# Hybrid Zoning Algorithm to Optimize Overhead in Smart Mobile Communication
## 2 Related Work  
Many studies have been carried out to reduce the cost of the protocol overhead in mobile communication. They aim to reduce the consumption of energy or to increase the reliability of the network. These techniques change the structure of nodes or reduce the number of transmissions. The authors of [18] proposed an improved hybrid location-based ad hoc routing (IHLAR) that combines topology-based routing and geographic routing to enhance the route request (RR) in Ad hoc On demand Distance Vector (AODV) protocol. Each node in IHLAR maintains a table of surrounding neighbors, as a virtual zone, that are at (p) hops. When establishing a RR, a source node or intermediate node uses pure flooding if the destination is within (p) hops and greedy-forwarding between virtual zones if the destination resides outside its zone. This mechanism helps to reduce the end-to-end delay related to the RR in case of long distance between a pair of nodes. However, the geographic routing leads to blockage when an intermediate node has no link to adjacent zone which may increase the delay. The authors of [19] proposed a hybrid algorithm to select a limited number of nodes as relays. The algorithm defines a reply area. It is the intersection between the signal range and the angle calculated based on the line between the source and the destination. As first optimization, only nodes inside the reply area relay the RR. As the second, and based on the location information received from the sender, a relay node calculates the distance between itself and the destination, and between the sender and the destination. The intermediate node rebroadcasts the packet only if it is closer to the destination than the initiator. This algorithm reduces the number of transmissions and redundant packets by choosing a small number of relay nodes. However, it needs to know previously the position of the destination nodes, which is not always available. In zone based multi-cast routing protocol (ZBMRP) [20], the authors combined a zoning technique with AODV protocol to reduce the overhead of multi-cast flooding. ZBMRP uses the route reply to organize nodes into groups to build multiple mesh networks along the source to the multi-castdestinations. Then, it uses tunneling technology to achieve packets between zones. The simulations showed that ZBMRP performs better than other multi-cast protocols in term of packet delivery ratio. However, The initiation phase to establish mesh networks increases the start of the multi-cast communication, which increases the end-to-end delay. The authors of [21] proposed core enabled hybrid routing (CEHR) protocol, which combines proactive and reactive mechanism to reduce the topology information generation in MANET. CEHR forms different subset of nodes called Core Nodes Set (CNS). Proactive traffic is allowed inside each CNS, while reactive traffic ensures inter zone communication. The proactive routing inside the CNS is enabled by Core Node (CN). This algorithm helps to reduce the transmission of the topology information and the RR between the CNS which enhances the packet delivery ratio. However, CEHR increases the size of control messages which impacts the throughput negatively. The authors of [22] proposed a hybrid algorithm based on the Cellular Automata (CA) and African Buffalo Optimization (ABO) algorithm in order to optimize the path selection and to decrease the energy consumption. The algorithm is integrated with AODV protocol and tries to enhance its QoS. AODV protocol sends the data packets after receiving the first route reply. However, AODV does not take into account the residual energy of nodes, which increases the link failure if one node dies. The major goal of CAABO is to establish route from the source to the destination that satisfies the QoS requirements of end-to-end delay and energy consumption that AODV neglects. However, the CAABO increases the size of the RR, such as CEHR, in order to introduce the QoS parameters which impacts the throughput.