TDMA-MAC shema težinskog grupiranja u VANET-u

In vehicle ad hoc network (VANET), the active safety messages, e.g. safety critical application (SCA) information, must be distributed timely by radio channels among vehicles to improve the driver safety. A weight clustering based TDMA-MAC scheme for VANET is presented in this paper. Considering the constrains of radio signal transmitting power in textit{Green Communication}, the vehicles (nodes) energy consumption in VANET is chosen as one important factor for cluster-head (CH) election, and entropy weight is calculated, which can reflect the subjective intention. For the clustering MAC scheme, each node in a cluster is allowed to communicate by borrowing the scheduling time slots that assigned to other nodes at an access probability. Simulation results reveal the values of access probability for which the network throughput and energy consumption under the weight clustering based MAC scheme yields the better performance compared to the region-based clustering MAC policy. Also, it has the lower average packet contention period, at the expense of a little longer average transmission time of SCA packet.U ad hoc mreži vozila (VANET), aktivne sigurnosne poruke, npr. informacije za sigurnosno kritične aplikacije, moraju biti distribuirane radijskim kanalom među vozilima na vrijeme, kako bi povećali sigurnost vozača. U ovom radu prikazana je TDMA-MAC shema VANET-a zasnovana na otežanom grupiranju. Razmatrajući ograničenja u snazi pri prijenosu radijskog signala u textit{Zelenim komunikacijama}, potrošnja energije u vozilima (čvorovi) odabrana je kao važan čimbenik za izbor voditelja grupe (CH), te se računa količina entropije, koja može odraziti subjektivnu namjeru. U svrhu MAC pristupa grupiranju, svakom čvoru grupe dozvoljena je komunikacija posudbom vremenskih intervala u rasporedu koji su pridruženi ostalim čvorovima s pridruženim vjerojatnostima pristupa.Simulacijski rezultati uz MAC shemu zasnovanu na otežanom grupiranju pokazuju bolje vrijednosti mrežne propusnosti i potrošnja energije, u odnosu na MAC sheme grupiranja zasnovane na regijama. Također, ovaj pristup ima niže prosječno vrijeme argumentacije paketa, na uštrb nešto dužeg prosječnog vremena prijenosa SCA paketa

A mechanized proof of loop freedom of the (untimed) AODV routing protocol

The Ad hoc On-demand Distance Vector (AODV) routing protocol allows the nodes in a Mobile Ad hoc Network (MANET) or a Wireless Mesh Network (WMN) to know where to forward data packets. Such a protocol is 'loop free' if it never leads to routing decisions that forward packets in circles. This paper describes the mechanization of an existing pen-and-paper proof of loop freedom of AODV in the interactive theorem prover Isabelle/HOL. The mechanization relies on a novel compositional approach for lifting invariants to networks of nodes. We exploit the mechanization to analyse several improvements of AODV and show that Isabelle/HOL can re-establish most proof obligations automatically and identify exactly the steps that are no longer valid.Comment: The Isabelle/HOL source files, and a full proof document, are available in the Archive of Formal Proofs, at http://afp.sourceforge.net/entries/AODV.shtm

Analysis of a Cooperative Strategy for a Large Decentralized Wireless Network

This paper investigates the benefits of cooperation and proposes a relay activation strategy for a large wireless network with multiple transmitters. In this framework, some nodes cooperate with a nearby node that acts as a relay, using the decode-and-forward protocol, and others use direct transmission. The network is modeled as an independently marked Poisson point process and the source nodes may choose their relays from the set of inactive nodes. Although cooperation can potentially lead to significant improvements in the performance of a communication pair, relaying causes additional interference in the network, increasing the average noise that other nodes see. We investigate how source nodes should balance cooperation vs. interference to obtain reliable transmissions, and for this purpose we study and optimize a relay activation strategy with respect to the outage probability. Surprisingly, in the high reliability regime, the optimized strategy consists on the activation of all the relays or none at all, depending on network parameters. We provide a simple closed-form expression that indicates when the relays should be active, and we introduce closed form expressions that quantify the performance gains of this scheme with respect to a network that only uses direct transmission.Comment: Updated version. To appear in IEEE Transactions on Networkin

Scoping study to identify potential circular economy actions, priority sectors, material flows and value chains

The circular economy is rapidly rising up political and business agendas. In contrast to today’s largely linear, ‘take-make-use-dispose’ economy, a circular economy represents a development strategy that enables economic growth while aiming to optimise the chain of consumption of biological and technical materials. A deep transformation of production chains and consumption patterns is envisaged to keep materials circulating in the economy for longer, re-designing industrial systems and encouraging cascading use of materials and waste. Although there are some elements of circularity such as recycling and composting in the linear economy (see Figure E1) where progress needs to be maintained, a circular economy goes beyond the pursuit of waste prevention and waste reduction to inspire technological, organisational and social innovation across and within value chains (see Figure E2). There are already several policies in place and activities underway that support a circular economy; however there remain a range of untapped opportunities, costs to be avoided and obstacles to be addressed in order to accelerate the move towards a circular economy in the EU. Against this backdrop, the European Commission (DG Environment) launched a Scoping study to identify potential circular economy actions, priority sectors, material flows & value chains. The study was carried out by the Policy Studies Institute (PSI), Institute for European Environmental Policy (IEEP), BIO and Ecologic Institute between November 2013 and July 2014. The aim of the study was to provide an initial scoping assessment of potential priorities and policy options to support the transition to a circular economy in the EU. The study reviewed existing literature, identified potential priority areas for action where accelerating the circular economy would be beneficial and where EU policy has a particular role to play, and developed policy options for consideration across a range of areas

The Impact of Digital Technologies and Sustainable Practices on Circular Supply Chain Management

Background: This study investigates how firms can enhance the functionality of their circular supply chains (CSCs) by adopting a portfolio of sustainable practices as well as digital technologies to increase performance. It analyzes the benefits that firms can obtain when investing in specific technologies to boost the impact of technologies and sustainable practices on CSCs, and further increase performance. Methods: We test several hypotheses by using structural equation modeling as well as multi-group analysis to verify whether CSCs can be achieved through sustainable practices and technologies and improve the firms' performance. Results: The empirical results partially support the research hypotheses. While the main research hypotheses are fully supported, the analysis of single digital technologies reveals that only a few solutions can contribute to both the management and the improvement of the CSC. Conclusions: Our findings demonstrate that the identification of green suppliers and ad hoc environmental regulations, combined with attention to the origin and provenance of raw materials, can promote a CSC. Moreover, transportation management systems (TMS) and the internet of things (IoT) are efficient technologies for managing transportation and product flow in the CSC. Furthermore, machine learning (ML) is effective in making positive green decisions, and 3D printing can extend product life