Impedance is an important characteristic of lithium-ion batteries since it directly influences their power capability. However, battery impedance is highly dependent on the operating condition and increases over the l...
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Impedance is an important characteristic of lithium-ion batteries since it directly influences their power capability. However, battery impedance is highly dependent on the operating condition and increases over the lifetime of the battery, due to degradation of the latter. Continuous tracking of the impedance can hence provide meaningful insights into the aging status of a battery. However, the on-line determination of battery impedance parameters, especially for its low-frequency part, is a challenging task, which has not yet been solved unambiguously in literature. This work provides an algorithm for the on-line determination of battery impedance, which features a novel approach to quantifying the impedance caused by diffusion processes at low frequencies. The algorithm works by parameterizing an equivalent circuit model comprised of RC elements, which reproduces the Li-ion kinetics. The on-line functionality is enabled by parameterizing the model during parameter identification windows of battery operating data, which allow for the separation of high-frequency and lowfrequency dynamics. The developed algorithm is designed in such a way that it can in future be embedded into a low-cost microcontroller by taking into account the relevant computational and memory limitations. During experimental validation with a commercial Li-ion battery, the root-mean-square error of the simulated voltage during diverse static and dynamic loads is reduced by over 50% compared to a benchmark algorithm without the proposed approach.
We show that a planarst-graphG admits two total orders on the setV∪E ∪F, whereV, E, andF are respectively the set of vertices, edges, and faces ofG, with |V| =n. Assuming thatG is to be dynamically modified by means...
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We show that a planarst-graphG admits two total orders on the setV∪E ∪F, whereV, E, andF are respectively the set of vertices, edges, and faces ofG, with |V| =n. Assuming thatG is to be dynamically modified by means of insertions of edges and expansions of vertices (and their inverses), we exhibit anO(n)-space dynamic data structure for the maintenance of these orders such that an update can be performed in timeO(logn). The discovered structural properties of planarst-graphs provide a unifying theoretical underpinning for several applications, such as dynamic point location in planar monotone subdivisions, dynamic transitive-closure query in planarst-graphs, and dynamic contact-chain query in convex subdivisions. The presented techniques significantly outperform previously known solutions of the same problems.
We consider the problem of scheduling permanent jobs on related machines in an on-line fashion. We design a new algorithm that achieves the competitive ratio of 3 + root 8 approximate to 5.828 for the deterministic ve...
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We consider the problem of scheduling permanent jobs on related machines in an on-line fashion. We design a new algorithm that achieves the competitive ratio of 3 + root 8 approximate to 5.828 for the deterministic version, and 3.31/ln 2.155 approximate to 4.311 for its randomized variant, improving the previous competitive ratios of 8 and 2e approximate to 5.436. We also prove lower bounds of 2.4380 on the: competitive ratio of deterministic algorithms and 1.8372 on the competitive ratio of randomized algorithms for this problem. (C) 2000 Academic Press.
We give a first-fit type algorithm, with running timeO(n), for the classical one-dimensional bin-packing problem, and examine it from a probabilistic point of view. Our main result is that the expected waste for this ...
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We give a first-fit type algorithm, with running timeO(n), for the classical one-dimensional bin-packing problem, and examine it from a probabilistic point of view. Our main result is that the expected waste for this algorithm isO(n 2/3).
We study an on-line problem of scheduling parallel jobs on two-dimensional meshes. Parallel jobs arrive dynamically according to the dependencies between them, which are unknown before the jobs appear. Each job may ne...
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We study an on-line problem of scheduling parallel jobs on two-dimensional meshes. Parallel jobs arrive dynamically according to the dependencies between them, which are unknown before the jobs appear. Each job may need more than one processor simultaneously and is required to be scheduled on a submesh of the processors which are located on a two-dimensional mesh, i.e., a job must be scheduled on a rectangle of given dimensions. The objective is to minimize the maximum completion time (makespan). We deal with a UET job system, in which all job processing times are equal. We show a lower bound of 3.859 and present a 5.25-competitive algorithm. It significantly improves a previous lower bound of 3.25 and a previous upper bound of 46/7. We consider also the rotated two-dimensional mesh, in which the parallel jobs can be rotated and the rotation of all the jobs is feasible. A lower bound of 3.535 is proven and an on-line algorithm with competitive ratio of at most 4.25 is derived. (c) 2006 Elsevier B.V. All rights reserved.
We consider a single batch machine on-line scheduling problem with jobs arriving over time. A batch processing machine can handle up to B jobs simultaneously as a batch, and the processing time for a batch is equal to...
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We consider a single batch machine on-line scheduling problem with jobs arriving over time. A batch processing machine can handle up to B jobs simultaneously as a batch, and the processing time for a batch is equal to the longest processing time among the jobs in it. Each job becomes available at its arrival time, which is not known in advance, and its characteristics, such as processing time and delivery time, become known at its arrival. Once the processing of a job is completed we deliver it to the destination. The objective is to minimize the time by which all jobs have been delivered. In this paper, we deal with two variants: the unbound model where B is sufficiently large and the bounded model where B is finite. We provide on-line algorithms with competitive ratio 2 for the unbounded model and with competitive ratio 3 for the bounded model. For when each job has the same processing time, we provide on-line algorithms with competitive ratios (root 5 + 1)/2, and these results are the best possible. (C) 2006 Elsevier B.V. All rights reserved.
One of the basic and fundamental scheduling problems is to minimize the machine completion time vector in the norm, a direct extension of the well-studied objective makespan ( norm), on parallel machines. We concentra...
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One of the basic and fundamental scheduling problems is to minimize the machine completion time vector in the norm, a direct extension of the well-studied objective makespan ( norm), on parallel machines. We concentrate on the on-line and preemptive version of this problem where jobs arrive one by one over a list to be allocated to two uniform machines with job preemption permitted. We present a best possible deterministic on-line scheduling algorithm for this problem along with a matching lower bound, generalizing existing results for the identical machines scheduling problem in the literature. One notable feature of this work is the highly involved technicality compared to similar analysis in the existing literature, mainly due to the intrinsic unavailability of a closed-form formula for the competitive ratio.
Traffic anomaly detection is critical for advanced Internet management. Existing detection algorithms generally convert the high-dimensional data to a long vector, which compromises the detection accuracy due to the l...
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Traffic anomaly detection is critical for advanced Internet management. Existing detection algorithms generally convert the high-dimensional data to a long vector, which compromises the detection accuracy due to the loss of spatial information of data. Moreover, they are generally designed based on the separation of normal and anomalous data in a time period, which not only introduces high storage and computation cost but also prevents timely detection of anomalies. Online and accurate traffic anomaly detection is critical but difficult to support. To address the challenge, this paper directly models the monitoring data in each time slot as a 2-D matrix, and detects anomalies in the new time slot based on bilateral principal component analysis (B-PCA). We propose several novel techniques in OnlineBPCA to support quick and accurate anomaly detection in real time, including a novel BPCA-based anomaly detection principle that jointly considers the variation of both row and column principal directions for more accurate anomaly detection, an approximate algorithm to avoid using iteration procedure to calculate the principal directions in a close-form, and a sequential anomaly algorithm to quickly update principal directions with low computation and storage cost when receiving a new data matrix at a time slot. To the best of our knowledge, this is the first work that exploits 2-D PCA for anomaly detection. We have conducted extensive simulations to compare our OnlineBPCA with the state-of-art anomaly detection algorithms using real traffic traces Abilene and GEANT. Our simulation results demonstrate that, compared with other algorithms, our OnlineBPCA can achieve significantly better detection performance with low false positive rate, high true positive rate, and low computation cost.
In this paper we study tire problem of assigning paths to packets oil N x N tori in an on-line and distributed fashion. By on-line we mean that the routing decisions must be made without any knowledge of future reques...
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In this paper we study tire problem of assigning paths to packets oil N x N tori in an on-line and distributed fashion. By on-line we mean that the routing decisions must be made without any knowledge of future requests. Being distributed is an equally important feature of our design. for Such algorithms need knot know the global configuration of the network in the process of routing packets. We use the technique of competitive analysis to measure the performance of our design, In addition to showing an Omega(log N) lower bound on the competitive ratio, we present both deterministic and randomized algorithms which are O(log N) competitive with respect to the maximum load (i.e., congestion) on communication links.
The problem of computing the strength and performing optimal reinforcement for an edge-weighted graph G(V, E, w) is well-studied. In this paper, we present fast (sequential linear time and parallel logarithmic time) o...
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The problem of computing the strength and performing optimal reinforcement for an edge-weighted graph G(V, E, w) is well-studied. In this paper, we present fast (sequential linear time and parallel logarithmic time) on-line algorithms for optimally reinforcing the graph when the reinforcement material is available continuously on-line. These are the first on-line algorithms for this problem. We invest O(\V\(3)\E\log\V\) time (equivalent to Omega(\V\) invocations of the fastest known algorithms for optimal reinforcement) in preprocessing the graph before the start of our algorithms. It is shown that the output of our on-line algorithms is as good as that of the off-linealgorithms. Thus our algorithms are better than the fastest off-linealgorithms in situations when a sequence of more than Omega(\V\) reinforcement problems need to be solved. The key idea is to make use of ideas underlying the theory of Principal Partition of a Graph. Our ideas are easily generalized to the general setting of polymatroid functions. We also present a new efficient algorithm for computation of the Principal Sequence of a graph.
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