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Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
Towards Detecting, Characterizing, And Rating Of Road Class Errors In Crowd-Sourced Road Network Databases, Johanna Guth, Sina Keller, Stefan Hinz, Stephan Winter
Towards Detecting, Characterizing, And Rating Of Road Class Errors In Crowd-Sourced Road Network Databases, Johanna Guth, Sina Keller, Stefan Hinz, Stephan Winter
Journal of Spatial Information Science
OpenStreetMap (OSM), with its global coverage and Open Database License, has recently gained popularity. Its quality is adequate for many applications, but since it is crowd-sourced, errors remain an issue. Errors in associated tags of the road network, for example, are impacting routing applications. Particularly road classification errors often lead to false assumptions about capacity, maximum speed, or road quality, possibly resulting in detours for routing applications. This study aims at finding potential classification errors automatically, which can then be checked and corrected by a human expert. We develop a novel approach to detect road classification errors in OSM by …
Step-Wise Deep Learning Models For Solving Routing Problems, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang
Step-Wise Deep Learning Models For Solving Routing Problems, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang
Research Collection School Of Computing and Information Systems
Routing problems are very important in intelligent transportation systems. Recently, a number of deep learning-based methods are proposed to automatically learn construction heuristics for solving routing problems. However, these methods do not completely follow Bellman's Principle of Optimality since the visited nodes during construction are still included in the following subtasks, resulting in suboptimal policies. In this article, we propose a novel step-wise scheme which explicitly removes the visited nodes in each node selection step. We apply this scheme to two representative deep models for routing problems, pointer network and transformer attention model (TAM), and significantly improve the performance of …
Multi-Decoder Attention Model With Embedding Glimpse For Solving Vehicle Routing Problems, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang
Multi-Decoder Attention Model With Embedding Glimpse For Solving Vehicle Routing Problems, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang
Research Collection School Of Computing and Information Systems
We present a novel deep reinforcement learning method to learn construction heuristics for vehicle routing problems. In specific, we propose a Multi-Decoder Attention Model (MDAM) to train multiple diverse policies, which effectively increases the chance of finding good solutions compared with existing methods that train only one policy. A customized beam search strategy is designed to fully exploit the diversity of MDAM. In addition, we propose an Embedding Glimpse layer in MDAM based on the recursive nature of construction, which can improve the quality of each policy by providing more informative embeddings. Extensive experiments on six different routing problems show …
Application-Aware Cross-Layer Enrgy-Eficient Routing Scheme, Xu Fang, Hiyin Zhang, Wang Jing, Xu Ning, Zhijong Wang, Deng Min
Application-Aware Cross-Layer Enrgy-Eficient Routing Scheme, Xu Fang, Hiyin Zhang, Wang Jing, Xu Ning, Zhijong Wang, Deng Min
Journal of System Simulation
Abstract: An aplication- aware cross-layer energy-effcient routing scheme (ACER) was presented to minimize the effect of supplt of terminals in ad hoc network composed of smart mobile devices. Features of energy consumption were sensed by application aware energy model with the application monitor and the remaining energy monitor. Stability of network path was monitored by link stability monitoring module in Data link layer. As the scheme used the idea of cross-layer design, network topology information, application-aware information in application layer and link-stability were utilized synthetically to make routing deisions in network layer;Simulations were crried out on NS2 platform. The …
Preforming A Vulnerability Assessment On A Secured Network, Mathias Sovine
Preforming A Vulnerability Assessment On A Secured Network, Mathias Sovine
Williams Honors College, Honors Research Projects
A computer network will be built using 3 routers, 1 switch, and 4 computers. The network will be used to simulate the connections between an at home office and the internet. The network will be divided into 3 sub-networks. The routers will be secured using methods like access control lists, changing default admin passwords, and network encryption. The switch will be secured using methods like switchport security and setting access passwords. Once the network is secured, three penetration testing techniques and three exploits will be performed on the network. The results of the exploits and penetration testing techniques will be …
Data And Resource Management In Wireless Networks Via Data Compression, Gps-Free Dissemination, And Learning, Xiaofei Cao
Data And Resource Management In Wireless Networks Via Data Compression, Gps-Free Dissemination, And Learning, Xiaofei Cao
Doctoral Dissertations
“This research proposes several innovative approaches to collect data efficiently from large scale WSNs. First, a Z-compression algorithm has been proposed which exploits the temporal locality of the multi-dimensional sensing data and adapts the Z-order encoding algorithm to map multi-dimensional data to a one-dimensional data stream. The extended version of Z-compression adapts itself to working in low power WSNs running under low power listening (LPL) mode, and comprehensively analyzes its performance compressing both real-world and synthetic datasets. Second, it proposed an efficient geospatial based data collection scheme for IoTs that reduces redundant rebroadcast of up to 95% by only collecting …