2,559 research outputs found
Recent Advances in Graph Partitioning
We survey recent trends in practical algorithms for balanced graph
partitioning together with applications and future research directions
Pressure Fluctuations in Natural Gas Networks caused by Gas-Electric Coupling
The development of hydraulic fracturing technology has dramatically increased
the supply and lowered the cost of natural gas in the United States, driving an
expansion of natural gas-fired generation capacity in several electrical
inter-connections. Gas-fired generators have the capability to ramp quickly and
are often utilized by grid operators to balance intermittency caused by wind
generation. The time-varying output of these generators results in time-varying
natural gas consumption rates that impact the pressure and line-pack of the gas
network. As gas system operators assume nearly constant gas consumption when
estimating pipeline transfer capacity and for planning operations, such
fluctuations are a source of risk to their system. Here, we develop a new
method to assess this risk. We consider a model of gas networks with
consumption modeled through two components: forecasted consumption and small
spatio-temporarily varying consumption due to the gas-fired generators being
used to balance wind. While the forecasted consumption is globally balanced
over longer time scales, the fluctuating consumption causes pressure
fluctuations in the gas system to grow diffusively in time with a diffusion
rate sensitive to the steady but spatially-inhomogeneous forecasted
distribution of mass flow. To motivate our approach, we analyze the effect of
fluctuating gas consumption on a model of the Transco gas pipeline that extends
from the Gulf of Mexico to the Northeast of the United States.Comment: 10 pages, 7 figure
Designing a scalable dynamic load -balancing algorithm for pipelined single program multiple data applications on a non-dedicated heterogeneous network of workstations
Dynamic load balancing strategies have been shown to be the most critical part of an efficient implementation of various applications on large distributed computing systems. The need for dynamic load balancing strategies increases when the underlying hardware is a non-dedicated heterogeneous network of workstations (HNOW). This research focuses on the single program multiple data (SPMD) programming model as it has been extensively used in parallel programming for its simplicity and scalability in terms of computational power and memory size.;This dissertation formally defines and addresses the problem of designing a scalable dynamic load-balancing algorithm for pipelined SPMD applications on non-dedicated HNOW. During this process, the HNOW parameters, SPMD application characteristics, and load-balancing performance parameters are identified.;The dissertation presents a taxonomy that categorizes general load balancing algorithms and a methodology that facilitates creating new algorithms that can harness the HNOW computing power and still preserve the scalability of the SPMD application.;The dissertation devises a new algorithm, DLAH (Dynamic Load-balancing Algorithm for HNOW). DLAH is based on a modified diffusion technique, which incorporates the HNOW parameters. Analytical performance bound for the worst-case scenario of the diffusion technique has been derived.;The dissertation develops and utilizes an HNOW simulation model to conduct extensive simulations. These simulations were used to validate DLAH and compare its performance to related dynamic algorithms. The simulations results show that DLAH algorithm is scalable and performs well for both homogeneous and heterogeneous networks. Detailed sensitivity analysis was conducted to study the effects of key parameters on performance
Firefly Algorithm: Recent Advances and Applications
Nature-inspired metaheuristic algorithms, especially those based on swarm
intelligence, have attracted much attention in the last ten years. Firefly
algorithm appeared in about five years ago, its literature has expanded
dramatically with diverse applications. In this paper, we will briefly review
the fundamentals of firefly algorithm together with a selection of recent
publications. Then, we discuss the optimality associated with balancing
exploration and exploitation, which is essential for all metaheuristic
algorithms. By comparing with intermittent search strategy, we conclude that
metaheuristics such as firefly algorithm are better than the optimal
intermittent search strategy. We also analyse algorithms and their implications
for higher-dimensional optimization problems.Comment: 15 page
Efficient graph-based dynamic load-balancing for parallel large-scale agent-based traffic simulation
Distributed Utilization Control for Real-time Clusters with Load Balancing
Recent years have seen rapid growth of online services that rely on large-scale server clusters to handle high volume of requests. Such clusters must adaptively control the CPU utilizations of many processors in order to maintain desired soft real-time performance and prevent system overload in face of unpredictable workloads. This paper presents DUC-LB, a novel distributed utilization control algorithm for cluster-based soft real-time applications. Compared to earlier works on utilization control, a distinguishing feature of DUC-LB is its capability to handle system dynamics caused by load balancing, which is a common and essential component of most clusters today. Simulation results and control-theoretic analysis demonstrate that DUC-LB can provide robust utilization control and effective load balancing in large-scale clusters
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