17 resultados para Resource Allocation


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A wireless mesh network is a mesh network implemented over a wireless network system such as wireless LANs. Wireless Mesh Networks(WMNs) are promising for numerous applications such as broadband home networking, enterprise networking, transportation systems, health and medical systems, security surveillance systems, etc. Therefore, it has received considerable attention from both industrial and academic researchers. This dissertation explores schemes for resource management and optimization in WMNs by means of network routing and network coding.^ In this dissertation, we propose three optimization schemes. (1) First, a triple-tier optimization scheme is proposed for load balancing objective. The first tier mechanism achieves long-term routing optimization, and the second tier mechanism, using the optimization results obtained from the first tier mechanism, performs the short-term adaptation to deal with the impact of dynamic channel conditions. A greedy sub-channel allocation algorithm is developed as the third tier optimization scheme to further reduce the congestion level in the network. We conduct thorough theoretical analysis to show the correctness of our design and give the properties of our scheme. (2) Then, a Relay-Aided Network Coding scheme called RANC is proposed to improve the performance gain of network coding by exploiting the physical layer multi-rate capability in WMNs. We conduct rigorous analysis to find the design principles and study the tradeoff in the performance gain of RANC. Based on the analytical results, we provide a practical solution by decomposing the original design problem into two sub-problems, flow partition problem and scheduling problem. (3) Lastly, a joint optimization scheme of the routing in the network layer and network coding-aware scheduling in the MAC layer is introduced. We formulate the network optimization problem and exploit the structure of the problem via dual decomposition. We find that the original problem is composed of two problems, routing problem in the network layer and scheduling problem in the MAC layer. These two sub-problems are coupled through the link capacities. We solve the routing problem by two different adaptive routing algorithms. We then provide a distributed coding-aware scheduling algorithm. According to corresponding experiment results, the proposed schemes can significantly improve network performance.^

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Vegetation patterns of mangroves in the Florida Coastal Everglades (FCE) result from the interaction of environmental gradients and natural disturbances (i.e., hurricanes), creating an array of distinct riverine and scrub mangroves across the landscape. We investigated how landscape patterns of biomass and total net primary productivity (NPPT), including allocation in above- and below-ground mangrove components, vary inter-annually (2001–2004) across gradients in soil properties and hydroperiod in two distinct FCE basins: Shark River Estuary and Taylor River Slough. We propose that the allocation of belowground biomass and productivity (NPPB) relative to aboveground allocation is greater in regions with P limitation and permanent flooding. Porewater sulfide was significantly higher in Taylor River (1.2 ± 0.3 mM) compared to Shark River (0.1 ± 0.03 mM) indicating the lack of a tidal signature and more permanent flooding in this basin. There was a decrease in soil P density and corresponding increase in soil N:P from the mouth (28) to upstream locations (46–105) in Shark River that was consistent with previous results in this region. Taylor River sites showed the highest P limitation (soil N:P > 60). Average NPPT was double in higher P environments (17.0 ± 1.1 Mg ha−1 yr−1) compared to lower P regions (8.3 ± 0.3 Mg ha−1 yr−1). Root biomass to aboveground wood biomass (BGB:AWB) ratio was 17 times higher in P-limited environments demonstrating the allocation strategies of mangroves under resource limitation. Riverine mangroves allocated most of the NPPT to aboveground (69%) while scrub mangroves showed the highest allocation to belowground (58%). The total production to biomass (P:B) ratios were lower in Shark River sites (0.11 yr−1); whereas in Taylor River sites P:B ratios were higher and more variable (0.13–0.24 yr−1). Our results suggest that the interaction of lower P availability in Taylor River relative to Shark River basin, along with higher sulfide and permanent flooding account for higher allocation of belowground biomass and production, at expenses of aboveground growth and wood biomass. These distinct patterns of carbon partitioning between riverine and scrub mangroves in response to environmental stress support our hypothesis that belowground allocation is a significant contribution to soil carbon storage in forested wetlands across FCE, particularly in P-limited scrub mangroves. Elucidating these biomass strategies will improve analysis of carbon budgets (storage and production) in neotropical mangroves and understanding what conditions lead to net carbon sinks in the tropical coastal zone.