Search results for "Network optimization"
showing 6 items of 6 documents
The Network Balance Realized by Routing Organization System
2011
In the presented paper, we propose to exploit routing organization for the purpose of managing network resources. According to our assumptions, we have the same quantity of materials, objects, tokens, tools etc. at our disposal in every node of the network. During network operation we must distribute resources between these nodes. It should be carried out as instantaneously and as economically as possible. Multi-Agent Systems are also used to deal with this kind of tasks and the centralised algorithms presented in this paper are to be used to measure the efficiency of the distributed MAS solution. From the logistical point of view, we have a sequence of stages with different states of token…
Discovery privacy threats via device de-anonymization in LoRaWAN
2021
LoRaWAN (Long Range WAN) is one of the well-known emerging technologies for the Internet of Things (IoT). Many IoT applications involve simple devices that transmit their data toward network gateways or access points that, in their turn, redirect data to application servers. While several security issues have been addressed in the LoRaWAN specification v1.1, there are still some aspects that may undermine privacy and security of the interconnected IoT devices. In this paper, we tackle a privacy aspect related to LoRaWAN device identity. The proposed approach, by monitoring the network traffic in LoRaWAN, is able to derive, in a probabilistic way, the unique identifier of the IoT device from…
Predicting lorawan behavior. How machine learning can help
2020
Large scale deployments of Internet of Things (IoT) networks are becoming reality. From a technology perspective, a lot of information related to device parameters, channel states, network and application data are stored in databases and can be used for an extensive analysis to improve the functionality of IoT systems in terms of network performance and user services. LoRaWAN (Long Range Wide Area Network) is one of the emerging IoT technologies, with a simple protocol based on LoRa modulation. In this work, we discuss how machine learning approaches can be used to improve network performance (and if and how they can help). To this aim, we describe a methodology to process LoRaWAN packets a…
Seismic Network Evaluation through Simulation: an application to the Italian RSNC-INGV
2010
Active Learning for Monitoring Network Optimization
2012
Kernel-based active learning strategies were studied for the optimization of environmental monitoring networks. This chapter introduces the basic machine learning algorithms originated in the statistical learning theory of Vapnik (1998). Active learning is closer to an optimization done using sequential Gaussian simulations. The chapter presents the general ideas of statistical learning from data. It derives the basics of kernel-based support vector algorithms. The active learning framework is presented and machine learning extensions for active learning are described in the chapter. Kernel-based active learning strategies are tested on real case studies. The chapter explores the use of a c…
The linear saturated decentralized strategy for constrained flow control is asymptotically optimal
2013
We present an algorithm for constrained network flow control in the presence of an unknown demand. Our algorithm is decentralized in the sense that it is implemented by a team of agents, each controlling just the flow on a single arc of the network based only on the buffer levels at the nodes at the extremes of the arc, while ignoring the actions of other agents and the network topology. We prove that our algorithm is also stabilizing and steady-state optimal. Specifically, we show that it asymptotically produces the minimum-norm flow. We finally generalize our algorithm to networks with a linear dynamics and we prove that certain least-square optimality properties still hold.