2327-4662 (c) 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2017.2776171, IEEE Internet of Things Journal 1 Abstract— To fulfill the needs of internet of mission critical things (IoMCT) wireless networking system, it is necessary that a large number of unmanned aerial vehicles (UAVs) and a large number of unmanned ground vehicles (UGVs) will be a dependable, autonomic, secure, and rapidly deployable network. In our system model, each UGVs and UAVs has only one mobile node, where any of the mobile nodes can communicate with each other directly without any central controller. Each mobile node is connected with a large number of ‘things’. A mobile node may transmit a large number of messages from its large number of things to a large number of mobile nodes at the same time. Similarly, one mobile node can receive a large number of packets from a large number of mobile nodes. Intuitively, each mobile node should have a large number of transmitters and a large number of receivers, to maintain a very high throughput (inverse of rejection probability) per mobile node. Obviously, a large number of transmitters and a large number of receivers increase the complexity and the cost of each mobile node. Results show that it is not essential that each mobile node should have a higher number of transmitters and receiver to obtain a very higher throughput per node. There are few other options to maintain a very high throughput per node, including the transmitting probability of each mobile node and receiving probability of each mobile node. That may reduce the complexity and cost of each mobile node significantly. Index Terms—Ad Hoc, aerial, ground, sensor, Internet of Things, mission critical, unmanned, wireless. I. INTRODUCTION he human driven vehicles are may be needed to immediately have access to the view of the field in some dangerous, dull, dirty, or mission critical applications. The unmanned vehicles (UVs) are the proper substitutions to avoid human losses. Unpiloted autonomous unmanned vehicles Jahangir H. Sarker, was with the University of Ottawa, Ottawa, ON K1N 6N5, Canada. He is now with the Electronics and Communications Engineering Department, College of Engineering and Computer Science at Al-Lith, Umm Al-Qura University, Al-Lith 21961, Kingdom of Saudi Arabia (e-mails: mhossai3@uottawa.ca; mjsarker@uqu.edu.sa). Ahmed M. Nahhas was with the College of Engineering at Al-Lith. He is now with the College of Engineering and Islamic Architecture, Umm Al-Qura University, Makkah 21955, Kingdom of Saudi Arabia (e-mail: amnahhas@uqu.edu.sa). Copyright (c) 2012 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org. (UVs) systems are ideally suited to persistent surveillance or search type missions in the frames of civil security and conflict situations or close combat, an operator or a group of stakeholders. Nowadays, different types of UVs, including unmanned aerial vehicles (UAVs) as well as unmanned ground vehicles (UGVs), are used for surveillance, crowd control, border patrol, firefighting, agriculture, navigation, and search and rescue purposes [1], [2], [3]. The coordination between unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) is a proactive research topic whose great value of application has attracted vast attention [4]. An efficient mission-critical wireless communication system equipped with sensors is essential for the effective supervise of emergency and natural disaster management [5]. The development of smart sensors in recent years has demands the advancements of wireless sensor networks. Wireless sensor networks (WSN) consist of micro-sensors capable of monitoring physical and environmental factors such as temperature, humidity, vibrations, motions, seismic events, etc. [6]. The emergence of the Internet of Things (IoT) paradigm has augmented the scope of WSNs demand, further cultivating the ongoing research in this field. The IoT is a network of smart objects interconnected through a communication medium. WSNs are expected to play a significant role in IoT, since the sensor nodes are the main building blocks of this concept [7], [8], [9]. The internet has resulted from revolutionary advances in electronics, telecommunications and information technologies, devices, and applications. The initial purpose of internet was to connect the people. However, by 2008, it connected more things than people [10]. The sheer number of these interconnected devices plays a key role in the IoT revolution. For example, Gartner research predicts that IoT will connect up to 50 to 100 billion devices by 2020. It is estimated that IoT will generate approximately 1.7 trillion US dollars by this time, with an approximate growth rate of 20% over year [11]. The internet of things (IoT) is consists of a very large number of simple actuators, sensors, and RFID tags, as well as more complex devices such as computers, self-driving vehicles, and autonomous robots. Among IoT systems, an important category is mission-critical IoT (MC-IoT) systems, which run applications and whose failure might have severe consequences. Mission-critical computing is becoming Optimizing the Number of Transmitters and Receivers per Node for an IoMCT Unmanned Wireless Networking System Jahangir H. Sarker, Senior Member, IEEE and Ahmed M. Nahhas, Senior Member, IEEE T