# Edge Computing: A Survey On the Hardware Requirements in the Internet of Things World
## 1 Introduction
Edge Computing paradigm is considered, from many, an environmentally friendlier alternative to the Cloud Computing one, due to its ability to restrain the volume of data to be moved, consequently cutting down the energy cost. Figure 1: Expected adoption growth of IoT devices. As described above, the decentralization of the workload is the focus of many works of research. The aim is to reduce the latency by offloading some of the tasks on surrounding servers [10; 11]. In fact, in urban environments, it is possible to rely on such infrastructure to enhance performances. However, in order to correctly manage the workload, there is often the need to split it homogeneously and to synchronize all the different duties. To achieve this goal, something more is required, such as an Operating System (OS). The use of a complete OS instead of a limited embedded firmware becomes a powerful tool when handling complex tasks. In order to manage multiple users and different scenarios, required for IoT, the main OS can run virtualized operating systems (which emulates the entire hardware resources required by an OS) or it can exploit the containerization paradigm, which lets the user have multiple instances of the OS running at the same time while sharing the kernel for resources allocation. The containerization of tasks makes the organization and the allocation of workloads more efficient, by exploiting the bandwidth of the system at its maximum, without exceeding constraints [12]. For sake of clarity, since this current survey is focusing on hardware aspects, OS and software related technologies are not discussed in the following sections; however, the reader can refer to the provided references for further details. This survey is intended to be an overview of the key aspects of IoT hardware platforms, designed for Edge Computing. Several state-of-the-art techniques, suitable for low power applications, are introduced and discussed through real examples. Section 2 presents the motivations that drive the continuous development of new architectures and techniques, with a special focus on the Edge Computing approach, by describing and emphasizing its importance. Section 3 depicts the landscape of a typical IoT node system, comprehensive of all its main features, ranging from the \"brain\" (Central Processing Unit) to its peripherals. First, Input/Output (IO) systems are presented as the main communication channels of the system (Section 3.1); a detailed analysis of several IO types is listed, providing pros and cons for every possible choice. Then, memories are introduced as fundamental elements for data retention. Even in this case, several solutions are presented, with a special focus on non-volatile memories (Section 3.3) (memory elements in which data are retained even in case of power failure or interruption). Power management (Section 3.4) is responsible for deciding which parts of the system should be turned off, when they are detected as not useful for the current task, or even for adjusting the local power supply parameters, such as the voltage level. After this unit, near-threshold behavior is described (Section 3.5) in order to better understand what are the consequences of power supply parameters tuning. Since Edge Computing heavily relies on data processing, an entire section is dedicated to this topic (Section 3.6). State-of-the-art algorithms and techniques able to reduce significantly the amount of data to be transmitted are discussed. Section 3.8 is completely devoted to the Central Processing Unit (CPU), explaining the evolution of single-core architectures and the reason for adopting the multi-core paradigm. Indeed, most modern IoT nodes are equipped with powerful processors, able to effectively distribute the computational load among the cores and, consequently, level out the power dissipation. Finally, a real platform, which sums up all the above-listed features, is presented in Section 4, while Section 5 concludes the paper by providing new challenges and future perspectives.