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Publications (10 of 108) Show all publications
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: 2020-02-04Bibliographically 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
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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
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: 2019-09-05Bibliographically 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
Liu, Y., Pang, Z., Dán, G., Lan, D. & Gong, S. (2018). A Taxonomy for the Security Assessment of IP-Based Building Automation Systems: The Case of Thread. IEEE Transactions on Industrial Informatics, 14(9), 4113-4123
Open this publication in new window or tab >>A Taxonomy for the Security Assessment of IP-Based Building Automation Systems: The Case of Thread
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2018 (English)In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 14, no 9, p. 4113-4123Article in journal (Refereed) Published
Abstract [en]

Motivated by theproliferation of wireless building automation systems (BAS) and increasing security-awareness among BAS operators, in this paper, we propose a taxonomy for the security assessment of BASs. We apply the proposed taxonomy to Thread, an emerging native IP-based protocol for BAS. Our analysis reveals a number of potential weaknesses in the design of Thread. We propose potential solutions for mitigating several identified weaknesses and discuss their efficacy. We also provide suggestions for improvements in future versions of the standard. Overall, our analysis shows that Thread has a well-designed security control for the targeted use case, making it a promising candidate for communication in next generation BASs.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Building automation systems (BASs), security analysis, Thread
National Category
Other Engineering and Technologies
Identifiers
urn:nbn:se:kth:diva-235455 (URN)10.1109/TII.2018.2844955 (DOI)000443994500032 ()2-s2.0-85048149192 (Scopus ID)
Funder
VINNOVASwedish Civil Contingencies Agency
Note

QC 20180927

Available from: 2018-09-27 Created: 2018-09-27 Last updated: 2018-09-27Bibliographically approved
Josilo, S. & Dán, G. (2018). Decentralized Scheduling for Offloading of Periodic Tasks in Mobile Edge Computing. In: IFIP NETWORKING 2018: . Paper presented at 17th IFIP Networking Conference (IFIP Networking), Univ Zurich, Zurich, SWITZERLAND, MAY 14-16, 2018 (pp. 469-477). IEEE conference proceedings
Open this publication in new window or tab >>Decentralized Scheduling for Offloading of Periodic Tasks in Mobile Edge Computing
2018 (English)In: IFIP NETWORKING 2018, IEEE conference proceedings, 2018, p. 469-477Conference paper, Published paper (Refereed)
Abstract [en]

Motivated by various surveillance applications, we consider wireless devices that periodically generate computationally intensive tasks. The devices aim at maximizing their performance by choosing when to perform the computations and whether or not to offload their computations to a cloud resource via one of multiple wireless access points. We propose a game theoretic model of the problem, give insight into the structure of equilibrium allocations and provide an efficient algorithm for computing pure strategy Nash equilibria. Extensive simulation results show that the performance in equilibrium is significantly better than in a system without coordination of the timing of the tasks’ execution, and the proposed algorithm has an average computational complexity that is linear in the number of devices.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2018
Series
IFIP NETWORKING
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-228081 (URN)10.23919/IFIPNetworking.2018.8696507 (DOI)000493755200060 ()2-s2.0-85065469615 (Scopus ID)
Conference
17th IFIP Networking Conference (IFIP Networking), Univ Zurich, Zurich, SWITZERLAND, MAY 14-16, 2018
Note

QC 20180518. QC 20200108

Available from: 2018-05-17 Created: 2018-05-17 Last updated: 2020-01-08Bibliographically approved
Josilo, S. & Dán, G. (2018). Joint Allocation of Computing and Wireless Resources to Autonomous Devices in Mobile Edge Computing. In: MECOMM 2018 - Proceedings of the 2018 Workshop on Mobile Edge Communications, Part of SIGCOMM 2018: . Paper presented at in Proc. of ACM SIGCOMM Mecomm'18 Workshop.
Open this publication in new window or tab >>Joint Allocation of Computing and Wireless Resources to Autonomous Devices in Mobile Edge Computing
2018 (English)In: MECOMM 2018 - Proceedings of the 2018 Workshop on Mobile Edge Communications, Part of SIGCOMM 2018, 2018Conference paper, Published paper (Refereed)
Abstract [en]

We consider the interaction between mobile edge computing (MEC) resource management and wireless devicesthat offload computationally intensive tasks through shared wireless links to edge cloud servers, so as to minimize their completion times. We model the interaction between the devices and the operator that optimizes the allocation of the wireless and computing resources as a Stackelberg game. We show that a pure strategy Stackelberg equilibrium exists, and we provide an efficient algorithm for computing equilibrium allocations. Our simulation results show that jointoptimization of the wireless and computing resources can provide a significant reduction of completion times at little increase in computational complexity compared to a system where resource allocation is not optimized. © 2018 Association for Computing Machinery.

Keywords
Computation offloading; Edge computing; Game theory
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-248578 (URN)10.1145/3229556.3229559 (DOI)2-s2.0-85056806780 (Scopus ID)
Conference
in Proc. of ACM SIGCOMM Mecomm'18 Workshop
Note

QC 20190423

Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-04-23Bibliographically approved
He, Q., Dán, G. & Fodor, V. (2018). Minimizing Age of Correlated Information for Wireless Camera Networks. In: IEEE INFOCOM 2018 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS): . Paper presented at IEEE Conference on Computer Communications (IEEE INFOCOM), APR 15-19, 2018, Honolulu, HI (pp. 547-552). IEEE
Open this publication in new window or tab >>Minimizing Age of Correlated Information for Wireless Camera Networks
2018 (English)In: IEEE INFOCOM 2018 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), IEEE , 2018, p. 547-552Conference paper, Published paper (Refereed)
Abstract [en]

Freshness of information is of critical importance for a variety of applications based on wireless camera networks where multi-view image processing is required. In this study, we propose to jointly optimize the use of communication and computing resources such that information from multiple views is delivered is obtained in a timely fashion. To this end, we extend the concept of age of information to capture packets carrying correlated data. We consider the joint optimization of processing node assignment and camera transmission policy, so as to minimize the maximum peak age of information from all sources. We formulate the multi-view age minimization problem (MVAM) and prove that it is NP-hard. We provide fundamental results including tractable cases and optimality conditions. To solve the MVAM efficiently, we develop a modular optimization algorithm following a decomposition approach. Numerical results show that, by employing our approach, the maximum peak age is significantly reduced in comparison to a traditional centralized solution with minimum-time scheduling.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Conference on Computer Communications Workshops, ISSN 2159-4228
National Category
Computer Systems
Identifiers
urn:nbn:se:kth:diva-239838 (URN)10.1109/INFCOMW.2018.8406914 (DOI)000450157700155 ()2-s2.0-85050667072 (Scopus ID)978-1-5386-5979-3 (ISBN)
Conference
IEEE Conference on Computer Communications (IEEE INFOCOM), APR 15-19, 2018, Honolulu, HI
Note

QC 20190107

Available from: 2019-01-07 Created: 2019-01-07 Last updated: 2020-01-29Bibliographically approved
Josilo, S. & Dán, G. (2018). Poster Abstract: Decentralized Fog Computing Resource Management for Offloading of Periodic Tasks. In: IEEE INFOCOM 2018 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS): . Paper presented at IEEE Conference on Computer Communications (IEEE INFOCOM), APR 15-19, 2018, Honolulu, HI. IEEE
Open this publication in new window or tab >>Poster Abstract: Decentralized Fog Computing Resource Management for Offloading of Periodic Tasks
2018 (English)In: IEEE INFOCOM 2018 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

Fog computing is recognized as a promising approach for meeting the computational and delay requirements of a variety of emerging applications in the Internet of Things. This work presents a game theoretical treatment of the resource allocation problem in a fog computing system where wireless devices periodically generate computationally intensive tasks, and aim at minimizing their own cost.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Conference on Computer Communications Workshops, ISSN 2159-4228
National Category
Computer Systems
Identifiers
urn:nbn:se:kth:diva-239840 (URN)10.1109/INFCOMW.2018.8406995 (DOI)000450157700056 ()2-s2.0-85050674779 (Scopus ID)978-1-5386-5979-3 (ISBN)
Conference
IEEE Conference on Computer Communications (IEEE INFOCOM), APR 15-19, 2018, Honolulu, HI
Note

QC 20190107

Available from: 2019-01-07 Created: 2019-01-07 Last updated: 2019-01-07Bibliographically approved
Josilo, S. & Dán, G. (2017). A Game Theoretic Analysis of Selfish Mobile Computation Offloading. In: IEEE INFOCOM 2017 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS: . Paper presented at IEEE Conference on Computer Communications (INFOCOM), MAY 01-04, 2017, Atlanta, GA. IEEE
Open this publication in new window or tab >>A Game Theoretic Analysis of Selfish Mobile Computation Offloading
2017 (English)In: IEEE INFOCOM 2017 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS, IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE INFOCOM, ISSN 0743-166X
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-224086 (URN)10.1109/INFOCOM.2017.8057148 (DOI)000425232200205 ()2-s2.0-85034110902 (Scopus ID)978-1-5090-5336-0 (ISBN)
Conference
IEEE Conference on Computer Communications (INFOCOM), MAY 01-04, 2017, Atlanta, GA
Note

QC 20180314

Available from: 2018-03-14 Created: 2018-03-14 Last updated: 2018-05-17Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-4876-0223

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