Browsing by Subject "Resource sharing"

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AIMD-based online MPLS traffic engineering for TCP flows via distributed multi-path routing
(Springer, 2004) Alparslan O.; Akar, N.; Karasan, E.
With this paper, we propose a distributed online traffic engineering architecture for MPLS networks. In this architecture, a primary and secondary MPLS LSP are established from an ingress LSR to every other egress LSR. We propose to split the TCP traffic between the primary and secondary paths using a distributed mechanism based on ECN marking and AIMD-based rate control. Inspired by the random early detection mechanism for active queue management, we propose a random early reroute scheme to adaptively control the delay difference between the primary and secondary LSPS. Considering the adverse effect of packet reordering on TCP performance for packet-based load balancing schemes, we propose that the TCP splitting mechanism operates on a per-flow basis. Using flow-based models developed for Internet traffic and simulations, we show that flow-based distributed multi-path traffic engineering outperforms on a consistent basis the case of a single path in terms of per-flow goodputs. Due to the elimination of out-of-order packet arrivals, flow-based splitting also enhances TCP performance with respect to packet-based splitting especially for long TCP flows that are hit hard by packet reordering. We also compare and contrast two queuing architectures for differential treatment of data packets routed over primary and secondary LSPS in the MPLS data plane, namely first-in-first-out and strict priority queuing. We show through simulations that strict priority queuing is more effective and relatively more robust with respect to the changes in the traffic demand matrix than first-in-first-out queuing in the context of distributed multi-path routing.
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A stochastic model for a macroscale hybrid renewable energy system
(Elsevier, 2016) Kocaman, A. S.; Abad, C.; Troy, T. J.; Huh, W. T.; Modi, V.
The current supply for electricity generation mostly relies on fossil fuels, which are finite and pose a great threat to the environment. Therefore, energy models that involve clean and renewable energy sources are necessary to ease the concerns about the electricity generation needed to meet the projected demand. Here, we mathematically model a hybrid energy generation and allocation system where the intermittent solar generation is supported by conventional hydropower stations and diesel generation and time variability of the sources are balanced using the water stored in the reservoirs. We develop a two-stage stochastic model to capture the effect of streamflows which present significant inter-annual variability and uncertainty. Using sample case studies from India, we determine the required hydropower generation capacity and storage along with the minimal diesel usage to support 1 GWpeak solar power generation. We compare isolated systems with the connected systems (through inter-regional transmission) to see the effects of geographic diversity on the infrastructure sizing and quantify the benefits of resource-sharing. We develop the optimal sizing relationship between solar and hydropower generation capacities given realistic cost parameters and real data and examine how this relationship would differ as the contribution of diesel is reduced. We also show that if the output of the solar power stations can be controlled (i.e. spill is allowed in our setting), operating them below their maximum energy generation levels may reduce the unit cost of the system.