An Effective Path Selection Strategy for Mutation Testing

2009 ◽  
Author(s):  
Mike Papadakis ◽  
Nicos Malevris
Keyword(s):  
Mutation Testing ◽  
Path Selection ◽  
Selection Strategy ◽  
Effective Path

A MPTCP Path Selection Strategy Based on Improved Grey Relational Analysis

2013 ◽  
Vol 401-403 ◽  
pp. 1766-1771 ◽  
Author(s):  
Lan Kou ◽  
Si Rui Chen ◽  
Rui Wang
Keyword(s):  
Transmission Control Protocol ◽  
Path Selection ◽  
Transport Layer ◽  
Reference Sequence ◽  
Gray Relational Analysis ◽  
Selection Strategy ◽  
Relational Analysis ◽  
Multiple Paths ◽  
End To End ◽  
Grey Relational

Multipath Transmission Control Protocol (MPTCP), a transport layer protocol, proposed by the IETF working group in 2009, can provide multipath communication end to end. It also can improve the utilization of network resources and network transmission reliability. However, that how to select multiple paths to improve the end to end overall throughput, and how to avoid the throughput declining by the performance difference, become the focus of this study. We propose a path selection strategy based on improved gray relational analysis, and set the optimal values of the QoS parameters for the selected paths as the reference sequence. According to the value of improved grey relational degree (IGRD) which is compared with reference sequence, we select the paths with better performance, smaller difference for transmission.

scholarly journals Fuzzy Based Obstacle Navigation and Effective Path Selection with Laser Range Finder

2014 ◽  
Vol 14 (14) ◽  
pp. 1594-1599
Author(s):  
P. Prasanna ◽  
S. Sethuraman ◽  
N.S. Manigandan ◽  
K. Ramkumar
Keyword(s):  
Path Selection ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range ◽  
Effective Path

scholarly journals TWO NEW PEDESTRIAN NAVIGATION PATH OPTIONS BASED ON SEMI-INDOOR SPACE

2020 ◽  
Vol VI-4/W1-2020 ◽  
pp. 175-182
Author(s):  
J. Yan ◽  
S. Zlatanova ◽  
A. A. Diakite
Keyword(s):  
Path Selection ◽  
Selection Strategy ◽  
Navigation Systems ◽  
Indoor Space ◽  
Pedestrian Navigation ◽  
Navigation Path ◽  
Shortest Distance ◽  
Making Choices ◽  
Navigation Experience ◽  
Indoor Spaces

Abstract. Navigation is very critical for our daily life, especially when we have to go through the unfamiliar areas where the spaces are very complex, such as completely bounded (indoor), partially bounded (semi-indoor and/or semi-outdoor), entirely open (outdoor), or combined. Current navigation systems commonly offer the shortest distance/time path, but it is not always appropriate for some situations. For instance, on a rainy day, a path with as many places that are covered by roofs/shelters is more attractive. However, current navigation systems cannot provide such kinds of navigation paths, which can be explained by that they lack information about such roofed/sheltered-covered spaces. This paper proposes two roofed/sheltered navigation path options by employing semi-indoor spaces in the navigation map: (i) the Most-Top-Covered path (MTC-path) and (ii) path to the Nearest sI-space from departure (NSI-path). A path selection strategy is introduced to help pedestrians in making choices between the two new path options and the traditional shortest path. We demonstrate and validate the research with path planning on two navigation cases. The results show the two path options and the path selection strategy bring in new navigation experience for humans.

Mobile Robot Decision-Making Based on Offline Simulation for Navigation over Uneven Terrain

2018 ◽  
Vol 30 (4) ◽  
pp. 671-682
Author(s):  
Yuichi Kobayashi ◽  
Masato Kondo ◽  
Yuji Hiramatsu ◽  
Hokuto Fujii ◽  
Tsuyoshi Kamiya ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Path Selection ◽  
Outdoor Environment ◽  
Selection Strategy ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicle ◽  
Uneven Terrain ◽  
Simulated Environment ◽  
Terrain Features ◽  
Selection Of

This paper presents an action decision framework for an autonomous mobile robot or an unmanned ground vehicle (UGV) to navigate an unknown environment. It is difficult for a UGV without global map information to decide which path to travel when it comes to a fork. However, locally observed terrain features can enable the UGV if it can utilize its past experience. The proposed path selection method utilizes correlations between features of the local terrain obtained by its laser range finder and the values of paths obtained through offline simulation using global path planning. During navigation, the UGV estimates the values of each path at a fork based on the correlation between the terrain feature and the value. It was confirmed that the proposed method allows the selection of paths that are more effective compared with a simple path selection strategy with which the UGV selects the closer path to the goal. The proposed method was evaluated in both a simulated environment and a real outdoor environment.

Resolving Unordered Issues for CMT-SCTP in Heterogeneous Wireless Network

2013 ◽  
Vol 380-384 ◽  
pp. 2152-2156
Author(s):  
Ye Peng Ni ◽  
Xiao Sen Chen ◽  
Jian Bo Liu
Keyword(s):  
Wireless Network ◽  
Packet Scheduling ◽  
Scheduling Algorithm ◽  
Main Idea ◽  
Path Selection ◽  
Selection Strategy ◽  
Heterogeneous Wireless Network ◽  
Available Bandwidth ◽  
Network Bandwidth ◽  
The Right

Concurrent Multi-path Transfer extension of the Stream Control Transport Protocol (CMT-SCTP) has great potential to improve the utilization of scarce network bandwidth resource. Traditional CMT-SCTP adopts Round Robin (RR) algorithms to carry out packet scheduling that could affect the performance of SCTP traffic as unordered issues. In this paper, we discuss the unordered issues and propose a novel packet scheduling algorithm to improve the performance in heterogeneous wireless network. Our main idea is predicting the packet arriving time and then provides a path selection strategy. Through measuring round-trip time (RTT) and available bandwidth, we achieve an algorithm to predict the arriving time of data packets on one path, then give a reasonable path selection strategy to make sure that data arrives in the right order. By using proposed algorithm, the unordered packets and receive buffer blocking are reduced. We evaluate the performance of our algorithm by comparing it with the RR algorithm and show that it can resolve several performance issues.

scholarly journals A Fuzzy Path Selection Strategy for Aircraft Landing on the Carrier

2018 ◽  
Author(s):  
Xichao Su ◽  
Yu Wu ◽  
Jingyu Song ◽  
Peilong Yuan
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Experimental Studies ◽  
Essential Elements ◽  
Path Selection ◽  
Selection Strategy ◽  
Aircraft Carrier ◽  
Aircraft Landing ◽  
Flight Deck

Landing is one of the most dangerous tasks in all the operations on the aircraft carrier, and the landing safety is very important to the pilot and the flight deck operation. The problem of landing path selection is studied in this paper as there several candidates corresponding to different situations. A fuzzy path selection strategy is proposed to solve the problem considering the fuzziness of environmental information and human judgment, and the goal is to provide the pilot with more reasonable decision. The strategy is based on Fuzzy Multi-attribute Group Decision Making (FMAGDM), which has been widely used in industry. Firstly, the background of the path selection problem is given. Then the essential elements of the problem are abstracted to build the conceptual model. A group decision-making method is applied to denote the preference of each decision maker for each alternative route, and the optimal landing path under the current environment is determined taking into account the knowledge and the weight of both decision makers. Experimental studies under different setups, i.e., different environments, are carried out. The results demonstrate that the proposed path selection strategy is validated in different environments, and the optimal landing paths corresponding to different environments can be determined.

scholarly journals Effective Path Determination Strategy for Mobile Sink in WSN

2019 ◽  
Vol 8 (3) ◽  
pp. 2442-2445
Keyword(s):  
Performance Metrics ◽  
Optimization Method ◽  
Mobile Sink ◽  
Path Selection ◽  
Data Problem ◽  
Minimum Number ◽  
Selection For ◽  
Effective Path ◽  
Rendezvous Points ◽  
Selection Of

In Wireless Sensor Network the delay in delivery of data problem can be reduced by using mobile sink. Mobility of the sink has been demonstrated to be the best method to reduce delay in the network. So the path selection for the movement of the sink plays an important role. Hence the selection of minimum number of stopping points are called Rendezvous Points (RPs) is very challenging in WSNs. So a productive procedure was proposed to choose the RPs to develop path for moving sink. At first set of potential points will be generated by using a technique and then using greedy algorithm the RPs were selected from the potential points set. Then an optimization method is used to get still more optimized points. At that point these points are utilized to select path for sink. Proposed algorithm was simulated with some current algorithms and results will be compared based on different performance metrics to demonstrate the viability of the present work.

scholarly journals Self-Adjusting Ant Colony Optimization Based on Information Entropy for Detecting Epistatic Interactions

Genes ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 114 ◽  
Author(s):  
Boxin Guan ◽  
Yuhai Zhao
Keyword(s):  
Ant Colony Optimization ◽  
Information Entropy ◽  
Large Scale ◽  
Association Studies ◽  
Detection Algorithm ◽  
Path Selection ◽  
Ant Colony ◽  
Selection Strategy ◽  
Nucleotide Polymorphisms ◽  
Epistatic Interactions

The epistatic interactions of single nucleotide polymorphisms (SNPs) are considered to be an important factor in determining the susceptibility of individuals to complex diseases. Although many methods have been proposed to detect such interactions, the development of detection algorithm is still ongoing due to the computational burden in large-scale association studies. In this paper, to deal with the intensive computing problem of detecting epistatic interactions in large-scale datasets, a self-adjusting ant colony optimization based on information entropy (IEACO) is proposed. The algorithm can automatically self-adjust the path selection strategy according to the real-time information entropy. The performance of IEACO is compared with that of ant colony optimization (ACO), AntEpiSeeker, AntMiner, and epiACO on a set of simulated datasets and a real genome-wide dataset. The results of extensive experiments show that the proposed method is superior to the other methods.

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