Bio-inspired Networking: analisi della letteratura applicata al modello MoK
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@mastersthesis{corbimokbionetworking2016,
abstract = {Scopo della tesi \`{e} quello di esplorare la letteratura in cerca di alternative applicabili rispetto agli approcci tradizionali per quanto riguarda la comunicazione nei sistemi distributi, specialmente nel caso di reti p2p con network altamente dinamiche, derivate da paradigmi bio-inspired. In particolare verranno analizzati i requisiti di MoK, un modello per la coordinazione di agenti software basato sulla distribuzione di informazioni in rete, e verranno isolate delle propriet\`{a} che possiamo ritenere adatte a risolvere le problematiche attaccate da tale modello, per poi ricercare determinati algoritmi, meccanismi e processi che dispongano di tali propriet\`{a} per soddisfare i requisiti di Mok.},
amseprint = {14788},
amspractice = {1055789},
author = {Corbi, Alessandro},
available = {2016-05-16},
contact = {Mariani, Stefano},
cosupervisor = {Mariani, Stefano},
cycle = {L},
description = {Bio-inspired networking -- e.g., swarming algorithms, immune-inspired networking, membrane computing, and the like -- is becoming more and more a viable alternative to more traditional approaches regarding communication in distribution systems, especially in the case of p2p highly dynamic networks. There, dissemination and retrieval of information often plays a key role in enabling the designed system to deliver its functionalities. Chemical-like diffusion, physics-inspired gradients, gossiping algorithms based on social networking principles, biological chemotaxis are just a few examples of nature-inspired (decentralized) approaches to networking and communication in distributed systems which have proven to be both efficient and effective. Common to all of them, are the notions of locality and neighbourhood, which enable the approaches to scale with the size of the network considered. The goal of the thesis is to survey the state of art regarding bio-inspired (possibly, nature-inspired) networking, then isolate a number of mechanisms, algorithms, and approaches to experiment with in the context of the Molecules of Knowledge model (MoK) for self-organisation of knowledge. While doing so, particular care should be put in analyzing and experimenting with different notions of neighbourhood, and different mechanisms and algorithms to build neighborhoods. The aim is that of detecting a core set of networking mechanisms enabling MoK goals and of investigate\`{i}ing their behavioral expressiveness.},
keywords = {MoK, Bio-inspired Networking, Disseminazione informazioni},
language = {it},
month = dec,
start = {2017-09-01},
supervisor = {Omicini, Andrea},
title = {Bio-inspired Networking: analisi della letteratura applicata al modello MoK},
type = {Bachelor's thesis},
year = 2017
}
abstract = {Scopo della tesi \`{e} quello di esplorare la letteratura in cerca di alternative applicabili rispetto agli approcci tradizionali per quanto riguarda la comunicazione nei sistemi distributi, specialmente nel caso di reti p2p con network altamente dinamiche, derivate da paradigmi bio-inspired. In particolare verranno analizzati i requisiti di MoK, un modello per la coordinazione di agenti software basato sulla distribuzione di informazioni in rete, e verranno isolate delle propriet\`{a} che possiamo ritenere adatte a risolvere le problematiche attaccate da tale modello, per poi ricercare determinati algoritmi, meccanismi e processi che dispongano di tali propriet\`{a} per soddisfare i requisiti di Mok.},
amseprint = {14788},
amspractice = {1055789},
author = {Corbi, Alessandro},
available = {2016-05-16},
contact = {Mariani, Stefano},
cosupervisor = {Mariani, Stefano},
cycle = {L},
description = {Bio-inspired networking -- e.g., swarming algorithms, immune-inspired networking, membrane computing, and the like -- is becoming more and more a viable alternative to more traditional approaches regarding communication in distribution systems, especially in the case of p2p highly dynamic networks. There, dissemination and retrieval of information often plays a key role in enabling the designed system to deliver its functionalities. Chemical-like diffusion, physics-inspired gradients, gossiping algorithms based on social networking principles, biological chemotaxis are just a few examples of nature-inspired (decentralized) approaches to networking and communication in distributed systems which have proven to be both efficient and effective. Common to all of them, are the notions of locality and neighbourhood, which enable the approaches to scale with the size of the network considered. The goal of the thesis is to survey the state of art regarding bio-inspired (possibly, nature-inspired) networking, then isolate a number of mechanisms, algorithms, and approaches to experiment with in the context of the Molecules of Knowledge model (MoK) for self-organisation of knowledge. While doing so, particular care should be put in analyzing and experimenting with different notions of neighbourhood, and different mechanisms and algorithms to build neighborhoods. The aim is that of detecting a core set of networking mechanisms enabling MoK goals and of investigate\`{i}ing their behavioral expressiveness.},
keywords = {MoK, Bio-inspired Networking, Disseminazione informazioni},
language = {it},
month = dec,
start = {2017-09-01},
supervisor = {Omicini, Andrea},
title = {Bio-inspired Networking: analisi della letteratura applicata al modello MoK},
type = {Bachelor's thesis},
year = 2017
}
