# A Cloud Based Disaster Management System
## 4 Extending the RPL Protocol with Cyber-Physical Objective Function  
The idea of our proposed routing protocol is to extend RPL by adding the cyber-physical objective function (Cyber-OF) to improve network performance. The IETF ROLL working group has proposed the IPv6 routing protocol for lossy and low power systems (RPL) [46] as a standard routing protocol for low power and lossy networks (LLNs). Although RPL can be executed on top of any MAC layer, it is mainly designed for low-power IEEE 802.15.4 and its variants [51]. The authors in [52] proposed a protocol to cover the diverse requirements imposed by different applications running on static or dynamic constraints that are suitable for RPL. Primary link and node routing metrics are used to report the number of traversed nodes along the path. The path length is expected to be minimized and network overhead is reduced. In [53], the authors addressed a routing metric, called TXPFI to minimize the node energy cost and deliver energy-efficient routing in RPL. Clearly, the topological distance between source and destination nodes and the expected number of frame transmissions have an impact on the TXPFI metric. The protocol specifies some basic mechanisms for point-to-point traffic essentially transmitting such point-to-point traffic between two sensors via the controller [54], and builds a destination oriented directed acyclic graph (DODAG) using an objective function and a set of metrics/constraints. Nodes in the network operate autonomously and manage several objective functions. In the literature, several objectives functions and extensions were proposed for RPL to improve its performance to specific use cases [55; 56]. In RLP [57], routing metrics and objectives functions (OF) are responsible for the construction of directed acyclic graph (DAG). In the IETF [58] standard, the routing metrics are not imposed. Thus, the parent selection is implementation-specific, which makes it an open research issue worth investigating. Considering the RPL OFs mentioned, it appears that they do not take into account environmental cyber-physical properties. Relying on a single measure or more in a significant condition (disaster, fire, hurricane, etc.) may consequently be ineffective and not meet the demands of the smart cities' application profile. For instance, applying the hop-count metric in emergencies may not be the speediest method to broadcast the network. Furthermore, the use of a single static OF may not meet the requirements of similar systems with different levels of event importance. Therefore, we modeled the Cyber-OF to facilitate its adjustment to the complex tree configuration concurrently in relation to the cyber-physical characteristics of the surroundings depending on the event importance. In fact, for ordinary data packets, the aim is to increase network life span; hence, the OF improves energy expenditure. In the case of a serious event, the system adapts its topology to reduce end-to-end delays. Consequently, we assumed an adjective behavior by taking into account two routing OFs, each utilizing a specific metric of interest, namely:  
* **Energy metric:** this measure represents energy expenditure within an RPL node. With this metric, it is feasible to prolong the system life-span. It is necessary to think about this measure for systems that have energy-efficiency concerns. * **End-to-end delay:** this is the typical time it takes for a packet to move from node to sink. This measure should be reduced for systems requiring real-time assurances. In normal mode, the Cyber-OF uses the energy metric in the attempt to reduce energy consumption. This means that RPL will choose the routes that minimize energy consumption. For the case of a critical event (i.e., alarm due to a fire), Cyber-OF switches to the delay metric (latency-OF) so that the routing protocol emphasis more the route that will deliver faster the critical messages. We use the latency-OF mode in case of a detected fire for example, while energy-OF mode is used during normal situations.