检索结果-内蒙古大学图书馆

algorithms and Hardness for Scaffold Filling to Maximize Increased Duo-Preservations

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022年第4期19卷 2071-2079页

作者： Ma, Jingjing Jiang, Haitao Zhu, Daming Yang, Runmin Shandong Univ Dept Comp Sci & Technol Qingdao 266237 Shandong Peoples R China

Scaffold filling is a critical step in DNA assembly. Its basic task is to fill the missing genes (fragments) into an incomplete genome (scaffold) to make it similar to the reference genome. There have been a lot of work under distinct measurements in the literature of genome comparison. For genomes with gene duplications, common string partition reveals the similarity more precisely, since it constructs a one-to-one correspondence between the same segments in the two genomes. In this paper, we adopt duo-preservation as the measurement, which is the complement of common string partition, i.e., the number of duo-preservations added to the number of common strings is exactly the length of a genome. Towards a proper scaffold filling, we just focus on the increased duo-preservations. This problem is called scaffold filling to maximize increased duo-preservations (abbr. SF-MIDP). We show that SF-MIDP is solvable in linear time for a simple version where all the genes of the scaffold are matched in a block-matching, but MAX SNP-complete for the general version, and cannot be approximated within 16263/16262. Moreover, we present a basic approximation algorithm of factor 2, by which the optimal solution can be described in a new way, and then, improve the approximation factor to 12/7 via a greedy method.

关键词： Duo-preservation scaffold filling MAX SNP-complete approximation algorithm

来源：评论

学校读者我要写书评

暂无评论

approximation Methods for Multiobjective Optimization Problems: A Survey

引用

INFORMS JOURNAL ON COMPUTING 2021年第4期33卷 1284-1299页

作者： Herzel, Arne Ruzika, Stefan Thielen, Clemens Univ Kaiserslautern Dept Math D-67663 Kaiserslautern Germany Tech Univ Munich TUM Campus Straubing D-94315 Straubing Germany

algorithms for approximating the nondominated set of multiobjective optimization problems are reviewed. The approaches are categorized into general methods that are applicable under mild assumptions and, thus, to a wide range of problems, and into algorithms that are specifically tailored to structured problems. All in all, this survey covers 52 articles published within the last 41 years, that is, between 1979 and 2020.

关键词： multiobjective optimization approximation algorithm approximate Pareto set survey

来源：评论

学校读者我要写书评

暂无评论

Maximizing k-submodular functions under budget constraint: applications and streaming algorithms

引用

JOURNAL OF COMBINATORIAL OPTIMIZATION 2022年第1期44卷 723-751页

作者： Pham, Canh, V Vu, Quang C. Ha, Dung K. T. Nguyen, Tai T. Le, Nguyen D. Phenikaa Univ Fac Comp Sci ORlab Hanoi 12116 Vietnam Peoples Secur Acad Fac Informat Secur Hanoi 10000 Vietnam Vietnam Natl Univ Univ Engn & Technol Fac Informat Technol Hanoi 10000 Vietnam Haiphong Univ Haiphong 180000 Vietnam

Motivated by the practical applications in solving plenty of important combinatorial optimization problems, this paper investigates the Budgeted k-Submodular Maximization problem defined as follows: Given a finite set V, a budget B and a k-submodular function f : (k + 1)(V) (sic) R+, the problem asks to find a solution s = (S-1, S-2,..., S-k) is an element of (k + 1)(V), in which an element e is an element of V has a cost c(i) (e) when added into the i -th set Si, with the total cost of s that does not exceed B so that f (s) is maximized. To address this problem, we propose two single pass streaming algorithms with approximation guarantees: one for the case that an element e has only one cost value when added to all i -th sets and one for the general case with different values of c(i) (e). We further investigate the performance of our algorithms in two applications of the problem, Influence Maximization with k topics and sensor placement of k types of measures. The experiment results indicate that our algorithms can return competitive results but require fewer the number of queries and running time than the state-of-the-art methods.

关键词： k-submodular Budget constraint approximation algorithm Streaming algorithm

来源：评论

学校读者我要写书评

暂无评论

Polynomial time approximation schemes for clustering in low highway dimension graphs

引用

JOURNAL OF COMPUTER AND SYSTEM SCIENCES 2021年 122卷 72-93页

作者： Feldmann, Andreas Emil Saulpic, David Charles Univ Prague Prague Czech Republic Sorbonne Univ LIP6 Paris France

We study clustering problems such as k-Median, k-Means, and Facility Location in graphs of low highway dimension, which is a graph parameter modeling transportation networks. It was previously shown that approximation schemes for these problems exist, which either run in quasi-polynomial time (assuming constant highway dimension) (Feldmann et al., 2018) [8] or run in FPT time (parameterized by the number of clusters k, the highway dimension, and the approximation factor) (Becker et al., 2018;Braverman et al., 2021) [9, 10]. In this paper we show that a polynomial-time approximation scheme (PTAS) exists (assuming constant highway dimension). We also show that the considered problems are NP-hard on graphs of highway dimension 1. (C) 2021 Elsevier Inc. All rights reserved.

关键词： approximation algorithm Highway dimension Clustering

来源：评论

学校读者我要写书评

暂无评论

Collision-free routing problem with restricted L-path

引用

DISCRETE APPLIED MATHEMATICS 2022年 319卷 71-80页

作者： Ajay, Jammigumpula Jana, Satyabrata Roy, Sasanka Media Net Bengaluru Karnataka India Indian Stat Inst Kolkata India

Given a set of vehicles that are allowed to move in a plane along a predefined directed rectilinear path, the collision-free routing problem seeks a maximum number of vehicles that can move without collision. This problem is known to be NP-hard (Ajaykumar et al., 2016). Here we study a variant of this problem called the constrained collision-free routing problem (in short, CCRP). In this problem, each vehicle is allowed only to move in a directed L-shaped path. First, we show that CCRP is NP-hard. Further, we prove that any beta-approximation algorithm for the maximum independent set problem in B-1-VPG graphs would produce a beta-approximation for CCRP. Also, we propose a 2-approximation algorithm for the maximum independent set problem on intersection graph of n unit-L frames (the union of a unit-length vertical and a unit-length horizontal line segment that shares an endpoint) with O(n) space and O(n(2)) time. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Maximum independent set Unit -L graphs approximation algorithm Collision -free Co -comparable graphs

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning Enhanced Greedy Optimization for Online Scheduling of Batched Tasks in Cloud HPC Systems

引用

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2022年第11期33卷 3003-3014页

作者： Yang, Yuanhao Shen, Hong Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou 510275 Peoples R China

In a large cloud data center HPC system, a critical problem is how to allocate the submitted tasks to heterogeneous servers that will achieve the goal of maximizing the system's gain defined as the value of completed tasks minus system operation costs. We consider this problem in the online setting that tasks arrive in batches and propose a novel deep reinforcement learning (DRL) enhanced greedy optimization algorithm of two-stage scheduling interacting task sequencing and task allocation. For task sequencing, we deploy a DRL module to predict the best allocation sequence for each arriving batch of tasks based on the knowledge (allocation strategies) learnt from previous batches. For task allocation, we propose a greedy strategy that allocates tasks to servers one by one online following the allocation sequence to maximize the total gain increase. We show that our greedy strategy has a performance guarantee of competitive ratio 1/1+kappa to the optimal offline solution, which improves the existing result for the same problem, where kappa is upper bounded by the maximum cost-to-gain ratio of each task. While our DRL module enhances the greedy algorithm by providing the likely-optimal allocation sequence for each batch of arriving tasks, our greedy strategy bounds DRL's prediction error within a proven worst-case performance guarantee for any allocation sequence. It enables a better solution quality than that obtainable from both DRL and greedy optimization alone. Extensive experiment evaluation results in both simulation and real application environments demonstrate the effectiveness and efficiency of our proposed algorithm. Compared with the state-of-the-art baselines, our algorithm increases the system gain by about 10% to 30%. Our algorithm provides an interesting example of combining machine learning (ML) and greedy optimization techniques to improve ML-based solutions with a worst-case performance guarantee for solving hard optimization problems.

关键词： Task scheduling deep reinforcement learning greedy optimization approximation algorithm

来源：评论

学校读者我要写书评

暂无评论

Data Aggregation in Low-Power Wireless Sensor Networks With Discrete Transmission Ranges: Sensor Signal Aggregation Over Graph

引用

IEEE SENSORS JOURNAL 2022年第21期22卷 21135-21144页

作者： Manuel, Ebin M. Pankajakshan, Vinod Mohan, Manil T. Indian Inst Technol Roorkee Dept Elect & Commun Roorkee 247664 Uttarakhand India Indian Inst Technol Roorkee Dept Math Roorkee 247664 Uttarakhand India

Conventional wireless sensor networks (WSNs) consist of sensors with continuous transmission range, which depends on the relative positions of the transmitter and the receiver. However, sensors with different discrete transmission ranges are preferred for future generation low-power sensor networks because of certain functional advantages. The discrete transmission ranges introduce connectivity constraints in transmitting the sensor data. The proliferation of low-power WSNs has led to the explosion of the volume of the data to be processed. As the transmission of the data is the major cause of energy depletion of sensors that critically affect the network lifetime, energy-efficient aggregation of the sensor data is an important networking problem. In this work, we address the data aggregation problem in networks with sensors of discrete transmission ranges. We model the problem as a solvable integer linear program. However, this method applies only to networks of small sizes because of the hardness of the program. To solve the problem in networks of large sizes, we introduce a graphical framework that captures the characteristics of the networks with sensors of discrete transmission ranges and design a polynomial-time approximation technique to find a solution. Furthermore, we embed compression techniques based on compressed sensing (CS), which are established to yield high data compaction for temporally and spatially correlated distributed sensor data streams, and evaluate the performance of the proposed methods.

关键词： Sensors Wireless sensor networks Distributed databases Data aggregation Sensor phenomena and characterization Overlay networks Temperature measurement approximation algorithm data aggregation integer linear program wireless sensor networks (WSNs)

来源：评论

学校读者我要写书评

暂无评论

Constrained App Data Caching Over Edge Server Graphs in Edge Computing Environment

引用

IEEE TRANSACTIONS ON SERVICES COMPUTING 2022年第5期15卷 2635-2647页

作者： Xia, Xiaoyu Chen, Feifei Grundy, John Abdelrazek, Mohamed Jin, Hai He, Qiang Deakin Univ Sch Informat Technol Geelong Vic 3220 Australia Monash Univ Fac Informat Technol Melbourne Vic 3800 Australia Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Hubei Peoples R China Swinburne Univ Technol Sch Software & Elect Engn Hawthorn Vic 3122 Australia

In recent years, edge computing, as an extension of cloud computing, has emerged as a promising paradigm for powering a variety of applications demanding low latency, e.g., virtual or augmented reality, interactive gaming, real-time navigation, etc. In the edge computing environment, edge servers are deployed at base stations to offer highly-accessible computing capacities to nearby end-users, e.g., CPU, RAM, storage, etc. From a service provider's perspective, caching app data on edge servers can ensure low latency in its users' data retrieval. Given constrained cache spaces on edge servers due to their physical sizes, the optimal data caching strategy must minimize overall user latency. In this article, we formulate this Constrained Edge Data Caching (CEDC) problem as a constrained optimization problem from the service provider's perspective and prove its NP-hardness. We propose an optimal approach named CEDC-IP to solve this CEDC problem with the Integer Programming technique. We also provide an approximation algorithm named CEDC-A for finding approximate solutions to large-scale CEDC problems efficiently and prove its approximation ratio. CEDC-IP and CEDC-A are evaluated on a real-world data set. The results demonstrate that they significantly outperform four representative approaches.

关键词： Edge computing data caching optimization approximation algorithm

来源：评论

学校读者我要写书评

暂无评论

The seeding algorithm for spherical k-means clustering with penalties

引用

JOURNAL OF COMBINATORIAL OPTIMIZATION 2022年第3期44卷 1977-1994页

作者： Ji, Sai Xu, Dachuan Guo, Longkun Li, Min Zhang, Dongmei Beijing Univ Technol Dept Operat Res & Sci Comp Beijing 100124 Peoples R China Qilu Univ Technol Shandong Acad Sci Sch Comp Sci & Technol Jinan 250353 Peoples R China Shandong Normal Univ Sch Math & Stat Jinan 250014 Peoples R China Shandong Jianzhu Univ Sch Comp Sci & Technol Jinan 250101 Peoples R China

Spherical k-means clustering as a known NP-hard variant of the k-means problem has broad applications in data mining. In contrast to k-means, it aims to partition a collection of given data distributed on a spherical surface into k sets so as to minimize the within-cluster sum of cosine dissimilarity. In the paper, we introduce spherical k-means clustering with penalties and give a 2max{2,M}(1+M)(lnk+2)-approximation algorithm. Moreover, we prove that when against spherical k-means clustering with penalties but on separable instances, our algorithm is with an approximation ratio 2max{3,M+1} with high probability, where M is the ratio of the maximal and the minimal penalty cost of the given data set.

关键词： approximation algorithm Spherical k-means clustering Penalty

来源：评论

学校读者我要写书评

暂无评论

Speed scaling scheduling of multiprocessor jobs with energy constraint and makespan criterion

引用

JOURNAL OF GLOBAL OPTIMIZATION 2022年第3期83卷 539-564页

作者： Kononov, Alexander Zakharova, Yulia RAS SB Sobolev Inst Math 4 Akad Koptyug Ave Novosibirsk 630090 Russia

We are given a set of parallel jobs that have to be executed on a set of speed-scalable processors varying their speeds dynamically. Running a job at a slower speed is more energy-efficient, however, it takes a longer time and affects the performance. Every job is characterized by the processing volume and the number or the set of the required processors. Our objective is to minimize the maximum completion time so that the energy consumption is not greater than a given energy budget. For various particular cases, we propose polynomial-time approximation algorithms, consisting of two stages. At the first stage, we give an auxiliary convex program. By solving this problem, we get processing times of jobs and a lower bound on the makespan. Then, at the second stage, we transform our problem into the corresponding scheduling problem with the constant speed of processors and construct a feasible schedule. We also obtain an "almost exact" solution for the preemptive settings based on a configuration linear program.

关键词： Multiprocessor job Speed scaling Energy Scheduling approximation algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：