# Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications
## 1 Introduction  
Mobile Wireless Sensor Networks (MWSN) had been popular for thousands of applications, including disaster recovery. It is evident that these networks are usually destroyed or inaccessible in disastrous situations (e.g., tornados, hurricanes, earthquakes and war) and emergency personnel do not get proper information for quick and proper incident responses. Hence, an alternative solution is greatly required in these types of emergency scenarios. Traditional solutions [1; 2; 3; 4] attempt to build up a Mobile Ad Hoc Network (MANET) by distributing antennas in the affected area. This may be a solution from a communication point of view but, in reality, the feasibility of these solutions for large-scale disasters tends to be zero. Other studies [5; 6; 7; 8] suggest wireless opportunistic networks, which are formed using sensors that are used in everyday use devices and objects (e.g., smartphone, tablet, PDA, vehicles, appliances, furniture) for monitoring heart rate, temperature, humidity, pressure, accelerometers. The idea of building an opportunistic recovery network for communication using those sensors may save many lives in disastrous situations. Thus, this type of solution provides improvements and efficiency for emergency rescue teams. Assuming the existence of a network with an end-to-end connection between the sender and receiver is far from the reality in a disaster scenario. Using the traditional data forwarding methods in such scenarios most likely results in a data delivery failure. Hence, a new type of data forwarding and routing protocol supporting delay tolerance and disruption is greatly required for such disastrous situations. Opportunistic forwarding is a protocol based on the mobility of nodes in a network wheresensors can communicate properly and efficiently manage their energy consumption and forward information to the first responders. In this protocol, nodes carry stored messages while moving around and forward them whenever an opportunity arises. This opportunity is simply making a contact with a node that knows how to route the message closer to the desired receiver. Hence, a route is built dynamically from the sender to the receiver. Any node can possibly be the next hop in an opportunistic forwarding. Figure 1 demonstrates such an opportunistic network for disaster recovery. On the other hand, a type of edge computing [9; 10] is emerging that integrates smart devices, e.g., sensors, with the opportunistic network, enabling local data processing along with processing data at the base station or central server. Though edge computing supports decentralized data processing, routing data is signification in such networks for disaster recovery. However, designing an efficient opportunistic routing protocol [8; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22] in terms of energy efficiency, reliability and successful message transmission is a major challenge because of the mobility of nodes (i.e., rescue team members), the low transmission ranges of devices (i.e., smartphones, sensors, Bluetooth). Hence, this paper introduces an opportunistic density cluster-based routing protocol (ODCR) for emergency/disastrous situations. This protocol supports the efficient management of the energy and an opportunistic communication aspect to tolerate delays and disruption and builds routes in a dynamic and infrastructure-less manner. The number of sensors and quantity of generated data extremely influences the performance of any routing protocol. Hence, we consider edge computing in sensors that reduce the amount of data transmitted. Moreover, we use a density-based clustering model in this routing protocol [7; 9; 10; 11; 12] so that the number of nodes performing data collection and transmission reduces to achieve energy efficiency. The proposed ODCR protocol uses opportunistic data forwarding and integrates both (i) density-based clustering and (ii) isolated nodes. In density-based clustering, each node is likely to reside in a cluster and exchanges information among the nodes in that cluster.