The exponential rise in wireless communication systems and allied applications has revitalized academiaindustries to achieve more efficient data transmission system to meet Quality-of-Service (QoS) demands. Amongst major wireless communication techniques, Mobile Ad-hoc Network (MANET) is found potential to provide decentralized and infrastructure less communication among multiple distributed nodes across network region. However, dynamic network conditions such as changing topology, congestion, packet drop, intrusion possibilities etc often make MANET's routing a tedious task. On the other hand, mobile network feature broadens the horizon for intruders to penetrate the network and causes performance degradation. Unlike classical MANET protocols where major efforts have been made on single network parameter based routing decision, this research paper proposes a novel Elitist Genetic Algorithm (EGA) Multi-Objective Optimization assisted Network Condition Aware QoS-Routing Protocol for Mobile Ad-hoc Networks (MNCQM). Our proposed MNCQM protocol exhibits two phase implementation where at first it performs node-profiling under dynamic network topology for which three factors; irregular MAC information exchange, queuing overflow and topological variations have been considered. Towards this objective node features like Packet Forwarding Probability (PFP) at the MAC layer, Success Probability of Data Transmission (SPDT) of a neighboring node, and Probability of Successful Data Delivery (PSDD) have been obtained to estimate Node-Trustworthiness Index (NTI), which is further used to eliminate untrustworthy nodes. In the second phase of implementation, a novel Evolutionary Computing assisted nondisjoint best forwarding path selection model is developed that exploits node's and allied link's connectivity and availability features to identify the quasi-sub-optimal forwarding paths. EGA algorithm intends to reduce hop-counts, connectivity-loss and node or link unavailability to estimate best forwarding node. One key feature of the proposed model is dual-supplementary forwarding path selection that enables alternate path formation in case of link outage and thus avoids any iterative network discovery phase.

The decentralized and infrastructure less feature of Mobile Ad-hoc network (MANET) has made it a potential networking solution to be used in major applications ranging natural disaster management, vehicular communication, industrial communication etc. Though, being a dominating mobile communication system, exceedingly high network topology and mobility pattern in MANETs make it trivial to achieve Quality of Service (QoS) delivery, particularly for event-driven (mission-critical) communication. With this motivation, in this research paper a robust QoS Oriented Cross-Synch Routing Protocol for Event Driven, Mission-Critical Communication named Q-CSRPM has been developed for MANET. The proposed Q-CSRPM routing protocol exploits cross-layer routing architecture by applying network layer, MAC layer and physical layer information of IEEE 802.11 standard to perform optimal best forwarding node selection and reliable path formation. Q-CSRPM protocol performed proactive node management, service differentiation based data prioritization and resource scheduling, and dynamic buffer assessment based congestion detection at the network layer, dynamic link quality estimation and packet velocity estimation at the MAC layer, and PHY switching control at the physical layer of the protocol stack. Q-CSRPM applies dynamic link quality, congestion probability and packet velocity of a node for best forwarding node selection to form forwarding path. The node information sharing across the layers of protocol stack enables optimal BFN selection and routing control. It strengthened Q-CSRPM to exhibit 98.2% and 93% of packet delivery ratio for real time data and non-real time data respectively. A minimum of 2% deadline miss ratio was observed.

The exponential rise in wireless communication systems and allied applications has revitalized academiaindustries to achieve more efficient data transmission system to meet Quality-of-Service (QoS) demands. Amongst major wireless communication techniques, Mobile Ad-hoc Network (MANET) is found potential to provide decentralized and infrastructure less communication among multiple distributed nodes across network region. However, dynamic network conditions such as changing topology, congestion, packet drop, intrusion possibilities etc often make MANET's routing a tedious task. On the other hand, mobile network feature broadens the horizon for intruders to penetrate the network and causes performance degradation. Unlike classical MANET protocols where major efforts have been made on single network parameter based routing decision, this research paper proposes a novel Elitist Genetic Algorithm (EGA) Multi-Objective Optimization assisted Network Condition Aware QoS-Routing Protocol for Mobile Ad-hoc Networks (MNCQM). Our proposed MNCQM protocol exhibits two phase implementation where at first it performs node-profiling under dynamic network topology for which three factors; irregular MAC information exchange, queuing overflow and topological variations have been considered. Towards this objective node features like Packet Forwarding Probability (PFP) at the MAC layer, Success Probability of Data Transmission (SPDT) of a neighboring node, and Probability of Successful Data Delivery (PSDD) have been obtained to estimate Node-Trustworthiness Index (NTI), which is further used to eliminate untrustworthy nodes. In the second phase of implementation, a novel Evolutionary Computing assisted nondisjoint best forwarding path selection model is developed that exploits node's and allied link's connectivity and availability features to identify the quasi-sub-optimal forwarding paths. EGA algorithm intends to reduce hop-counts, connectivity-loss and node or link unavailability to estimate best forwarding node. One key feature of the proposed model is dual-supplementary forwarding path selection that enables alternate path formation in case of link outage and thus avoids any iterative network discovery phase.

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India is a highly populated country and with this comes the problem of transportation and logistics involved with accommodating the transportation of people and goods all over the nation. Infrastructure such as roads, highways and toll booths is a huge undertaking in terms of state finances, resulting in delayed improvements and maintenance to the transportation system around the country. With a population of this size, a high amount of vehicle traffic is to be expected in the transportation sector. This increases the chances of accidents which results in the loss of innocent lives, time, and goods. To solve this problem, we introduce a novel idea of a Virtual Toll counter with an Accident control mechanism system based on GPS. By comparing the position of the vehicle and the toll plaza, the owner of the vehicle can be charged from the account. We suggest using GPS to set up geofences by providing the latitude and longitude of the toll plaza's corner as a solution. The owner of the car can have their account debited by comparing the position of the vehicle and the toll plaza. This system can serve up to 300 vehicles per hour. The accident alarm system, also based on GPS, sends an emergency notification to the nearest first aid centre moments after the accident has occurred using a GSM module & coordinates the incident through a GPS module. In the unusual instance of no casualties, a switch is provided to stop the message from being sent. This can help the medical rescue team save valuable time.