# MCCM: An Approach for Connectivity and Coverage Maximization
## 1 Introduction  
Growth in technology and computing power is continuously progressing and transforming the way societies connect to each other and to the physical world. The tendency to bring smartness to living and environments to make them more adaptive, autonomous and personalized to human needs, prepares the ground to smart worlds [1]. The Internet of Things (IoT) is defined by the International Telecommunication Union (ITU) [2] and the European Research Cluster on the Internet of Things (IERC) [3] as a dynamic global network infrastructure with self-configuring capabilities based on standard and inter-operable communication protocols. Mostly a smart network of linked objects and machines, which communicate information via wireless technology and the cloud [4]. Wireless Sensor Network (WSN) plays an important role in conjunction with IoT. It consists of many distributed sensors for environmental monitoring tasks. It brings more control, precisions, early alerts, monitoring and tracking the environment. This is reflected in many projects such as Array of Things (AoT) [5], NEOM City [6, 7], Google's Loon [8], etc. Google's Loon project aims to create an aerial wirelessnetwork formed by nodes such as satellites, balloons, drones, or fixed-wing aircraft. These flying nodes provide network access and rescue missions over areas in disaster scenarios.  
Although IoT has great benefits, it has some major challenges such as: Connectivity and coverage, energy consumption, reliability and privacy. The initial deployment of devices in an area of interest might not always meet the mission needs (rescue or military). The basic requirement after deployment is to have sufficient coverage and connectivity [9]. In many cases, the mobility feature of devices is used to maximize the coverage [10]. Wireless sensor devices can sense, process, and in some applications move and organize themselves for coverage missions. These tasks drain devices' energy and become very challenging especially for power-constrained devices [11]. For this purpose, energy saving during coverage maximization should be considered, and it is necessary to cover all targets areas with a minimum number of devices.  
In this paper, we are interested in maintaining connectivity and coverage in wireless distributed networks composed of heterogeneous mobile devices. Our work consists of three parts (1) a distributed algorithm for Coverage Maximization and Maintaining Connectivity (MCCM) between group of neighboring devices, (2) gaps bridging between disjoint groups, and (3) comparison and validation of the proposed distributed algorithm. The algorithm ensures that each device is connected to at least two other devices in the network. This setup increases the network resistance against failure as well as reliability.  
The remaining part of the paper is organized as follows: In Section 2, we investigate related works on connectivity and coverage maximization. The motivation and contribution of the work are presented in Sections 3 and 4 respectively. The performance of the algorithm as well as a comparative study with related works are discussed in Section 5. Section 6 concludes the paper.