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Publications (10 of 121) Show all publications
Kouyoumdjieva, S. T. & Karlsson, G. (2019). Experimental Evaluation of Precision of a Proximity-based Indoor Positioning System. In: 2019 15th Annual Conference on Wireless On-demand Network Systems and Services, WONS 2019 - Proceedings: . Paper presented at 15th Annual Conference on Wireless On-demand Network Systems and Services, WONS 2019; Victoria-Laubernhorn in Wengen, Wengen; Switzerland; 22 January 2019 through 24 January 2019 (pp. 130-137). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8795488.
Open this publication in new window or tab >>Experimental Evaluation of Precision of a Proximity-based Indoor Positioning System
2019 (English)In: 2019 15th Annual Conference on Wireless On-demand Network Systems and Services, WONS 2019 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 130-137, article id 8795488Conference paper, Published paper (Refereed)
Abstract [en]

Bluetooth Low Energy beacons are small transmitters with long battery life that are considered for providing proximity-based services. In this work we evaluate experimentally the performance of a proximity-based indoor positioning system built with off-the-shelf beacons in a realistic environment. We demonstrate that the performance of the system depends on a number of factors, such as the distance between the beacon and the mobile device, the positioning of the beacon as well as the presence and positioning of obstacles such as human bodies. We further propose an online algorithm based on moving average forecasting and evaluate the algorithm in the presence of human mobility. We conclude that algorithms for proximity-based indoor positioning must be evaluated in realistic scenarios, for instance considering people and traffic on the used radio bands. The uncertainty in positioning is high in our experiments and hence the success of commercial context-aware solutions based on BLE beacons is highly dependent on the accuracy required by each application.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
proximity-based indoor positioning, Bluetooth Low Energy, Estimote beacons, Aruba beacons
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-244612 (URN)10.23919/WONS.2019.8795488 (DOI)2-s2.0-85071688690 (Scopus ID)9783903176133 (ISBN)
Conference
15th Annual Conference on Wireless On-demand Network Systems and Services, WONS 2019; Victoria-Laubernhorn in Wengen, Wengen; Switzerland; 22 January 2019 through 24 January 2019
Note

QC 20190301

Available from: 2019-02-22 Created: 2019-02-22 Last updated: 2019-10-09Bibliographically 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 ()
Note

QC 20181016

Available from: 2018-10-15 Created: 2018-10-15 Last updated: 2019-02-12Bibliographically 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
Trifunovic, S., Kouyoumdjieva, S. T., Distl, B., Pajevic, L., Karlsson, G. & Plattner, B. (2017). A Decade of Research in Opportunistic Networks: Challenges, Relevance, and Future Directions. IEEE Communications Magazine, 55(1), 168-173, Article ID 7823357.
Open this publication in new window or tab >>A Decade of Research in Opportunistic Networks: Challenges, Relevance, and Future Directions
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2017 (English)In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 55, no 1, p. 168-173, article id 7823357Article in journal (Refereed) Published
Abstract [en]

Opportunistic networks are envisioned to complement traditional infrastructure-based communication by allowing mobile devices to communicate directly with each other when in communication range instead of via the cellular network. Due to their design, opportunistic networks are considered to be an appropriate communication means in both urban scenarios where the cellular network is overloaded, as well as in scenarios where infrastructure is not available, such as in sparsely populated areas and during disasters. However, after a decade of research, opportunistic networks have not yet been ubiquitously deployed. In this article we explore the reasons for their absence. We take a step back, and first question whether the use cases that are traditionally conjured to motivate opportunistic networking research are still relevant. We also discuss emerging applications that leverage the presence of opportunistic connectivity. Further, we look at past and current technical issues, and we investigate how upcoming technologies would influence the opportunistic networking paradigm. Finally, we outline some future directions for researchers in the field of opportunistic networking.

Place, publisher, year, edition, pages
IEEE, 2017
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-200320 (URN)10.1109/MCOM.2017.1500527CM (DOI)000394680300026 ()2-s2.0-85009942059 (Scopus ID)
Note

QC 20170206

Available from: 2017-01-24 Created: 2017-01-24 Last updated: 2017-11-29Bibliographically approved
Danielis, P., Kouyoumdjieva, S. T. & Karlsson, G. (2017). UrbanCount: Mobile Crowd Counting in Urban Environments. In: Chakrabarti, S Saha, HN (Ed.), 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON): . Paper presented at 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), October 03-05, 2017, Univ British Columbia, Vancouver, Canada (pp. 640-648). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>UrbanCount: Mobile Crowd Counting in Urban Environments
2017 (English)In: 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) / [ed] Chakrabarti, S Saha, HN, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 640-648Conference paper (Refereed)
Abstract [en]

Surveillance, management and estimation of spontaneous crowd formations in urban environments, e.g., during open-air festivals or rush hours, are necessary measures for city administration. Most solutions that implement these measures however require additional costly hardware installations (e.g., installation of observation cameras) and infrastructure support, and often pose privacy concerns. In this work, we present UrbanCount, a fully distributed crowd counting protocol for cities with high crowd densities. UrbanCount relies on mobile device-to-device communication to perform crowd estimation. Each node collects crowd size estimates from other participants in the system whenever in communication range and immediately integrates these estimates into a local estimate. The objective of UrbanCount is to produce a precise mapping of the local estimate to the anticipated global result while preserving node privacy. We evaluate the proposed protocol via extensive tracedriven simulations of synthetic and realistic mobility models. Furthermore, we investigate the dependency between accuracy and density, and demonstrate that in dense environments the local estimate does not deviate by more than 2% for synthetic and 7% for realistic scenarios. Index Terms-Crowd counting,

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
Keywords
Crowd counting, device-to-device communication, mobile networks
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-220872 (URN)000418335300112 ()978-1-5386-3371-7 (ISBN)
Conference
8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), October 03-05, 2017, Univ British Columbia, Vancouver, Canada
Note

QC 20180108

Available from: 2018-01-08 Created: 2018-01-08 Last updated: 2018-01-08Bibliographically approved
Helgason, Ó., Kouyoumdjieva, S. T., Pajevic, L., Yavuz, E. A. & Karlsson, G. (2016). A Middleware for Opportunistic Content Distribution. Computer Networks
Open this publication in new window or tab >>A Middleware for Opportunistic Content Distribution
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2016 (English)In: Computer Networks, ISSN 1389-1286, E-ISSN 1872-7069Article in journal (Refereed) Epub ahead of print
Abstract [en]

In this work we present a middleware architecture for a mobile peer-to-peer content distribution system. Our architecture allows wireless content dissemination between mobile nodes without relying on infrastructure support. In addition, it supports the dissemination of contents between the wireless ad-hoc domain and the wired Internet. In the ad-hoc domain, contents are exchanged opportunistically when nodes are within communication range. Applications access the service of our platform through a publish/subscribe interface and therefore do not have to deal with low-level opportunistic networking issues or matching and soliciting of contents. Our middleware consists of three key components. A content structure that facilitates dividing contents into logical topics and allows efficient matching of content lookups and downloading under sporadic node connectivity. A solicitation protocol that allows nodes to solicit content meta-information in order to discover contents available at a neighboring node and to download content entries disjointedly from different nodes. An API that allows applications to access the system services through a publish/subscribe interface. In this work we present the design and implementation of our middleware and describe a set of applications that use the services provided by our middleware. We also assess the performance of the system using our Android implementation as well as a simulation implementation for large-scale evaluation.

Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
middleware, opportunistic communication, device-to-device communication, mobile wireless networks, content distribution
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-176474 (URN)10.1016/j.comnet.2016.05.026 (DOI)000385326600004 ()2-s2.0-84988919169 (Scopus ID)
Note

QC 20160608

Available from: 2015-11-05 Created: 2015-11-05 Last updated: 2019-10-28Bibliographically approved
Kouyoumdjieva, S. T. & Karlsson, G. (2016). Device-to-Device Mobile Data Offloading for Music Streaming. In: 2016 IFIP Networking Conference (IFIP Networking) and Workshops, IFIP Networking 2016: . Paper presented at 2016 IFIP Networking Conference (IFIP Networking) and Workshops, IFIP Networking 2016, Vienna, Austria, 17 May 2016 through 19 May 2016 (pp. 377-385). Institute of Electrical and Electronics Engineers (IEEE), Article ID 7497219.
Open this publication in new window or tab >>Device-to-Device Mobile Data Offloading for Music Streaming
2016 (English)In: 2016 IFIP Networking Conference (IFIP Networking) and Workshops, IFIP Networking 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 377-385, article id 7497219Conference paper, Published paper (Refereed)
Abstract [en]

Device-to-device communication (also referred to as opportunistic networking) is considered a feasible means for offloading mobile data traffic. Due to the sporadic nature of contact opportunities, applications in the domain of device-todevice communication are assumed to be delay-tolerant, with content delivery deadlines being in the order of hours. However, predictions suggest that by 2020 more than 75% of the traffic volumes at mobile operators will be generated by multimedia contents which is often seen as data served in real-time. In this paper we explore how the concept of opportunistic networking can be used for dissemination of real-time streaming contents for users in urban environments without degrading quality of experience. We first present a general framework for offloading multimedia data that is organized in terms of playlists, and we then investigate the performance of the framework in realistic urban environments using the music streaming service Spotify as a use-case. Our results show that it is feasible to use opportunistic device-to-device communication in the context of music streaming. We demonstrate that the system performance is insensitive to a number of parameters such as playlist length distribution, and initial content availability distribution, however it exhibits sensitivity towards the amount of requested data and the node density.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Keywords
mobile data offloading, device-to-device communication, opportunistic networking, music streaming, Spotify
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-176477 (URN)10.1109/IFIPNetworking.2016.7497219 (DOI)000383224900043 ()2-s2.0-84982283841 (Scopus ID)978-3-9018-8283-8 (ISBN)
Conference
2016 IFIP Networking Conference (IFIP Networking) and Workshops, IFIP Networking 2016, Vienna, Austria, 17 May 2016 through 19 May 2016
Note

QC 20161019

Available from: 2015-11-05 Created: 2015-11-05 Last updated: 2016-10-19Bibliographically approved
Danielis, P., Kouyoumdjieva, S. T. & Karlsson, G. (2016). DiVote: A Distributed Voting Protocol for Mobile Device-to-Device Communication. In: Proceedings of the 28th International Teletraffic Congress, ITC 2016: . Paper presented at 28th International Teletraffic Congress, ITC 2016, University of Wurzburg, Wurzburg, Germany, 12 September 2016 through 16 September 2016 (pp. 69-77). , 1
Open this publication in new window or tab >>DiVote: A Distributed Voting Protocol for Mobile Device-to-Device Communication
2016 (English)In: Proceedings of the 28th International Teletraffic Congress, ITC 2016, 2016, Vol. 1, p. 69-77Conference paper, Published paper (Refereed)
Abstract [en]

Distributed aggregation algorithms have traditionally been applied to environments with no or rather low rates of node churn. The proliferation of mobile devices in recent years introduces high mobility and node churn to these environments, thus imposing a new dimension on the problem of distributed aggregation in terms of scalability and convergence speed. To address this, we present DiVote, a distributed voting protocol for mobile device-to-device communication. We investigate a particular use case, in which pedestrians equipped with mobile phones roam around in an urban area and participate in a distributed yes/no poll, which has both spatial and temporal relevance to the community. Each node casts a vote and collects votes from other participants in the system whenever in communication range; votes are immediately integrated into a local estimate. The objective of DiVote is to produce a precise mapping of the local estimate to the anticipated global voting result while preserving node privacy. Since mobile devices may have limited resources allocated for mobile sensing activities, DiVote utilizes D-GAP compression. We evaluate the proposed protocol via extensive trace-driven simulations of realistic pedestrian behavior, and demonstrate that it scales well with the number of nodes in the system. Furthermore, in densely populated areas the local estimate of participants does not deviate by more than 3% from the global result. Finally, in certain scenarios the achievable compression rate of DiVote is at least 19% for realistic vote distributions.

Keywords
device-to-device communication, opportunistic networks, mobile wireless networks, distributed algorithms
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-187737 (URN)10.1109/ITC-28.2016.118 (DOI)000393569000009 ()2-s2.0-85013067873 (Scopus ID)
Conference
28th International Teletraffic Congress, ITC 2016, University of Wurzburg, Wurzburg, Germany, 12 September 2016 through 16 September 2016
Note

QC 20160926

Available from: 2016-06-29 Created: 2016-05-27 Last updated: 2017-06-07Bibliographically approved
Kouyoumdjieva, S. T. & Karlsson, G. (2016). Energy-Aware Opportunistic Mobile Data Offloading Under Full and Limited Cooperation. Computer Communications, 84, 84-95
Open this publication in new window or tab >>Energy-Aware Opportunistic Mobile Data Offloading Under Full and Limited Cooperation
2016 (English)In: Computer Communications, ISSN 0140-3664, E-ISSN 1873-703X, Vol. 84, p. 84-95Article in journal (Refereed) Epub ahead of print
Abstract [en]

Opportunistic networking (a.k.a. device-to-device communication) is considered a feasible means for offloading mobile data traffic. Since mobile nodes are battery-powered, opportunistic networks must be expected to satisfy the user demand without greatly affecting battery lifetime. To address this requirement, this work introduces progressive selfishness, an adaptive and scalable energy-aware algorithm for opportunistic networks used in the context of mobile data offloading. The paper evaluates the performance of progressive selfishness in terms of both application throughput and energy consumption via extensive trace-driven simulations of realistic pedestrian behavior. The evaluation considers two modes of nodal cooperation: full and limited, with respect to the percentage of nodes in the system that adopt progressive selfishness. The paper demonstrates that under full cooperation the proposed algorithm is robust against the distributions of node density and initial content availability. The results show that in certain scenarios progressive selfishness achieves up to 85% energy savings during opportunistic downloads while sacrificing less than 1% in application throughput. Furthermore, the study demonstrates that in terms of total energy consumption (by both cellular and opportunistic downloads) in dense environments the performance of progressive selfishness is comparable to downloading contents directly from a mobile network. Finally, the paper shows that progressive selfishness is robust against the presence of non-cooperative nodes in the system, and that in certain scenarios the system-level performance does not deteriorate significantly under limited cooperation even when 50% of the nodes in the system do not adhere to the specifics of the algorithm.

Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
mobile data offloading, selfishness, duty cycling, energy savings, opportunistic networking
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-176472 (URN)10.1016/j.comcom.2016.02.008 (DOI)000376552400009 ()2-s2.0-84962157148 (Scopus ID)
Note

QC 20160429

Available from: 2015-11-05 Created: 2015-11-05 Last updated: 2019-10-28Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-3704-1338

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