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Publications (10 of 114) Show all publications
Josilo, S. & Dán, G. (2020). Computation Offloading Scheduling for Periodic Tasks in Mobile Edge Computing. IEEE/ACM Transactions on Networking, 28(2), 667-680
Open this publication in new window or tab >>Computation Offloading Scheduling for Periodic Tasks in Mobile Edge Computing
2020 (English)In: IEEE/ACM Transactions on Networking, ISSN 1063-6692, E-ISSN 1558-2566, Vol. 28, no 2, p. 667-680Article in journal (Refereed) Published
Abstract [en]

Motivated by various delay sensitive applications, we address the problem of coordinating the offloading decisions of wireless devices that periodically generate computationally intensive tasks. We consider autonomous devices that aim at minimizing their own cost by choosing when to perform their tasks and whether or not to offload their tasks to an edge cloud through one of the multiple wireless links. We develop a game theoretical model of the problem, prove the existence of pure strategy Nash equilibria and propose a polynomial complexity algorithm for computing an equilibrium. Furthermore, we characterize the structure of the equilibria, and by providing an upper bound on the price of anarchy of the game we establish an asymptotically tight bound on the approximation ratio of the proposed algorithm. Our simulation results show that the proposed algorithm achieves significant performance gain compared to uncoordinated computation offloading at a computational complexity that is on average linear in the number of devices.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020
Keywords
Task analysis, Performance evaluation, Computational modeling, Cloud computing, Approximation algorithms, Energy consumption, Edge computing, Computation offloading, game theory, decentralized resource management
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-273515 (URN)10.1109/TNET.2020.2968209 (DOI)000528838300018 ()2-s2.0-85079604134 (Scopus ID)
Note

QC 20200519

Available from: 2020-05-19 Created: 2020-05-19 Last updated: 2020-05-19Bibliographically approved
Shereen, E. & Dán, G. (2020). Model-Based and Data-Driven Detectors for Time Synchronization Attacks Against PMUs. IEEE Journal on Selected Areas in Communications, 38(1), 169-179
Open this publication in new window or tab >>Model-Based and Data-Driven Detectors for Time Synchronization Attacks Against PMUs
2020 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 38, no 1, p. 169-179Article in journal (Refereed) Published
Abstract [en]

Precise time synchronization of Phasor Measurement Units (PMUs) is critical for monitoring and control of smart grids. Thus, time synchronization attacks (TSAs) against PMUs pose a severe threat to smart grid security. In this paper we present an approach for detecting TSAs based on the interaction between the time synchronization system and the power system. We develop a phasor measurement model and use it to derive an accurate closed form expression for the correlation between the frequency adjustments made by the PMU clock and the resulting change in the measured phase angle, without an attack. We then propose one model-based and three data-driven TSA detectors that exploit the change in correlation due to a TSA. Using extensive simulations, we evaluate the proposed detectors under different strategies for implementing TSAs, and show that the proposed detectors are superior to state-of-the-art clock frequency anomaly detection, especially for unstable clocks.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2020
Keywords
Clocks, Phasor measurement units, Synchronization, Detectors, Phase measurement, Frequency measurement, Power system stability, PMU, time synchronization attacks, phasor measurements, security, cyber-physical systems, correlation, clock synchronization, data-driven detection, machine learning
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-268779 (URN)10.1109/JSAC.2019.2952017 (DOI)000510714300015 ()2-s2.0-85074856246 (Scopus ID)
Note

QC 20200225

Available from: 2020-02-25 Created: 2020-02-25 Last updated: 2020-02-25Bibliographically approved
Zhao, P., Fodor, G., Dán, G. & Telek, M. (2019). A Game Theoretic Approach to Uplink Pilot and Data Power Control in Multi-Cell Multi-User MIMO Systems. IEEE Transactions on Vehicular Technology, 68(9), 8707-8720
Open this publication in new window or tab >>A Game Theoretic Approach to Uplink Pilot and Data Power Control in Multi-Cell Multi-User MIMO Systems
2019 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 68, no 9, p. 8707-8720Article in journal (Refereed) Published
Abstract [en]

In multi-user multiple-input-multiple-output (MU-MIMO) systems that employ pilot-symbol aided channel estimation, the pilot-to-data power ratio (PDPR) has a large impact on the system performance. In this paper, we consider the problem of setting the PDPR in multi-cell MU-MIMO systems in the presence of channel estimation errors, intercell interference and pilot contamination. To analyze and address this problem, we first develop a model of the multi-cell MU-MIMO system and derive a closed-form expression for the mean squared error of the uplink received data symbols. Building on this result, we then propose two decentralized PDPR-setting algorithms based on game theoretic approaches that are applicable in multi-cell systems. We find that both algorithms converge to a Nash equilibrium and provide performance improvements over systems that do not properly set the PDPR, while they maintain different levels of fairness.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Multi-antenna systems, channel state information, estimation techniques, receiver algorithms
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-261969 (URN)10.1109/TVT.2019.2927127 (DOI)000487191500036 ()2-s2.0-85077498421 (Scopus ID)
Note

QC 20191014

Available from: 2019-10-14 Created: 2019-10-14 Last updated: 2020-03-09Bibliographically approved
Li, Z. & Dán, G. (2019). Dynamic Cheap Talk for Robust Adversarial Learning. In: 10th International Conference on Decision and Game Theory for Security, GameSec 2019: . Paper presented at 30 October 2019 through 1 November 2019 (pp. 297-309). Springer
Open this publication in new window or tab >>Dynamic Cheap Talk for Robust Adversarial Learning
2019 (English)In: 10th International Conference on Decision and Game Theory for Security, GameSec 2019, Springer , 2019, p. 297-309Conference paper, Published paper (Refereed)
Abstract [en]

Robust adversarial learning is considered in the context of closed-loop control with adversarial signaling in this paper. Due to the nature of incomplete information of the control agent about the environment, the belief-dependent signaling game formulation is introduced in the dynamic system and a dynamic cheap talk game is formulated with belief-dependent strategies for both players. We show that the dynamic cheap talk game can further be reformulated as a particular stochastic game, where the states are beliefs of the environment and the actions are the adversarial manipulation strategies and control strategies. Furthermore, the bisimulation metric is proposed and studied for the dynamic cheap talk game, which provides an upper bound on the difference between values of different initial beliefs in the zero-sum equilibrium.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Bisimulation metric, Cheap talk signaling game, Stochastic game, Decision theory, Stochastic systems, Adversarial learning, Bisimulations, Closed-loop control, Control strategies, Incomplete information, Manipulation strategy, Signaling game, Game theory
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-268452 (URN)10.1007/978-3-030-32430-8_18 (DOI)2-s2.0-85076410808 (Scopus ID)9783030324292 (ISBN)
Conference
30 October 2019 through 1 November 2019
Note

QC 20200409

Available from: 2020-04-09 Created: 2020-04-09 Last updated: 2020-04-09Bibliographically approved
Lee, G., Ko, H., Pack, S., Pacifici, V. & Dán, G. (2019). Fog-Assisted Aggregated Synchronization Scheme for Mobile Cloud Storage Applications. Paper presented at IEEE International Conference on Computer Communications (INFOCOM), APR, 2014, Toronto, CANADA. IEEE Access, 7, 56852-56863
Open this publication in new window or tab >>Fog-Assisted Aggregated Synchronization Scheme for Mobile Cloud Storage Applications
Show others...
2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 56852-56863Article in journal (Refereed) Published
Abstract [en]

Cloud storage applications, such as Dropbox and Google Drive, have recently become very popular among mobile users. In these applications, a cloud server is responsible for synchronizing updates to files among mobile users, and thus if files are shared by many mobile users and are frequently updated then the resulting synchronization traffic can be significant. In order to reduce the synchronization traffic with providing acceptable access latency, we propose a fog-assisted aggregated synchronization (FAS) scheme in which the fog computing server and the cloud server conduct localized and aggregated synchronizations, respectively. We develop an analytical model of the FAS scheme based on renewal-reward theory and use it for model-based adjustment of the timer that controls the trade-off between access latency and synchronization traffic. We use analytical and simulation results to give insight into the effects of the timer, the update-to-access ratio, the number of mobile users, and the sensitivity to the arrival process. The analytical and simulation results demonstrate that the FAS scheme can reduce the synchronization traffic significantly with acceptable access latency compared to conventional schemes.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-252999 (URN)10.1109/ACCESS.2019.2914450 (DOI)000468487800001 ()2-s2.0-85065893864 (Scopus ID)
Conference
IEEE International Conference on Computer Communications (INFOCOM), APR, 2014, Toronto, CANADA
Note

QC 20190619

Available from: 2019-06-19 Created: 2019-06-19 Last updated: 2019-06-19Bibliographically approved
He, Q., Dán, G. & Fodor, V. (2019). On Emptying a Wireless Network with Minimum-Energy under Age Constraints. In: INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019: . Paper presented at IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM Workshops 2019, Paris, France, April 29 - May 2, 2019 (pp. 668-673). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>On Emptying a Wireless Network with Minimum-Energy under Age Constraints
2019 (English)In: INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 668-673Conference paper, Published paper (Refereed)
Abstract [en]

Timely information delivery and low energy consumption are of critical importance for a variety of wireless applications. In this paper, we address the link scheduling problem of emptying a network with minimum energy, subject to a maximum peak age constraint for each information source. We formulate the minimum-energy scheduling with age constraints (MESA) problem in its general form and prove that it is NP-hard. We derive fundamental results, such as lower and upper bounds of the minimum energy consumption, and the conditions when a TDMA schedule is optimal. We propose the deadline-first-with-revision (DFR) algorithm for constructing a scheduling solution, and evaluate its performance under two rate functions. Numerical results show that DFR achieves a significant energy reduction compared to a minimum age scheduling solution.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Energy utilization, Scheduling, Wireless networks, Energy reduction, Information delivery, Information sources, Low energy consumption, Lower and upper bounds, Minimum energy consumption, Numerical results, Wireless application, Time division multiple access
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-268413 (URN)10.1109/INFCOMW.2019.8845089 (DOI)2-s2.0-85073191912 (Scopus ID)9781728118789 (ISBN)
Conference
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM Workshops 2019, Paris, France, April 29 - May 2, 2019
Note

QC 20200428

Available from: 2020-04-28 Created: 2020-04-28 Last updated: 2020-05-02Bibliographically approved
Josilo, S. & Dán, G. (2019). Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks. IEEE Transactions on Mobile Computing, 18(1), 207-220
Open this publication in new window or tab >>Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks
2019 (English)In: IEEE Transactions on Mobile Computing, ISSN 1536-1233, E-ISSN 1558-0660, Vol. 18, no 1, p. 207-220Article in journal (Refereed) Published
Abstract [en]

Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper, we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized 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. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic 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.

Place, publisher, year, edition, pages
IEEE COMPUTER SOC, 2019
Keywords
Computation offloading, mobile edge computing, Nash equilibria, decentralized algorithms
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-269571 (URN)10.1109/TMC.2018.2829874 (DOI)000452441000016 ()2-s2.0-85045992116 (Scopus ID)
Note

QC 20200406

Available from: 2020-04-06 Created: 2020-04-06 Last updated: 2020-04-28Bibliographically approved
Dán, G. & Mazumdar, R. (2019). Welcome Message from the Technical Program Co-Chairs. Paper presented at 27 August 2019 through 29 August 2019. 31st International Teletraffic Congress, ITC 2019, Article ID 8879431.
Open this publication in new window or tab >>Welcome Message from the Technical Program Co-Chairs
2019 (English)In: 31st International Teletraffic Congress, ITC 2019, article id 8879431Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-268555 (URN)10.1109/ITC31.2019.00005 (DOI)2-s2.0-85074783630 (Scopus ID)
Conference
27 August 2019 through 29 August 2019
Note

QC 20200414

Available from: 2020-04-14 Created: 2020-04-14 Last updated: 2020-04-14Bibliographically approved
Josilo, S. & Dán, G. (2019). Wireless and Computing Resource Allocation for Selfish Computation Offloading in Edge Computing. In: IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2019): . Paper presented at IEEE Conference on Computer Communications (IEEE INFOCOM), APR 29-MAY 02, 2019, Paris, FRANCE (pp. 2467-2475). IEEE
Open this publication in new window or tab >>Wireless and Computing Resource Allocation for Selfish Computation Offloading in Edge Computing
2019 (English)In: IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2019), IEEE , 2019, p. 2467-2475Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of allocating wireless and computing resources to a set of autonomous wireless devices in an edge computing system. Devices in the system can decide whether or not to use edge computing resources for offloading computing tasks so as to minimize their completion time, while the edge cloud operator can allocate wireless and computing resources to the devices. We model the interaction between devices and the operator as a Stackelberg game, prove the existence of Stackelberg equilibria, and propose an efficient decentralized algorithm for computing equilibria. We provide a bound on the price of anarchy of the game, which also serves as an approximation ratio bound for the proposed algorithm. Our simulation results show that the joint allocation of wireless and computing resources by the operator can halve the completion times compared to a system with static resource allocation. At the same time, the convergence time of the proposed algorithm is approximately linear in the number of devices, and thus it could be effectively implemented for edge computing resource management.

Place, publisher, year, edition, pages
IEEE, 2019
Series
IEEE INFOCOM, ISSN 0743-166X
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-257831 (URN)10.1109/INFOCOM.2019.8737480 (DOI)000480426400275 ()2-s2.0-85068224988 (Scopus ID)978-1-7281-0515-4 (ISBN)
Conference
IEEE Conference on Computer Communications (IEEE INFOCOM), APR 29-MAY 02, 2019, Paris, FRANCE
Note

QC 20190905

Available from: 2019-09-05 Created: 2019-09-05 Last updated: 2020-04-27Bibliographically approved
Zhao, P. & Dán, G. (2018). A Benders Decomposition Approach for Resilient Placement of Virtual Process Control Functions in Mobile Edge Clouds. IEEE Transactions on Network and Service Management, 15(4), 1460-1472
Open this publication in new window or tab >>A Benders Decomposition Approach for Resilient Placement of Virtual Process Control Functions in Mobile Edge Clouds
2018 (English)In: IEEE Transactions on Network and Service Management, ISSN 1932-4537, E-ISSN 1932-4537, Vol. 15, no 4, p. 1460-1472Article in journal (Refereed) Published
Abstract [en]

Replacing hardware controllers with software-based virtual process control functions (VPFs) is a promising approach for improving the operational efficiency and flexibility of industrial control systems. VPFs can be executed in edge clouds in 5G mobile networks or in the wireless backhaul, which can further improve efficiency. Nonetheless, for the acceptance of virtualization in industrial control systems, a fundamental challenge is to ensure that the placement of VPFs be resilient to component failures and cyber-attacks, besides being efficient. In this paper we address this challenge by considering that VPF placement costs are incurred by reserving mobile edge computing (MEC) resources, executing VPF instances, and by data communication. We formulate the VPF placement problem as an integer programming problem, considering resilience as a constraint. We propose a solution based on generalized Benders decomposition and based on linear relaxation of the resulting sub-problems, which effectively reduces the number of integer variables to the number of MEC nodes. We evaluate the proposed solution with respect to operational cost, efficiency, and scalability in a simulated metropolitan area. Our results show that the proposed solution reduces the total cost significantly compared to a greedy baseline algorithm and a local search heuristic, and can scale to moderate problem instances.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Mobile edge computing, resilient facility location, software controller, virtual function placement, IoT
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-241213 (URN)10.1109/TNSM.2018.2873178 (DOI)000454221200021 ()2-s2.0-85054398549 (Scopus ID)
Projects
CERCES
Note

QC 20190118

Available from: 2019-01-18 Created: 2019-01-18 Last updated: 2019-03-18Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-4876-0223

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