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Mobile ad hoc network (MANET) is a collection of wireless mobile nodes that dynamically forms a temporary network without using any centralized administration. The challenge in MANET is to find a path between communicating nodes. This type of network is characterized by the absence of centralized infrastructure, dynamic topology, constraint of energy, heterogeneity of nodes, multi-hop, and limited bandwidth.
Routing in MANET means finding a path between the source and destination where packets can be forwarded. This Process is extremely challenging because of the dynamic features, limited bandwidth, frequent topology changes caused by node mobility and power energy consumption of MANET. Routing protocol should not only find the shortest path between the source and destination, but should also be adaptive. Routing protocols can be classified into three main categories, namely, proactive, reactive, and hybrid protocols. The third category combines the two cited protocols mechanisms, hence its name:
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Proactive Routing Protocols: Control packets are constantly broadcasted in the network to maintain the state of the link between each pair of nodes. A table is constructed at each node, where each entry indicates the next hop to a certain destination. This method provides readily available information during data transfer. However, one disadvantage of this algorithm is the need to track all topology changes. This requirement is difficult to fulfil when several nodes are present or when nodes are mobile (Dash & Balabantary, 2014). The most important routing protocols in this class are Destination Sequence Distance Vector (DSDV (Perkins, 1994)) and Optimized Link State Routing (OLSR (Jacquet & Muhlethaler, 2001)).
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Reactive Routing Protocols: (or on demand), paths are created and maintained as needed. When a node requires routing, a global discovery procedure of paths is launched to obtain a valid path to the destination. This approach is efficient, but it can lead increased delays because routing information is not immediately available when needed. The most important routing protocols in this class are: Ad hoc on demand Distance Vector (AODV (Perkins & Bhagwat, 1999)) and Dynamic Source Routing (DSR (Johnson & Maltz, 1996)).
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Hybrid protocols: Hybrid protocols are a combination of the two cited approaches. These protocols use a proactive approach to examine the close neighborhood (on two or three hops), and they have the paths in the immediate neighborhood. The hybrid protocol uses the techniques of reactive protocols beyond the predefined area to identify routes between non-neighboring nodes (more than two or three hops). The most important routing protocol in this class is Zone Routing Protocol (ZRP (Hass & Pearlman, 2002)).
Several optimization problems still do not have a general algorithm for their solution in polynomial time. This condition limits the use of exact methods in solving problems of small sizes. In recent years, most of the meta-heuristics presented in the literature to solve optimization problems are biologically inspired. These meta-heuristics include genetic algorithms (GA), simulated annealing, neural networks, particle swarm optimization and ant colony optimization (ACO).
The algorithms that are inspired by the principles of natural biological evolution and distributed collective behavior of social colonies have shown excellence in dealing with complex optimization problems and are becoming increasingly popular. However, owing to the limited transmission range of such networks, the decentralized operation relies on the cooperative participation of all nodes. The main aim of this study is to propose a new approach based on the bee colony for the resolution of the routing problem in mobile ad hoc networks (MANETs).
The reminder of this paper is organized as follows: Section 2 describes the swarm intelligence (SI)-based routing in MANET. Section 3 provides the background of bee-based routing in MANET. The proposed approach is described in Section 4. Section 5 discusses the simulation results. Finally, the conclusion and future works are presented in Section 6.