If node A could recognise the reason for packet loss, it could take appropriate strategy to handle in this situation. Rayanchu et al. Figure 9 shows that different actions are performed after a loss diagnosis. In the case of a collision, a BEB algorithm will be performed and in the case of a weak signal some parameters such as data rate and transmission power will be tuned. The previous approach was used in WiFi where only a small number of nodes were used. This work concentrates on WSN where multiple nodes are communicating together in a mesh network.
The approach in this work uses exactly the characteristics of a mesh network where a node usually has multiple neighbours. As already shown in Figure 10 , node A was not receiving any Ack from node B. However, node C receives the data successfully and knows it was addressed to its neighbour B. As node B never replied with Ack, node C assumes that the data packet was forwarded to B without any collisions between A and B. The only problems why node B was not able to reply with an Ack are as follows: The last case is only visible to node B and is not a collision between these three nodes.
As node C knows that there is no collision between node A and B, it assumes that there could only be a weak signal and sends a neighbour-Ack N-Ack packet after a timeout to node A. After receiving N-Ack packet, node A recognises that C is not the destination node and it assumes this packet has not arrived properly at node B. Using the BEB algorithm in this scenario would increase the time and energy consumption by idle listening. Instead of this, node A should retransmit the data packet immediately and does not increase CW. Figure 11 shows the timely behaviour of the protocol idea.
If node A sends a packet, it defines an Ack timeout and within that it expects an Ack from node B. In this case, due to the weak signal, node B will be unable to respond with an Ack. After the Ack timeout, node C sends a neighbour-Ack to show that it does not receive an Ack at all which offers node A to retransmit the packet immediately.
It ensures the sender node A has enough time to switch from transmitting to receiving mode and to receive the Ack reply. Initially, this new protocol idea decreases the throughput slightly in an ideal environment with no packet loss. However, the new protocol waits additionally for the neighbour-Ack which decreases the protocol throughput slightly. Theoretically, the new idea results in a small mean backoff time and a high throughput. If the wireless channel causes packet loss due to a weak signal, the neighbour-Ack provides support by keeping the backoff time reduced.
This enables transmitting more packets in a short period and therefore increases the throughput. In the case of a collision a BEB algorithm will be triggered to increase the retransmission time and in the case of a weak signal, a neighbour-Ack will be received and the packet directly retransmitted. It checks first whether the channel is idle or not and then it transmits the data packet; otherwise, it increases the backoff time. After a data packet is transmitted, the node waits for an Ack.
If there is no Ack received, the node waits for a neighbour-Ack. If both Acks are not received, the backoff time increases. The flowchart in Figure 15 gives an overview of the process in the receiving nodes. Each receiving node checks first if the packet is directed to it. For packets which are not directed to the node, the node checks whether the destination node is already sending an Ack back to the source or not, and it sends a neighbour-Ack.
The implemented protocol requires the simulation of collisions and weak signal. To ensure that the MiXiM framework can simulate this kind of behaviour, different scenarios were created and simulated. The MiXiM framework provides the simulation of real environment behaviour such as signal strength, attenuation, and delay. It implements the physical and MAC layer of the To prepare the simulation environment, values such as maximum distance or SNR which are based on the To decide if a packet is received correctly, a signal quality criterion should be defined.
As all scenarios are based on the But to find an appropriate BER value, some reference or recommendation is required. Based on a user guide for WSN node product which uses It allows calculating the necessary BER: The used packet length in all scenarios is bits. Using Figure 16 , an approximate SNR value of 1. This value is used as a criterion for all the following scenarios. This scenario simulates the collision between two packets which are transmitted at the same time.
As a collision scenario in WSN requires at least three nodes where two nodes send at the same time, the third node is listening and detects the collision. Figure 17 shows the scenario where node and node send data at the same time and node is receiving. In accordance with the BEB algorithm, the nodes increase the contention window by detecting collisions.
If node and node send at the same time, a collision occurs, and node cannot reply with an Ack because the data is corrupted. Both sender nodes recognise this unsuccessful data transmission and use the BEB algorithm to increase the contention window. In this bigger contention window, both nodes chose a random time for retransmission to avoid another collision. Originally the probability of collisions decreases if the contention window grows and the collision should be resolved. However, in this scenario, the CSMA MAC layer was manipulated to let all nodes choose the last possible retransmission time within the contention window.
This will let the nodes collide consequently and enable resolving the situation if the BEB algorithm increases the contention window correctly. It is visible that the contention window increases the first ten retransmissions exponentially and reaches a value of It uses this value for the next six retransmissions. After 16 unsuccessful retransmissions, a MAC Error message will inform the upper layers.
This scenario see Figure 18 simulates a transmission between two nodes where the distance causes a weak signal. The SNR of this signal is below the allowed threshold, and that causes packet loss. The MiXiM framework provides different wireless channel modes which influence the signal strength. To simulate channel behaviour in WSN two different models are used simultaneously.
This model simulates the basic attenuation influence on the signal depending on the distance of the node. Figure 19 shows the theoretical and experimental results. The experimental environment consists of two nodes which communicate with each other at different distances. However, this measurement result shows the relative signal strength. Furthermore, the experimental result shows that near the area of 20 meters the signal energy weakens quickly and above 20 meters it weakens slowly [ 28 ].
This behaviour requires a breakpoint model which simulates the attenuation in the closer range to be lower [ 30 ] and at longer range it grows higher and especially after the breakpoint in the opposite way. The following values enable simulating the red model in Figure Logarithmical Shadowing Model. This model simulates physical effects such as reflection, diffraction, scattering, and absorption [ 20 ]. This shadowing let the signal fading and enables simulating that two nodes have from time to time, the good or bad signal between each other.
The model calculates a random x value from the normal distribution. These two scenarios show that the MiXiM framework provides the necessary simulation base for subsequent implementation.
The new protocol requires that only the direct neighbours can send acknowledgments in the case of an acknowledgment failure by the two direct participant nodes. This is the reason why the implementation uses additionally a NeighbourList to save the neighbours for each node.
Each node learns about the neighbour during the transmissions and saves the information about its neighbours in this list. Taking advantage of this protocol requires that all nodes communicate before. This can be done by a simple broadcast packet exchange before the data transaction. The new implementation defines an additional rxDirectAckTimer method which is the deadline for Acks from directed nodes.
The initial rxAckTimer method is used as the deadline for neighbour-Ack.
MiXiM: Class List
The implementation requires running different tests to prove the basic functionality of the implemented MAC protocol. The test case in Figure 22 uses the usual three-node setup which was already described in previous sections. As Figure 23 shows, all three nodes use the same layer model. As the test application layer is responsible for creating the new packets, this was programmed to make the implementation based tests which create the necessary communication between these three nodes. Figure 24 shows how the application layer performs.
It first sends a broadcast from every node. This broadcast enables the nodes to learn from each other. After broadcasting, the only node or node A sends one data packet to node or node B. An implementation requires tests which are repeatable for tracing and debugging. The described analogue models previously have random signal quality behaviour which is not useful for implementation tests.
To provide repeatability, a special ScenarioModel method for implementation scenarios is used. The success of the data packet from node Figure 23 and subsequent packets depends on this model.
- Performance Analysis of MAC Layer Protocols in Wireless Sensor Network - Semantic Scholar.
- Performance Analysis of MAC Layer Protocols in Wireless Sensor Network.
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The connections between the nodes are viewed in Figure The ScenarioModel method allows enabling or disabling each of these connections by setting a value in an array. This array has a length of nine and its indexes represent the connections in Figure The implementation test framework let only node send the data packet. Based on this, different constructive scenarios should be tested to prove and debug the implementation.
The following Table 1 lists all possible constructive scenarios and compares both MAC protocols by using the same test parameters. Both protocols are using an exponential backoff and in case the backoff increases, both protocols choose the latest time interval as a worst case. In case of an invalid connection, the BEB increase the number of time slots, and a MAC Error will occur after a max backoff time The first scenario shows nearly the same resolving time as calculated max backoff time.
The reason for the inaccuracy is that the calculated time does not consider the additional delay for processing inside the nodes. The results show some behaviour differences between both protocols. The recorded time is the real value excluding the time which is necessary for previous broadcasts. In the first scenario, the data packet does not arrive at any other node. Node will never receive an acknowledgment and repeat the transmission 16 times and drop the packet by the end.
But this is only 0. The disadvantage of this protocol is shown in scenario This scenario is a successful transmission between both nodes A and B. It triggers an additional neighbour-Ack which is not necessary and spends time as well. This overhead increases the time shortly by Based on all these scenarios, it shows that the usage of the neighbour for acknowledging increases the reliability and reduces time in cases where the backoff increases exponentially.
In cases of successful transmission between direct participants, the time increases. The next section shows if this protocol brings an advantage in a real communication scenario where the time for communication is chosen randomly, and the packets are arriving depending on the signal strength which varies from time to time.
Similar to the implementation, the simulation requires a test environment as well. This environment creates a communication load and handles the success of the transmission. The new MAC protocol is designed to detect weak signals and to increase the throughput. The simulation requires throughput performance tests and an application layer which constantly sends new packets after previous packets have arrived successfully. Figure 26 shows how the simulation application layer performs.
It sends initial broadcast packets to enable the node to learn from each other. After all broadcasts are sent, a transmission of data packets is started by a simulation time of 10 seconds. As all nodes send first at the same time, a collision red will be caused, and each node triggers the BEB algorithm to choose a random backoff time for retransmission.
After that, each node sends to one of its neighbours and then it sends a data packet to its other neighbours as well not visible in the figure. This is one sending period. After every node sent a packet to each neighbour successfully, a new period for transmissions will be started. The number of period cycles in this layer is adjustable. Both simulation scenarios use this application layer, and the number of periodic cycles in both simulations is adjusted to 50 so that every node sends data packets to its neighbours.
Following parameters in each layer are used in both simulation scenarios as in Table 2.
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Institutional Sign In. Sensor nodes consume more energy when they have to send data and the consumption of energy depends on many factors. A class to represent the result of a processed packet that is not noise by the Decider. Defines an extended DeciderResult for the protocol which stores the bit-rate of the transmission. Defines an extended DeciderResult for the It allows to pass to the MAC layer the demodulate bit values, so that it the MAC layer can compare these demodulated bit values with the bit values actually encoded by the MAC layer at the origin.
This class is the interface for a Decider to the BasePhyLayer. This Decider models a non-coherent energy-detection receiver that synchronizes on the first sync preamble sequence that is "long enough" and "powerful enough". This is defined with the respective fields tmin and syncThreshold. This Decider models a non-coherent energy-detection receiver. Moves another Mapping in its time dimension.
Represents a set of dimensions which is used to define over which dimensions a mapping is defined the domain of the mapping.
Placeholder module that simply "translates" netwControlInfo to macControlInfo. Takes a source ConstMapping with a domain A and a set of KeyEntries for a domain B and creates a clone of the source mapping with the domain B and the KeyEntries passed. MappingIterator implementation for FilledUpMappings.
Non-Const version of the BaseFilteredIterator. Meant to be used for MappingIterator instances. HostState is published by the battery to announce host failure. This class regroups static methods needed to generate a pulse-level representation of an IEEE Clients can receive change notifications from the Blackboard via this interface. Short description for this AnalogueModel.
Provides an interpolateable iterator for any Container which maps from keys to values which is able to change the underlying Container.
Implementation of a Modified Wireless Sensor Network MAC Protocol for Critical Environments
Represents a std:: Helper class -specialization for multiDimMapping which is used by an InterpolateableMap as return value of the "getValue " - method. Mapping used to represent attenuation of a signal by JakesFading. Given two iterators defining a range of key-value-pairs this class provides linear interpolation of the value at an arbitrary key-position.
Specialization of the Linear-template which provides LinearInterpolation for pointer two Mappings. Used by MultiDimMapping. Helper class which represents a linear interpolation between two other mappings. Helper-class for the MultiDimMapping which provides an Iterator which linear interpolates between two other Mapping iterators. Or in other words, it provides an Iterator for an linear interpolated Mapping.
Linear movement model. Base class for mobility models where movement consists of a sequence of linear movements of constant speed. Adds multi channel support to Mac Stores information which is needed by the physical layer when sending a MacPkt. This control info allows to store the IEEEA config parameters that were used to generate the accompanying signal. Represents a changeable mapping mathematical function from at least time to double. Defines an iterator for a Mapping which is able to iterate over the Mapping. Models the mobility of with mass, making random motions.
This is the coordinator module of the MoBAN mobility model. Note that all WBAN instances may use the same input files if they are exactly in the same situation.