Differentiated Processing Policies for Near-real Time and Reliable Traffics in Ad Hoc Network

Author(s):  
Min Yin ◽  
Quan Yu
Keyword(s):  
2021 ◽  
Vol 12 (1) ◽  
pp. 53-72
Author(s):  
Mohsin Khan ◽  
Bhavna Arora

Connected automated vehicle (CAV) technology is the core for the new age vehicles in research phase to communicate with one another and assimilation of vehicular ad-hoc network (VANET) for the transference of data between vehicles at a quantified place and time. This manuscript is an enactment of the algorithms associated to the maintenance of secure distance amongst vehicles, lane shifting, and overtaking, which will diminish the occurrence of collisions and congestions especially phantom jams. Those implementations are centered over CAV and VANET technology for the interconnection of the vehicles and the data transmission. The data is associated to the aspects of a vehicle such as speed, position, acceleration, and acknowledgements, which acts as the fundamentals for the computation of variables. In accordance with the environment of a particular vehicle (i.e., its surrounding vehicles), real-time decisions are taken based on the real-time computation of the variables in a discrete system.


Author(s):  
Suriya Pinitkan ◽  
Nawaporn Wisitpongphan

As aging society era is getting near, number of elders who live alone is increasing. These people often need special care. Due to this reason, we propose Abnormal Activity Detection and Notification Platform (AADN) for Real-Time Ad Hoc Network which can help taking care of these people. The proposed platform relies on human tracking using cameras that are installed in different rooms inside the house. AADN will take as input images from the cameras to process and output activity in the form of human pose and objects with their relative distant to the detected human. Relationship Degree of Human Object Interaction (RD-HOI) will be analyzed every minute and be used to distinguish abnormal behavior by means of decision tree. In addition, activities will be used to generate routine behavior log and AADN will notify the person in charge of taking care of the subject if the detected activity differs from the routine. The proposed platform can achieve human pose accuracy of up to 99.66% by using COCO with VGG-NB model and can correctly identify object 68% of the time. Our experiments showed that AADN could notify abnormal activity by using RD-HOI when human and harmful objects were clearly visible in the picture and could correctly notify abnormal activity when time spent in a certain activity differed from the routine by a certain threshold given sufficient amount of data.


2014 ◽  
Vol 986-987 ◽  
pp. 2082-2085
Author(s):  
Zhi Ping Ding

Cognitive Radio Ad Hoc Network (CRAHN), established on the cognitive radio environment, configures the Ad Hoc Network which possesses the internal capacity. How to effectively control the power consumption is an important issue in the CRAHN for CRAHN‘s main power type is battery. At present, the energy-saving routing research in CRAHN is mainly based on the real-time routing mechanism. It means that it should be routed again after transferring an archive. In order to increase the network route’s surviving time and save the power consumption, it introduces a routing mechanism whose purpose is to optimize the communication algorithm’s performance by improving the existing routing mechanism in the Ad Hoc network.


Sign in / Sign up

Export Citation Format

Share Document