Browsing by Author "Rangarajan, Raghuraman"
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- Automated resource allocation for T-ResPublication . Gaur, Shashank; Rangarajan, Raghuraman; Tovar, EduardoThis paper presents a demo of an extension developed to support an existing programming abstraction for IoT: mTRes. mT-Res is an extension of the T-Res programming abstraction, which allows users to write applications using a web framework independent of resources. The paper describes an automated mechanism for allocate resources to such applications and adapt to changes in those resources.
- Bringing Context-awareness to wireless sensor networksPublication . Gaur, Shashank; Rangarajan, Raghuraman; Tovar, Eduardo• Programming abstraction has been a major focus of research in WSN • With IoT, heterogeneous devices with different capabilities brings in new issues. • Essential features for systems to support these changes and user to write applications are as follwoing: • Abstraction, Mobility and Modularity
- Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid NetworkPublication . Loureiro, João; Rangarajan, Raghuraman; Tovar, EduardoXDense is a proposed wired mesh grid sensor network system tailored for scenarios that benefit from thousands of sensors per square meter. XDense has scalable network topology and protocols, customizable to application specifics, that enables complex feature extraction in realtime from observed phenomena by exploiting communication and distributed processing capabilities of such network topologies. XDense has been designed with closed-loop CPS applications like active flow control of aircraft wing surfaces in mind. It uses a plug-n-play architecture that allows dimensioning of application specific networks. In this paper, we evaluate the performance of XDense in a fluid dynamic application scenario. With experiments on feature detection and realtime scenarios, we demonstrate the potential of the architecture and discuss practical implementation issues.
- Experiments with XDense: A Dense Grid Sensor Network for Distributed Feature ExtractionPublication . Loureiro, João; Rangarajan, Raghuraman; Tovar, EduardoWe propose XDense, a wired mesh grid sensor network architecture tailored for scenarios that benefit from thousands of sensors per square meter. XDense has a scalable network topology and protocol, customizable to application specifics, that enables complex feature extraction in realtime from the observed phenomena by exploiting the communication and distributed processing capabilities of such network topologies. We detail XDense’s node and network architecture, protocols, and principles of operation. To demonstrate XDense’s potentials, we evaluate it’s response time, data traffic metrics and accuracy in the context of detecting fluid dynamic features.
- Extending T-Res with mobility for context-aware IoTPublication . Gaur, Shashank; Rangarajan, Raghuraman; Tovar, EduardoIn this paper, we develop a framework for building context-aware applications in IoT. The IoT paradigm brings in various new issues such as macroprogramming, interoperability for heterogeneous devices and in-network processing. Solutions to these issues can enable IoT to support all available resources in an efficient manner and also enable ease of access for users. In addition, this can help in collecting useful information about the user and the system, such as context. Understanding context of different entities and taking actions accordingly will enable a context-aware IoT. However, no complete solution is available to this issue of achieving context-awareness in IoT. In this paper, as a step towards a context-aware framework, we present a mobilityenabling extension of the T-Res programming abstraction. We implement a web-based framework for users to write contextaware applications. We then describe and implement an automated mechanism for deploying these applications.
- Extensive Analysis of a Real-Time Dense Wired Sensor Network Based on Traffic ShapingPublication . Loureiro, João; Rangarajan, Raghuraman; Nikolic, Borislav; Soares Indrusiak, Leandro; Tovar, EduardoXDense is a novel wired 2D mesh grid sensor network system for application scenarios that benefit from densely deployed sensing (e.g., thousands of sensors per square meter). It was conceived for cyber-physical systems that require real-time sensing and actuation, like active flow control on aircraft wing surfaces. XDense communication and distributed processing capabilities are designed to enable complex feature extraction within bounded time and in a responsive manner. In this article, we tackle the issue of deterministic behavior of XDense. We present a methodology that uses traffic-shaping heuristics to guarantee bounded communication delays and the fulfillment of memory requirements. We evaluate the model for varied network configurations and workload, and present a comparative performance analysis in terms of link utilization, queue size, and execution time. With the proposed traffic-shaping heuristics, we endow XDense with the capabilities required for real-time applications
- Feature Extraction in Densely Sensed Environments: Extensions to Multiple Broadcast DomainsPublication . Vahabi, Maryam; Gupta, Vikram; Albano, Michele; Rangarajan, Raghuraman; Tovar, EduardoThe vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with a low overhead. In this article, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.
- A module for the XDense architecture in ns-3Publication . Loureiro, João; Albano, Michele; Cerqueira, Tiago; Rangarajan, Raghuraman; Tovar, EduardoThe acquisition of data regarding some dynamic phenomena can require extremely dense deployments of sensors and high sampling rates. We propose XDense [1], a wired mesh grid sensor network architecture (see Figure 1a) tailored for scenarios that benefit from thousands of sensors per square meter. XDense has scalable network topology and it enables complex feature extraction in real-time from the observed phenomena, by exploiting distributed processing capabilities and inter-node communication, the latter being represented in Figure 1b.
- Real-Time Dense Wired Sensor Network Based on Traffic ShapingPublication . Loureiro, João; Rangarajan, Raghuraman; Nikolic, Borislav; Indrusiak, Leandro; Tovar, EduardoXDense is a novel wired 2D-mesh grid sensor network system for application scenarios that benefit from densely deployed sensing (e.g. thousands of sensors per square meter). It was conceived for closed-loop cyber-physical systems (CPS) that require real-time actuation, like active flow control (AFC) on aircraft wing surfaces. XDense communication and distributed processing capabilities are designed such that they enable to extract complex features within bounded time and in a responsive manner. In this paper we tackle the issue of deterministic behavior of XDense. We present a methodology that uses traffic shaping heuristics to guarantee bounded communication delays and the fulfillment of memory requirements. We evaluate the model for varied network configurations and workload, and demonstrate the effectiveness of running real-time applications supported on XDense.
- Simulation Module and Tools for XDense Sensor NetworkPublication . Loureiro, João; Santos, Pedro; Rangarajan, Raghuraman; Tovar, EduardoWe present a NS-3 module developed for wired 2D mesh grid sensor network systems, that resemble Network-on-Chip architectures. It has been designed to enable complex feature extraction from sensed data in realtime with distributed processing. We provide the design specifications, communication and processing delay models and a high level system model for XDense using NS-3. We validate our module by comparing its performance with a hardware implementation.