1,900 research outputs found

    Efficient FFT Algorithms for Mobile Devices

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    Increased traffic on wireless communication infrastructure has exacerbated the limited availability of radio frequency ({RF}) resources. Spectrum sharing is a possible solution to this problem that requires devices equipped with Cognitive Radio ({CR}) capabilities. A widely employed technique to enable {CR} is real-time {RF} spectrum analysis by applying the Fast Fourier Transform ({FFT}). Today’s mobile devices actually provide enough computing resources to perform not only the {FFT} but also wireless communication functions and protocols by software according to the software-defined radios paradigm. In addition to that, the pervasive availability of mobile devices make them powerful computing platform for new services. This thesis studies the feasibility of using mobile devices as a novel spectrum sensing platform with focus on {FFT}-based spectrum sensing algorithms. We benchmark several open-source {FFT} libraries on an Android smartphone. We relate the efficiency of calculating the {FFT} to both algorithmic and implementation-related aspects. The benchmark results also show the clear potential of special {FFT} algorithms that are tailored for sparse spectrum detection

    High-Fidelity Spectrum Characterization with Low-Cost Sensors

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    With the increasing use of wireless technologies, we see a heavy use of the spectrum at certain frequencies whereas it is underutilized at other frequencies. We need to utilize the currently underutilized spectrum. Hence, a paradigm called Dynamic Spectrum Access arises. Dynamic Spectrum Access looks for opportunity to utilize this underutilized spectrum by allowing devices to opportunistically access spectrum that is not actively used. DSA, however, requires spectrum sensing and spectrum characterization across time, space, and frequency for opportunistic devices to know where to operate. Spectrum sensing is the process of collecting power level traces from the radio-frequency spectrum, whereas spectrum characterization determines how many transmitters occupy a given spectrum and what are their temporal and frequency characteristics. Traditional spectrum sensing and characterization is performed with expensive sensors, which renders the task economically-infeasible. Our project introduces a low-cost alternative, which is more mobile and cost efficient. A typical issue with low cost sensors is that the scans from the low-cost sensor are of lower quality compared to scans from a higher-cost alternative. In this end, we compare the characterizations of the spectrum from the low cost sensor to the high-cost sensor across time, frequency, and space. We conduct granularity, sensitivity,transmitter pattern, and mobility experiments to compare the scans of the two sensors in different scenarios. We analyze the two characterizations from the two sensors in a controlled setting to see if the scans of the two are comparable. From the mobility and granularity experiments, we observe that scans from the low-cost sensors are comparable to the scans from the high-cost sensors. However, as expected, we do see lower sensitivity in the low-cost sensor. Comparing the two scans will help us form a better picture of the kind of ii infrastructure we can build using the two sensors that is both economically feasible and can give us high-fidelity scans

    Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements

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    Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)

    Reconfigurable middleware architectures for large scale sensor networks

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    Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task reconfiguration and high-level object recomposition. Through the layered approach of SENSIX, the software developer creates a domain-specific sensing architecture by defining a customized task specification and utilizing object inheritance. In addition, SENSIX performs better at large scales (on the order of 1000 nodes or more) than other sensor network middleware which do not include such unified facilities for vertical integration

    Spectrum Sensing and Security Challenges and Solutions: Contemporary Affirmation of the Recent Literature

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    Cognitive radio (CR) has been recently proposed as a promising technology to improve spectrum utilization by enabling secondary access to unused licensed bands. A prerequisite to this secondary access is having no interference to the primary system. This requirement makes spectrum sensing a key function in cognitive radio systems. Among common spectrum sensing techniques, energy detection is an engaging method due to its simplicity and efficiency. However, the major disadvantage of energy detection is the hidden node problem, in which the sensing node cannot distinguish between an idle and a deeply faded or shadowed band. Cooperative spectrum sensing (CSS) which uses a distributed detection model has been considered to overcome that problem. On other dimension of this cooperative spectrum sensing, this is vulnerable to sensing data falsification attacks due to the distributed nature of cooperative spectrum sensing. As the goal of a sensing data falsification attack is to cause an incorrect decision on the presence/absence of a PU signal, malicious or compromised SUs may intentionally distort the measured RSSs and share them with other SUs. Then, the effect of erroneous sensing results propagates to the entire CRN. This type of attacks can be easily launched since the openness of programmable software defined radio (SDR) devices makes it easy for (malicious or compromised) SUs to access low layer protocol stacks, such as PHY and MAC. However, detecting such attacks is challenging due to the lack of coordination between PUs and SUs, and unpredictability in wireless channel signal propagation, thus calling for efficient mechanisms to protect CRNs. Here in this paper we attempt to perform contemporary affirmation of the recent literature of benchmarking strategies that enable the trusted and secure cooperative spectrum sensing among Cognitive Radios

    CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

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    After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges
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