KLAIM: A Kernel Language for Agents Interaction and Mobility

We investigate the issue of designing a kernel programming language for mobile computing and describe KLAIM, a language that supports a programming paradigm where processes, like data, can be moved from one computing environment to another. The language consists of a core Linda with multiple tuple spaces and of a set of operators for building processes. KLAIM naturally supports programming with explicit localities. Localities are first-class data (they can be manipulated like any other data), but the language provides coordination mechanisms to control the interaction protocols among located processes. The formal operational semantics is useful for discussing the design of the language and provides guidelines for implementations. KLAIM is equipped with a type system that statically checks access rights violations of mobile agents. Types are used to describe the intentions (read, write, execute, etc.) of processes in relation to the various localities. The type system is used to determine the operations that processes want to perform at each locality, and to check whether they comply with the declared intentions and whether they have the necessary rights to perform the intended operations at the specific localities. Via a series of examples, we show that many mobile code programming paradigms can be naturally implemented in our kernel language. We also present a prototype implementaton of KLAIM in Java

Mobile Applications in X-KLAIM

Networking has turned computers from isolated data processors into powerful communication and elaboration devices, called global computers; an illustrative example is the World–Wide Web. Global computers are rapidly evolving towards programmability. The new scenario has called for new programming languages and paradigms centered around the notions of mobility and location awareness. In this paper, we briefly present X-KLAIM, an experimental programming language for global computers, and show a few programming examples

Maximum likelihood localization: When does it fail?

Maximum likelihood is a criterion often used to derive localization algorithms. In particular, in this paper we focus on a distance-based algorithm for the localization of nodes in static wireless networks. Assuming that Ultra Wide Band (UWB) signals are used for inter-node communications, we investigate the ill-conditioning of the Two-Stage Maximum-Likelihood (TSML) Time of Arrival (ToA) localization algorithm as the Anchor Nodes (ANs) positions change. We analytically derive novel lower and upper bounds for the localization error and we evaluate them in some localization scenarios as functions of the ANs' positions. We show that particular ANs' configurations intrinsically lead to ill-conditioning of the localization problem, making the TSML-ToA inapplicable. For comparison purposes, we also show, through some examples, that a Particle Swarm Optimization (PSO)-based algorithm guarantees accurate positioning also when the localization problem embedded in the TSML-ToA algorithm is ill-conditioned

Investigating the Resilience of Unstructured Supernode Networks

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Low-complexity UWB-based collision avoidance system for automated guided vehicles

This paper describes a low-complexity collision avoidance system for automated guided vehicles (AGVs) based on active ultra-wide band (UWB) modules. In particular, we consider an industrial warehouse where all the AGVs and target nodes (TNs) (e.g., people) are equipped with active UWB modules. A communication session between a pair of UWB modules permits the exchange of information and the estimation of the distance between them. The UWB module positioned on an AGV is connected to an on-board computer; whenever the UWB module on an AGV receives a message from a TN, it communicates all the received data to the on-board computer that can decide to stop the AGV if the range estimate is below a given threshold. This prevents undesired collisions between the AGV and the TN. In this paper, we present the experimental results of the proposed collision avoidance system obtained using the UWB modules, PulsON 410 ranging and communication modules (P410 RCMs), produced by Time Domain

Low-Complexity One-Dimensional Edge Detection in Wireless Sensor Networks

In various wireless sensor network applications, it is of interest to monitor the perimeter of an area of interest. For example, one may need to check if there is a leakage of a dangerous substance. In this paper, we model this as a problem of one-dimensional edge detection, that is, detection of a spatially nonconstant one-dimensional phenomenon, observed by sensors which communicate to an access point (AP) through (possibly noisy) communication links. Two possible quantization strategies are considered at the sensors: (i) binary quantization and (ii) absence of quantization. We first derive the minimum mean square error (MMSE) detection algorithm at the AP. Then, we propose a simplified (suboptimum) detection algorithm, with reduced computational complexity. Noisy communication links are modeled either as (i) binary symmetric channels (BSCs) or (ii) channels with additive white Gaussian noise (AWGN)

A novel approach for energy- and memory-efficient data loss prevention to support Internet of Things networks

Internet of Things integrates various technologies, including wireless sensor networks, edge computing, and cloud computing, to support a wide range of applications such as environmental monitoring and disaster surveillance. In these types of applications, IoT devices operate using limited resources in terms of battery, communication bandwidth, processing, and memory capacities. In this context, load balancing, fault tolerance, and energy and memory efficiency are among the most important issues related to data dissemination in IoT networks. In order to successfully cope with the abovementioned issues, two main approaches—data-centric storage and distributed data storage—have been proposed in the literature. Both approaches suffer from data loss due to memory and/or energy depletion in the storage nodes. Even though several techniques have been proposed so far to overcome the abovementioned problems, the proposed solutions typically focus on one issue at a time. In this article, we propose a cross-layer optimization approach to increase memory and energy efficiency as well as support load balancing. The optimization problem is a mixed-integer nonlinear programming problem, and we solve it using a genetic algorithm. Moreover, we integrate the data-centric storage features into distributed data storage mechanisms and present a novel heuristic approach, denoted as Collaborative Memory and Energy Management, to solve the underlying optimization problem. We also propose analytical and simulation frameworks for performance evaluation. Our results show that the proposed method outperforms the existing approaches in various IoT scenarios

MHD simulations of three-dimensional Resistive Reconnection in a cylindrical plasma column

Magnetic reconnection is a plasma phenomenon where a topological rearrangement of magnetic field lines with opposite polarity results in dissipation of magnetic energy into heat, kinetic energy and particle acceleration. Such a phenomenon is considered as an efficient mechanism for energy release in laboratory and astrophysical plasmas. An important question is how to make the process fast enough to account for observed explosive energy releases. The classical model for steady state magnetic reconnection predicts reconnection times scaling as $S^{1/2}$ (where $S$ is the Lundquist number) and yields times scales several order of magnitude larger than the observed ones. Earlier two-dimensional MHD simulations showed that for large Lundquist number the reconnection time becomes independent of $S$ ("fast reconnection" regime) due to the presence of the secondary tearing instability that takes place for $S \gtrsim 1 \times 10^4$. We report on our 3D MHD simulations of magnetic reconnection in a magnetically confined cylindrical plasma column under either a pressure balanced or a force-free equilibrium and compare the results with 2D simulations of a circular current sheet. We find that the 3D instabilities acting on these configurations result in a fragmentation of the initial current sheet in small filaments, leading to enhanced dissipation rate that becomes independent of the Lundquist number already at $S \simeq 1\times 10^3$.Comment: 11 pages, 11 figures, accepted for publication in MNRA

Tiles for Concurrent and Located Calculi

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