# Energy-Optimized Content Refreshing of Age-of-Information-Aware Edge Caches in IoT Systems
## 6 Conclusions  
In this work, we considered an IoT network composed of devices that sample the environment periodically and of applications that need to be aware of the state of these devices as timely as possible to, for example, support decision making or detect anomalies. However, the timeliness of the state updates is limited by the constraints of the IoT devices and networks, especially by the device energy constraints. Indeed, energy is a scarce  
Figure 14: Service delay for \(\lambda=1/180\) s\({}^{-1}\). resource, as typically devices do not have a fixed power supply, but they rely on batteries or harvest energy. The energy consumption of the device mainly depends on the sensing energy consumption and on the transmission energy consumption; so, the objective of IoT-system management is to minimize them while guaranteeing information freshness. Indeed, minimizing the energy consumption of devices can reduce the operating costs of the network, as it prolongs a device's lifetime. A possible method is using a caching system because it can help in reducing sensing frequency and transmission frequency. Typically, IoT networks are accessed through gateways/proxies that act as intermediaries between devices and applications. Usually, these gateways/proxies are also used to provide a better system performance, e.g., they implement a cache to lower the energy consumption on the device. Hence, several cache refreshing schemes have been proposed in the literature that minimizes freshness and energy consumption or balance freshness and service latency. We instead minimize the energy consumption on the device and consider the freshness of the data, measured by AoI, as a constraint in terms of percentile of the distribution, because typically applications establish a threshold on the value of the AoI. So, we considered a cache-enabled proxy deployed at the edge in between devices and applications: it receives the requests for status updates of a device from an application and responds using its cached item or, if the cached item is expired, it fetches the last update from the device, refreshes the cache, and delivers it to the application. The freshness of a cached item is quantified using the AoI metrics, and a cached item is no longer considered fresh when its AoI exceeds the value of the cache parameter denoted as refresh window, W. In a preliminary version of this work [10], we proposed a model for this cache management scheme. In this work, we leverage that model to define and solve an optimization problem that configures the cache parameter W to minimize the energy consumption on the device, which depends on the average poll frequency and on the sampling frequency, while satisfying an AoI constraint expressed by the application. We apply our proposed cache-enabled proxy in two different emulated IoT scenarios that use the LWM2M protocol for device management: in the first one, requests are generated according to a Poisson distribution, while in the second one requests are periodic. Results show that our proposed solution minimizes energy consumption while satisfying the AoI requirements. Moreover, this per-device cache uses a simple yet effective management scheme that does not pose any limitation on the number of applications issuing requests on the device and that has constant complexity, i.e., it only involves a comparison between the AoI of the cached item and its refresh window. So, our solution can be easily applied in deployments involving multiple IoT devices just scaling vertically, i.e., adding more resources to the proxy, or scaling horizontally, i.e., replicating the proxy. In future work, we aim to consider also different cache refreshing policies, e.g., the cache could be updated using observing streams from the device. Conceptualization: M.P., A.V. and E.M.; software: M.P. ; writing--original draft: M.P. and A.V. ; writing--review and editing: M.P., A.V. and E.M. All authors have read and agreed to the published version of the manuscript.