The 802.11 standard defines the Wired Equivalent Privacy (WEP) and encapsulation of data frames. It is intended to provide data privacy to the level of a wired network. WEP suffered threat of attacks from hackers owing to certain security shortcomings in the WEP protocol. Lately, many new protocols like WiFi Protected Access (WPA), WPA2, Robust Secure Network (RSN) and 802.11i have come into being, yet their implementation is fairly limited. Despite its shortcomings one cannot undermine the importance of WEP as it still remains the most widely used system and we chose to address certain security issues and propose some modifications to make it more secure. In this paper we have proposed a modification to the existing WEP protocol to make it more secure. We achieve Message Privacy by ensuring that the encryption is not breached. The proposed enhancements attempt to rectify the vulnerabilities to enhance the WEP with Private IV and Session Time for improved authentication process. In the proposed algorithm we can use all possible 2 24 different IVs without making them predictable for an attacker, eliminates the IV collision ensuring Message Privacy that further strengthens security of the existing WEP.

Wireless body area networks (WBAN) have improved healthcare industries to a large extent by providing contactless measurements and remote data analysis. However, the challenges encountered are mostly in the form of energy depletion scenarios, which results in the reduction of network lifetime to a large extent. This work presents an effective model to provide energy-efficient routing and enhanced energy harvesting mechanisms to improve network lifetime. The ant colony optimization (ACO) method has been extended to include a fitness function that takes into account several factors, and this is the basis for the routing model. These processes ensure effective routing, which conserves energy and, in turn, results in enhanced network lifetime. Performance of the proposed model has been compared with the existing state-of-the-art models in the domain. Comparison with the metaheuristic-based model, cooperative energy efficient and priority based reliable routing protocol with network coding (CEPRAN), indicates the efficiency of the energy harvesting mechanism used in the proposed work. When compared with models using energy harvesting mechanisms, results exhibit higher network lifetime, depicting the efficiency of the proposed routing mechanism.

Saving the environment is the alarming red-hot topic of this trendy world. A proper arrangement is required to monitor different environmental pollutions. Many researchers and volunteers are developing and deploying Wireless Sensor Networks (WSN) for this purpose. Internet-of-Things (IoT) is one of the widely used cost-effective modern technologies to design wireless sensor nodes. Three fresh functional modules are introduced in this work to constitute the proposed work named as 'Strengthening IoT-WSN Architecture for Environmental Monitoring' (SIAEM) which is indented to overcome some impuissance of applying generalized wireless sensor network architecture in the field of environmental pollution monitoring. The functional modules introduced in this work are Customized Clustering of IoT-WSN Nodes (CCIN) and Energy Aware State Change Routing Protocol (EASCRP). The objective of this proposed IoT-WSN architecture is to reduce the Latency, Jitter, End-to-End delay and Power Consumption whereas, improving the performance parameters such as Throughput and Packet Delivery Ratio. The impact of proposed method in the performance of IoT-WSN network is measured and stated using benchmark network simulator.Assign Duty relay node to node Node will broadcast Relay_Node_Declaration message B. IoT-WSN routing protocolsNetwork protocols are a set of conventions followed in a network environment for initiating connections, manage communication resource stability, adoption of new nodes, discarding existing nodes and safely switching different connections based on the necessities. There are several types of protocols involved in a communication such as Basic network communication protocols, Network security protocols, Network routing protocols and Network management protocols. Here the routing protocols are used to establish connections by analyzing possible communication paths between source and destination nodes. The indent of a routing protocol can be communication speed, network stability, optimum power utilization or the combination of more than one objective. Commonly used protocols in IoT are Bluetooth protocol, WiFi IEEE 802.11 b/g/n, MQTT, CoAP, DDS, AMQP, LoRa and Zigbee.

The recent generation has a lot of information for analysing growth in future prediction. Especially India is an extensive agricultural resource for the world's expansive economic growth. But in extensive data analysis, a problem for the recommendation of the seasonal crop is tedious because of improper feature analysis due to varying periods in weather conditions. So time variation-based big data analysis is essential for research improvement. To resolve this problem, we propose a Timestamp feature variation-based weather prediction using multi-perception neural classification (TFV-MPNC) for successive crop recommendation in big data analysis. Initially, the pre-processing was carried out to prepare the redundant noise dataset for fast prediction. Initially, the Preprocessing ensures the Contemporary Forecasting rate (CFR) for predicting the previous deficiency rate. Based on that Time stamp feature analysis (TSFA). The Dense region harvest rate (DRHR) was evaluated, and features were decision using Fuzzy intensive decision Function (FIDF), selected the scaled features and trained with multi-perception neural classification (MPNN). The proposed system produces higher forecasting by prediction features as well supportive to the weather dependences related to higher classification rate in precision, and recall has the best classification result.

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