Adelina Madhja

Distributed wireless power transfer in sensor networks with multiple Mobile Chargers

We investigate the problem of efficient wireless power transfer in wireless sensor networks. In our approach, special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network information. We propose four new protocols for efficient charging, addressing key issues which we identify, most notably (i) what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.

Hierarchical, collaborative wireless energy transfer in sensor networks with multiple Mobile Chargers

Wireless energy transfer is used to fundamentally address energy management problems in Wireless Rechargeable Sensor Networks (WRSNs). In such networks mobile entities traverse the network and wirelessly replenish the energy of sensor nodes. In recent research on collaborative wireless charging, the mobile entities are also allowed to charge each other.In this work, we enhance the collaborative feature by forming a hierarchical charging structure. We distinguish the Chargers in two groups, the hierarchically lower Mobile Chargers which charge sensor nodes and the hierarchically higher Special Chargers which charge Mobile Chargers. We define the Coordination Decision Problem and prove that it is NP-complete. Also, we propose a new protocol for 1-D networks which we compare with a state of the art protocol. Motivated by the improvement in 1-D networks, we propose and implement four new collaborative charging protocols for 2-D networks, in order to achieve efficient charging and improve important network properties. Our protocols are either centralized or distributed, and assume different levels of network knowledge.Extensive simulation findings demonstrate significant performance gains, with respect to non-collaborative state of the art charging methods. In particular, our protocols improve several network properties and metrics, such as the network lifetime, routing robustness, coverage and connectivity. A useful feature of our methods is that they can be suitably added on top of non-collaborative protocols to further enhance their performance.

Hierarchical, collaborative wireless charging in sensor networks

Wireless power transfer is used to fundamentally address energy management problems in Wireless Rechargeable Sensor Networks. In such networks mobile entities traverse the network and wirelessly replenish the energy of sensor nodes. In recent research on collaborative wireless charging, the mobile entities are also allowed to charge each other. In this work, we enhance the collaborative feature by forming a hierarchical charging structure. We distinguish the chargers into two groups, the hierarchically lower Mobile Chargers (MCs) which charge sensor nodes and the hierarchically higher Special Chargers (SCs) which charge MCs. We propose and implement four new collaborative charging protocols, in order to achieve efficient charging and improve important network properties. Our protocols are either centralized or distributed, and assume different levels of network knowledge. Extensive simulation findings demonstrate significant performance gains, with respect to non-collaborative state of the art charging methods. In particular, our protocols improve several network properties and metrics, such as the network lifetime, routing robustness, coverage and connectivity. A useful feature of our methods is that they can be suitably added on top of non-collaborative protocols to further enhance their performance.

Efficient, distributed coordination of multiple mobile chargers in sensor networks

We investigate the problem of efficient wireless energy recharging in Wireless Rechargeable Sensor Networks (WRSNs). In such networks special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network information. We propose four new protocols for efficient recharging, addressing key issues which we identify, most notably (i) what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.

Energy Aware Network Formation in Peer-to-Peer Wireless Power Transfer

This paper addresses wirelessly networked populations of nodes (agents) that can both transmit and receive wireless power among each other, interacting locally in a peer to peer manner. In this setting, we study the important problem of network formation, in particular how the agents can distributively create a star structure. Extending the state of the art, we introduce energy considerations in network formation: in addition to the star construction, our goal is to achieve a certain target energy distribution among the agents. We assume a generalized, more realistic energy loss factor which may differ for each pairwise power exchange. We propose four interaction protocols aiming both to construct the star structure and also converge to the target energy distribution. Our protocols assume different amounts of network knowledge, achieving different efficient trade-offs with performance, measured in terms of how close they get to the targeted energy distribution, as well as their energy efficiency and convergence time.

Peer-to-Peer Energy-Aware Tree Network Formation

We study the fundamental problem of distributed energy-aware network formation with mobile agents of limited computational power that have the capability to wirelessly transmit and receive energy in a peer-to-peer manner. Specifically, we design simple distributed protocols consisting of a small number of states and interaction rules for the construction of both arbitrary and binary trees. Further, we theoretically and experimentally evaluate a plethora of energy redistribution protocols that exploit different levels of knowledge in order to achieve desired energy distributions which require, for instance, that every agent has twice the energy of the agents of higher depth (according to the tree network). Our study shows that without using any knowledge about the network structure, such energy distributions cannot be achieved in a timely manner, which means that there might be high energy loss during the redistribution process. On the other hand, only a few extra bits of information seem to be enough to guarantee quick convergence to energy distributions that satisfy particular properties, yielding low energy loss.

Peer-to-Peer Wireless Energy Transfer in Populations of Very Weak Mobile Nodes

Wireless energy transfer provides the potential to efficiently replenish the energy and prolong the lifetime of nodes in adhoc networks. Current state-of-the-art studies utilize strong charger stations (equipped with large batteries) with the main task of transmitting their available energy to the network nodes. Different to these works, in this paper, we investigate interactive, peer-to- peer wireless energy exchange in populations of resource limited mobile agents, without the use of any special chargers. The agents in this model are capable of mutual energy transfer, acting both as transmitters and receivers of wireless energy. In such types of adhoc networks, we propose protocols that address two important problems: the problem of energy balance between agents, and the problem of distributively forming a certain network structure (a star) with an appropriate energy distribution among the agents. We evaluate key performance properties (and their trade-offs) of our protocols, such as their energy and time efficiency, as well as the achieved distance to the target energy distribution.

Privacy Flag: A crowdsourcing platform for reporting and managing privacy and security risks

Nowadays we are witnessing an unprecedented evolution in how we gather and process information. Technological advances in mobile devices as well as ubiquitous wireless connectivity have brought about new information processing paradigms and opportunities for virtually all kinds of scientific and business activity. These new paradigms rest on three pillars: i) numerous powerful portable devices operated by human intelligence, ubiquitous in space and available, most of the time, ii) unlimited environment sensing capabilities of the devices, and iii) fast networks connecting the devices to Internet information processing platforms and services. These pillars implement the concepts of crowdsourcing and collective intelligence. These concepts describe online services that are based on the massive participation of users and the capabilities of their devices.in order to produce results and information which are more than the sum of the part. The EU project Privacy Flag relies exactly on these two concepts in order to mobilize roaming citizens to contribute, through crowdsourcing, information about risky applications and dangerous web sites whose processing may produce emergent threat patterns, not evident in the contributed information alone, reelecting a collective intelligence action. Crowdsourcing and collective intelligence, in this context, has numerous advantages, such as raising privacy-awareness among people. In this paper we summarize our work in this project and describe the capabilities and functionalities of the Privacy Flag Platform.

Assigning Hierarchy to Collaborative Mobile Charging in Sensor Networks

Wireless power transfer is used to fundamentally address energy management problems in Wireless Rechargeable Sensor Networks (WRSNs). In such networks, mobile entities traverse the network and wirelessly replenish the energy of sensor nodes. In recent research on collaborative mobile charging, the mobile entities are also allowed to charge each other. In this chapter, we enhance the collaborative feature by forming a hierarchical charging structure. We distinguish the Chargers in two groups, the hierarchically lower, called Mobile Chargers, that charge sensor nodes and the hierarchically higher, called Special Chargers, that charge Mobile Chargers. We define the Coordination Decision Problem and prove that it is NP-complete. Also, we propose a new protocol for 1-D networks which we compare with a state-of-the-art protocol. Motivated by the improvement in 1-D networks, we design four new collaborative charging protocols for 2-D networks to achieve efficient charging and improve important network properties. Our protocols are either centralized or distributed, and assume different levels of network knowledge. Extensive simulation findings demonstrate significant performance gains, with respect to non-collaborative state-of-the-art charging methods. In particular, our protocols improve several network properties and metrics, such as the network lifetime, routing robustness, coverage, and connectivity. A useful feature of our methods is that they can be suitably added on top of non-collaborative protocols to further enhance their performance.

Distributed Coordination Protocols for Wireless Charging in Sensor Networks

In this chapter, we investigate the problem of efficient wireless power transfer in wireless sensor networks where special mobile entities called Mobile Chargers, traverse the network and wirelessly replenish the energy of sensor nodes. The methods we present are distributed and use limited network information. More specifically, we propose four new protocols for efficient wireless charging while addressing key issues such as the identification of what are good coordination procedures and what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state-of-the-art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.