Analysis of New L5 Algorithm Embedded with Modified AES Algorithm in Address Allocation Schemes

Networking is ubiquitous. In this fast-moving world, routing plays a major role for a myriad of purposes in the internet space. Address allocation is a vital component in routing. It is very much important to route the packets securely to the preferred destination. The routing of packets is not as efficient as it should have been. The current routing process is tedious and time consuming. The vulnerabilities found in the AES algorithm have been exploited by hackers and sniffers. In order to overcome these backlogs, two new mathematically validated approaches, namely, new L5 routing algorithm and modifiedAES algorithm are proposed in this article. The proposed schemes circumscribe the possibilities of hacking. The mathematical exploration of the proposed schemes results in reduced time and space complexities. The newly proposed routing algorithm achieves fault tolerance, secure transmission of data and provides congestion contro

A Survey on Investigating the Need for Intelligent Power-Aware Load Balanced Routing Protocols for Handling Critical Links in MANETs

In mobile ad hoc networks connectivity is always an issue of concern. Due to dynamism in the behavior of mobile nodes, efficiency shall be achieved only with the assumption of good network infrastructure. Presence of critical links results in deterioration which should be detected in advance to retain the prevailing communication setup. This paper discusses a short survey on the specialized algorithms and protocols related to energy efficient load balancing for critical link detection in the recent literature. This paper also suggests a machine learning based hybrid power-aware approach for handling critical nodes via load balancing

A Distance Vector Hop and Differential Evolution based Interception Strategy for detecting Cross Border Infiltration in Underground Tunnel

Securing the external border of a nation through potential surveillance is considered to be highly essential for safeguarding them from terrorists and other national armies that intentionally try to conquer regions. The infiltration of trespassers and terrorists into a territory is considered to greatly influence the harmony and peace of a nation. In this context, conventional border surveillance systems safeguard the border regions based on the pre-determined routes at various time intervals. However, the intensive involvement of human in patrolling is determined as the major challenge in the process of safeguarding longer border areas. Moreover, detecting the infiltration of terrorists through the underground tunnel is considered to be the other challenge. At this juncture, wireless sensor networks are considered to be the best suitable candidate for safeguarding the external borders through real-time monitoring to attain maximized accuracy, efficiency in the detection and least human intervention. In this paper, Distance Vector-Hop (DV-Hop) and Differential Evolution (DE)-based Interception Strategy (DV-Hop-DE-IS) is proposed for accurate detection of cross border infiltration in the underground tunnel. This proposed DV-Hop-DE-IS includes the merits of converting the discrete values of hop count into a highly accurate continuous value depending on the information received from the number of shared one-hop nodes that exists between neighbouring nodes. This problem of intruder detection is formulated as the minimum optimization problem that could be optimally solved through the utilization of the Differential Evolution algorithm with maximized efficiency. The simulation results of the DV-Hop-DE-IS confirmed better detection rate, accuracy with a reduced false positive rate compared to the benchmarked intruder detection approaches