Distributed Hybrid Simulation of the Internet of Things and Smart Territories

This paper deals with the use of hybrid simulation to build and compose heterogeneous simulation scenarios that can be proficiently exploited to model and represent the Internet of Things (IoT). Hybrid simulation is a methodology that combines multiple modalities of modeling/simulation. Complex scenarios are decomposed into simpler ones, each one being simulated through a specific simulation strategy. All these simulation building blocks are then synchronized and coordinated. This simulation methodology is an ideal one to represent IoT setups, which are usually very demanding, due to the heterogeneity of possible scenarios arising from the massive deployment of an enormous amount of sensors and devices. We present a use case concerned with the distributed simulation of smart territories, a novel view of decentralized geographical spaces that, thanks to the use of IoT, builds ICT services to manage resources in a way that is sustainable and not harmful to the environment. Three different simulation models are combined together, namely, an adaptive agent-based parallel and distributed simulator, an OMNeT++ based discrete event simulator and a script-language simulator based on MATLAB. Results from a performance analysis confirm the viability of using hybrid simulation to model complex IoT scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487

Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any "thing" we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring application

JAG: Reliable and Predictable Wireless Agreement under External Radio Interference

Wireless low-power transceivers used in sensor networks typically operate in unlicensed frequency bands that are subject to external radio interference caused by devices transmitting at much higher power.communication protocols should therefore be designed to be robust against such interference. A critical building block of many protocols at all layers is agreement on a piece of information among a set of nodes. At the MAC layer, nodes may need to agree on a new time slot or frequency channel, at the application layer nodes may need to agree on handing over a leader role from one node to another. Message loss caused by interference may break agreement in two different ways: none of the nodes uses the new information (time slot, channel, leader) and sticks with the previous assignment, or-even worse-some nodes use the new information and some do not. This may lead to reduced performance or failures. In this paper, we investigate the problem of agreement under external radio interference and point out the limitations of traditional message-based approaches. We propose JAG, a novel protocol that uses jamming instead of message transmissions to make sure that two neighbouring nodes agree, and show that it outperforms message-based approaches in terms of agreement probability, energy consumption, and time-to-completion. We further show that JAG can be used to obtain performance guarantees and meet the requirements of applications with real-time constraints.CONETReSens

Shared versus distributed memory multiprocessors

The question of whether multiprocessors should have shared or distributed memory has attracted a great deal of attention. Some researchers argue strongly for building distributed memory machines, while others argue just as strongly for programming shared memory multiprocessors. A great deal of research is underway on both types of parallel systems. Special emphasis is placed on systems with a very large number of processors for computation intensive tasks and considers research and implementation trends. It appears that the two types of systems will likely converge to a common form for large scale multiprocessors

AnonPri: A Secure Anonymous Private Authentication Protocol for RFID Systems

Privacy preservation in RFID systems is a very important issue in modern day world. Privacy activists have been worried about the invasion of user privacy while using various RFID systems and services. Hence, significant efforts have been made to design RFID systems that preserve users\u27 privacy. Majority of the privacy preserving protocols for RFID systems require the reader to search all tags in the system in order to identify a single RFID tag which not efficient for large scale systems. In order to achieve high-speed authentication in large-scale RFID systems, researchers propose tree-based approaches, in which any pair of tags share a number of key components. Another technique is to perform group-based authentication that improves the tradeoff between scalability and privacy by dividing the tags into a number of groups. This novel authentication scheme ensures privacy of the tags. However, the level of privacy provided by the scheme decreases as more and more tags are compromised. To address this issue, in this paper, we propose a group based anonymous private authentication protocol (AnonPri) that provides higher level of privacy than the above mentioned group based scheme and achieves better efficiency (in terms of providing privacy) than the approaches that prompt the reader to perform an exhaustive search. Our protocol guarantees that the adversary cannot link the tag responses even if she can learn the identifier of the tags. Our evaluation results demonstrates that the level of privacy provided by AnonPri is higher than that of the group based authentication technique

AnonPri: A Secure Anonymous Private Authentication Protocol for RFID Systems

Privacy preservation in RFID systems is a very important issue in modern day world. Privacy activists have been worried about the invasion of user privacy while using various RFID systems and services. Hence, significant efforts have been made to design RFID systems that preserve users\u27 privacy. Majority of the privacy preserving protocols for RFID systems require the reader to search all tags in the system in order to identify a single RFID tag which not efficient for large scale systems. In order to achieve high-speed authentication in large-scale RFID systems, researchers propose tree-based approaches, in which any pair of tags share a number of key components. Another technique is to perform group-based authentication that improves the tradeoff between scalability and privacy by dividing the tags into a number of groups. This novel authentication scheme ensures privacy of the tags. However, the level of privacy provided by the scheme decreases as more and more tags are compromised. To address this issue, in this paper, we propose a group based anonymous private authentication protocol (AnonPri) that provides higher level of privacy than the above mentioned group based scheme and achieves better efficiency (in terms of providing privacy) than the approaches that prompt the reader to perform an exhaustive search. Our protocol guarantees that the adversary cannot link the tag responses even if she can learn the identifier of the tags. Our evaluation results demonstrates that the level of privacy provided by AnonPri is higher than that of the group based authentication technique

Noise in neurons is message-dependent

Neuronal responses are conspicuously variable. We focus on one particular aspect of that variability: the precision of action potential timing. We show that for common models of noisy spike generation, elementary considerations imply that such variability is a function of the input, and can be made arbitrarily large or small by a suitable choice of inputs. Our considerations are expected to extend to virtually any mechanism of spike generation, and we illustrate them with data from the visual pathway. Thus, a simplification usually made in the application of information theory to neural processing is violated: noise {\sl is not independent of the message}. However, we also show the existence of {\sl error-correcting} topologies, which can achieve better timing reliability than their components.Comment: 6 pages,6 figures. Proceedings of the National Academy of Sciences (in press