In proceedings of the international symposium on mobile Ad Hoc networking and computing p. Computer Communications. The evolution of MAC protocols in wireless sensor networks: a survey.
The Evolution of MAC Protocols in Wireless Sensor Networks: A Survey - Semantic Scholar
Efficient clustering-based data aggregation techniques for wireless sensor networks. Wireless Networks. Survey of MAC protocol for wireless sensor networks. In second international conference on advances in computing and communication engineering pp. An energy-efficient MAC protocol for wireless sensor networks. In proceedings of the annual joint conference of the IEEE computer and communications societies pp.
International symposium on algorithms and experiments for sensor systems, wireless networks and distributed robotics pp. In international symposium on computers and communications pp. An adaptive energy-efficient MAC protocol for wireless sensor networks. In proceedings of the international conference on embedded networked sensor systems pp.
An adaptive energy-efficient and low-latency MAC for data gathering in wireless sensor networks. In proceedings of the international symposium on parallel and distributed processing p. Medium access control with a dynamic duty cycle for sensor networks.
In wireless communications and networking conference pp. R-MAC: reservation medium access control protocol for wireless sensor networks. In local computer networks pp. One of the key factors for introducing BN-MAC is to reduce energy consumption while addressing idle listening, overhearing, mobility, and congestion concerns. The network is constructed as a flat single-hop topology. BN-MAC follows the concept of the owner slot. The node has complete access to its owner slot, similar to TDMA-based approaches.
The remaining slots are accessed through the CSMA approach. The CSMA approach preserves energy and controls collisions. In addition, BN-MAC eliminates idle listening in each region to achieve a considerable energy saving. Bi-directional traffic inside each region of the WSN promotes smooth data exchange and efficient use of the bandwidth. Additionally, BN-MAC uses dynamic contention free slot exchange, which increases network scalability under even a heavy traffic load.
BN-MAC consists of the following phases: finding the list of one-hop neighbors, intra-semi-synchronous transmission scheduling, inter-synchronous transmission scheduling, and selection of a BN. These operations are performed once during the setup process and are not performed again until the network topology is physically changed.
In this approach, the initial costs for running these operations are balanced while achieving a better throughput and reduced energy consumption during intra- and inter-transmission. When a node intends to start communication with its neighbor node after accessing the channel, the node sends an Anycast message to its one-hop neighbor nodes to obtain the details of neighboring nodes.
This process helps to reduce overhead and manage network load balancing. The process of sending the Anycast ensures that the intended neighboring nodes are able to talk with each other, even if they possess different sleeping and communication schedules. The neighbor discovery process consists of short messages short preambles , which consume less network bandwidth and improve the throughput.
Each node randomly sends a short preamble for finding the list of intended neighbor nodes using Anycast after two seconds for 15 s. This timing is used obtain maximum throughput; packet sending intervals from 1 to 10 s were considered, but the time interval of 2 s provides the maximum throughput. We have also set the packet sending time at 15 s to facilitate the successful completion of the packet sending process. If we set the time less than or higher than 15 s, then the node energy is wasted. The node is unable to complete the packet sending cycle when the time is less than 15 s, and when the time is greater than 15 s, the node comes into the idle situation because after finishing the packet sending task and thus waits on the channel until the level of set time is reached.
The node discovery process in BN-MAC consists of a one-hop neighbor node, but nodes are able to obtain two-hop neighbor information that is helpful for expanding cross-layering support. The two-hop information that has been obtained is also used for slot allocation, which enables the node to increase mobility because the node retains the information even when the two-hop node is moving.
BN-MAC is scalable because the one-hop topological change is easy to handle; each node knows the schedule of the one-hop neighbor node. BN-MAC uses a promising time scheduler because the assigned slot does not exceed the one-hop neighborhood. BN-MAC also performs the without changing the time slots of existing nodes.
The localized time slot allocation which is used with channels to synchronize for the whole network. Otherwise, conflict between different traffic flows can occur. It also helps the node to gather allocation information for all 1-hop and 2-hop neighbor nodes. This feature of slot allocation re-use improves throughput and reduces node latency. The intra-semi-synchronized process starts with channel sampling. The node wakes up for a short period of time to sample the medium.
Channel sampling is performed once during the channel allocation time. After channel sampling, each node initially sends a short preamble message asynchronously using the Anycast approach within the one-hop neighbor node to obtain the list of one-hop neighbor nodes. When the sender receives a reply from the one-hop neighbor nodes, the sender attempts to fix the schedule with the intended one-hop neighbor nodes nodes that are chosen for future communication before sending the data.
Each node knows the wake-up and sleep schedule of its intended neighbors. These dual features of sending a short preamble asynchronously to obtain the list of neighbor nodes and fixing the schedule synchronously reduce the network overhead. When the sender completes the scheduling process with the intended nodes, the sender chooses the shortest efficient path for sending the data using the LDSNS model, as explained in [ 33 ].
This model helps to reduce energy consumption and the links with the network layer. The use of a short preamble message allows for reductions in overhead and latency at each hop.
- MAC Protocols for Energy Harvesting Wireless Sensor Networks: Survey.
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The short-preamble-enabled MAC protocols have an advantage over the long-preamble-enabled MAC protocols due to their low-power duty cycle mechanism. The existing lower power listening LPL technique uses a long preamble and suffers from the overhearing problem, which increases energy consumption in non-targeted receivers, such as Z-MAC. LPL also increases latency at each hop [ 34 ]. In the long-preamble techniques, the node must wait until the long preamble is received before it starts receiving data and acknowledgments. This approach increases energy consumption on both the sender and receiver sides.
Targeted receivers are also affected because the targeted receivers have to wait until the long preamble is received, causing increased energy consumption. X-MAC uses a short preamble message to reduce the energy consumption and latency, but one disadvantage of X-MAC is that the destination address of the node is inserted into each short preamble message. X-MAC forces all nodes to check the preamble to determine whether they are targeted nodes, which increases energy consumption and the duty cycle wake-up process.
X-MAC is based on an asynchronous mechanism, and no schedule of neighbor nodes is maintained, making it more difficult for each node to send data without prior scheduling information. Unlike X-MAC, BN-MAC deploys both asynchronous features for sending short preamble messages to obtain the list of one-hop neighbor nodes and synchronous features for fixing the schedule with the intended neighbors.
The MAC protocol should be capable of handling spatial correlation while also adjusting to changes in the number of competing nodes [ 35 ]. When multiple nodes want to communicate with the same neighbor node within the region, BN-MAC uses a slotted contention window. Then, the nodes randomly select a slot in the contention window. The winner of the slot obtains access to the medium for communication. Thus, there is small probability of collision at the medium. BN-MAC has another feature the helps to reduce packet loss. If multiple nodes attempt to select the same slot, BN-MAC uses sampling and randomization such that each node has an equal probability of accessing the channel.
Furthermore, BN-MAC uses congestion window slots, whereas the other MAC protocols use 1—32 contention windows for randomized listening before sending the preamble messages. This increased number of slots reduces congestion and latency and allows higher throughput to be obtained. These experiments indicated that BN-MAC produces the maximum throughput when slots are used, as shown in Figure 4. Hence, the use of window slots increases the throughput considerably.
Sensor nodes also perform automatic buffering within the region during intra-communication to reduce the drop rate and prolong the network lifetime. X-MAC uses a short preamble with a target address to access the channel to communicate with another node. However, all of the nodes en route will remain awake until the short preambles are received by the destination node, which results in increased energy consumption. X-MAC also has a delay of transmission for sending the packets until the receiver wakes up [ 36 ].
The BN-MAC protocol does not use the target address of the node when sending a short preamble message. Thus, all of the nodes do not continue to wait; instead, only the intended node wakes up to receive the short preamble. Thus, each node is in sleep mode for a longer period of time. In addition, BN-MAC uses an automatic packet buffering process similar to that used in [ 37 ]; this process reduces the wake-up time and increases the network lifetime.
In the automatic buffering process, the node uses a promiscuous mode that enables the node to listen to all ongoing data traffic and coordinates, if requested. Furthermore, the node saves a copy of the received packet regardless of the intended destination of the data packet until receipt of the packet is acknowledged by the destination node. Such buffering requires a relay that is used by the saturated conditions because each node is able to cooperate in sending data packets to other buffers.
As mentioned above, a short preamble consumes less energy and prolongs the network lifetime. Let us find the energy consumed for channel sampling and short preamble messages. During intra-communication, the node that transmits its clock to the one-hop neighbor is called the parent, and the receiving node at the one-hop neighborhood is called the child.
The nodes that are synchronized with the clock often use a short preamble without the target address of the node that reduces the energy consumption. The average short preamble reception time could be reduced because the receiving node wakes up based on the stored schedule of the neighbor nodes. The average energy consumed by the parent and child nodes can be obtained as follows:. From Equations 3 and 4 , we can obtain the total energy consumed sending the short preamble during the event monitoring time. Equation 3 represents the energy consumed by the parent node in sending the short preamble within the one-hop neighbor nodes, whereas Equation 4 represents the energy consumed by the child node in receiving and sending by the short preamble to the two-hop neighbor nodes and also acknowledges the parent node.
BN-MAC can clearly identify the consumed energy of the short preamble prior to sending the data. Figure 8 presents the superiority of BN-MAC compared with other low-duty-cycle MAC protocols in terms of time consumed in sending the short preamble to confirm the synchronization process for forwarding the data. All of the nodes in BN-MAC maintain the same time frame during synchronization and maintain a time slot of 0.
Each node maintains its own local frame, which matches the frame size of the neighborhood to avoid potential conflicts while contending with neighbors. The nodes compete for CSMA equally during the contention phase because the random exponential back-off an algorithm that uses response to multiplicatively reduce the node's frequent access to the channel dynamically in order to find the acceptable node to access the channel, as the part of network congestion avoidance preserves the right of each node to compete fairly for scheduled slots.
Intra-semi-synchronous communication is performed inside the region because BN-MAC is designed purely for the region-based network, as many WSN application areas require a region-based network. The intra-semi-synchronized transmission schedule is compatible with all types of radios, such as CC and CC The previous section highlights how to access the channel and forward the data inside regions.
This section explains how to set the schedules within and outside regions. Inter-synchronized transmission is performed from one region to other regions. The BN receives intraregional data packets within the region, and the BN forwards the inter data packets outside of the region. The BN does not wait to receive an acknowledgment from all of the region nodes. In this manner, each node knows the BNIS.
The BNIS consists of the current time, the next distribution time, the next collection time, and the schedule for obtaining intraregional data packets from the nodes of the region, as shown in Figure 9.
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The BNIS also has the responsibility of exchanging traffic slots between the source and the destination and describing the related offset time. Once the BN announces its schedule for the nodes of the region, all of the nodes are responsible for following the given schedule. At the end of the scheduled time of the region nodes, the BN synchronizes with another BN of a region to exchange an interregional synchronous schedule to send and receive data communication. After the contention period starts, the node responsible for the data exchange requests the schedule-slot for the next scheduled distribution time.
The nodes only remain active during the BNIS. When the BN intends to communicate with another BN of a region, the BN begins the interregional synchronized transmission schedule by using carrier sensing. We tested the intercommunication performance of BN-MAC and other hybrid protocols in terms of throughput and average energy consumption.
An Energy-Efficient MAC Protocol for Wireless Sensor Network
We use varying numbers of transmitting nodes at a low duty cycle. Figure 10 presents the average energy consumption for each transmitter node, illustrating that BN-MAC is superior to the other hybrid MAC protocols at a low duty cycle. As mentioned above, BN-MAC has an intra-semi-synchronous transmission schedule that follows the low-duty-cycle mechanism as well as the inter-synchronized transmission schedule that supports the low duty cycle under heavy traffic.
BN-MAC also consumes less energy over a heavy traffic load using the low duty cycle. Figure 11 presents the potential increase in throughput obtained via BN-MAC during heavy traffic at a low duty cycle. Another reason for BN-MAC's superior throughput performance is the use of BNs, which have automatic buffering capacity to store packets instead of discarding them.
No one node is compelled to declare itself as a BN based on a probability-based calculation. Each sensor node possesses a different energy level in the region after monitoring the event at any given time. The sensor nodes are actively involved in monitoring the events and forwarding the data of the targeted events to the BN.
This situation leads to the death of the BN before the other nodes that are not actively involved. Thus, the BN faces a shortage of energy. To overcome this problem, the proposed BNVSP helps to determine the energy level of each node to select a BN based on the maximum residual energy of the sensor node in each region. Each sensor node announces its residual energy after completing the event monitoring process. This maximum residual energy amount determines whether the node should be considered a BN candidate or not but depends on the residual energy of the sensor node and the distance from the node to the base station.
We categorize the energy of sensors into six levels is given in Table 1. Algorithm 1 determines energy level for each sensor node. When the energy level of the BN that is already working decreases, the responsibility is shifted from one BN to another BN using the election flag bit EFB , a signal alert sent by BN in the network for the election of new BN when decreasing its energy level. The proactive method is used to select the next BN to reduce the overhead associated with this process. The base station broadcasts a short preamble message to each WSN node. Each node calculates its distance from the base station based on the signal strength.
The node that receives a short preamble becomes a candidate for the BN. Other factors are also considered when selecting the final BN, including the energy of the BN consumed during the contention time for election comparison time of the energy level , the energy consumption of the sensor node in each state, and the time spent in each state and the transmitted data at each step. All candidate BNs check their radio range and residual energy. The radio range is selected by the short preamble sent by the base station, and the residual energy is selected using the BNVSP, as shown in Table 1.
The residual energy level for choosing the BNs is determined as follows:. Let us determine the residual energy level of each sensor node. If the sensor node completes the event, then the sensor node decreases its energy level. Therefore, the energy used in the event is equal to the difference between the sensor node's final and initial energy levels:. If part or all of the consumed energy in the sensor node is renewable Rn e , then the new energy of the sensor node C R n e can be found as follows:. We obtain the energy of the sensor node by substituting for 1 2 V z e c d 1 as follows:.
The current BN also sends a signal for a new election when the battery is running down. After the election process, the new BN resumes its duty and the current BN terminates its function. The new BN is automatically selected, allowing network disturbances to be avoided. The node is periodically set into the sleep state in the duty cycling protocol [ 39 ]. The node can maintain a tradeoff between data latency and energy consumption by fixing the state of either sleep or wake-up automatically. The node consumes less energy at a higher latency for data delivery with a lower duty cycle.
Once a node wakes up during its active duty cycle time, it should listen to the channel for a specific period of time to determine whether other nodes are available for communication. This situation creates difficulties and increases the overhead of the MAC protocol due to idle listening, which is a major source of energy consumption. The nodes continue to monitor the channel for incoming traffic, which increases energy consumption. Some of the WSN applications require transfer at a low data rate, but the sensor nodes remain idle for a longer period of time after performing their specific events.
It is not advisable to keep the sensor nodes in the idle state for a significant period of time. Thus, the energy consumed in idle time can be computed using Equation 12 :. Our goal is to transition the sensor nodes into the sleep state if no event is underway. Equations 12 and 13 indicate that the states of operations in the sensor nodes can be established automatically. An automatic change of transitions can be justified if Equation 15 is satisfied:. The above model indicates that the energy consumption due to idle listening can be avoided.
The BN also announces its schedule; therefore, there is no probability of consuming energy. This model decides the nature of the environment, i. The IDM model forces the sensor nodes [ 41 ] to work on either the passive or active mode of communication in response to the nature of the environment.
The IDM model helps to reduce energy consumption in both modes but particularly in the passive mode. The sensor nodes working in the passive mode do not consume the energy of their battery but may instead harvest energy, such as solar energy from the environment. K sensor nodes collect information regarding the IOE and then determine the nature of the environment.
We have set values for the IOEs. The detection process is based on the maximized probability of detection MPD method used by the Neyman-Pearson Lemma [ 42 ]. The K sensor nodes start the detection process from the UE because they are initially unaware of the nature of the environment. One of the requirements for statistical optimization is establishing an expected value of UE.
Hence, we maximize the expected value of the probability to detect UE with respect to the constraints of the expected value of the probability:. We use the following probabilities to detect UEs and IEs:. Let us assume that the sensor nodes detect the environment independently. Thus, K sensor nodes detect UE based on the set probability values:. This condition indicates the presence of an OE. E i and E j indicate the energy saved by nodes i and j during transmission, respectively.
Thus, we can define the total saved energy of the WSN using Equation 7 :. The amount of energy consumed is calculated using Equation 23 :. We also prove the energy saved using the WSNs using Lemma 1. Bluetooth-enabled sensor nodes follow the energy preservation process during the passive mode using the integration method. Here, we present the numerical time integrators that allow energy P e to be preserved.
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- 1. Introduction.
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- The Evolution of MAC Protocols in Wireless Sensor Networks: A Survey.
We begin by assuming an x-point quadrature formula with nodes N i. The required weight of a i is obtained through Lagrange basis polynomials in interruption as follows:. Note that all the values for different real numbers cannot be equal to a i. We use the polynomial p d 0 for satisfying the degree:. The quadrature formula with nodes N i and weights a i decreases the integrator to a specific collection of methods. The solution obtained with these methods depends on the specific factorization of the vector field.
It also provides the significant understanding about the dynamics, even if the preliminary problem's value cannot be solved systematically. Thus, the Hamiltonian system becomes an energy-saving integrator. This result demonstrates that the sensor nodes also consume a minimum amount of energy during the passive mood. Real WSN environments use low-power radios because of their high asymmetrical communication range and stochastic link characteristics.
Simulation results could be slightly different from realistic experimental results [ 43 ]. If we make simple assumptions regarding wireless radio propagation, then the simulation results could be significantly different from realistic wireless radio features and diverse transmission power. It is critical to select a simulator that produces results that are reasonably close to the real environment. Thus, for our experimental simulation setup, we use ns In our experiments, the WSN is disseminated into N regions to collect information more quickly. We have simulated different realistic mobility- and static-based scenarios.
The simulation scenarios consist of nodes with a m transmission range. The initial energy of each sensor node is set to 40 J. The sensing mode is 12 mW. The total simulation time is 35 min, and the pause time is set to 30 s during phase initialization at the start of the simulation. During this phase, the BN is in the warm up phase, and the remaining sensor nodes are automatically in power-saving mode.
The presented results are an average of 10 simulation runs. The simulation parameters are illustrated in Table 2. We conducted several simulation tests from different perspectives but with a particular focus on the network coverage efficiency after deploying 1 to sensor nodes. Network coverage can be regarded as how efficiently WSNs monitor the targeted area of interest.
Network coverage can be considered a measure of the quality of service QoS. Network coverage efficiency is measured in different ways depending on the nature of the applications and what is being monitored. The coverage is also crucial for maintaining the connectivity, which is defined as the capability of the sensor nodes to reach the base station. To measure the network coverage, we have created 15 sessions simultaneously to determine the actual behavior of the network using highly congested network scenarios.
The homogeneous set of nodes with a deterministic positioning attempts to guarantee the network coverage and connectivity with a minimum number of sensor nodes. The nodes are distributed in the targeted area of interest into regions to determine where to deploy the sensor nodes. The limited energy resources must be used efficiently when choosing the BN because the BN is one of the major nodes in each region selected based on the presence of a high energy level using the LEI algorithm, which improves the connectivity of the WSN for a longer period of time.
Furthermore, sensor nodes must be transitioned into the sleep mode using the AAS model while conserving energy to adjust the transmission range properly so that the sensor nodes may use the minimum amount of energy needed to communicate with the BN and neighbor nodes. The performance of BN-MAC is also improved because the one-hop neighbor node searches are optimized using LDSNS so that the data can be forwarded to the base station using the shortest and most efficient path.
Energy is preserved by alleviating the routing load on some sensor nodes. By reducing the energy consumed via data routing, the network coverage is improved by prolonging the lifetimes of the sensor nodes. The minimum number of sensor nodes that are required to cover the entire network can be calculated as follows:. Let us assume that the sensing range is smaller than the dimensions of the monitoring area. However, a more accurate heuristic solution is required to follow these bounds closely regardless of changes that occur in the network parameters. BN-MAC outperforms the other hybrid protocols because the other hybrid protocols are not capable of achieving the same network lifetime with an increased number of nodes.
The network lifetime depends largely on the battery lifetime of the sensor node. The major concern is to extend the lifetime with respect to energy limitations. One way of extending the lifetime of the sensor nodes is to turn off redundant nodes and let the redundant nodes go into the sleep state to conserve energy. Our coverage-preserving BN idea reduces the energy consumption and therefore increases the system lifetime. BN-MAC has the ability to manage traffic and reduce the idle listening time. The BN-MAC mechanism consists of a semi-synchronous approach that helps to reduce the channel accessing time.
BN-MAC also uses a short preamble message for accessing the channel without an integrated destination address in each preamble that reduces energy consumption and prolongs the network lifetime. The sensor nodes in BN-MAC use three directions down, up, and local to transmit data to neighbors according to whether the nodes are 1-hop closer, 1-hop farther, or at the same hop distance, respectively. When a sensor node has data to send, the sensor node first senses the channel to confirm whether the channel is free. If the channel is free, the sensor node transmits a short preamble message without a destination address because the destination address consumes the excess network bandwidth and reduces the network connectivity.
We include transmission, propagation, and processing delays that help the preamble message to arrive at the required node during the channel polling time that also guarantees delivery of the data packets to the sensor node. The preamble transmission also overcomes the problem associated with small drifts in the clocks. Packet transmission starts when the transmission of the preamble ends. BN-MAC has automatic buffering because each node waits for the first packet to arrive, after which the remaining packets are buffered automatically to shorten the average packet delivery delay.
The semi-synchronous mechanism is one of the most significant characteristics of BN-MAC because the semi-synchronous mechanism reduces the average packet delay. Figure 18 presents the average packet delay of BN-MAC and other participating protocols at different mobility rates.
BN-MAC can manage its timeframe, number of random access frames, and rate of transfer frames while maintaining a nearly constant average delay. In contrast, Z-MAC and other competing hybrid MAC protocols does not have the mobility support, and thus, the average delay is increased. BN-MAC receives routing support from the EAP protocol at the network layer, which also helps to minimize the time needed for path discovery and route maintenance.
Figure 19 presents the number of packets delivered by BN-MAC and other protocols using variable packet sizes. BN-MAC delivers more packets than the other protocols. BN-MAC uses a balanced semi-synchronous schedule between the neighbor nodes. A semi-synchronous schedule helps to reduce energy consumption. Thus, the node energy exhibits a sharp decrease as the packet size exceeds an optimal length. This trend can be attributed to the maximum overhead, which increases the average re-transmission and thus decreases throughput. As the packet size increases, the exposed interval and probability of an interfering node increase.
When BN-MAC uses contention windows to avoid interfering nodes, there is a marginal likelihood that the packets will be dropped. In this manner, the size of the packets does not decrease the performance. Thus, there is a marginal likelihood of packet re-transmission. BN-MAC is also advantageous in terms of sampling and randomization, thus avoiding the packet loss. The other MAC protocols use 1—16 contention windows for randomized listening before sending their preamble message. BN-MAC configures the contention window to slots. Less energy is consumed because the idle listening time is controlled, as the sensor node consumes the maximum amount of its energy without performing actions on the channel.
The AAS model brings the sensor node into the sleep state after the event processes are no longer being monitored. Thus, the AAS model helps to maintain the fairness of the energy in the network during events. The capacity to send packets at faster rate is affected as the sensing range is increased. In duty cycling, the node is periodically placed into the sleep state, which is effective for decreasing the energy dissipation in the network.
The packet adjustment-based duty cycle feature of BN-MAC also effectively reduces energy consumption without significantly reducing throughput and increasing latency. Other participating MAC protocols take an even longer period of time to access the channel and deliver the packets, thus increasing the energy consumption. Thus, there is not a sufficient amount of power remaining in the other MAC protocols to send data for longer distances.
In this experiment, we measure the strength of the BN when floods are first sent to other regions. The packet delivery ratio of the BN is calculated as the total number of flood messages received from all nodes and delivered to other regions, which is divided by the total number of distinctive messages generated by all nodes.
Each message of the node consists of a sequential number to find the uniqueness of the message. The BN-MAC curve is considerably higher than those for the other curves because the delivery ratio remains stable with the different network traffic floods.
The high delivery rate is maintained because latency and idle listening are controlled. As a result, the same message is re-transmitted multiple times, and the packet delivery rate is reduced dramatically. Figure 23 presents the latency of BN-MAC and the other hybrid protocols at different hops and traffic flows. BN-MAC provides uniform latency at various hops and different numbers of flows. The BN-MAC mechanism uses Anycast for scheduling and unicast for sending data at the one-hop neighbor node, which helps to improve the throughput and reduces the latency.
There is also an extremely small probability of failure of a one-hop path. If a one-hop path fails, then a second alternative best one-hop path is chosen for intraregional data communication based on the stored information for the one-hop neighbor nodes. The mechanisms of the other MAC protocols support a multi-hop path technique. If one path fails, then it is difficult to immediately regain a path. Thus, the latency is increased, and the throughput decreases. Routing in WSNs is usually assorted due to several limited constraints. The network performance depends on flexibility of routing protocol.
From other side, an effective energy-efficient routing protocol design is big challenge for energy-constrained network [ 44 ]. In this experiment, our aim to choose proper routing protocol from existing routing protocols that should be compatible with BN-MAC features to create robust WSN. The suitability of routing protocol generally depends on application requirements because routing protocols maintain and discover the routes in the network.
The function of routing protocols extend network lifetime while maintaining the high-quality of connectivity and allowing the reliable communication between nodes. The sensor nodes are not accessible in some conditions because they are either located on the unreachable points or undergrounded for sensing the events. Hence, immediate human access to those sensor nodes is not possible [ 45 ]. Therefore, routing protocols should be mobility aware to deal with WSN applications' node mobility, event mobility and sink mobility. Hierarchal routing protocols HRPs categorize the nodes based on their functionality.
Nodes are divided into groups or clusters, and head node is selected to coordinate with inside and outside of the cluster [ 46 ]. The HRPs are proposed to increase network lifetime. However, HRPs are not using multi-hop communication. Attribute or data-centric based is another category of routing Protocols that is named as sensor protocols for information via negotiation SPIN.
These routing protocols distribute the information among the sensor nodes using energy-constrained efficiently [ 47 ]. The base of SPIN communication nodes depends on specific knowledge of application. SPIN allows sensor nodes to disseminate information using less energy resources efficiently. SPIN-RL does not provide optimal route at 1-hop destination, but helps to improve the search capability.
Energy aware routing protocol EAP is the energy efficient that uses sub-optimal routes to enhance the network lifetime. In EAP, single efficient path is chosen from many multiple paths to preserve energy. EAP has also priority over directed diffusion routing protocol family because EAP improves network performance and saves energy LDSNS reduces energy consumption while choosing an efficient route to path.
EAP helps to maintain resource awareness, and improves the network lifetime. EAP also possesses some hierarchal features, which can support to BN to coordinate with intra and inter data transmission efficiently. In this experiment, we have used WSN consisting of 16 hop-destination with 15 concurrent established sessions. If, we analyze the Figure 24 , it is observed that time for maximum hop number is calculated 0. The competing hybrid MAC protocols have used their original underlying routing protocols. Each region consists of several sensor nodes that are controlled and coordinated by BN.
Proactive Energy-Efficiency: Evaluation of Duty-Cycled MAC Protocols in Wireless Sensor Networks
In this experiment, BN broadcasts the control message while setting the paths for data transmission. The broadcasting message process consumes enough energy amount but sensor nodes lack the adequate energy resources. From other side, EAP chooses single efficient path from group of multiple paths to save energy. Figure 25 shows broken routes during entire simulation time. The competing MAC protocols experience the problem due to use of their original routing protocols. As a result, those protocols took enough time for route discovery.
The route discovery time could be longer in some critical circumstances. Further, it is also easier to discover the route in WSNs based on single hop discovery process. The single-hop discovery process can handle the scalability and maintain the network mobility efficiently [ 37 ]. Path detection time for each hop is varied because it depends on the density of nodes that can be calculated as follows:.
Let us assume that F p is the probability density function a function that defines the comparative probability for the random variable to yield desired value; it is usually associated with absolutely continuous univariate distributions. Thus, the value of H [ Nr ] can be calculated as follows:. Determining the discovery time for broken links at each path, we need to consider the number of hops, network size and velocity of each node. Substitute the value of N a in Equation 32 to get Equation 34 :. Energy consumption has been known to be one of the greatest challenges of WSNs and will continue to be an immense challenge for the deployment of WSNs because the advancement in battery technology has been slower than the growth of processing power and data communication rates.
This challenge has attracted researchers to introduce several new energy-efficient protocols to address this problem [ 48 ]. Hybrid MAC protocols are of paramount importance because they have lower energy consumption and better scalability than other categories of MAC protocols. The Z-MAC protocol belongs to the hybrid family that supports multi-hop topology, and the nodes are fixed at their positions. The global time synchronization is used to synchronize the nodes, and slots are assigned to nodes but not fixed for each node.
Z-MAC competes for the channel within any slot for data transmission. The assigned node is given high priority, which reduces collisions. The latency is increased, and the throughput is moderated. Z-MAC faces some problems because of the use of long preamble messages with a destination address, which increases the duty cycle and energy consumption. The fixed topology limits the node scalability of WSNs.
The setup of the network phase becomes more difficult when a new node joins or leaves the network. Mobile nodes are unable to receive and send data packets. As a result, the network paths are broken. Speck-MAC is efficient in transmitting the unicast messages, but the sender wastes excess energy by sending additional frames even though the receiver has already received the frames. The additional frames consume channel bandwidth and thus reduce the packet delivery rate. Speck-MAC supports mobility when the network path is broken, which increases latency.