Vehicular Ad hoc Networks (VANETs), a subsection of Mobile Ad hoc Networks (MANETs), have strong future application prospects. Because topology structures are rapidly changing, determining a route that can guarantee a good Quality of Service (QoS) is a critical issue in VANETs. Routing is a critical component that must be addressed in order to utilize effective communication among vehicles. The purpose obtained from this study is to compare the AODV and GPSR performance in terms of Packet Delivery Ratio, Packet Drop Ratio, Throughput, and End-to-End Delay by applying three scenarios, the first scenario focuses on studying these protocols in terms of QoS while changing the number of vehicles at a constant speed of 40Km/h, and for the second scenario changing the speed value while keeping a constant number of vehicles which is 100, the third involves changing the communication range at a constant speed and vehicle number. This study represents a foundation for researchers to help elaborate on the strength and weaknesses of these two protocols. OMNeT++ in conjunction with SUMO is used for simulation.
The objective in Data Grids is to reduce access and file (replica) transfer latencies, as well as to avoid single site congestion by the numerous requesters. To facilitate access and transfer of the data, the files of the Data Grid are distributed across the multiple sites. The effectiveness of a replica selection strategy in data grids depends on its ability to serve the requirement posed by the users' jobs. Most jobs are required to be executed at a specific execution time. To achieve the QoS perceived by the users, response time metrics should take into account a replica selection strategy. Total execution time needs to factor latencies due to network transfer rates and latencies due to search and location. Network resources affect the speed of moving the required data and searching methods can reduce scope for replica selection. This paper presents a replica selection strategy that adapts its criteria dynamically so as to best approximate application providers’ and clients’ requirements. We introduce a new selection technique (EST) that shows improved performance over the more common algorithms.