Programming Wireless Sensor Networks with Logical Neighborhoods: A Road Tunnel Use Case

Wireless sensor networks (WSNs) involving actuation are increasingly envisioned in a range of fields [1]. Among these, there is considerable interest in leveraging off WSNs to improve safety in road tunnels [4]. Researchers are envi- sioning tunnels equipped with WSN nodes that gather physi- cal readings such as temperature and light, monitor the struc- tural integrity of the tunnel, and sense the presence of vehi- cles to detect a possible traffic congestion. Based on sensed data, the system operates a variety of devices, such as ven- tilation fans inside the tunnel, and traffic lights at the en- trances. For instance, when a sensor detects the presence of a fire in a sector, the fans in the same sector are activated, and the traffic lights are turned red to prevent further vehicles from entering the tunnel

Pervasive Games in a Mote-Enabled Virtual World Using Tuple Space Middleware

Pervasive games are a new and exciting field where the user experience benefits from the blending of real and virtual elements. Players are no longer confined to computer screens. Rather, interactions with devices embedded within the real world and physical movements become an integral part of the gaming experience. Several prototypes of pervasive games have been proposed by both industry and academia. However, in such games the issues arising from the integration of players and real world, the management of the context surrounding the players, and the need for communication and distributed coordination are often addressed in an ad-hoc fashion. Therefore, the underlying software fabric is often not reusable, ultimately slowing down the diffusion of pervasive games. In this paper we describe the design and implementation of a pervasive game on top of TinyLIME, a middleware system supporting data sharing among mobile and embedded devices. By illustrating the design of a pervasive game we developed, we argue concretely that the programming abstractions supported by TinyLIME greatly simplify the data and context management characteristics of pervasive games, and provide an effective and reusable building block for their development. TinyLIME was originally designed to support applications where mobile users collect data from sensors scattered in the physical environment. We build upon this capability to put forth a second contribution, namely, the use of wireless sensor devices (or motes) as a computing platform for pervasive games. Besides reporting physical data for the sake of the game, we use motes to store information relevant to the game plot, e.g., virtual objects. Motes are typically very small in size, and therefore can be hidden in the environment, enhancing the sense of immersion in a virtual world. To the best of our knowledge, this original use of wireless sensor devices is novel in the scientific and gaming literature. Furthermore, it is naturally supported by TinyLIME, yielding a unified programming abstraction that spans the heterogeneous gaming platform we propose

de Sitter Vacua, Renormalization and Locality

We analyze the renormalization properties of quantum field theories in de Sitter space and show that only two of the maximally invariant vacuum states of free fields lead to consistent perturbation expansions. One is the Euclidean vacuum, and the other can be viewed as an analytic continuation of Euclidean functional integrals on $RP^d$. The corresponding Lorentzian manifold is the future half of global de Sitter space with boundary conditions on fields at the origin of time. We argue that the perturbation series in this case has divergences at the origin, which render the future evolution of the system indeterminate without a better understanding of high energy physics.Comment: JHEP Latex, 13 pages, v2. references adde

Relation Between Einstein And Quantum Field Equations

We show that there exists a choice of scalar field modes, such that the evolution of the quantum field in the zero-mass and large-mass limits is consistent with the Einstein equations for the background geometry. This choice of modes is also consistent with zero production of these particles and thus corresponds to a preferred vacuum state preserved by the evolution. In the zero-mass limit, we find that the quantum field equation implies the Einstein equation for the scale factor of a radiation-dominated universe; in the large-mass case, it implies the corresponding Einstein equation for a matter-dominated universe. Conversely, if the classical radiation-dominated or matter-dominated Einstein equations hold, there is no production of scalar particles in the zero and large mass limits, respectively. The suppression of particle production in the large mass limit is over and above the expected suppression at large mass. Our results hold for a certain class of conformally ultrastatic background geometries and therefore generalize previous results by one of us for spatially flat Robertson-Walker background geometries. In these geometries, we find that the temporal part of the graviton equations reduces to the temporal equation for a massless minimally coupled scalar field, and therefore the results for massless particle production hold also for gravitons. Within the class of modes we study, we also find that the requirement of zero production of massless scalar particles is not consistent with a non-zero cosmological constant. Possible implications are discussed.Comment: Latex, 24 pages. Minor changes in text from original versio

The Case for Approximate Intermittent Computing

We present the concept of approximate intermittent computing and concretely demonstrate its application. Intermittent computations stem from the erratic energy patterns caused by energy harvesting: computations unpredictably terminate whenever energy is insufficient and the application state is lost. Existing solutions maintain equivalence to continuous executions by creating persistent state on non-volatile memory, enabling stateful computations to cross power failures. The performance penalty is massive: system throughput reduces while energy consumption increases. In contrast, approximate intermittent computations trade the accuracy of the results for sparing the entire overhead to maintain equivalence to a continuous execution. This is possible as we use approximation to limit the extent of stateful computations to the single power cycle, enabling the system to completely shift the energy budget for managing persistent state to useful computations towards an immediate approximate result. To this end, we effectively reverse the regular formulation of approximate computing problems. First, we apply approximate intermittent computing to human activity recognition. We design an anytime variation of support vector machines able to improve the accuracy of the classification as energy is available. We build a hw/sw prototype using kinetic energy and show a 7x improvement in system throughput compared to state-of-the-art system support for intermittent computing, while retaining 83% accuracy in a setting where the best attainable accuracy is 88%. Next, we apply approximate intermittent computing in a sharply different scenario, that is, embedded image processing, using loop perforation. Using a different hw/sw prototype we build and diverse energy traces, we show a 5x improvement in system throughput compared to state-of-the-art system support for intermittent computing, while providing an equivalent output in 84% of the cases

Infrared Behavior of the Pressure in gϕ3g \phi^3 Theory Reexamined

We reinvestigate the infrared behavior of the pressure in the $g \phi^3$ scalar theory in six dimensions. This problem was first studied by Almeida and Frenkel and more recently by Carrington et al., that certified their results under certain approximations. We employ an alternative technique, instead of the approximation methods necessary to truncate the Schwinger-Dyson equations, often considered to calculate the pressure nonperturbatively. A daisy-type sum, implemented through the modified self-consistent resummation (MSCR), is enough to take care of the infrared divergences ensuring the finiteness of the pressure.Comment: Revtex4, 7 pages, 1 figur

Design and compilation of an object-oriented macroprogramming language for wireless sensor networks

open5siWireless sensor network (WSN) programming is still largely performed by experts in a node-centric way using low-level languages such as C. Although numerous higher-level abstractions exist, each simplifying a specific aspect of distributed programming, real applications often require to combine multiple abstractions into a single program. Using current programming frameworks, this represents a difficult task. In previous work, we therefore defined a conceptual framework that facilitates abstraction composition by defining sound compositional rules among few fundamental abstraction categories. The framework is extensible: programmers can add new abstractions within the boundaries determined by the compositional rules. In this paper we describe the design of a language - called MPL - that instantiates this conceptual framework. To support the extensible nature of the framework, the language is object-oriented, which allows programmers to add new abstractions by inheriting from existing classes that implement predefined interfaces. We modeled the syntax after Java, to make it more palatable to inexperienced embedded programmers. Compared to Java, we modified the language to enable efficient execution on WSN devices. We designed and implemented a compiler that translates MPL language into executable C code, which spares the overhead of a virtual machine. By comparing MPL implementations against functionally-equivalent Contiki/C implementations of several benchmark applications, we determined that the performance overhead of MPL is limited, and yet the programming task is simplified.openOppermann, Felix Jonathan; Römer, Kay; Mottola, Luca; Picco, Gian Pietro; Gaglione, AndreaOppermann, Felix Jonathan; Römer, Kay; Mottola, Luca; Picco, Gian Pietro; Gaglione, Andre

Hummingbird: An Energy-Efficient GPS Receiver for Small Satellites

Global positioning system (GPS) is the most widely adopted localization technique for satellites in low earth orbits (LEOs). To enable many state-of-the-art applications on satellites, the exact position of the satellites is necessary. With the increasing demand for small satellites, the need for a low-power GPS for satellites is also increasing. However, building low-power GPS receivers for small satellites poses significant challenges, mainly due to the high speeds (similar to 7.8 km/s) of satellites and low available energy. While duty cycling the receiver is a possible solution, the high relative Doppler shift among the GPS satellites and the small satellite contributes to an increase in Time to First Fix (TTFF), which negatively impacts energy consumption. Further, if the satellite tumbles, the GPS receiver may not be able to receive signals properly from the GPS satellites, thus leading to an even longer TTFF. In the worst case, the situation may result in no GPS fix due to disorientation of the receiver antenna. In this work, we elucidate the design of a low-cost, low-power GPS receiver for small satellites. We also propose an energy optimization algorithm to improve the TTFF. With the extensive evaluation of our GPS receiver on an operational nanosatellite, we show that up to 96.16% of energy savings can be achieved using our algorithm without significantly compromising (similar to 10 m) the positioning accuracy

AIM: Acoustic Inertial Measurement for Indoor Drone Localization and Tracking

We present Acoustic Inertial Measurement (AIM), a one-of-a-kind technique for indoor drone localization and tracking. Indoor drone localization and tracking are arguably a crucial, yet unsolved challenge: in GPS-denied environments, existing approaches enjoy limited applicability, especially in Non-Line of Sight (NLoS), require extensive environment instrumentation, or demand considerable hardware/software changes on drones. In contrast, AIM exploits the acoustic characteristics of the drones to estimate their location and derive their motion, even in NLoS settings. We tame location estimation errors using a dedicated Kalman filter and the Interquartile Range rule (IQR). We implement AIM using an off-the-shelf microphone array and evaluate its performance with a commercial drone under varied settings. Results indicate that the mean localization error of AIM is 46% lower than commercial UWB-based systems in complex indoor scenarios, where state-of-the-art infrared systems would not even work because of NLoS settings. We further demonstrate that AIM can be extended to support indoor spaces with arbitrary ranges and layouts without loss of accuracy by deploying distributed microphone arrays

Quantum Diffeomorphisms and Conformal Symmetry

We analyze the constraints of general coordinate invariance for quantum theories possessing conformal symmetry in four dimensions. The character of these constraints simplifies enormously on the Einstein universe $R \times S^3$. The $SO(4,2)$ global conformal symmetry algebra of this space determines uniquely a finite shift in the Hamiltonian constraint from its classical value. In other words, the global Wheeler-De Witt equation is {\it modified} at the quantum level in a well-defined way in this case. We argue that the higher moments of $T^{00}$ should not be imposed on the physical states {\it a priori} either, but only the weaker condition $\langle \dot T^{00} \rangle = 0$. We present an explicit example of the quantization and diffeomorphism constraints on $R \times S^3$ for a free conformal scalar field.Comment: PlainTeX File, 37 page