## 1 Introduction  
The world has witnessed several technological advances, especially in the areas of pervasive computing, ubiquitous computing, security, and open-source hardware (OSH) development [1; 2; 3]. Since its inception, IoT has experienced tremendous growth in all application areas such as agriculture, industry, automation, smart city, and healthcare [1; 4; 5; 6]. Every time an IoT device collects sensor data from a physical entity, it requires a gateway or Internet connection to transmit this data to the remote applications and users. This results in huge network traffic and a degradation of the network's backhaul dependency. Apart from this, the extensive use of IoT sensor data for transmission over long distances incurs costs and is associated with significant power consumption [7; 8; 9]. In the absence of a suitable network technology, IoT sensor data might be limited to the near periphery from which it originates. As a result, the quality of service is minimized, and the reliability is neglected. As a result, the entire IoT ecosystem evolves into an unstable concept where IoT sensor data is not always available to remote applications. Existing Internet backhaul and cloud computing-centric approaches are mainly responsible for such obstacles. Standalone hotspots are regularly used in our daily life [10; 11]. Normally, a cell phone with subscriber network connectivity and available data packets can be seamlessly used as a mobile hotspot for other interested devices that are nearby to access the Internet. It becomes problematic when the hotspot that an interested user's device is trying to connect to has no network coverage or is out of subscription, limiting the ability to break the coverage of the hotspot for the interested device [12; 13]. This calls into question the usability, quality of service, and reliability of such hotspots. Dew computing is a recent development in computing that aims to leverage in-network dependencies and collaborative approaches for remote cloud servers [14; 15; 16]. Dew servers are such devices that follow the dew computing idea and perform needed activities such as data access to local machines that are independent of network availability [17]. Dew computing is based on the principles of the synchronization function, which allows such dew devices to operate locally and require very little Internet connection to synchronize with their cloud replica [18; 19; 20]. In dew computing, each user has a cloud replica with a local clone of the same content. At the time of writing, dew computing is still in its early stages and thus focuses mainly on services that are related to network data access for its end devices [21]. However, the long-term goal of dew computing is to provide higher reliability, better availability, and user-centric data access, as well as a provider that is primarily independent of Internet connectivity. Distributed hotspot networks are an idea that has been discussed for a long time and has received increasing attention in both the industry and in academia in recent years. However, to date, no such fully self-organizing distributed hotspot network exists, either in research or in practice [22]. The idea of using Wi-Fi as an enabler for hotspot deployment is currently under investigation [23]. However, Wi-Fi struggles with limited range, signal interference, bandwidth usage, and security [24]. Using Wi-Fi on a large number of IoT devices may pose various challenges in terms of power consumption, which may shorten the battery life of IoT devices [25]. On the other hand, LoraWAN can be considered as an alternative to Wi-Fi to provide wide-area connectivity with improved security and battery life for IoT devices [25; 26]. However, it faces problems such as having a low data rate, a small packet size, and an unsuitability for real-time applications.