Enhanced dynamic source routing for verifying trust in mobile ad hoc network for secure routing

Secure data transfer in mobile ad hoc network (MANET) against malicious attacks is of immense importance. In this paper, we propose a new enhanced trust model for securing the MANET using trust-based scheme that uses both blind trust and referential trust. In order to do this, the trust relationship function has to be integrated with the dynamic source routing (DSR) protocol for making the protocol more secure. We thoroughly analyze the DSR protocol and generate the performance matrices for the data pertaining to packets sent, packets received, packets loss, and throughput. We also analyze the outcome attained from the improvised trust establishment scheme by using the three algorithm implementations in NS2 simulator for detecting and preventing various types of attacks.

Smart Resource Allocation Scheme for Mimo Microstrip Wireless Communication

In this paper we have proposed a minimum noise shortest path determination scheme considering the amount of delay and energy consumed with respect to each path. An artificial neural network has been employed for classifying the minimum noise shortest path from the source to destination. A simulation work has been carried out with respect to different Signal-to-Noise (SNR) values in a thirty-node network with one Internet node and 100 bits of message length. Also, a comparison has been made between plain Dynamic Source Routing (DSR) and integrating the minimum noise shortest path algorithm with DSR. The simulation results show that with the increase of SNR, noise constraint in the path reduces, and data throughput increases.

Source Routing for Distributed Big Data-Based Cognitive Internet of Things (CIoT)

Dynamic opportunistic channel access with software-defined radio at a network layer in distributed cognitive IoT introduces a concurrent channel selection along with end-to-end route selection for application data transmission. State-of-the-art cognitive IoT big data-based routing protocols are not explored in terms of how the spectrum management is being coordinated with the network layer for concurrent channel route selection during end-to-end channel route discovery for data transmission of IoT and big data applications. In this paper, a reactive big data-based “cognitive dynamic source routing protocol” is proposed for cognitive-based IoT networks to concurrently select the channel route at the network layer from source to destination. Experimental results show that the proposed protocol cognitive DSR with concurrent channel route selection criteria is outperformed. This will happen when it is compared with the existing distributed cognitive DSR with independent channel route application data transmission.

Scalable and Reliable Data Center Networks by Combining Source Routing and Automatic Labelling

Today, most user services are based on cloud computing, which leverages data center networks (DCNs) to efficiently route its communications. These networks process high volumes of traffic and require exhaustive failure management. Furthermore, expanding these networks is usually costly due to their constraint designs. In this article, we present enhanced Torii (eTorii), an automatic, scalable, reliable and flexible multipath routing protocol that aims to accomplish the demanding requirements of DCNs. We prove that eTorii is, by definition, applicable to a wide range of DCNs or any other type of hierarchical network and able to route with minimum forwarding table size and capable of rerouting around failed links on-the-fly with almost zero cost. A proof of concept of the eTorii protocol has been implemented using the Ryu SDN controller and the Mininet framework. Its evaluation shows that eTorii balances the load and preserves high-bandwidth utilization. Thus, it optimizes the use of DCN resources in comparison to other approaches, such as Equal-Cost Multi-Path (ECMP).

A dynamic source routing protocol based on path reliability and link monitoring repair

The two most essential factors for mobile self-organizing networks applicable to drones are reliability and stability. In harsh communication environments, such as mountainous regions and natural disasters, the use of satellites and terrestrial communication stations has severe time delays due to the high speed of UAVs, resulting in frequent communication interruptions with UAVs. Therefore, UAVs need to establish self-organizing networks for communication and information sharing. High-speed movement will lead to rapid changes in the network topology, resulting in established links being in an unstable connection state and even frequent routing errors, thus preventing the establishment of stable communication links. In order to improve the communication quality of UAVs under high-speed movement, we propose a dynamic source routing protocol based on path reliability and monitoring repair mechanism (DSR-PM). The model performs data transmission by filtering the best reliability path. The link state information is monitored during transmission and broken links are repaired in time to ensure the communication stability and reliability of the links and improve the data transmission efficiency. We simulated the approach in NS2 software and the simulation results show that the DSR-PM protocol effectively reduces parameters such as overhead, packet loss and delay, improves network throughput, and provides better communication performance.