# QoS Enabled Layered Based Clustering for Reactive Flooding in the Internet of Things
## 1 Introduction  
The Internet of Things (IoT) has become quite famous in the recent years. Many of our daily routine devices are getting connected with us, covering many capabilities like sensing, autonomy, and contextual awareness [1]. The IoT results from Internet progress and the innovative evolution of smart devices has led to the development of the new computing prototype. IoT is the nextrevolutionary technology in converting the present communication infrastructure into a completely future network [2]. IoT is expected to contain very large numbers of sensors collecting and passing on data on environmental conditions, physiological measurements, machine operational data, etc. IoT provides an integration of various sensors and objects that can communicate directly with one another without human intervention [3,4]. The primary purpose of the IoT is to allow a secure data exchange between the real world devices and applications [5]. IoT is, therefore, based upon the integration of several communication solutions, identification and tracking technologies, sensor and actuator networks, and distributed smart objects [6]. These objects/devices are connected to each other and share the same network for communicating with each other. These devices are connected with the sensor to detect the particular surrounding conditions and analyze the situation and work accordingly. IoT devices are also programmed to make decisions automatically or inform [7], according to the user, so that the user can make the best decision. This interconnected network can bring a great deal of advancement in the technology of applications and services which can bring economic benefit to global business development. Many devices are connected to the Internet to share the local information in cyberspace. Moreover, IoT promises a smart environment that would offer immense savings of time, energy, good quality of service (QoS), and less delay and resources [8]. Dynamic resource scheduling for heterogeneous workloads in IoT is critical for ensuring QoS, level of energy consumptions on each mode, and the traffic delay during data transmission [9]. Energy consumptions, QoS, and delay are the major challenging requirements for IoT networks since data transmission in the IoT network is based on priority [10]. Additionally, it is a known fact that IoT has the potential for a wide range of applications relating to agriculture, transportation, health, education, supply chain, farming, plant disease diagnosis, poultry, irrigation, and pest control [11] and each application requires a large number of sensors to connect and communicate with each other, which may reduce the QoS of the network due to inefficient resource utilization, traffic delay due to redundant messages/queries because each device has direct access to cloud resources, and energy consumption [12,13], as illustrated in Figure 1.  
Figure 1: Layer-based system model with different motes communicating redundantly in IoT. Figure 1 shows the system model with different sensor motes communicating with each other between the physical (sensor) and network layers of IoT. From the figure it can be seen that redundant messages, unwanted queries and network flooding are the major causes of inefficient utilization of resources, thus making IoT devices consume more energy and high computational time (i.e., delay in data transmission), which, in turn, affects the network QoS [14]. Moreover, solving these issues in IoT networks is demanding due to the constraint nature of the devices with limited energy. Presently, to the best of our knowledge, no mechanisms for identification of redundant queries have been developed in this domain. Following are the contributions of this paper: We examine several approaches for tackling unwanted and redundant communication in the IoT network to enable us to understand the sequence of actions that take place when the flooding are happening and propose the cluster-based flooding (CBF) technique.