## 4 Lifetime Improvement Mechanisms in Routing
### Bio-Inspired Mechanisms  
In recent years, new communications and calculation models have been originated from insect sensory systems that have directed to considerable progress like bio-inspired routing. In Ant Colony Optimization (ACO) a colony of artificial ants is one of the most biological ways to create solutions guided by information obtained from trial and error and the pheromone paths. In spite of not having much intelligence or strength, ants can successfully make colonies that consist of a very highly-organized society [22]. Some protocols based on ACO mechanism are as follows:  
_Artificial Fish Swarm Optimization (AFSO)_ as a biological algorithm copying animal cooperation is the main motivation for [20] in order to suggest a new hierarchical routing protocol for WSNs. Based on the behavior of fish, this mechanism is used to solve the NP-hard problem considered to find \(k\) optimal clusters among the network. A central control which is implemented by the sink is used for  
Figure 7: **(a)** Using maximum power level. **(b)** Power control mechanism in EECA (transmission range \(\leq\) R). this algorithm due to the scattering the cluster heads through the network. The sink operates this scheme at the artificial fish swarm optimization cluster head (AFSOCH) setup phase with the help of GPS. In this protocol, two other energy efficient strategies are used as follows: firstly, the sensor nodes which are not involved in data transmission phase can go to the sleep mode and conserve their energy. Secondly, by using another CH, a cluster head is able to forward data packets when it is far away from the sink node. On the other hand, a multi-hop pattern is followed by the algorithm to relay data towards the sink. Moreover, different Code Division Multiple Access (CDMA) codes can be used among the multiple clusters to have parallel communication. Experimental results [20] demonstrate that AFSO could decrease the total energy dissipation of the network more than 20% compared to the LEACH [46] protocol. Just like its predecessor LEACH, AFSO could decrease intra-cluster and inter-cluster interferences by using two kinds of MAC protocol, CDMA and Time-Division Multiple Access (TDMA). Employing these mechanisms results in more energy conservation and network lifetime extension. However the execution overhead caused by periodic CH selection imposes unwanted energy consumption throughout the sensor field. The _Energy-Efficient Ant Based Routing Algorithm (EEABR)_[47] is a new communication scheme for WSNs, which is based on the Ant Colony Optimization (ACO) metaheuristic. A colony of artificial ants that travels through the WSN is used in EEABR so that they can search for paths between the sensor nodes and a sink. To increase the lifetime of the WSN, these paths should be energy-efficient and short in length at the same time. The next hop for each ant will be selected with a probability that is a function of following factor: the amount of pheromone trail present on the connections between the nodes and the node energy. An ant travels back through the built path when it arrives at the destination node. At the same time, it updates the pheromone trail by an amount that is based on the number of nodes of the path and the energy quality. The EEABR protocol can build an energy optimized routing tree after some reiterations. Simulation results [47] indicate that EEABR improves the average (mean) residual energy compared to the basic ant-based routing algorithm (BABR). The difference between the average values varied between 17% and 25%. Nevertheless, one of the drawbacks of EEABR scheme is that in contrast with previous algorithm, it does not consider energy conservation mechanisms based on the node status management [48]. These mechanisms which are implemented in MAC and physical layers allow the sensor nodes switching between sleep and wakeup modes and hence save energy. Another energy-efficient algorithm based on Ant Colony Optimization is presented by authors of [49].