Showing papers by "Gyorgy Dan published in 2017"

Smart Meter Data Privacy: A Survey

Abstract: Automated and smart meters are devices that are able to monitor the energy consumption of electricity consumers in near real-time. They are considered key technological enablers of the smart grid, as the real-time consumption data that they can collect could enable new sophisticated billing schemes, could facilitate more efficient power distribution system operation and could give rise to a variety of value-added services. At the same time, the energy consumption data that the meters collect are sensitive consumer information; thus, privacy is a key concern and is a major inhibitor of real-time data collection in practice. In this paper, we review the different uses of metering data in the smart grid and the related privacy legislation. We then provide a structured overview, shortcomings, recommendations, and research directions of security solutions that are needed for privacy-preserving meter data delivery and management. We finally survey recent work on privacy-preserving technologies for meter data collection for the three application areas: 1) billing; 2) operations; and 3) value-added services including demand response.

A game theoretic analysis of selfish mobile computation offloading

Abstract: Offloading computation to a mobile cloud is a promising approach for enabling the use of computationally intensive applications by mobile devices. In this paper we consider autonomous devices that maximize their own performance by choosing one of many wireless access points for computation offloading. We develop a game theoretic model of the problem, prove the existence of pure strategy Nash equilibria, and provide a polynomial time algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices we show that all improvement paths are finite. We provide a bound on the price of anarchy of the game, thus our algorithm serves as an approximation algorithm for the global computation offloading cost minimization problem. We use extensive simulations to provide insight into the performance and the convergence time of the algorithms in various scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.

Joint Optimization of Service Function Placement and Flow Distribution for Service Function Chaining

Abstract: In this paper, we consider the problem of optimal dynamic service function (SF) placement and flow routing in a SF chaining (SFC) enabled network. We formulate a multi-objective optimization problem to maximize the acceptable flow rate and to minimize the energy cost for multiple service chains. We transform the multi-objective optimization problem into a single-objective mixed integer linear programming (MILP) problem, and prove that the problem is NP-hard. We propose a polynomial time algorithm based on linear relaxation and rounding to approximate the optimal solution of the MILP. Extensive simulations are conducted to evaluate the effects of the energy budget, the network topology, and the amount of server resources on the acceptable flow rate. The results demonstrate that the proposed algorithm can achieve near-optimal performance and can significantly increase the acceptable flow rate and the service capacity compared to other algorithms under an energy cost budget.

Portunes+: Privacy-Preserving Fast Authentication for Dynamic Electric Vehicle Charging

Abstract: Dynamic contactless charging is an emerging technology for charging electric vehicles (EVs) on the move. For efficient charging and for proper billing, dynamic charging requires secure communication between the charging infrastructure and the EVs that supports very frequent real-time message exchange for EV authentication. In this paper, we propose Portunes+, an authentication protocol for charging pads to authenticate an EVs identity. Portunes+ uses pseudonyms to provide location privacy, allows EVs to roam between different charging sections and receive a single bill, and achieves fast authentication by relying on symmetric keys and on the spatiotemporal location of the EV. We have implemented Portunes+ on RaspberryPi 2 Model B with 900 MHz CPU and 1 GB RAM. Portunes+ allows the EV to generate authentication information within 0.15 ms and allows charging pads to verify the information within 0.11 ms. In comparison, Elliptic Curve Digital Signature Algorithm signature generation and verification take over 9 ms and over 14 ms, respectively.

The Software-Defined Vehicular Cloud: A New Level of Sharing the Road

Abstract: A vehicular cloud (VC) is a type of mobile ad hoc cloud in which multiple vehicles share their resources and perform collaborative jobs. In this article, we propose a software-defined (SD) VC (SDVC) architecture to achieve flexible VC control and efficient resource utilization in a centralized manner.

Reliable Video Streaming With Strict Playout Deadline in Multihop Wireless Networks

Abstract: Motivated by emerging vision-based intelligent services, we consider the problem of rate adaptation for high-quality and low-delay visual information delivery over wireless networks using scalable video coding. Rate adaptation in this setting is inherently challenging due to the interplay between the variability of the wireless channels, the queuing at the network nodes, and the frame-based decoding and playback of the video content at the receiver at very short time scales. To address the problem, we propose a low-complexity model-based rate adaptation algorithm for scalable video streaming systems, building on a novel performance model based on stochastic network calculus. We validate the analytic model using extensive simulations. We show that it allows fast near-optimal rate adaptation for fixed transmission paths, as well as cross-layer optimized routing and video rate adaptation in mesh networks, with less than $\text{10}$ % quality degradation compared to the best achievable performance.

Resilient placement of virtual process control functions in mobile edge clouds

Abstract: Virtual Process Control Functions (VPFs) are a promising solution for replacing hardware controllers in industrial control processes in order to improve operational efficiency. With the introduction of Mobile Edge Computing (MEC) in 5G networks, VPFs could even be executed on cloud resources close to the mobile network edge to further improve operational efficiency. Nonetheless, for this to happen, it is fundamental to ensure that the placement of VPFs be resilient to potential cyber-attacks and component failures, besides being efficient. In this paper we address this problem by considering that VPF placement costs are incurred by reserving MEC resources, executing VPF instances, and by data transmission. We formulate the VPF placement problem as an integer programming (IP) problem, with resilience as a constraint. We propose a VPF placement algorithm based on generalized Benders decomposition and based on linear relaxation of the resulting sub-problems, which effectively reduces the number of integer variables to that of the number of MEC nodes. We evaluate the proposed solution with respect to operational cost, efficiency, and scalability, and compare it with a greedy baseline algorithm. Extensive simulations show that our algorithm performs well in realistic scenarios.

Distributed Caching Algorithms for Interconnected Operator CDNs

Abstract: Fixed and mobile network operators increasingly deploy managed content distribution networks (CDNs) with the objective of reducing the traffic on their transit links and to improve their customers’ quality of experience. As network operator managed CDNs (nCDNs) become commonplace, operators will likely provide common interfaces to interconnect their nCDNs for mutual benefit, as they do with peering today. In this paper, we consider the problem of using distributed algorithms for computing a cache allocation for nCDNs. We show that if every network operator aims to minimize its cost and bilateral payments are not allowed, then it may be impossible to compute a cache allocation. For the case when bilateral payments are possible, we propose two distributed algorithms, the aggregate value compensation and the object value compensation algorithms, which differ in terms of the level of parallelism they allow and in terms of the amount of information exchanged between nCDNs. We prove that the algorithms converge, and we propose a scheme to ensure ex-post individual rationality. Simulations performed on a real autonomous system-level network topology and synthetic topologies show that the algorithms have geometric rate of convergence, and scale well with the graphs’ density and the nCDN capacity.

A continuum of undetectable timing-attacks on PMU-based linear state-estimation

Abstract: Recent innovations in protection and control applications for power systems require the use of Phasor Measurement Unit (PMU) measurements. PMUs rely on precise time synchronization and have been shown to be vulnerable to time synchronization attacks. In this paper, we explore time synchronization attacks against PMU measurements that are undetectable by state-of-the-art Bad-Data Detection (BDD) algorithms, used for Linear State-Estimation (LSE). We show that compromising three or more PMUs enables an attacker to create a continuum of undetectable attacks, and based on geometric arguments we provide a closed form expression for computing the attacks. Furthermore, we provide an algorithm for identifying PMU measurements that are vulnerable to the considered attacks. We use simulations on the IEEE 39-Bus benchmark power system to show that attacks can have a significant impact in terms of power flow mis-estimation that could lead to the violation of ampacity limits in transmission lines.

A Proxy-Based Collaboration System to Minimize Content Download Time and Energy Consumption

Abstract: Mobile collaborative community (MCC) is an emerging technology that allows multiple mobile nodes (MNs) to perform a resource intensive task, such as large content download, in a cooperative manner. In this paper, we introduce a proxy-based collaboration system for the MCC where a content proxy (CProxy) determines the amount of chunks and the sharing order scheduled to each MN, and the received chunks are shared among MNs via Wi-Fi Direct. We formulate a multi-objective optimization problem to minimize both the collaborative content download time and the energy consumption in an MCC, and propose a heuristic algorithm for solving the optimization problem. Extensive simulations are carried out to evaluate the effects of the number of MNs, the wireless bandwidth, the content size, and dynamic channel conditions on the content download time and the energy consumption. Our results demonstrate that the proposed algorithm can achieve near-optimal performance and significantly reduce the content download time and has an energy consumption comparable to that of other algorithms.

Performance Analysis of Reliable Video Streaming with Strict Playout Deadline in Multi-Hop Wireless Networks.

Abstract: Motivated by emerging vision-based intelligent services, we consider the problem of rate adaptation for high quality and low delay visual information delivery over wireless networks using scalable video coding. Rate adaptation in this setting is inherently challenging due to the interplay between the variability of the wireless channels, the queuing at the network nodes and the frame-based decoding and playback of the video content at the receiver at very short time scales. To address the problem, we propose a low-complexity, model-based rate adaptation algorithm for scalable video streaming systems, building on a novel performance model based on stochastic network calculus. We validate the model using extensive simulations. We show that it allows fast, near optimal rate adaptation for fixed transmission paths, as well as cross-layer optimized routing and video rate adaptation in mesh networks, with less than $10$\% quality degradation compared to the best achievable performance.

Distributed Algorithms for Feature Extraction Off-loading in Multi-Camera Visual Sensor Networks.

Abstract: Real-time visual analysis tasks, like tracking and recognition, require swift execution of computationally intensive algorithms. Visual sensor networks can be enabled to perform such tasks by augme ...