Georgios Kalogridis

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Optimization of energy consumption in future intelligent energy networks (or Smart Grids) will be based on grid-integrated near-real-time communications between various grid elements in generation, transmission, distribution and loads. This paper discusses some of the challenges and opportunities of communications research in the areas of smart grid and(More)
This paper discusses some of the challenges and opportunities of communications research in the area of smart grids and smart metering. It is clear that the communications research community has been actively seeking the 'next big thing' after interests in recent hot topics such as cognitive radio, cooperative communications, and MIMO have more or less(More)
Smart metering is an essential element of the future smart grid development. However, frequent data collected by home smart meters reveal a wealth of information about residential appliance usage. This gives rise to the smart metering privacy problem. Smart metering data privacy can be protected by using a battery to mask energy usage profiles. However,(More)
Network survivability performance provides an assessment of how well a network supports its functionalities in adverse conditions. This paper studies a wireless network survivability scenario, in which ad hoc routing failures occur due to node mobility, and it enhances and validates previously published results in the following manner: a) it analyses ad hoc(More)
The data collected by a home smart meter can potentially reveal sensitive private information about the home resident(s). In this paper, we study how home energy resources can be used to protect the privacy of the collected data. In particular we: a) introduce a power mixing algorithm to selectively protect a set of consumption events; b) develop a range of(More)
Privacy protection is one of the key requirements of smart grids. To understand the importance of privacy threats it is necessary to study nature of power signals. In this paper, we propose a well-known statistical method which relies on the empirical probability distribution. The method is used to reveal trends in the power signal data and how these trends(More)