scholarly journals Automatic Route Search Algorithm for Examination of Electric Power Facilities Installation Work

1994 ◽  
Vol 114 (2) ◽  
pp. 223-232
Author(s):  
Fujiwa Kato ◽  
Takao Noguchi ◽  
Tetsuji Santo ◽  
Kazufumi Kaneda ◽  
Eihachiro Nakamae
2013 ◽  
Vol 33 (5) ◽  
pp. 1194-1196
Author(s):  
Fei DU ◽  
Zhiguo DONG ◽  
Lin MIAO ◽  
Yupeng TUO

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3945
Author(s):  
Muhammad Sohail ◽  
Rashid Ali ◽  
Muhammad Kashif ◽  
Sher Ali ◽  
Sumet Mehta ◽  
...  

The Internet of Things (IoT) is a world of connected networks and modern technology devices, among them vehicular networks considered more challenging due to high speed and network dynamics. Future trends in IoT allow these inter networks to share information. Also, the previous security solutions to vehicular IoT (VIoT) much emphasize on privacy protection and security related issues using public keys infrastructure. However, the primary concern about efficient trust assessment, authorized users malfunctioning, and secure information dissemination in vehicular wireless networks have not been explored. To cope with these challenges, we propose a trust enhanced on-demand routing (TER) scheme, which adopts TrustWalker (TW) algorithm for efficient trust assessment and route search technique in VIoT. TER comprised of novel three-valued subjective logic (3VSL), TW algorithm, and ad hoc on-demand distance vector (AODV) routing protocol. The simulated results validate the accuracy of the proposed scheme in term of throughput, packet drop ratio (PDR), and end to end (E2E) delay. In the simulation, the execution time of the TW algorithm is analyzed and compared with another route search algorithm, i.e., Assess-Trust (AT), by considering real-world online datasets such as Pretty Good Privacy and Advogato. The accuracy and efficiency of the TW algorithm, even with a large number of vehicle users, are also demonstrated through simulations.


2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
De-Xin Yu ◽  
Zhao-Sheng Yang ◽  
Yao Yu ◽  
Xiu-Rong Jiang

Combined with improved Pallottino parallel algorithm, this paper proposes a large-scale route search method, which considers travelers’ route choice preferences. And urban road network is decomposed into multilayers effectively. Utilizing generalized travel time as road impedance function, the method builds a new multilayer and multitasking road network data storage structure with object-oriented class definition. Then, the proposed path search algorithm is verified by using the real road network of Guangzhou city as an example. By the sensitive experiments, we make a comparative analysis of the proposed path search method with the current advanced optimal path algorithms. The results demonstrate that the proposed method can increase the road network search efficiency by more than 16% under different search proportion requests, node numbers, and computing process numbers, respectively. Therefore, this method is a great breakthrough in the guidance field of urban road network.


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