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AODV is a mature and widely accepted routing protocol for Mobile Ad hoc Networks (MANET), it has low processing and memory overhead and low network utilization, and works well even in high mobility situation. We modified AODV to use these dominating sets, resulting in the AODV-DS protocol. Our contribution in addressing the fragility of a minimum connected dominating set in the presence of mobility and cross-traffic. We develop three heuristics to fortify the dominating set process against loss by re-introducing some redundancy using a least-first set cover rather than a greedy set cover. AODV-DS exhibits about a 70% savings in RREQ traffic while maintaining the same or better latency and delivery ratio for 30 source nodes in a graph of 50 nodes. It was also about as fair as conventional AODV in distributing the RREQ burden among all nodes, except in cases of low-mobility and few source nodes. For low-mobility networks, it was not as fair to forwarding nodes as AODV, but better than AODV with Dominant Pruning (DP)

Global warming and climate change are responsible for many disasters. Floods pose a serious risk and require immediate management and strategies for optimal response times. Technology can respond in place of humans in emergencies by providing information. As one of these emerging artificial intelligence (AI) technologies, drones are controlled in their amended systems by unmanned aerial vehicles (UAVs). In this study, we propose a secure method of flood detection in Saudi Arabia using a Flood Detection Secure System (FDSS) based on deep active learning (DeepAL) based classification model in federated learning to minimize communication costs and maximize global learning accuracy. We use blockchain-based federated learning and partially homomorphic encryption (PHE) for privacy protection and stochastic gradient descent (SGD) to share optimal solutions. InterPlanetary File System (IPFS) addresses issues with limited block storage and issues posed by high gradients of information transmitted in blockchains. In addition to enhancing security, FDSS can prevent malicious users from compromising or altering data. Utilizing images and IoT data, FDSS can train local models that detect and monitor floods. A homomorphic encryption technique is used to encrypt each locally trained model and gradient to achieve ciphertext-level model aggregation and model filtering, which ensures that the local models can be verified while maintaining privacy. The proposed FDSS enabled us to estimate the flooded areas and track the rapid changes in dam water levels to gauge the flood threat. The proposed methodology is straightforward, easily adaptable, and offers recommendations for Saudi Arabian decision-makers and local administrators to address the growing danger of flooding. This study concludes with a discussion of the proposed method and its challenges in managing floods in remote regions using artificial intelligence and blockchain technology.

The various routing protocols in Mobile Ad hoc Networks follow different strategies to send the information from one node to another. The nodes in the network are non static and they move randomly and are prone to link failure which makes always to find new routes to the destination. This research mainly focused on the study of the characteristics of multipath routing protocols in MANETS. Two of the multipath routing protocols were investigated and a comparative study along with simulation using NS2 was done between DSR and AODV to propose an enhanced approach to reach the destination maintaining the QoS. A possible optimization to the DSR and AODV routing protocols was proposed to make no node to be overburdened by distributing the load after finding the alternate multipath routes which were discovered in the Route discovery process. The simulation shows that the differences in the protocol highlighted major differences with the protocol performance. These differences have been analyzed with various network size, mobility, and network load. A new search table named Search of Next Node Enquiry Table (SONNET) was proposed to find the best neighbor node. Using SONNET the node selects the neighbor which can be reached in less number of hops and with less time delay and maintaining the QoS.

Abstract:In modern distributed systems, replication receives particular attention for providing high data availability, fault tolerance and enhance the performance of the system. It is an important mechanism because it enables organizations to provide users with access to current data where and when they need it. However, this way of data organization introduces low data consistency and data coherency as more than one replicated copies need to be updated. Expensive synchronization mechanisms are needed to maintain the consistency and integrity of data among replicas when changes are made by the transactions. In this paper, we present Neighbor Replication on Grid (NRG) daemon in order to manage replication and transactions in distributed system. NRG Transaction Model has been implemented in order to preserve the data consistency and availability. Based on experiment and result, it shows that NRG daemon guarantees consistency and obey serializability through the synchronization approach.