Abstract: We study the important problem of tracking moving
targets in wireless sensor networks. We try to overcome the
limitations of standard state of the art tracking methods based on
continuous location tracking, i.e. the high energy dissipation and
communication overhead imposed by the active participation of
sensors in the tracking process and the low scalability, especially
in sparse networks. Instead, our approach uses sensors in a
passive way: they only record and judiciously spread information
about observed target presence in their vicinity; this information
is then used by the (powerful) tracking agent to locate the target
by just following the traces left at sensors. Our protocol is greedy,
local, distributed, energy efficient and very successful, in the
sense that (as shown by extensive simulations) the tracking agent
manages to quickly locate and follow the target; also, we achieve
good trade-offs between the energy dissipation and latency.
Abstract: Human mobility monitoring and respective traces are important for understanding human behavior, respective patterns and associated context. Such data can be potentially used in business intelligence-oriented systems, for providing added value commercial services or insight to internal enterprise procedures. At the same time, smartphones are rapidly becoming an indispensable tool for our everyday life, while their advanced networking and computing capabilities are increasingly being used as enablers for new applications. We discuss here a system using a stable computing and networking infrastructure along with smartphone applications, based on commodity technologies, meant to be deployed rapidly and provide analytics almost in real-time for such aspects. We also discuss a related scenario in order to provide insight as to where our system could be used. We briefly present the deployment of our system in two settings, an office building and a research exhibition event, along with our experiences. Our findings show that it is feasible and efficient to deploy and operate our system relatively easy, producing meaningful data.
Abstract: This paper presents results from the IST Phosphorus project that studies and implements an optical Grid test-bed. A significant part of this project addresses scheduling and routing algorithms and dimensioning problems of optical grids. Given the high costs involved in setting up actual hardware implementations, simulations are a viable alternative. In this paper we present an initial study which proposes models that reflect real-world grid application traffic characteristics, appropriate for simulation purposes. We detail several such models and the corresponding process to extract the model parameters from real grid log traces, and verify that synthetically generated jobs provide a realistic approximation of the real-world grid job submission process.
Abstract: In this work, we explore context-aware application scenarios that become possible utilizing semantically-rich information derived from real-world mobility and presence traces. Traces produced by people carrying personal mobile devices, capturing social and contextual interactions, serve as enables for Future Internet applications. We discuss the fundamental concepts, technical issues and related research challenges. We propose a reference architecture for setting up a system that collects such traces in a Smart City environment. We present the algorithms used to process the traces and infer interactions and interests for the observed populations. We conduct two 3-day trial deployments: one in an office environment and the other in the context of a Smart Conference application. We discuss our findings regarding the system's capability to track interactions and the overall efficacy of the application.
Abstract: In this paper, we describe the implementation of
applying and testing the ”Lightweight Target Tracking using
Passive Traces algorithm” [1] on a FIRE wireless sensors testbed
located in the Theoretical Computer Science/Sensors Lab in
Geneva, Switzerland. We provide information about the hardware
installation and configuration, the changes we did to the
algorithm to adapt it to a real testbed as well as the tools we
implemented to operate the network and receive feedback from
the algorithm’s operation. Finally, we discuss the performance
evaluation findings of our implementation.
Abstract: Wireless sensor network research usually focuses on the reliable and efficient collection of data. Here, we address the next step in the traces lifetime: we aim at investigating and evaluating, by qualitative and quantitative means, data repositories of already collected measurements. We propose the use of a set of new metrics, which enable reliable evaluation of algorithms using traces (both in average cases and "stressful" setups) removing the need for running algorithms in a real testbed, at least in the development stage.
Abstract: Wireless sensor network research usually focuses on the reliable and efficient collection of data. In
this paper we focus on the next step in the lifetime of traces: we aim at investigating and evaluating, by
qualitative and quantitative means, data repositories of already collected measurements. Concerning the
collected datasets, several important topics arise like the need of exchanging traces between researchers
using a common representation of the traces and the need for common classi cation of the traces based on
a commonly-agreed set of statistical characteristics for in retrospect utilization. In order to qualitatively
address these issues, we propose the use of a novel set of metrics focusing on the in-network data aggregation
problem class. These metrics enable reliable evaluation of algorithms using the same benchmark traces (both
in average cases and \stressful" setups) removing the need for running algorithms in a real testbed, at least
in the initial development stage. We present the results of our research as a rst approach for addressing this
problem, and in order to con rm our method, we characterized several traces with the proposed metrics.
We validate the metrics by predicting the performance of three data-aggregation schemes using the available
traces and checking the results by actually running the algorithms
Abstract: Recent activity in the field of Internet-of-Things experimentation has focused on the federation of discrete testbeds, thus placing less effort in the integration of other related technologies, such as smartphones; also, while it is gradually moving to more application-oriented paths, such as urban settings, it has not dealt in large with applications having social networking features. We argue here that current IoT infrastructure, testbeds and related software technologies should be used in such a context, capturing real-world human mobility and social networking interactions, for use in evaluating and fine-tuning realistic mobility models and designing human-centric applications. We discuss a system for producing traces for a new generation of human-centric applications, utilizing technologies such as Bluetooth and focusing on human interactions. We describe the architecture for this system and the respective implementation details presenting two distinct deployments; one in an office environment and another in an exhibition/conference event (FET'11, The European Future Technologies Conference and Exhibition) with 103 active participants combined, thus covering two popular scenarios for human centric applications. Our system provides online, almost real-time, feedback and statistics and its implementation allows for rapid and robust deployment, utilizing mainstream technologies and components.
