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.

Collaborative Mobile Energy Awareness

Abstract: We have created a mobile energy measurement application and gathered energy measurement data from over 725,000 devices, running over 300,000 applications, in heterogeneous environments, and constructed models of what is normal in each context for each application. We have used this data to find energy abnormalities in the wild, and provide users of our application advice on how to deal with them. These abnormalities cannot be discovered in laboratory conditions due to the rich interaction of the smartphone and its operating environment. Employing a collaborative mobile energy-awareness application with thousands of users allows us to gather a large amount of data in a short time. Such a large and diverse dataset has helped us answer many research questions. Our work is the first collaborative approach in the area of mobile energy debugging. Information received from each device running our application improves the advice given to other users running the same applications. The author has developed a context data gathering hub for smartphones, discovered the need for a common API that unifies network connectivity, energy awareness, and user experience, and investigated the impact of mobile collaborative energy awareness applications, to find previously unknown energy bugs on smartphones, and to improve users’ knowledge of smartphone energy behavior.

A Gap Analysis of Low-Cost Outdoor Air Quality Sensor In-Field Calibration

Abstract: In recent years, interest in monitoring air quality has been growing. Traditional environmental monitoring stations are very expensive, both to acquire and to maintain, therefore their deployment is generally very sparse. This is a problem when trying to generate air quality maps with a fine spatial resolution. Given the general interest in air quality monitoring, low-cost air quality sensors have become an active area of research and development. Low-cost air quality sensors can be deployed at a finer level of granularity than traditional monitoring stations. Furthermore, they can be portable and mobile. Low-cost air quality sensors, however, present some challenges: they suffer from crosssensitivities between different ambient pollutants; they can be affected by external factors such as traffic, weather changes, and human behavior; and their accuracy degrades over time. Some promising machine learning approaches can help us obtain highly accurate measurements with low-cost air quality sensors. In this article, we present low-cost sensor technologies, and we survey and assess machine learning-based calibration techniques for their calibration. We conclude by presenting open questions and directions for future research.

Dessy: Search and Synchronization on the Move

Abstract: Current smartphones have a storage capacity of several gigabytes. More and more information is stored on mobile devices. To meet the challenge of information organization, we turn to desktop search. Users often possess multiple devices, and synchronize (subsets of) information between them. This makes file synchronization more important. This paper presents Dessy, a desktop search and synchronization framework for mobile devices. Dessy supports synchronization of search results, individual files, and directory trees. It allows finding and synchronizing files that reside on remote computers, or the Internet. The contributions of this paper include an energy usage evaluation of the system. Dessy is closely integrated with the Syxaw file synchronizer, which provides efficient file and metadata synchronization, optimizing network usage.

Toward Blue Skies: City-Scale Air Pollution Monitoring Using UAVs

Abstract: Dangers associated with poor air quality are driving deployments of air quality monitoring technology worldwide. Having a comprehensive understanding of the health effects of pollutants requires understanding both the distribution and dispersion of pollutants in the environment, but currently this information is highly difficult to capture. This article presents a vision for city-scale air pollution monitoring that uses unmanned aerial vehicles (UAVs) to complement current ground and infrastructure-based measurements with a vertical profile of pollutants. We highlight the key requirements and research challenges, demonstrate the benefits UAVs bring through measurements from an industrial and a residential location, and establish a research roadmap for the path forward.

Software-Defined Networking: A Comprehensive Survey

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.

A survey of mobile cloud computing: architecture, applications, and approaches

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.

Software-Defined Networking: A Comprehensive Survey

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.