20615876
Linear Time Algorithms for Parallel Machine Scheduling
This paper addresses linear time algorithms for parallel machine scheduling problems. We introduce a kind of threshold algorithms and discuss their main features. Three linear time threshold algorithm classes DT, PT and DTm are studied thoroughly. For all classes, we study their best possible algorithms among each class. We also present their application to several scheduling problems. The new algorithms are better than classical algorithms in time complexity and/or worst-case ratio. Computer-aided proof method is used in the proof of main results, which greatly simplifies the proof and decreases case by case analysis.
15248292
Preemptive online algorithms for scheduling with machine cost
Abstract.For most scheduling problems the set of machines is fixed initially and remains unchanged. Recently Imreh and Noga proposed adding the concept of machine cost to scheduling problems and considered the so-called List Model problem. For this problem, we are given a sequence of independent jobs with positive sizes, which must be processed non-preemptively on a machine. No machines are initially provided, and when a job is revealed the algorithm has the option to purchase new machines. The objective is to minimize the sum of the makespan and cost of machines. In this paper, a modified model of List Model is presented where preemption is allowed. For this model, it is shown that better performance is possible. We present an online algorithm with a competitive ratio of $(2\sqrt{6} + 2)/5\approx 1.3798$ while the lower bound is 4/3. For the semi-online problem with decreasing sizes, we design an optimal algorithm with a competitive ratio of 4/3, which improves the known upper bound of 3/2. The algorithm does not introduce any preemption, and hence is also an optimal semi-online algorithm for the non-preemptive semi-online problem. For the semi-online problem with known largest size, we present an optimal algorithm with a competitive ratio of 4/3.
29901411
Bin Packing and Covering Problems with Rejection
In this paper we consider the following problems: We are given a set of n items {u1, i¾?, un}, each item ui is characterized by its size wi∈ 0,1] and its penalty/profit pii¾? 0, and a number of unit-capacity bins. An item can be either rejected, in which case we pay/get its penalty/profit, or put into one bin under the constraint that the total size of the items in the bin is not greater/smaller than 1. No item can be spread into more than one bin. The objective is to minimize/maximize the sum of the number of used/covered bins and the penalties/profits of all rejected items. We call the problems bin packing/covering with rejection penalties/profits, and denoted by BPR and BCR respectively. For the online BPR problem, we present an algorithm with an absolute competitive ratio of 2.618 while the lower bound is 2.343, and an algorithm with an asymptotic competitive ratio of arbitrarily close to 7/4 while the lower bound is 1.540. For the offline BPR problem, we present an algorithm with an absolute worst-case ratio of 2 while the lower bound is 3/2, and an algorithm with an asymptotic worst-case ratio of 3/2. For the online BCR problem, we show that no algorithm can have an absolute competitive ratio of greater than 0, and present an algorithm with an asymptotic competitive ratio of 1/2, which is the best possible. For the offline BCR problem, we also present an algorithm with an absolute worst-case ratio of 1/2 which matches the lower bound.
807866
Surface reconstruction with triangular B-splines
This paper presents a modeling technique for reconstructing a triangular B-spline surface from a set of scanned 3D points. Unlike existing surface reconstruction methods based on tensor-product B-splines which primarily generate a network of patches and then enforce certain continuity (usually, G/sup 1/ or C/sup 1/) between adjacent patches, our algorithm can avoid the complicated procedures of surface trimming and patching. In our framework, the user simply specifies the degree n of the triangular B-spline surface and fitting error tolerance /spl epsi/. The surface reconstruction procedure generates a single triangular B-spline patch that has C/sup n-1/ continuity over smooth regions and C/sup 0/ on sharp features. More importantly, all the knots and control points are determined by minimizing a linear combination of interpolation and fairness functionals. Examples are presented which demonstrate the effectiveness of the technique for real data sets.
290365
Spline Thin-Shell Simulation of Manifold Surfaces
It has been technically challenging to effectively model and simulate elastic deformation of spline-based, thin-shell objects of complicated topology. This is primarily because traditional FEM are typically defined upon planar domain, therefore incapable of constructing complicated, smooth spline surfaces without patching/trimming. Moreover, at least C1 continuity is required for the convergence of FEM solutions in thin-shell simulation. In this paper, we develop a new paradigm which elegantly integrates the thin-shell FEM simulation with geometric design of arbitrary manifold spline surfaces. In particular, we systematically extend the triangular B-spline FEM from planar domains to manifold domains. The deformation is represented as a linear combination of triangular B-splines over shell surfaces, then the dynamics of thin-shell simulation is computed through the minimization of Kirchhoff-Love energy. The advantages given by our paradigm are: FEM simulation of arbitrary manifold without meshing and data conversion, and the integrated approach for geometric design and dynamic simulation/analysis. Our system also provides a level-of-detail sculpting tool to manipulate the overall shapes of thin-shell surfaces for effective design. The proposed framework has been evaluated on a set of spline models of various topologies, and the results demonstrate its efficacy in physics-based modeling, interactive shape design and finite-element simulation.
15418267
Incorporating Rigid Structures in Non-rigid Registration Using Triangular B-Splines
For non-rigid registration, the objects in medical images are usually treated as a single deformable body with homogeneous stiffness distribution. However, this assumption is invalid for certain parts of the human body, where bony structures move rigidly, while the others may deform. In this paper, we introduce a novel registration technique that models local rigidity of pre-identified rigid structures as well as global non-rigidity in the transformation field using triangular B-splines. In contrast to the conventional registration method based on tensor-product B-splines, our approach recovers local rigid transformation with fewer degrees of freedom (DOFs), and accurately simulates sharp features (C0 continuity) along the interface between deformable regions and rigid structures, because of the unique advantages offered by triangular B-splines, such as flexible triangular domain, local control and space-varying smoothness modeling. The accurate matching of the source image with the target one is accomplished through the use of a variational framework, in which a composite energy, measuring the image dissimilarity and enforcing local rigidity and global smoothness, is minimized subject to pre-defined point-based constraints. The algorithm is tested on both synthetic and real 2D images for its applicability. The experimental results show that, by accurately modeling sharp features using triangular B-splines, the deformable regions in the vicinity of rigid structures are less constrained by the global smoothness regularization and therefore contribute extra flexibility to the optimization process. Consequently, the registration quality is improved considerably.
1259633
An autonomic routing framework for sensor networks
Current routing services for sensor networks are often designed for specific applications and network conditions, thus have difficulty in adapting to application and network dynamics. This paper proposes an autonomic framework to promote the adaptivity of routing services in sensor networks. The key idea of this framework is to maintain some feature functions that are decoupled from originally-integrated routing services. This separation enables significant service changes to be done by only tuning these functions. Measures including parameterization are taken to save the energy for changing these functions. Further, this framework includes a monitoring module to support a policy-based collaborative adaptation. This paper shows an example autonomic routing service conforming to this framework.
45341657
3-D Reconstruction of Macroscopic Optical Brain Slice Images
We present a method for reconstruction of macroscopic optical images of post-mortem brain slices to form a 3-D volume. This forms a key part of a series of procedures to allow post mortem findings to be accurately registered with MR images, and more generally provides a method for 3-D mapping of the distribution of pathological changes throughout the brain. In this preliminary work, four brains from a study of Creutzfeldt-Jakob disease were examined. After brain fixation, the pathologist cut coronal slices several mm thick through the brain. The anterior and posterior faces of each slice were photographed. We show that the 2-D co-registration of each such pair of images was most effectively obtained if the slice was placed in a jig before photographing. Fiducials on the jig were detected automatically and point-based rigid registration computed. For co-registration between slices, i.e., across a single cut, an intensity-based method for 2-D non-rigid registration is used which provided satisfactory results. By propagating the 2-D registrations through the volume and using the known slice thickness, the 3-D volume was reconstructed.