Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol
Abstract
:1. Introduction
- Source nodes (normal node with sensors).
- Intermediate sensor nodes (particularly cluster heads in clustered networks).
- BS.
- To monitor and record activities within the supervised area.
- To detect and record events inside the supervised area.
- Evaluation based on selected standards and parameters.
- The best way to monitor regions, minimize cost, and maximize network efficiency.
- Cut down the adverse impacts of the high mobility of UAVs.
- Traditional routing protocols cannot efficiently manage flying networks due to high node mobility and topology changes.
2. Background
2.1. Flying Ad Hoc Networks (FANETS)
- (1)
- Wireless transmission unit, consisting of two modules of radio frequency for emission and reception that provide wireless connectivity for linking the node to the network.
- (2)
- Sensing unit, incorporating the data attained by one or more sensors, and an ADC (Analog to Digital Converter) for converting a sensor-produced analogue signal into a numerical signal.
- (3)
- Treatment unit, whereby the CPU, storage, and routing protocol are the main parts. This unit performs the protocols of communication that enable communication between nodes.
2.2. Low-Energy Adaptive Clustering Hierarchy (LEACH)
- The clustering in the LEACH protocol reduces the amount of energy used for communication between sensor nodes and the BS, extending the network’s longevity.
- Data aggregation used by CH saves a significant amount of energy by reducing the associated data locally.
- Nodes in the network are placed into sleep mode, which does not get a TDMS slot as CH assigned TDMA schedules. Thus, collisions within the cluster are prevented, and the sensor node battery life is extended.
- Every sensor node in the LEACH protocol has an equal probability of becoming the CH at least once. This randomized rotation of the CH increases the network lifespan.
- At the end of each cycle, the CH is selected at random from all sensor nodes. There would be an equal chance for both high-energy sensor nodes and low-energy sensor nodes to attain the tag of CH. If the CH is picked as the sensor node with the least energy, it will expire fast, the network’s resilience is harmed, and the network’s lifespan is reduced.
- LEACH does not guarantee the position and quantity of CHs in each round. In a basic LEACH, cluster formation is random, resulting in an unbalanced distribution of clusters in the network.
- CH’s position in some clusters may be in the center of the clusters, while in others, the CH’s location may be towards the cluster’s edges. As a result, intra-cluster communication in this circumstance consumes more energy and reduces the sensor network’s overall performance.
3. Related Work
4. Proposed Methodology
4.1. Setup Phase
4.1.1. Cluster Formulation and Cluster Head Selection
Algorithm 1 for Setup Phase: |
Some Notations used in algorithm: NN: Numbers of nodes CH: Cluster Head BS: Base station N: For Every node START All N in NN has probability to be selected as CH For Every Node (N), where N ∈ NN For every N select random number between 0 and 1 If (Select random number <= T(n)) Then N is selected as CH and N broadcast a message of its CH status Else N become Ordinary Node N receive Message by other about their CH status End of if End of for loop For Every CH (Procedure to Select Min Distance between N and CH and CH to BS) Each node Select CH with Min distance to reach BS After previous step Node become a part of selected CH End of for loop For Every CH TDMA Schedule is constructed for each node(N) to Transfer data CH send information about the TDMA schedule to each Node(N) End of for loop |
4.1.2. Steady-State Phase
5. Experimental Results, Analysis, and Discussion
5.1. Number of Clusters
5.2. Consistency in Number of Cluster Head
5.3. Cluster Lifetime
5.4. Residual Energy
5.5. Probability of Delivery Success
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Protocol | Description | Research Focus | Modelling Criteria |
---|---|---|---|
LEACH | Basic approach | Load balancing | Energy saving |
LEACH-B | LEACH-B ensures a near-optimal number of CHs in each turn. After that, it considers the leftover energy when selecting CHs after the first round. | Equilibrating the count of CH | Left over energy |
LEACH-C | The BS uses a centralized algorithm to generate clusters and elect CHs based on node location and leftover energy. | Varying in CH | Position of BS and persisting energy of nodes |
LEACH-M | For data transmission to the BS, LEACH-M makes use of both conventional nodes and CH mobility. As a result, it’s well-suited to mobile surroundings. | Mobility and status of nodes | Mobility factor |
LEACH-I | CHs are chosen based on the amount of energy left, the position of the nodes, and the number of neighbors they had. The leftover energy is then used to update the threshold function. As a result, I-LEACH calculates the ideal cluster size. | Efficiency of energy | Resting energy, Neighbors number and node’s location |
LEACH-VH | CHs are chosen based on left over energy, and when the remainder energy of a cluster head reaches a certain level, a VH node takes over as the CH. | Multiple CHs in the cluster | Resting energy |
LEACH-T | LEACH-T analyses leftover energy while forming clusters and envisions a network with the optimal number of CHs. | Optimum Count of CHs | Resting energy |
LEACH-TB | Always a predetermined number of CHs is there. Thus, TB-LEACH CHs depend on a random timer for selection. | Cluster head varying | Random timer |
Improved-LEACH | Distance and left-over energy are two criteria in the selection of CHs. | Efficiency of energy | Distance from node to BS |
EADCR | Improve network life by employing the FCM method to set up clusters and choose CHs using a fitness function that relies on the Euclidean distance and nodes ‘s remaining energy. | Efficiency of energy | Euclidean distance and left-over energy |
BN LEACH | This model for choosing CHs use the Bayesian Network. | Balancing the load | Density, distance and residual energy |
Protocol | Category | Advantages | Limitations |
---|---|---|---|
LEACH | Residual energy | —Enhances the network’s life cycle by utilizing the TDMA schedule. —Balancing energy usage. —The number of packets for communication is decreased. —Reduces nodes’ energy discharge. | —Assuming that CH nodes are not uniformly deployed. Random election of CH. —The number of nodes is not distributed evenly in each cluster —Uses the single hop. |
LEACH-B | —Consistent Count of CHs. —Considers leftover energy after the initial turn —Improves the longevity of the network. | —Growth in overhead cost. | |
LEACH-C | Centralized | —optimum no. of clusters. —high no. of turns in a small network zone —The residual energy is the key for CH selection. —The strategy of centralization provides better distribution of CHs. | —Needs location information of nodes. Centralization brings in an overhead on the Base station. —The single hop transmission adds an additional overhead |
LEACH-M | Mobility | —CHs as well as non-CH node as high mobility. —An extremely efficient in terms of energy | —Supplementary overhead. |
LEACH-I | Residual energy | —Chose CH grounded on the left-over energy and node’s location. | —CH combines received data to save costs of further data transfer, but nodes that receiving different data it is not practical. |
LEACH-VH | Energy efficiency | —CHs selection on the fundament of the leftover energy. —Substitutes CH by VH node when the main CH attains a threshold. | —Supplementary treatment for VH node. —Drives data from CHs to Bs in a single hop. |
LEACH-T | —Determines the number of time slots in TDMA based on the number cluster members. —Bids an optimum count of clusters. | —CHs are selected randomly. | |
LEACH-TB | —Enhances the network’s life cycle and the CHs count is fixed | —Grounded on a random timer CHs selection is carried out. | |
Improved-LEACH | Distance | —Enhancing network performance through optimal CH selection. | —Complexity of calculation |
EADCR | —Improve the network lifespan | —CH selection is a complex process | |
BN LEACH | —Execute better than other | —High complexity |
Protocol | No of CH’s | CH Selection | No of Nodes in Cluster | Cluster Method | Mobility | Scalability | Energy Efficiency | Residuary Energy | Localization |
---|---|---|---|---|---|---|---|---|---|
LEACH | Indeterminate | Random | Indeterminate | Disseminated | Static | Fixed | High | No | No |
LEACH-B | Determinate | Random, Residual Energy | Indeterminate | Disseminated | Static | Effective | Very High | Yes | Yes |
LEACH-C | Determinate | Residual Energy | Indeterminate | Centralized | Static | Effective | Very High | Yes | Yes |
LEACH-M | Indeterminate | Residual Energy, Mobility | Indeterminate | Disseminated | Mobile | Very effective | Very High | Yes | Yes |
LEACH-I | Determinate | Residual Energy, | Indeterminate | Disseminated | Static | Very effective | Very High | Yes | No |
LEACH-VH | Indeterminate | Residual Energy, | Indeterminate | Disseminated | Static | Very effective | Very High | Yes | Yes |
LEACH-T | Determinate | Residual Energy, | Indeterminate | Disseminated | Static | Effective | High | Yes | No |
LEACH-TB | Determinate | Random | Indeterminate | Disseminated | Static | Fixed | High | No | No |
Improved-LEACH | Indeterminate | Distance and residual Energy | Indeterminate | Disseminated | Static | Effective | High | Yes | Yes |
EADCR | Determinate | Euclidean distance, Residual Energy | Indeterminate | Centralized | Static | Effective | Very High | Yes | Yes |
BN LEACH | Indeterminate | Density, Distance Residual Energy | Indeterminate | Disseminated | Static | Effective | High | Yes | Yes |
Parameter | Default Value |
---|---|
Simulation area | 100 × 100 |
Number of nodes | 100 |
Minimum distance between nodes | 2 m |
Simulation runs | 10 |
Simulation time | 120 s |
BS position | (50, 50) |
Initial energy | 0.5 J |
Probability of becoming a node as CH | 0.1 |
Energy for transferring of each bit | 50 × 0.000000001 |
Energy for receiving | 50 × 0.000000001 |
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Bharany, S.; Sharma, S.; Badotra, S.; Khalaf, O.I.; Alotaibi, Y.; Alghamdi, S.; Alassery, F. Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol. Energies 2021, 14, 6016. https://doi.org/10.3390/en14196016
Bharany S, Sharma S, Badotra S, Khalaf OI, Alotaibi Y, Alghamdi S, Alassery F. Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol. Energies. 2021; 14(19):6016. https://doi.org/10.3390/en14196016
Chicago/Turabian StyleBharany, Salil, Sandeep Sharma, Sumit Badotra, Osamah Ibrahim Khalaf, Youseef Alotaibi, Saleh Alghamdi, and Fawaz Alassery. 2021. "Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol" Energies 14, no. 19: 6016. https://doi.org/10.3390/en14196016