Through recent technology advances in the field of wireless energy transmission, Wireless Rechargeable Sensor Networks (WRSN) have emerged. In this new paradigm for WSNs a mobile entity called Mobile Charger (MC) traverses the network and replenishes the dissipated energy of sensors. In this work we first provide a formal definition of the charging dispatch decision problem and prove its computational hardness. We then investigate how to optimize the tradeoffs of several critical aspects of the charging process such as a) the trajectory of the charger, b) the different charging policies and c) the impact of the ratio of the energy the MC may deliver to the sensors over the total available energy in the network. In the light of these optimizations, we then study the impact of the charging process to the network lifetime for three characteristic underlying routing protocols; a greedy protocol, a clustering protocol and an energy balancing protocol. Finally, we propose a Mobile Charging Protocol that locally adapts the circular trajectory of the MC to the energy dissipation rate of each sub-region of the network. We compare this protocol against several MC trajectories for all three routing families by a detailed experimental evaluation. The derived findings demonstrate significant performance gains, both with respect to the no charger case as well as the different charging alternatives; in particular, the performance improvements include the network lifetime, as well as connectivity, coverage and energy balance properties.

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Circular Economy is a novel economic model, where every 'asset' is not wasted but reused and upscaled. The Internet of Things-IoT paradigm can underpin the transition to a Circular Economy by enabling fine-grained and continuous asset tracking. However, there are issues related to security and privacy of IoT devices that generate and handle sensitive and personal data. The use of Blockchain technology provides an answer to this issue, however, its application raises issues related to the highly-constrained nature of these networks. In this paper, Edge Computing is presented as a solution to this issue, providing a way in which Blockchain and Edge Computing can be used together to address the constrained nature of IoT. Furthermore, we present the challenges that this combination poses and the opportunities that it brings. We propose an architecture that decreases the IoT devices requirements for memory capacity and increases the overall performance. We also discuss the architecture design and the challenges that it has, comparing it to the traditional Blockchain architecture as well as an Edge Computing architecture for Mobile Blockchain. The paper closes with a discussion and future extensions of our work are presented, as well.

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The widespread adoption of truly portable, smart devices and Do-It-Yourself computing platforms by the general public has enabled the rise of new network and system paradigms. This abundance of well-connected, well-equipped, affordable devices, when combined with crowdsourcing methods, enables the development of systems with the aid of the crowd. In this work, we introduce the paradigm of Crowdsourced Systems, systems whose constituent infrastructure, or a significant part of it, is pooled from the general public by following crowdsourcing methodologies. We discuss the particular distinctive characteristics they carry and also provide their ''canonical'' architecture. We exemplify the paradigm by also introducing Crowdcloud, a crowdsourced cloud infrastructure where crowd members can act both as cloud service providers and cloud service clients. We discuss its characteristic properties and also provide its functional architecture. The concepts introduced in this work underpin recent advances in the areas of mobile edge/fog computing and co-designed/cocreated systems.