arXiv subjects

Cihan Emre Kement

Publications and source records attributed to Cihan Emre Kement.

4 recordsLinked to original sources

arXiv2023

Sustaining Dynamic Traffic in Dense Urban Areas with High Altitude Platform Stations (HAPS)

The impact of information and communication technologies on global energy consumption is increasing every year, and mobile networks account for a significant portion of it. More than 50% of the total energy consumption of mobile networks is issued from radio access networks (RANs), due mainly to the rapid penetration of data-intensive applications and the increasing heterogeneity, dynamicity, and unpredictability of traffic. To tackle these high-demanding problems, RAN densification through the installation of additional base stations in high-demand areas is conventionally used. However, this leads to inefficient energy use and over-provisioning issues. In this context, high altitude platform stations (HAPS) may be used to complement RANs and sustain their services in densely populated areas, where traffic can peak unpredictably. Due to their wide coverage areas, substantial communication payloads, and green energy model, HAPS super macro base stations (SMBSs) are capable of handling the massive and dynamic mobile data traffic of ground users. In this paper, we show how HAPS-SMBSs can complement RANs and serve the dynamic and unpredictable traffic demands of users in an energy-efficient manner. Through the simulation of a case study, we demonstrate the performance of a HAPS-SMBS compared to the conventional RAN densification method and analyze the two approaches in terms of sustainability.

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arXiv2021

Privacy Protection via Joint Real and Reactive Load Shaping in Smart Grids

Frequent metering of electricity consumption is crucial for demand side management in smart grids. However, metered data can be processed fairly easily by employing well-established nonintrusive appliance load monitoring techniques to infer appliance usage, which reveals information about consumers' private lives. Existing load shaping techniques for privacy primarily focus only on altering metered real power, whereas smart meters collect reactive power consumption data as well for various purposes. This study addresses consumer privacy preservation via load shaping in a demand response scheme, considering both real and reactive power. We build a multi-objective optimization framework that enables us to characterize the interplay between privacy maximization, user cost minimization, and user discomfort minimization objectives. Our results reveal that minimizing information leakage due to a single component, e.g., real power, would suffer from overlooking information leakage due to the other component, e.g., reactive power, causing sub-optimal decisions. In fact, joint shaping of real and reactive power components results in the best possible privacy preservation performance, which leads to more than a twofold increase in privacy in terms of mutual information.

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arXiv2020

Holistic Privacy for Electricity, Water, and Natural Gas Metering in Next Generation Smart Homes

In smart electricity grids, high time granularity (HTG) power consumption data can be decomposed into individual appliance load signatures via Nonintrusive Appliance Load Monitoring techniques to expose appliance usage profiles. Various methods ranging from load shaping to noise addition and data aggregation have been proposed to mitigate this problem. However, with the growing scarcity of natural resources, utilities other than electricity (such as water and natural gas) have also begun to be subject to HTG metering, which creates privacy issues similar to that of electricity. Therefore, employing privacy protection countermeasures for only electricity usage is ineffective for appliances that utilize additional/other metered resources. As such, existing privacy countermeasures and metrics need to be reevaluated to address not only electricity, but also any other resource that is metered. Furthermore, a holistic privacy protection approach for all metered resources must be adopted as the information leak from any of the resources has a potential to render the privacy preserving countermeasures for all the other resources futile. This paper introduces the privacy preservation problem for multiple HTG metered resources and explores potential solutions for its mitigation.

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arXiv2020

Load Shaping Based Privacy Protection in Smart Grids: An Overview

Fine-grained energy usage data collected by Smart Meters (SM) is one of the key components of the smart grid (SG). While collection of this data enhances efficiency and flexibility of SG, it also poses a serious threat to the privacy of consumers. Through techniques such as nonintrusive appliance load monitoring (NALM), this data can be used to identify the appliances being used, and hence disclose the private life of the consumer. Various methods have been proposed in the literature to preserve the consumer privacy. This paper focuses on load shaping (LS) methods, which alters the consumption data by means of household amenities in order to ensure privacy. An overview of the privacy protection techniques, as well as heuristics of the LS methods, privacy measures, and household amenities used for privacy protection are presented in order to thoroughly analyze the effectiveness and applicability of these methods to smart grid systems. Finally, possible research directions related to privacy protection in smart grids are discussed.

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