Towards Self-Control of Service Rate for Battery Management in Energy Harvesting Devices

We consider the operation of an energy harvesting wireless device (sensor node) powered by a rechargeable battery, taking non-idealities into account. In particular, we consider sudden decrease and increase of the battery level (leakage and charge recovery consequently) due to the inner diffusion processes in the battery. These processes are affecting the stability of the device operation. In particular, leakage accelerates the depletion of the battery, which results in inactive periods of the device and, thus, potential data loss. In this paper, we propose a simplified self-control management of a battery expressed by restrictions, which could be used for an efficient operational strategy of the device. To achieve this, we rely on the double-queue model which includes the imperfections of the battery operation and bi-dimensional battery value. This includes both apparent, i.e., available at the electrodes and true energy levels of a battery. These levels can be significantly different because of deep discharge events and can equalize thanks to charge recovery effect. We performed some simulation and observed that we can diminish the models variable number to predict possible unwanted events such as apparent discharge events (when the areas near electrodes are depleted while other areas of the battery still contain some energy) and data losses. This observation helps to achieve sufficiently effective self-control management by knowing and managing just few parameters, and therefore offers valuable directions for the development of autonomic and self-sustainable operation

Sustainable Management of Energy-Harvesting Communication Systems

IoT systems have been massively infiltrating our everyday's life for various applications. One of the main constraints inhibiting the further development of these applications is the limited autonomy of present day batteries. Moreover, energy sustainability is a crucial requirement for systems employed in critical mission applications. A widely used approach to increase the autonomy of IoT systems is the use of renewable sources of energy such as solar, wind, heat, and others to power the devices. For instance, one of the most widespread solutions for wireless sensor nodes is the use of solar panels, which can provide reasonable power input. Their efficiency is determined by the panel's material that defines the conversion efficiency. Renewable sources of energy are too erratic to provide complete system reliability unless over-dimensioned. In reality, energy supply is often limited, which causes the need for adaption of the node operational strategy to ensure the functional reliability of the system. However, the unreliable nature of renewable energy causes several challenges, which we address in this work. In particular, this thesis investigates the effect of battery imperfections caused by inner diffusion processes in the battery on the energy harvesting wireless device operation and effective energy-balancing strategies for different scenarios and system types. We propose 1) the transmission strategy, that takes into account the battery properties (leakage, charge recovery, deep discharge, etc.), and reduces the data losses and discharge events; 2) adaptive sampling algorithms, that balances the erratic energy arrivals, validated on the industrial data-logger powered by a solar panel; and 3) energy cooperation in WSN and Smart City contexts. We also focus on critical-mission IoT systems, where the freshness of delivered packets to the monitoring node by the information sources (communication nodes) is the important parameter to be tracked. In this context, we set the objective of age of information minimization taking into account the battery constraints, asymmetry in reliability of information sources, and stability of energy arrivals, that is, the energy harvesting rate. This array of strategies covers a wide range of applications, scenarios, and requirements. For instance, they can be applied to a smart city represented as a large system of interconnected smart services, or a WSN employed for critical mission applications. We demonstrated that the knowledge of battery and environmental characteristics, and the asymmetric properties of a system is beneficial for designing transmission/sensing strategies.I sistemi IoT si sono massivamenti entrati nella vita quotidiana per varie applicazioni. Uno dei principali vincoli che inibiscono l'ulteriore sviluppo di queste applicazioni è l'autonomia limitata delle batterie attuali. Inoltre, la sostenibilità energetica è un requisito cruciale per i sistemi impiegati in applicazioni mission-critical. Un approccio ampiamente utilizzato per aumentare l'autonomia dei sistemi IoT è l'uso di fonti energetiche rinnovabili come solare, eolico, termico e altri per alimentare i dispositivi. Ad esempio, una delle soluzioni più diffuse per i nodi di sensori wireless è l'uso di pannelli solari, che possono fornire un ragionevole input di energia. La loro efficienza è determinata dal materiale del pannello che definisce l'efficienza di conversione. Le fonti energetiche rinnovabili sono troppo irregolari per garantire la completa affidabilità del sistema se non sovradimensionate. In realtà, l'approvvigionamento energetico è spesso limitato, il che causa la necessità di adattamento della strategia operativa del nodo per garantire l'affidabilità funzionale del sistema. Tuttavia, la natura inaffidabile delle energie rinnovabili provoca diverse sfide, che affrontiamo in questo lavoro. In particolare, questa tesi studia l'effetto delle imperfezioni della batteria causate dai processi di diffusione interna della batteria sul funzionamento del dispositivo wireless per la raccolta di energia e strategie efficaci di bilanciamento dell'energia per diversi scenari e tipi di sistema. Proponiamo 1) la strategia di trasmissione, che tiene conto delle proprietà della batteria (perdite, recupero della carica, scarica profonda, ecc.) E riduce le perdite di dati e gli eventi di scarica; 2) algoritmi di campionamento adattivo, che bilanciano gli arrivi irregolari di energia, validati sul data logger industriale alimentato da un pannello solare; e 3) cooperazione energetica in contesti WSN e Smart City. Ci concentriamo anche su sistemi IoT di missione critica, in cui la freschezza dei pacchetti consegnati al nodo di monitoraggio da parte delle fonti di informazione (nodi di comunicazione) è il parametro importante da tracciare. In questo contesto, fissiamo l'obiettivo dell'età della minimizzazione delle informazioni tenendo conto dei vincoli della batteria, dell'asimmetria nell'affidabilità delle fonti di informazione e della stabilità degli arrivi di energia, ovvero della velocità di raccolta dell'energia. Questa serie di strategie copre una vasta gamma di applicazioni, scenari e requisiti. Ad esempio, possono essere applicati a una città intelligente rappresentata come un grande sistema di servizi intelligenti interconnessi o come WSN impiegato per applicazioni mission-critical. Abbiamo dimostrato che la conoscenza della batteria e delle caratteristiche ambientali e le proprietà asimmetriche di un sistema sono utili per la progettazione di strategie di trasmissione / rilevamento

Sustainable Management of Energy-Harvesting Communication Systems

IoT systems have been massively infiltrating our everyday's life for various applications. One of the main constraints inhibiting the further development of these applications is the limited autonomy of present day batteries. Moreover, energy sustainability is a crucial requirement for systems employed in critical mission applications. A widely used approach to increase the autonomy of IoT systems is the use of renewable sources of energy such as solar, wind, heat, and others to power the devices. For instance, one of the most widespread solutions for wireless sensor nodes is the use of solar panels, which can provide reasonable power input. Their efficiency is determined by the panel's material that defines the conversion efficiency. Renewable sources of energy are too erratic to provide complete system reliability unless over-dimensioned. In reality, energy supply is often limited, which causes the need for adaption of the node operational strategy to ensure the functional reliability of the system. However, the unreliable nature of renewable energy causes several challenges, which we address in this work. In particular, this thesis investigates the effect of battery imperfections caused by inner diffusion processes in the battery on the energy harvesting wireless device operation and effective energy-balancing strategies for different scenarios and system types. We propose 1) the transmission strategy, that takes into account the battery properties (leakage, charge recovery, deep discharge, etc.), and reduces the data losses and discharge events; 2) adaptive sampling algorithms, that balances the erratic energy arrivals, validated on the industrial data-logger powered by a solar panel; and 3) energy cooperation in WSN and Smart City contexts. We also focus on critical-mission IoT systems, where the freshness of delivered packets to the monitoring node by the information sources (communication nodes) is the important parameter to be tracked. In this context, we set the objective of age of information minimization taking into account the battery constraints, asymmetry in reliability of information sources, and stability of energy arrivals, that is, the energy harvesting rate. This array of strategies covers a wide range of applications, scenarios, and requirements. For instance, they can be applied to a smart city represented as a large system of interconnected smart services, or a WSN employed for critical mission applications. We demonstrated that the knowledge of battery and environmental characteristics, and the asymmetric properties of a system is beneficial for designing transmission/sensing strategies

An optimization framework for energy topologies in smart cities

The definition of “energy topologies” based on energetic cooperation (exploitation and exchange) between interconnected objects is an important feature that can be implemented in Smart Cities. Based on the presence of energy harvesting devices, it is aimed at providing system-wide sustainability by allowing exchange of stored and supplied energy in a similar fashion to communication of data. In this paper, we investigate the possibility of integrating energy cooperation within the design of the energy topology, or, in other words, by establishing energy links between objects, in particular wireless smart nodes powered by harvesting renewable energy sources. To do so, we construct an optimization model, where it is guaranteed that wireless nodes during operation will not be depleted and the optimal energy transfer does not exceed the energy demands of other communication nodes. We analyze how the system conditions can affect the energy topology, in particular, energy harvesting capabilities, energy levels, and energy thresholds. We also identify some theoretical limits for the system to guarantee complete sustainability, that is, nodes do not go out of charge. Also we demonstrated the effectiveness of the model comparing it with the system operation without applied optimization

Asymmetry in energy-harvesting wireless sensor network operation modeled via Bayesian games

We consider the management of an energy harvesting wireless sensor network, inspired by game theory so as to obtain a distributed multi-agent operation. In particular, we focus on asymmetries in the nodes energetic capabilities, and how do they impact on the resulting performance. We frame the problem as a repeated Bayesian game with asymmetric players and incomplete information, where also the private information available at each node is asymmetric. We find out that instead of a proportionally fair resource utilization, such a situation ends up in an even more unbalanced situation, which leads to an inefficient management where certain nodes are utilized beyond their fair share. Future research directions are identified so as to recover information about asymmetries from the strategic gameplay of the sensors and thus enable a better management