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.
1033072
Gathercast with active networks
Small packets constitute a large fraction of packets in the Internet. Gathercast is a network layer service that combines small packets going to the same destination into a single packet, reducing the number of packets in the network and saving computations at intermediate routers. We propose a new model for gathercast using active network techniques. With this model, gathercast is built throughout the network with low overhead, service parameters can be dynamically adjusted and end-user applications obtain benefits from gathercast without knowing its existence. We also present an implementation of the active gathercast.
28965598
A semantic matchmaker service on the grid
A fundamental task on the Grid is to decide what jobs to run on what computing resources based on job or application requirements. Our previous work on ontology-based matchmaking discusses a resource matchmaking mechanism using Semantic Web technologies. We extend our previous work to provide dynamic access to such matchmaking capability by building a persistent online matchmaking service. Our implementation uses the Globus Toolkit for the Grid service development, and exploits the monitoring and discovery service in the Grid infrastructure to dynamically discover and update resource information. We describe the architecture of our semantic matchmaker service in the poster.
206892321
Building programmable routing service for sensor networks
Current routing services for sensor networks are application-specific. They are pre-configured into nodes, and thus have difficulty in adapting to different applications and network conditions. This paper describes a framework to build programmable routing services for sensor networks. This framework includes a parameter space that identifies both common and different properties among routing services. With this parameter space, different routing services can be obtained with small programming effort. A programmable routing architecture is proposed to maintain this parameter space and support energy-efficient service deployment. This paper presents implementation details of this programmable framework and shows simulation results.
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.
9015785
Brain Image Analysis Using Spherical Splines
We propose a novel technique based on spherical splines for brain surface representation and analysis. This research is strongly inspired by the fact that, for brain surfaces, it is both necessary and natural to employ spheres as their natural domains. We develop an automatic and efficient algorithm, which transforms a brain surface to a single spherical spline whose maximal error deviation from the original data is less than the user-specified tolerance. Compared to the discrete mesh-based representation, our spherical spline offers a concise (low storage requirement) digital form with high continuity (C n − − 1 continuity for a degree n spherical spline). Furthermore, this representation enables the accurate evaluation of differential properties, such as curvature, principal direction, and geodesic, without the need for any numerical approximations. Thus, certain shape analysis procedures, such as segmentation, gyri and sulci tracing, and 3D shape matching, can be carried out both robustly and accurately. We conduct several experiments in order to demonstrate the efficacy of our approach for the quantitative measurement and analysis of brain surfaces.
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.
5843308
A C1 Globally Interpolatory Spline of Arbitrary Topology
Converting point samples and/or triangular meshes to a more compact spline representation for arbitrarily topology is both desirable and necessary for computer vision and computer graphics. This paper presents a C1 manifold interpolatory spline that can exactly pass through all the vertices and interpolate their normals for data input of complicated topological type. Starting from the Powell-Sabin spline as a building block, we integrate the concepts of global parametrization, affine atlas, and splines defined over local, open domains to arrive at an elegant, easy-to-use spline solution for complicated datasets. The proposed global spline scheme enables the rapid surface reconstruction and facilitates the shape editing and analysis functionality.
2201352
On Mitigating Network Partitioning in Peer-to-Peer Massively Multiplayer Games
Recently, peer-to-peer infrastructure has been proposed to support massively multiplayer games in the literature. However, when underlying network partitions due to network outages, the game world will partition into several parallel game worlds and it is difficult and costly to merge them when the network partitions disappear. Existing approaches resort to a centralized server to arbitrate. Aiming at mitigating the effects brought by network partitions, we propose a fully distributed algorithm based on state-stack matching. Our theoretical analysis and numerical results show that our approach can resolve the merging issue at the least loss of game states with high probability.