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Eemil Lagerspetz

Bio: Eemil Lagerspetz is an academic researcher from University of Helsinki. The author has contributed to research in topics: Mobile computing & Mobile device. The author has an hindex of 18, co-authored 69 publications receiving 1468 citations. Previous affiliations of Eemil Lagerspetz include Helsinki Institute for Information Technology.


Papers
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Journal ArticleDOI
09 Jul 2021
TL;DR: In this article, the problem of private data release through probabilistic modeling is formulated, and the problem is transformed into choosing a model for the data, allowing also the inclusion of prior knowledge, which improves the quality of the synthetic data.
Abstract: Summary Differential privacy allows quantifying privacy loss resulting from accession of sensitive personal data. Repeated accesses to underlying data incur increasing loss. Releasing data as privacy-preserving synthetic data would avoid this limitation but would leave open the problem of designing what kind of synthetic data. We propose formulating the problem of private data release through probabilistic modeling. This approach transforms the problem of designing the synthetic data into choosing a model for the data, allowing also the inclusion of prior knowledge, which improves the quality of the synthetic data. We demonstrate empirically, in an epidemiological study, that statistical discoveries can be reliably reproduced from the synthetic data. We expect the method to have broad use in creating high-quality anonymized data twins of key datasets for research.

6 citations

Proceedings ArticleDOI
22 Feb 2019
TL;DR: An innovative and novel approach for assessing energy footprint of mobile and wearable systems using thermal imaging using an off-the-shelf thermal camera used to monitor thermal radiation of a device while it is operating an application.
Abstract: Energy-efficiency remains a critical design consideration for mobile and wearable systems, particularly those operating continuous sensing. Energy footprint of these systems has traditionally been measured using hardware power monitors (such as Monsoon power meter) which tend to provide the most accurate and holistic view of instantaneous power use. Unfortunately applicability of this approach is diminishing due to lack of detachable batteries in modern devices. In this paper, we propose an innovative and novel approach for assessing energy footprint of mobile and wearable systems using thermal imaging. In our approach, an off-the-shelf thermal camera is used to monitor thermal radiation of a device while it is operating an application. We develop the general theory of thermal energy-efficiency, and demonstrate its feasibility through experimental benchmarks where we compare energy estimates obtained through thermal imaging against a hardware power monitor.

6 citations

Posted Content
TL;DR: It is shown that, on average, applications lose 70% of their users in the first week, while very popular applications (top 100) lose only 45%.
Abstract: The value of mobile apps is traditionally measured by metrics such as the number of downloads, installations, or user ratings. A problem with these measures is that they reflect actual usage at most indirectly. Indeed, analytic companies have suggested that retention rates, i.e., the number of days users continue to interact with an installed app are low. We conduct the first independent and large-scale study of retention rates and usage behavior trends in the wild. We study their impact on a large-scale database of app-usage data from a community of 339,842 users and more than 213,667 apps. Our analysis shows that, on average, applications lose 70% of their users in the first week, while very popular applications (top 100) lose only 45%. It also reveals, however, that many applications have more complex usage behavior patterns due to seasonality, marketing, or other factors. To capture such effects, we develop a novel app-usage behavior trend measure which provides instantaneous information about the "hotness" of an application. We identify typical trends in app popularity and classify applications into archetypes. From these, we can distinguish, for instance, trendsetters from copycat apps. In our results, roughly 40% of all apps never gain more than a handful of users. Less than 0.4% of the remaining 60% are constantly popular, 1% flop after an initial steep rise, and 7% continuously rise in popularity. We conclude by demonstrating that usage behavior trend information can be used to develop better mobile app recommendations. With the proposed usage-based measures (retention and trend), we are able to shift sovereignty in app recommendations back to where it really matters: actual usage statistics, in contrast to download count and user ratings which are prone to manipulation by people.

5 citations

Proceedings ArticleDOI
15 Oct 2018
TL;DR: This paper presents MegaSense, an air pollution monitoring system for realizing low-cost, near real-time and high resolution spatio-temporal air pollution maps of urban areas, which integrates with the 5G cellular network and leverages mobile edge computing for sensor management and distributed pollution map creation.
Abstract: This demo presents MegaSense, an air pollution monitoring system for realizing low-cost, near real-time and high resolution spatio-temporal air pollution maps of urban areas. MegaSense involves a novel hierarchy of multi-vendor distributed air quality sensors, in which accurate sensors calibrate lower cost sensors. Current low-cost air quality sensors suffer from measurement drift and they have low accuracy. We address this significant open problem for dense urban areas by developing a calibration scheme that detects and automatically corrects drift. MegaSense integrates with the 5G cellular network and leverages mobile edge computing for sensor management and distributed pollution map creation. We demonstrate MegaSense with two sensor types, a state of the art air quality monitoring station and a low-cost sensor array, with calibration between the two to improve the accuracy of the low-cost device. Participants can interact with the sensors and see air quality changes in real-time, and observe the mechanism to mitigate sensor drift. Our re-calibration method minimizes the error for NO2 and O3 81% of the time (vs single calibration) and reduces the mean relative error by 25%-45%.

5 citations

Journal ArticleDOI
21 Apr 2021
TL;DR: It is revealed that there is significant evolution in long-term app usage that 60%-70% of users change their app usage patterns during the duration of more than 3 years and a variety of app pattern change modes are discovered.
Abstract: In the past decade, mobile app usage has played an important role in our daily life. Existing studies have shown that app usage is intrinsically linked with, among others, demographics, social and economic factors. However, due to data limitations, most of these studies have a short time span and treat users in a static manner. To date, no study has shown whether changes in socioeconomic status or other demographics are reflected in long-term app usage behavior. In this paper, we contribute by presenting the first ever long-term study of individual mobile app usage dynamics and how app usage behavior of individuals is influenced by changes in socioeconomic demographic factors over time. Through a novel app dataset we collected, from which we extracted records of 1608 long-term users with more than 3-year app usage and their detailed socioeconomic attributes, we verify the stable correlation between user app usage and user socioeconomic attributes over time and identify a number of representative app usage patterns in connection with specific user attributes. On the basis, we analyze the long-term app usage dynamics and reveal that there is significant evolution in long-term app usage that 60–70% of users change their app usage patterns during the duration of more than 3 years. We further discover a variety of app pattern change modes and demonstrate that the long-term app usage behavior change reflects corresponding transition in socioeconomic attributes, such as change of civil status, family size, transition in job or economic status.

4 citations


Cited by
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Journal ArticleDOI
01 Jan 2015
TL;DR: This paper presents an in-depth analysis of the hardware infrastructure, southbound and northbound application programming interfaces (APIs), network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications, and presents the key building blocks of an SDN infrastructure using a bottom-up, layered approach.
Abstract: The Internet has led to the creation of a digital society, where (almost) everything is connected and is accessible from anywhere. However, despite their widespread adoption, traditional IP networks are complex and very hard to manage. It is both difficult to configure the network according to predefined policies, and to reconfigure it to respond to faults, load, and changes. To make matters even more difficult, current networks are also vertically integrated: the control and data planes are bundled together. Software-defined networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns, introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper, we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound application programming interfaces (APIs), network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms—with a focus on aspects such as resiliency, scalability, performance, security, and dependability—as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

3,589 citations

Journal ArticleDOI
TL;DR: A survey of MCC is given, which helps general readers have an overview of the MCC including the definition, architecture, and applications and the issues, existing solutions, and approaches are presented.
Abstract: Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) discussed in mobile computing. This paper gives a survey of MCC, which helps general readers have an overview of the MCC including the definition, architecture, and applications. The issues, existing solutions, and approaches are presented. In addition, the future research directions of MCC are discussed. Copyright © 2011 John Wiley & Sons, Ltd.

2,259 citations

Posted Content
TL;DR: Software-Defined Networking (SDN) as discussed by the authors is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network.
Abstract: Software-Defined Networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound APIs, network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms -- with a focus on aspects such as resiliency, scalability, performance, security and dependability -- as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

1,968 citations