# A Middleware Solution for Wireless IoT Applications in Sparse Smart Cities
## 2 Related Work  
Smart City environments and IoT applications have received a considerable attention from scientific literature in recent years. Just to provide some notable examples, consider that Smart Cities can provide a new generation of real-time and time-critical, location-, social-, and context-aware services to their digital citizens, such as for emergency and health-care [4], surveillance [5], entertainment, and social good [6; 7]. Recent research activity has been focused on many different IoT-related topics such as event forecasting [8], WSN routing protocols [9], multi-sensor information fusion [10], business model and profit maximization [11], ontologies [12], service models [13], quality of experience [14], and even advanced concepts for the prioritization of raw data processing and information dissemination such as Quality of Information (QoI) [15] and Value-of-Information [16]. Researchers have also developed a multitude of application-specific solutions for issues in diagnostics [17; 18], environmental monitoring [19; 20], and social interest [21]. However, designing and developing Wireless IoT Applications for sparse Smart City environments still represents a significant challenge which calls for the development of new models and paradigms at both the architectural and the communication paradigm level. From an architectural point of view, Fog Computing represents one of the most interesting and relevant research areas supporting the development and management of Wireless IoT Applications in Smart City environments. For instance, Stack4 Things is a Fog Computing platform for IoT applications proposing a Cyber-Physical System with Functions Virtualization (CPSFV) to manage sensors and actuators, group them together, make easier their mutual interaction, and enable the specialization of their behavior [22]. The last task is performed via contextualization, defined as the Cloud-controlled injection of code, in the form of plugins, into any sensor/actuator managed by the Stack4 Things platform. [PERSON] and [PERSON] [23] proposed the Edge Operating System (EOS), a software architecture that leverages concepts and tools from Software Defined Networking (SDN) and Network Functions Virtualization (NFV) to exploit the processing power of network infrastructure elements. Information Centric Networking (ICN) is another promising research field presenting solutions to support application communication in wireless and heterogeneous networking environments, also allowing easier deployment and management of Wireless IoT Applications in sparse Smart Cities. For instance, [PERSON] et al. presented an ICN architecture for IEEE 802.11 MANETs called CHANET [24]. CHANET relies on naming to identify the content and it makes use of broadcast for the transmission of both interest packets and data. Other interesting techniques implemented in CHANET to increase effectiveness in the wireless environment are the overhearing of nearby nodes' transmissions and the local decision-making processes regarding packet forwarding. [PERSON] [25] described an opportunistic, content-centric architecture that takes advantage of the increasing number of pervasive systems available today to share content. The proposed Information and Context Oriented Networking (ICON) framework encompasses techniques that come from both the research fields of data-centric networking and opportunistic networking. ICON exploits caching strategies developed in ICN to share and place contents across devices in the network, and it relies on opportunistic strategies based on social- and location-based information, and the knowledge about application data usage, to route and forward the content to nodes interested in it. Finally, [PERSON] et al. [26] proposed mobile social networks that are specifically designed for Smart Cities with the goal of pushing citizens to actively participate in generating and sharing information related to quality of life.