# Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks
## 2 Related Work
### Cluster Protocol in VANET  
This component defines few clustering algorithms of Hypertext Transfer Protocol (Wireless sensor networks WSNs), and their advantages and disadvantages are studied. Hypertext Transfer Protocol (LEACH) [22] is a self-organizer clustering protocol that uses cluster based hierarchical routing to distribute an energy load on network devices. In this algorithm, the role of the cluster head is played by all existing nodes in each round in order to achieve uniform energy consumption. LEACH algorithm has two stages: 1-setting up stage 2-stable stage. In the first stage, clusters are formed and in the stable stage, communications are directed to cluster head sent to the roadside unit after being received and aggregated. For each node, the value between 0 and 1 is computed in the first round, if the computed value is less than the specified value (called threshold) for a node and is considered a head cluster. Ignoring \"node residual energy\" in selecting the cluster head and random selection at beginning of each round are the weak points of this algorithm. Distributed load balancing unequal clustering using fuzzy approach (DUCF) [23] is a clustering algorithm-based o fuzzy system. In this algorithm criteria such as \"residual energy\", \"node grade\" and \"each node distance to the road side unit\" are used to form the cluster. In DUCF, unequal clustering is used to yield balanced energy consumption. Using imbalanced clustering and FSs (fuzzy systems) is said to be the advantage of this method. The disadvantages are to select head cluster in very round which leads to maximize consumption of energy. Multi-objective fuzzy clustering algorithm (MOFCA) [24] is an extra clustering algorithm based on fuzzy system. This algorithm is presented to solve \"energy hole\" and \"hotspot\" problems. In this method \"residual energy\", \"distance to road side unit, and \"node density\" are all used as fuzzy parameters, and in the starting of every round, random head clusters are selected. The selection of head cluster in this method is according to energy-based competition radius. Using unequal clustering in this algorithm causes balanced energy consumption, which is considered an advantage, and clustering in each round is taken to be a disadvantage. Energy aware unequal clustering fuzzy (EAUCF) [25] is another clustering method presented to increase a network's lifetime. This algorithm is based on fuzzy system in which \"residual energy\" and \"distance to road side unit\" are used as fuzzy parameters. In order to improve previous methods' performances, a complete probable approach is not used for node selection, and periodic exchange of cluster head role among the nodes is done using fuzzy system. This algorithm increases lifetime in static networks, but it is not suitable for dynamic ones [26]. One weak point of this algorithm is that clusters must be estimated before clustering, making the algorithm complicated. Another problem in EAUCF method is ignoring \"node density\" as a parameter in cluster head selection. As a result of this, a node with few neighbors might be selected as the cluster head. Stability can be considered as one of the advantages of this algorithm. The EAFCA algorithm [27] is presented to improve clustering in wireless sensor networks. In this algorithm, data transmission inside each cluster is done in a multi-hop way, and the competition radius for each cluster is considered to be equal to two hops. It uses \"residual energy\", \"node density\", and \"centralization degree\" for cluster head selection. Considering communications inside the cluster in a multi-hop way is one of the advantages of this method. In this algorithm, clustering is done in every round, which increases the quantity of sent control messagesand decreases the lifetime. The FLECH algorithm [28] is a hierarchical clustering algorithm based on fuzzy system. In this algorithm, \"residual energy\", \"centralization degree\", and \"distance to road side unit\" are used to elect the cluster head.