<p> Wireless mesh networks are now being used to deploy radio coverage in a large variety of outdoor applications. One of the major obstacles that these networks face is that of providing the nodes with electrical power and wired network connections. Solar powered mesh nodes are increasingly used to eliminate the need for these types of connections, making the nodes truly tether-less. In these types of networks however, the cost of the energy collection and storage components can be a significant fraction of the total node cost, which motivates a careful selection of these resources.</p> <p> This thesis focusses on key issues relating to the deployment and operation of solar powered wireless mesh networks. First, the problem of provisioning the mesh nodes with a suitable solar panel and battery configuration is considered. This is done by assuming a bandwidth usage profile and using historical solar insolation data for the desired deployment location. A resource provisioning algorithm is proposed based on the use of temporal shortest-path routing and taking into account the node energy-flow for the target deployment time period. A methodology is introduced which uses a genetic algorithm (GA) to incorporate energy-aware routing into the resource assignment procedure. Results show that the proposed resource provisioning algorithm can achieve large cost savings when compared to conventional provisioning methods.</p> <p> During post-deployment network operation, the actual bandwidth profile and solar insolation may be different than that for which the nodes were originally provisioned. To prevent node outage, the network must reduce its workload by flow controlling its input traffic. The problem of admitting network bandwidth flows in a fair manner is also studied. A bound is first formulated which achieves the best max/min fair flow control subject to eliminating node outage. The bound motivates a proposed causal flow control algorithm whose operation uses prediction based on access to on-line historical weather data. The results show that the proposed algorithm performs well when compared to the analytic bound that is derived for this problem.</p> <p> Finally, as user traffic evolves, the network resources need to be updated. This problem is considered using a minimum cost upgrade objective. A mixed integer linear programming (MILP) formulation is derived to obtain a lower bound on the network update cost. A genetic algorithm is used to determine practical cost-effective network resource upgrading. The results show that the proposed methodology can obtain significant cost savings.</p> / Thesis / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/18924 |
| Date | 01 1900 |
| Creators | Badawy, Ghada |
| Contributors | Todd, Terence D., Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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