Change search
Link to record
Permanent link

Direct link
BETA
Alternative names
Publications (10 of 77) Show all publications
Zeng, M., Du, R., Fodor, V. & Fischione, C. (2019). Computation Rate Maximization for Wireless Powered Mobile Edge Computing with NOMA. In: Proceedings 20th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM 2019): . Paper presented at 20th IEEE International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM), Washington, DC, JUN 10-12, 2019. IEEE
Open this publication in new window or tab >>Computation Rate Maximization for Wireless Powered Mobile Edge Computing with NOMA
2019 (English)In: Proceedings 20th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM 2019), IEEE , 2019Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we consider a mobile edge computing (MEC) network, that is wirelessly powered. Each user harvests wireless energy and follows a binary computation offloading policy, i.e., it either executes the task locally or offloads it to the MEC as a whole. For the offloading users, non-orthogonal multiple access (NOMA) is adopted for information transmission. We consider rate-adaptive computational tasks and aim at maximizing the sum computation rate of all users by jointly optimizing the individual computing mode selection (local computing or offloading), the time allocations for energy transfer and for information transmission, together with the local computing speed or the transmission power level. The major difficulty of the rate maximization problem lies in the combinatorial nature of the multiuser computing mode selection and its involved coupling with the time allocation. We also study the case where the offloading users adopt time division multiple access (TDMA) as a benchmark, and derive the optimal time sharing among the users. We show that the maximum achievable rate is the same for the TDMA and the NOMA system, and in the case of NOMA it is independent from the decoding order, which can be exploited to improve system fairness. To maximize the sum computation rate, for the mode selection we propose a greedy solution based on the wireless channel gains, combined with the optimal allocation of energy transfer time. Numerical results show that the proposed solution maximizes the computation rate in homogeneous networks, and binary offloading leads to significant gains. Moreover, NOMA increases the fairness of rate distribution among the users significantly, when compared with TDMA.

Place, publisher, year, edition, pages
IEEE, 2019
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-264864 (URN)10.1109/WoWMoM.2019.8792997 (DOI)000494803500029 ()2-s2.0-85071470115 (Scopus ID)978-1-7281-0270-2 (ISBN)978-1-7281-0271-9 (ISBN)
Conference
20th IEEE International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM), Washington, DC, JUN 10-12, 2019
Note

QC 20191217

Available from: 2019-12-17 Created: 2019-12-17 Last updated: 2020-01-03Bibliographically approved
Zeng, M. & Fodor, V. (2019). On the Performance of Parallel Processing in Dynamic Resource Sharing Systems. In: Proceedings - 20th International Conference on High Performance Computing and Communications, 16th International Conference on Smart City and 4th International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018: . Paper presented at 20th International Conference on High Performance Computing and Communications, 16th IEEE International Conference on Smart City and 4th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018, 28 June 2018 through 30 June 2018 (pp. 30-36). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>On the Performance of Parallel Processing in Dynamic Resource Sharing Systems
2019 (English)In: Proceedings - 20th International Conference on High Performance Computing and Communications, 16th International Conference on Smart City and 4th International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 30-36Conference paper, Published paper (Refereed)
Abstract [en]

Parallel processing has the potential of significantly decreasing the service time for a single computational task. Meanwhile, as each task occupies more resources, the number of simultaneously supported tasks declines. This tradeoff is interesting when resources are accessed by many users in a dynamic way, like in the case of cloud or fog computing. In this paper, we evaluate how the level of parallelization and the eventual overheads affect the response time in these dynamic resource sharing systems. We show the counterintuitive finding that even when parallelization has no overhead, the allocation of all resources to a task is suboptimal if the service times have large coefficient of variation. Moreover, we evaluate the scalability properties, and provide guidelines for the optimal level of parallelization under different types of overhead.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Dynamic Resource Sharing, Parallel Processing, Queuing theory, Computation theory, Data communication systems, Fog computing, Queueing theory, Smart city, Time sharing systems, Coefficient of variation, Computational task, Optimal level, Parallelizations, Service time, Parallel processing systems
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-248249 (URN)10.1109/HPCC/SmartCity/DSS.2018.00036 (DOI)000468511200005 ()2-s2.0-85062549943 (Scopus ID)9781538666142 (ISBN)
Conference
20th International Conference on High Performance Computing and Communications, 16th IEEE International Conference on Smart City and 4th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018, 28 June 2018 through 30 June 2018
Note

QC 20190411

Available from: 2019-04-11 Created: 2019-04-11 Last updated: 2019-06-26Bibliographically approved
Liu, D., Fodor, V. & Rasmussen, L. K. (2019). Will Scale-Free Popularity Develop Scale-Free Geo-Social Networks?. IEEE Transactions on Network Science and Engineering, 6(3), 587-598
Open this publication in new window or tab >>Will Scale-Free Popularity Develop Scale-Free Geo-Social Networks?
2019 (English)In: IEEE Transactions on Network Science and Engineering, Vol. 6, no 3, p. 587-598Article in journal (Refereed) Published
Abstract [en]

Empirical results show that spatial factors such as distance, population density and communication range affect our social activities, also reflected by the development of ties in social networks. This motivates the need for social network models that take these spatial factors into account. Therefore, in this paper we propose a gravity-low-based geo-social network model, where connections develop according to the popularity of the individuals, but are constrained through their geographic distance and the surrounding population density. Specifically, we consider a power-law distributed popularity, and random node positions governed by a Poisson point process. We evaluate the characteristics of the emerging networks, considering the degree distribution, the average degree of neighbors and the local clustering coefficient. These local metrics reflect the robustness of the network, the information dissemination speed and the communication locality. We show that unless the communication range is strictly limited, the emerging networks are scale-free, with a rank exponent affected by the spatial factors. Even the average neighbor degree and the local clustering coefficient show tendencies known in non-geographic scale-free networks, at least when considering individuals with low popularity. At high-popularity values, however, the spatial constraints lead to popularity-independent average neighbor degrees and clustering coefficients.

National Category
Computer Systems
Identifiers
urn:nbn:se:kth:diva-258825 (URN)10.1109/TNSE.2018.2841942 (DOI)000484296800027 ()2-s2.0-85047804112 (Scopus ID)
Note

QC 20190926

Available from: 2019-09-10 Created: 2019-09-10 Last updated: 2020-01-08Bibliographically approved
Zeng, M. & Fodor, V. (2018). Energy-efficient Resource Allocation for NOMA-assisted Mobile Edge Computing. In: 2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC): . Paper presented at 29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2018; Bologna; Italy; 9 September 2018 through 12 September 2018 (pp. 1794-1799). IEEE
Open this publication in new window or tab >>Energy-efficient Resource Allocation for NOMA-assisted Mobile Edge Computing
2018 (English)In: 2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC), IEEE , 2018, p. 1794-1799Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we evaluate the effect of increased wireless spectral efficiency on the performance of mobile edge computing. Specifically, we study the energy minimization of computation offloading for a multi carrier non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system. A joint radio-and-computational resource allocation problem is formulated, in which three different resources should be appropriately allocated, including subcarriers, transmission power and computational resources. The formulated resource allocation problem belongs to mixed integer nonlinear programming (MILNP) and is NP-hard. We propose therefore a heuristic solution consisting of two steps, NOMA clustering and subcarrier allocation, and joint computational resource and power allocation. Our numerical results show that NOMA based MEC significantly outperforms its OMA counterpart, especially in scenarios with strict delay limits, where both the transmission and the computational resources become scarce.

Place, publisher, year, edition, pages
IEEE, 2018
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-244577 (URN)000457761900375 ()2-s2.0-85060521523 (Scopus ID)
Conference
29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2018; Bologna; Italy; 9 September 2018 through 12 September 2018
Note

QC 20190308

Available from: 2019-03-08 Created: 2019-03-08 Last updated: 2019-03-08Bibliographically approved
Pajevic, L., Fodor, V. & Karlsson, G. (2018). Ensuring Persistent Content in Opportunistic Networks via Stochastic Stability Analysis. ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), 3(4), 16:1-16:23, Article ID 16.
Open this publication in new window or tab >>Ensuring Persistent Content in Opportunistic Networks via Stochastic Stability Analysis
2018 (English)In: ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), ISSN 2376-3639, Vol. 3, no 4, p. 16:1-16:23, article id 16Article in journal (Refereed) Published
Abstract [en]

The emerging device-to-device communication solutions and the abundance of mobile applications and services make opportunistic networking not only a feasible solution but also an important component of future wireless networks. Specifically, the distribution of locally relevant content could be based on the community of mobile users visiting an area, if long-term content survival can be ensured this way. In this article, we establish the conditions of content survival in such opportunistic networks, considering the user mobility patterns, as well as the time users keep forwarding the content, as the controllable system parameter.

We model the content spreading with an epidemic process, and derive a stochastic differential equations based approximation. By means of stability analysis, we determine the necessary user contribution to ensure content survival. We show that the required contribution from the users depends significantly on the size of the population, that users need to redistribute content only in a short period within their stay, and that they can decrease their contribution significantly in crowded areas. Hence, with the appropriate control of the system parameters, opportunistic content sharing can be both reliable and sustainable.

Place, publisher, year, edition, pages
ACM Digital Library, 2018
Keywords
Opportunistic networks, content sharing, mobility, stochastic epidemic modeling, stochastic differential equations, Markov processes, network performance modeling, network performance analysis, mobile ad hoc networks
National Category
Telecommunications
Research subject
Telecommunication
Identifiers
urn:nbn:se:kth:diva-236081 (URN)10.1145/3232161 (DOI)000456551400002 ()2-s2.0-85074676469 (Scopus ID)
Note

QC 20181016

Available from: 2018-10-15 Created: 2018-10-15 Last updated: 2020-02-04Bibliographically 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
Zanuso, G., Fodor, V., Peretti, L. & Wallmark, O. (2018). Networked electric drives in the Industry 4.0. In: : . Paper presented at 21ST INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS) (pp. 724-729). IEEE
Open this publication in new window or tab >>Networked electric drives in the Industry 4.0
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Industrial automation has been recently challenged by new initiatives such as Industry 4.0, which promises higher connectivity between the devices in an industrial plant. The goal of this work is to discuss how electric drives, widely employed in industry, could benefit from this increased connectivity. Specific applications, such as condition monitoring and multi drive systems, are considered to show the advantages of the industrial network presence, combined with the introduction of new data driven methods. Moreover, the status of industrial communication technologies is depicted, and their suitability for condition monitoring and multi-drive systems applications is described.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
condition monitoring, electric drives, industrial networks, multi-drive systems
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-243993 (URN)10.23919/ICEMS.2018.8549205 (DOI)000456286600137 ()2-s2.0-85060036918 (Scopus ID)
Conference
21ST INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS)
Note

QC 20190214

Available from: 2019-02-14 Created: 2019-02-14 Last updated: 2019-02-14Bibliographically approved
Pajevic, L., Fodor, V. & Karlsson, G. (2018). Predicting the Users’ Next Location From WLAN Mobility Data. In: 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN): . Paper presented at IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), JUN 25-27, 2018, Washington, USA.
Open this publication in new window or tab >>Predicting the Users’ Next Location From WLAN Mobility Data
2018 (English)In: 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), 2018Conference paper, Published paper (Refereed)
Abstract [en]

Accurate prediction of user mobility allows the efficient use of resources in our ubiquitously connected environment. In this work we study the predictability of the users’ next location, considering a campus scenario with highly mobile users. We utilize Markov predictors, and estimate the theoretical predictability limits. Based on the mobility traces of nearly 7400 wireless network users, we estimate that the maximum predictability of the users is on average 82%, and we find that the best Markov predictor is accurate 67% of the time. In addition, we show that moderate performance gains can be achieved by leveraging multi-location prediction.

Keywords
Mobility prediction, Trace-collection analysis, WLAN, Entropy, Markov processes, Prediction algorithms, Feature extraction
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-235990 (URN)10.1109/LANMAN.2018.8475117 (DOI)000447699400011 ()2-s2.0-85055773185 (Scopus ID)978-1-5386-4533-8 (ISBN)
Conference
IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), JUN 25-27, 2018, Washington, USA
Note

QC 20181016

Available from: 2018-10-11 Created: 2018-10-11 Last updated: 2019-05-07Bibliographically approved
Pajevic, L., Fodor, V. & Karlsson, G. (2018). Revisiting the Modeling of User Association Patterns in a University Wireless Network. In: 2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC): . Paper presented at IEEE Wireless Communications and Networking Conference (WCNC), APR 15-18, 2018, Barcelona, SPAIN. IEEE
Open this publication in new window or tab >>Revisiting the Modeling of User Association Patterns in a University Wireless Network
2018 (English)In: 2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an analysis of a large trace of user associations in a university wireless network, which includes around one thousand access points over live campuses. The trace is obtained from RADIUS authentication logs and its merit is in its recency, scale and duration. We propose a methodology for extracting association statistics from these logs, and look at visiting time distributions and processes of user arrivals to access points. We find that a large fraction of the network-around half of all access points-experiences time-varying Poisson arrival process, and association distributions can be modeled by two-stage hyper-exponential distributions at most of the access point. While network associations in campus wireless networks have been extensively studied in the literature, our study reveals changing patterns in user arrival processes and association durations, which seem to be characteristic for networks of predominantly mobile users, and allows the use of tractable network occupancy models.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Wireless Communications and Networking Conference, ISSN 1525-3511
Keywords
WLAN, user mobility, trace-collection analysis
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-232292 (URN)000435542401031 ()2-s2.0-85049215446 (Scopus ID)978-1-5386-1734-2 (ISBN)
Conference
IEEE Wireless Communications and Networking Conference (WCNC), APR 15-18, 2018, Barcelona, SPAIN
Note

QC 20180719

Available from: 2018-07-19 Created: 2018-07-19 Last updated: 2018-10-16Bibliographically approved
Zeng, M. & Fodor, V. (2018). Sum-Rate Maximization under QoS Constraint in MIMO-NOMA Systems. In: 2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC): . Paper presented at IEEE Wireless Communications and Networking Conference (WCNC), APR 15-18, 2018, Barcelona, SPAIN. IEEE
Open this publication in new window or tab >>Sum-Rate Maximization under QoS Constraint in MIMO-NOMA Systems
2018 (English)In: 2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses the power allocation challenge for the downlink transmission in non-orthogonal multiple access (NOMA) systems applying multiple input multiple output transceivers. We consider the case when users are paired to form NOMA clusters, and share a common power budget. We provide low complexity power allocation methods within the clusters and across the clusters, that, together, maximize the sum-rate of the network, while guaranteeing a minimum quality of service for the users with weak channel condition. We show that compared to equal power allocation for the clusters, the proposed power allocation scheme improves the system fairness significantly, without decreasing the aggregate performance.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Wireless Communications and Networking Conference, ISSN 1525-3511
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-232298 (URN)10.1109/WCNC.2018.8377195 (DOI)000435542401083 ()2-s2.0-85049213034 (Scopus ID)978-1-5386-1734-2 (ISBN)
Conference
IEEE Wireless Communications and Networking Conference (WCNC), APR 15-18, 2018, Barcelona, SPAIN
Note

QC 20180719

Available from: 2018-07-19 Created: 2018-07-19 Last updated: 2019-03-27Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2764-8099

Search in DiVA

Show all publications