# Unmanned Aerial Vehicles Enabled IoT Platform for Disaster Management
## 4 Case Study: NDN Architecture for Ground IoT Network  
The information regarding disaster situation can be collected using the ground IoT network. Compared to conventional fire detection and alarm systems on the ground, sensors network for IoT can be more effective, efficient and reliable for disaster management scenarios. The NDN architecture is a potential candidate to achieve these goals. Here, our main objective is to handle the ground IoT network for wildfire scenario using NDN architecture. NDN is evolving as the most likely or prominent information-centric future Internet architecture [18; 21; 57]. NDN is a content retrieval architecture rather than a host-centric network in both wired and wireless domains. Moreover, its unique and innovative functionalities such as caching ability inside the node, name-based communication and routing schemes favor the basic requirements of IoT architecture. An IoT-based communication mechanism is quite different from today's Internet due to the existence of resource-dependent devices, immense volume of small data exchange and diversity in traffic types [18; 58]. Furthermore, it also has loopholes in the traditional end-to-end communication mechanism. In other words, it emphasizes on \"what\" are the required data instead of \"where\" are the required data [18; 19]. NDN describes a robust, flexible and straightforward output-driven communication mechanism based on the interchange of two unique packet types, namely \"Interest\" and \"Data\" packets, which carry categorical, application-explicit data content names. NDN ensures content integrity and validity by sponging the data publisher's signature and other relevant verification information constraints in each data packet. Moreover, based on local requirements, a complete or partial subset of the overall network nodes can cache contents to increase the data retrieval rate while decreasing the overall network overhead [34; 59]. Each NDN node keeps and preserves three data structures [18; 20; 58; 59]:  
* **Content store (CS):** CS maintains short-term caching of incoming data packets.
* **Forwarding information base (FIB):** FIB maintains the path between interests and actual data.
* **Pending interest table (PIT):** PIT keeps track of the unsolicited interest(s) that are not yet satisfied with a corresponding response data packet.  
Moreover, each NDN consumer node publishes an interest to find appropriate data through producer node in the network [34; 58]. In the first step, it explores for a longest name prefix match in its CS. The node reply-back \"Data\" packet to the corresponding arriving interface of processed interest only if an exact match is found. Otherwise, \"Interest\" packet is rejected or discarded if there is a matching PIT entry found in the data structure. This phenomenon is executed when an equivalent interest request has already dispatched. In contrast, if it is not the situation, a new PIT entry is established in its PIT, and finally, the \"Interest\" is further accelerated to the path stored in the FIB structure. In addition to this, \"Data\" packets track the series of PIT entries back to the consumers.  
Hence, if a match does not exist in the PIT structure, then the \"Data\" packet is categorized as unsolicited and is dropped [59; 60].  
Wildfire situations produce multiple network fragmentations. Therefore, to retrieve the data from such a fragmented network, NDN mechanism is very effective due to its data-caching facility inside each node structure. Moreover, it also ensures minimal delay between consumer and producer NDN nodes, especially in a disaster situation. To validate this point, it does not need to republish the interest message in the case of network fragmentation. It can retrieve data from the nodes data structure hierarchy included in the network path [21; 37].