0. In the AUT-Lohi protocol, the competitive node only intercepts one T max , and the tone frame may collide with the data packets in next cycle.
In the ST-Lohi protocol, two-way epicophosis led to the collision between tone frames and data packets, and between data packets. The relationship between network throughput and packet delivery rate and number of nodes. Legend: The correlation among the network throughput, a data packet transmission rate, and b node quantity of the three different MAC protocols was compared.
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The network throughput of the three MAC protocols was proportional to the quantity of sensor nodes refer to Fig. When the node quantity reached 80, the network throughput would gradually approximate to its saturation.
Nodes with better link quality could transmit data reliably with each other. For the relationship among the data packet transmission success rate of sensor nodes, the data packet transmission rate and node transmission radius of three different MAC protocols were compared. The data packet transmission success rate of sensor nodes of three different MAC protocols was disproportional to the transmission rate refer to Fig.
When this was proportional to the data packet transmission rate, the data packet transmission success rate of the BSPMDP-MAC protocol became higher than that of other two protocols. The competitive nodes obtained channel access privilege via the tone frame competition in the ST-Lohi protocol. When collision occurred, the random collision backoff was used to affect the data packet transmission success rate. One low-probability tone frame collision as used in the AUT-Lohi protocol.
When collision occurred, the confliction backoff algorithm was used to reduce competition time and decrease the loss rate of packets in AUT-Lohi. When the data packet transmission rate was lower, this method was effective. When the data packet transmission rate increased, the transmission success rate of data packets quickly decreased. The relationship between packet transmission rate and packet transmission rate and node. Legend: For the relationship among the data packet transmission success rate of sensor nodes, the a data packet transmission rate and b node transmission radius of three different MAC protocols were compared.
The data packet transmission success rate of sensor nodes is disproportional to the transmission radius for the three MAC protocols refer to Fig. When the transmission radius of the sensor node increased, the adjacent nodes of each sensor node also increased.
Therefore, the nodes fiercely competed for channel use privilege, the channel collision probability increased, and the data packet transmission success rate was significantly reduced. The correlation between the energy consumption of the sensor node and node quality for three different MAC protocols:. The energy consumption of the sensor nodes was disproportional to the node quantity for the three MAC protocols refer to Fig.
When the sensor nodes increase, the communication distance between sensor nodes would become shorter.