Smart meters networks are rapidly becoming a reality in many developed countries. In this thesis, we focus on the optimization of a network of smart meters operated by the wM-Bus protocol, which is the de-facto metering standard in Europe. In such a scenario, data concentrators receive data from smart meters using the wM-Bus protocol and relay it to a central server using a legacy mobile cellular backhauling technology such as GSM/GPRS. Due to the massive amount of data produced by meters installed in urban scenarios and the association-less nature of the wM-Bus protocol, data concentrators may be overloaded with many duplicate measurement packets, causing capacity problems on the backhauling links and computational overload at the central server. To solve these issues, we propose a data-driven optimization framework to populate forwarding whitelists at each data concentrator so that (i) load is balanced among the different concentrators and (ii) the overall performance of the network in terms of packet reception rate and received signal strength are maximized. We also propose a heuristic algorithm to generate near optimal forwarding whitelists in acceptable computing time. Extensive experiments are performed on a real scenario consisting of a city wide, fully operative, gas meter network deployed in northern Italy. Results show that the proposed heuristic is able to produce whitelists that reduce the average backhauling traffic as much as 80%, with a corresponding network quality which on the one hand stays within 4% of the one computed by the optimal solution and on the other hand turns to improve as much as 60% the one provided by the currently functioning whitelists creation process.
Le reti di smart meters (i.e. contatori intelligenti) sono ormai diventate una realtà tecnologica importante in quasi tutti i paesi sviluppati. Questo lavoro di tesi si propone di ottimizzare le prestazioni di una rete di contatori, capaci di comunicare via wireless attraverso il protocollo wM-Bus, diventato da qualche anno lo standard più utilizzato in questo contesto. Nello scenario considerato, una rete di accentratori di dati riceve messaggi dai contatori (montati in-loco rispetto al fenomeno da monitorare) e in- oltra tali messaggi ad un server centrale, attraverso una delle tecnologie tradizionali per comunicazioni cellulari, come per esempio GSM/GPRS. A causa da un lato degli enormi volumi di dati generati dai contatori in contesti urbani e dall’altro della natura non-associativa del protocollo wM- Bus, i suddetti concentratori di dati possono sovraccaricarsi, determinando inoltre problemi di capacità sui collegamenti backhaul (data la presenza di molti pacchetti duplicati) e sovraccarichi al server centrale. Per risolvere questo problema, proponiamo un processo di ottimizzazione che, sfruttando i dati ricevuti dai sensori, permetta ad ogni concentratore di creare Liste di Inoltro (i.e. Whitelists) in maniera tale che (i) ogni contatore sia controllato da un solo concentratore, (ii) il carico (cioè la somma dei contatori gestiti) sia bilanciato tra i concentratori e (iii) le prestazioni della rete siano ottimizzate in termini di qualità del canale, espressa a sua volta in termini di Packet Error Rate (PER) e Received Signal Strength (RSS). In quest’ottica, proponiamo anche un’euristica che approssimi l’ottimo generando le suddette liste in tempi di esecuzione xi LIST OF TABLES xii ragionevoli. Gli esperimenti sono stati realizzati considerando un caso reale di una rete di contatori gas localizzata in una città del nord Italia. I risultati dimostrano che l’euristica proposta è in grado di realizzare liste di inoltro che riducono il carico medio sul collegamento backhaul fino all’80%, assi- curando prestazioni prossime all’ottimo (il Gap è del 4% circa) e di gran lunga migliori rispetto all’attuale procedimento di creazione delle liste realizzato nella rete.
Load balancing and performance optimization in WM-bus smart meter networks
PIMPINELLA, ANDREA
2017/2018
Abstract
Smart meters networks are rapidly becoming a reality in many developed countries. In this thesis, we focus on the optimization of a network of smart meters operated by the wM-Bus protocol, which is the de-facto metering standard in Europe. In such a scenario, data concentrators receive data from smart meters using the wM-Bus protocol and relay it to a central server using a legacy mobile cellular backhauling technology such as GSM/GPRS. Due to the massive amount of data produced by meters installed in urban scenarios and the association-less nature of the wM-Bus protocol, data concentrators may be overloaded with many duplicate measurement packets, causing capacity problems on the backhauling links and computational overload at the central server. To solve these issues, we propose a data-driven optimization framework to populate forwarding whitelists at each data concentrator so that (i) load is balanced among the different concentrators and (ii) the overall performance of the network in terms of packet reception rate and received signal strength are maximized. We also propose a heuristic algorithm to generate near optimal forwarding whitelists in acceptable computing time. Extensive experiments are performed on a real scenario consisting of a city wide, fully operative, gas meter network deployed in northern Italy. Results show that the proposed heuristic is able to produce whitelists that reduce the average backhauling traffic as much as 80%, with a corresponding network quality which on the one hand stays within 4% of the one computed by the optimal solution and on the other hand turns to improve as much as 60% the one provided by the currently functioning whitelists creation process.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/140034