# Robust Evolutionary-Game-Based Routing for Wireless Multimedia Sensor Networks
## 2 Related Works
It is based on clustering and exploits Monte Carlo techniques to determine the target locations cooperatively. This protocol was intended for mobile target tracking using camera sensors by considering perspective projection and observation noises. In [26], a mathematical model for QoS-aware route determination method for WMSNs is reported. The mathematical model is used to find optimal path for providing appropriate shared radio that satisfies the QoS for a wide range of real-time intensive media. To manage hop-by-hop switching in the proposed routing scheme, a mathematical model based on the Lagrangian relaxation method is used. Objective functions with embedded criteria are used to decide the pathway from the source to the sink. A new routing mechanism for WMSNs based on software defined networking (SDN) technology is introduced in [27]. SDN can facilitate with the visibility of network resources and programmable interfaces. The routing protocol devised in [27] is basically a QoS-aware routing mechanism for WMSNs. The protocol could achieve high throughput for video/audio data. A new multiobjective approach to solve the routing problem in WMSNs is presented in [28]. Delay and expected transmission count were considered as QoS requirements. The authors of [28] could avoid conflicts among the QoS parameters that may lead to suboptimal solutions. A novel routing approach named GEEC is reported in [17]. GEEC belongs to the group of clustering routing protocols. The simultaneous achievement of energy exhausts the equilibrium, and lifetime extension was gained through the mechanism of evolutionary game theory. The work proposed in [18] is a clustering protocol for WSNs. This work can be separated into three phases. First, an algorithm for optimal cluster size was given along with a mathematical model targeting to solve the hotspot problem. Next, for the prevention of anarchism in selecting CH, the evolutionary game theory is used. Finally, a novel energy-efficient routing protocol based on evolutionary game theory is proposed. As discussed earlier, the amount of data is large in WMSNs, data redundancy can cause a significant level of energy wastage and reduced network lifetime. So far, there are two protocols that have worked upon routing to avoid data redundancy. QMOR [14] is one of them. The authors aim at selecting and prioritizing the forwarder list to gain an energy-efficient delivery of multimedia data under specific QoS requirements. First, the protocol introduces a redundancy avoidance mechanism to avoid multimedia traffic by taking advantage of multiple sink nodes. In that study, multi-sink aware operations were integrated into an opportunistic routing framework to reduce energy consumption. QMOR exhibits significant performance increase in terms of energy consumption, delay and reliability. In QMOR, opportunistic routing is exploited; thus, overhearing occurs in the network that can significantly decrease the network lifetime because of the huge chunks of data. A protocol proposed by [PERSON] and [PERSON] facilitates multimedia node clustering that satisfies FoV constraints. In this routing approach, the main criteria for creating clusters is the overlapping of FoVs of the two nearby sensor nodes. Given that the overlapped area of two multimedia sensor nodes is wide, the two sensors will act similarly from the coverage point of view, and they are selected as cluster members. It is not necessary for nodes in the same clusters to be neighbors. This clustering method conserves energy and prolongs network lifetime by creating the potential of cooperation among nodes belonging to the same cluster and avoiding redundant sensing and processing [20]. The proposed scheme does not compare the performance results with any other similar or standardized protocol. Furthermore, important routing metrics, such as packet delivery ratio or end-to-end delay, were not considered. We refer to this protocol as AB routing (Alae and [PERSON] routing) for simplicity in our study. LEACH is a distributed cluster formation algorithm.