# A Pervasive Collaborative Architectural Model at the Network's Periphery
###### Abstract  
Pervasive collaborative computing within the Internet of Things (IoT) has progressed rapidly over the last decade. Nevertheless, emerging architectural models and their applications still suffer from limited capacity in areas like power, efficient computing, memory, connectivity, latency and bandwidth. Technological development is still in progress in the fields of hardware, software and wireless communications. Their communication is usually done via the Internet and wireless via base stations. However, these models are sometimes subject to connectivity failures and limited coverage. The models that incorporate devices with peer-to-peer (P2P) communication technologies are of great importance, especially in harsh environments. Nevertheless, their power-limited devices are randomly distributed on the periphery where their availability can be limited and arbitrary. Despite these limitations, their capabilities and efficiency are constantly increasing. Accelerating development in these areas can be achieved by improving architectures and technologies of pervasive collaborative computing, which refers to the collaboration of mobile and embedded computing devices. To enhance mobile collaborative computing, especially in the models acting at the network's periphery, we are interested in modernizing and strengthening connectivity using wireless technologies and P2P communication. Therefore, the main goal of this paper is to enhance and maintain connectivity and improve the performance of these pervasive systems while performing the required and expected services in a challenging environment. This is especially important in catastrophic situations and harsh environments, where connectivity is used to facilitate and enhance rescue operations. Thus, we have established a resilient mobile collaborative architectural model comprising a peripheral autonomous network of pervasive devices that considers the constraints of these resources. By maintaining the connectivity of its devices, this model can operate independently of wireless base stations by taking advantage of emerging P2P connection technologies such as Wi-Fi Direct and those enabled by LoPy4 from Pycom such as LoRa, BLE, Sigfox, Wi-Fi, Radio Wi-Fi and Bluetooth. Likewise, we have designed four algorithms to construct a group of devices, calculate their scores, select a group manager, and exchange inter-group and intra-group messages. The experimental study we conducted shows that this model continues to perform efficiently, even in circumstances like the breakdown of wireless connectivity due to an extreme event or congestion from connecting a huge number of devices. p 20  
machines, security systems and cars are connected to each other. This is what [PERSON] [1] first called the IoT in 1999. IoT supports a wide variety of networks interconnected through a variety of devices, including servers, databases, computers, laptop and wearable devices like smartphones and personal digital assistants. The improvement of the Internet has accelerated the development of practical solutions to the various problems of distributed systems, such as heterogeneity, openness, connectivity, security, scalability, failures, transparency and quality of service [2]. Advances in technology like device miniaturization and both P2P and wireless communication have enabled the integration of pervasive devices into distributed systems. These enhance and expand collaborative mobile computing by using small low-cost devices (wearable/portable) present in the physical environments of users, including homes, offices, and even natural environments. This model of computing allows the interaction of remote and mobile users to perform different activities using a variety of pervasive devices. This interaction has become an effective technique for dealing with complex problems by breaking them down into smaller sub-problems processed adequately on large networks.