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Vehicular ad hoc network (VANET) is an emerging trend where vehicles communicate with each other and possibly with a roadside unit to assist various applications like monitoring, managing and optimizing the transportation system. Collaboration among vehicles is significant in VANET. Resource constraint is one of the great challenges of VANETs. Because of the absence of centralized management, there is pitfall in optimal resource allocation, which leads to ineffective routing. Effective reliable routing is quite essential to achieve intelligent transportation. Stochastic dynamic programming is currently employed as a tool to analyse, develop and solve network resource constraint and allocation issues of resources in VANET. We have considered this work as a geographical-angular-zone-based two-phase dynamic resource allocation problem with a homogeneous resource class. This work uses a stochastic dynamic programming algorithm based on relaxed approximation to generate optimal resource allocation strategies over time in response to past task completion status history. The second phase resource allocation uses the observed outcome of the first phase task completion to provide optimal viability in resulting decisions. The proposed work will be further extended for the scenario that deals with heterogeneous resource class. Simulation results show that the proposed scheme works significantly well for the problems with identical resources.

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In this digital era, technological importance has been excellent support for making decisions in agriculture. The development of agriculture has been under development for the past few years due to a lack of technology usage and environmental changes. The aim of this paper is to reach farmers marketing through technology. The study used a statistical survey design technique to collect data from farmers for their awareness of e-Commerce. E-Agriculture is a platform to support the marketing of agricultural products. The main objective of our project is to establish a bridge between a farmer and a customer. The price will be fixed by the farmers, and there is no intermediate between farmers and the customers. So the customers also get their products (vegetables/fruits/grains, etc…) at the actual price, and also, the farmers get the right estimate from a customer.

A cognitive wireless powered communication network (CWPCN) for spectrum distribution in IoMT based healthcare systems is employed with a principal network, which in turn deals with security issues from various attacks like Denial of Service (DoS), Man-In-the-Middle, or phishing attacks. In this, a new protocol is proposed for wireless powered SU (secondary users) so as to cooperate with PU (primary user) of the healthcare network. At the time of wireless power transfer (WPT) in a IoMT based healthcare network, the first harvest energy of SUs was carried from power signals broadcasted by the cognitive hybrid access point. Then the harvested energy is employed while gaining transmission opportunities simultaneously all through the phase of Wireless Information Transfer (WIT) of healthcare system. Furthermore, Fuzzy based cluster greedy algorithm is introduced for reducing the interruption of PU secrecy prospect and to offer the best optimal values in the healthcare data. In this approach, the injection impact and reactive jamming attacks on wireless transmission are analyzed. These can be recognized through a Convolutional Neural Network (CNN) to detect different attack types and classify them. Finally, the results were compared with the existing method.