# A Family of ACO Routing Protocols for Mobile Ad Hoc Networks
## 2 Related Work
The most representative reactive ACO routing protocols are the following:  
The ant-colony-based routing algorithm for mobile ad hoc networks (ARA) [6] is a reactive protocol in which the entries of routing table contain pheromone values that facilitate the choice of the neighbor. The authors affirm that, in the considered scenarios, the performance of this protocol is very similar to the DSR, presenting less overhead. However, it includes neither the scenarios representing a high network load, nor multimedia data. DSR [7] is similar to Ad Hoc On-Demand Distance Vector (AODV) in that it forms a route on-demand when a transmitting node requests one. However, it uses source routing instead of relying on the routing table at each intermediate device. The ant-based distributed routing algorithm for ad-hoc networks (ADRA) [8] is a reactive algorithm in which the ants move through the network between pairs of nodes chosen randomly. The authors assert that ADRA presents less average end-to-end delay, a lower overhead and a better delivered packet ratio than DSR. Furthermore, it allows them to optimize various QoS parameters, such as link quality, node load, and so on. The improved ant colony optimization routing algorithm for mobile ad hoc networks (PACONET) [9] is a reactive routing protocol where the forward ants explore the paths in the network in search of paths from a source to a destination in restrictive broadcast mode, and the backward ants establish the acquired path by the forward ants. The most representative hybrid ACO routing protocols are the following:  
Mobile agent-based routing protocol for mobile ad hoc networks [10], better known as Ant-AODV, is a hybrid routing form based on ACO and the AODV routing protocol. AntHocNet [11] is an adaptive, multipath and hybrid ACO routing algorithm. Data from 2004 and for almost ten years have had many extensions and variations to improve their performance. As mentioned above, AntHocNet is an algorithm hybrid (reactive and proactive), multipath and adaptive. AntHocNet follows a structure similar to AntNet Flying Ants (AntNet-FA), but it differs in its characteristics. The adaptive property, which occurs in AntHocNet, is suited to traffic and network conditions. In the behavior of AntHocNet, the following phases are distinguished:  
1. Routing information setup: It starts with sending, on-demand, agents for the calculation of the path to the destination. This phase is supported by the property of multipath, which is considered of great importance, since they have to create the routes as soon as possible, so that the least number of data packets is lost. 2. Data routing: In this phase, data are sent in a unicast and stochastic manner using the pheromones of the routing tables, which have all of the nodes locally. This routing strategy aims to expand the data load, getting a better load balancing. 3. Path maintenance and the exploration of another new one: In this phase, while a data session is ready to relay the information, maintenance proactive ants are sent according to the data sending rate. The purpose of this phase is to upgrade the quality of the route links and the values of the pheromone between the path that goes from the origin to the destination. 4. Management of link failures: In this phase, the nodes can detect link failures. Once they are detected, AntHocNet tries to mitigate using different mechanisms like sending messages of failure notification and the route local repair. The simulations analyze different scenarios in terms of the number of nodes, mobility and the density of nodes. In general, in all of them, AntHocNet has similar behavior to or even better than AODV. In particular, a better delivered packet ratio than AODV is obtained; the end-to-end delay is slightly higher in AntHocNet than in AODV for most simple scenarios (high density and short paths), improving in AntHocNet for more complex scenarios. [PERSON]'s thesis [12] is an evolution of AntHocNet, regarding [PERSON]'s thesis [11] and other works, such as [13].