561 research outputs found
Distributed Algorithms for Scheduling on Line and Tree Networks
We have a set of processors (or agents) and a set of graph networks defined
over some vertex set. Each processor can access a subset of the graph networks.
Each processor has a demand specified as a pair of vertices , along
with a profit; the processor wishes to send data between and . Towards
that goal, the processor needs to select a graph network accessible to it and a
path connecting and within the selected network. The processor requires
exclusive access to the chosen path, in order to route the data. Thus, the
processors are competing for routes/channels. A feasible solution selects a
subset of demands and schedules each selected demand on a graph network
accessible to the processor owning the demand; the solution also specifies the
paths to use for this purpose. The requirement is that for any two demands
scheduled on the same graph network, their chosen paths must be edge disjoint.
The goal is to output a solution having the maximum aggregate profit. Prior
work has addressed the above problem in a distibuted setting for the special
case where all the graph networks are simply paths (i.e, line-networks).
Distributed constant factor approximation algorithms are known for this case.
The main contributions of this paper are twofold. First we design a
distributed constant factor approximation algorithm for the more general case
of tree-networks. The core component of our algorithm is a tree-decomposition
technique, which may be of independent interest. Secondly, for the case of
line-networks, we improve the known approximation guarantees by a factor of 5.
Our algorithms can also handle the capacitated scenario, wherein the demands
and edges have bandwidth requirements and capacities, respectively.Comment: Accepted to PODC 2012, full versio
Malunion of Pediatric Forearm Shaft Fractures: Management Principles and Techniques.
PURPOSE OF REVIEW: Clinically significant malunion of forearm diaphyseal fractures is an uncommon but potentially disabling condition amongst children and adolescents. We present the preoperative evaluation, including imaging, and discuss surgical indications and contemporary approaches to manage such patients, including an illustrative case. RECENT FINDINGS: While advances in three-dimensional (3D) simulation, modeling, and patient-specific instrumentation have expanded the surgical armamentarium, their impact on long-term outcomes compared to traditional methods remains unknown. Successful outcome following surgical correction of malunion following a both-bone forearm fracture can be achieved with careful patient selection, appropriate indications, and a well-planned surgical execution
Distributed and Parallel Algorithms for Set Cover Problems with Small Neighborhood Covers
In this paper, we study a class of set cover problems that satisfy a special
property which we call the {\em small neighborhood cover} property. This class
encompasses several well-studied problems including vertex cover, interval
cover, bag interval cover and tree cover. We design unified distributed and
parallel algorithms that can handle any set cover problem falling under the
above framework and yield constant factor approximations. These algorithms run
in polylogarithmic communication rounds in the distributed setting and are in
NC, in the parallel setting.Comment: Full version of FSTTCS'13 pape
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Chylous Leak During Posterior Approach to Juvenile Scoliosis Surgery: A Case Report.
CaseWe report the first documented case of chylous leak recognized intraoperatively during posterior spinal instrumentation and fusion for juvenile scoliosis in a female patient with a history of thoracotomy and decortication for an empyema.ConclusionsThoracic duct injury can lead to severe morbidity and mortality because of chylothorax formation. Although chylous leaks are a well-documented complication of the anterior approach to spine surgery, leaks during the posterior approach are rarely reported. When these chylous leaks are recognized intraoperatively, the likelihood of serious complications may be minimized by drain placement before closure
A Near-linear Time Constant Factor Algorithm for Unsplittable Flow Problem on Line with Bag Constraints
Consider a scenario where we need to schedule a set of jobs on a system offering some resource (such as electrical power or communication bandwidth), which we shall refer to as bandwidth. Each job consists of a set (or bag) of job instances. For each job instance, the input specifies the start time, finish time, bandwidth requirement and profit. The bandwidth offered by the system varies at different points of time and is specified as part of the input. A feasible solution is to choose a subset of instances such that at
any point of time, the sum of bandwidth requirements of the chosen instances does not exceed the bandwidth available at that point of time, and furthermore, at most one instance is picked from each job.
The goal is to find a maximum profit feasible solution. We study this problem under a natural assumption called the no-bottleneck assumption (NBA), wherein the bandwidth requirement of any job instance is at most the minimum bandwidth available. We present a simple, near-linear time constant factor approximation algorithm for this problem, under NBA. When each job consists of only one job instance, the above problem is the same as the well-studied unsplittable flow problem (UFP) on lines. A constant factor approximation algorithm is known for the UFP on line, under NBA.
Our result leads to an alternative constant factor approximation algorithm for this problem. Though the approximation ratio achieved by our algorithm is inferior, it is much simpler, deterministic and faster in comparison to the existing algorithms. Our algorithm runs in near-linear time (), whereas the running time of the known algorithms is a high order polynomial. The core idea behind our algorithm is a reduction from the varying bandwidth case to the easier uniform bandwidth case, using a technique that we call slicing
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