Nowadays, networks use many different paths to exchange data. However, our research will construct a reliable path in the networks among a huge number of nodes for use in tele-surgery using medical applications such as healthcare tracking applications, including tele-surgery which lead to optimizing medical quality of service (m-QoS) during the COVID-19 situation. Many people could not travel due to the current issues, for fear of spreading the covid-19 virus. Therefore, our paper will provide a very trusted and reliable method of communication between a doctor and his patient so that the latter can do his operation even from a far distance. The communication between the doctor and his/her patient will be monitored by our proposed algorithm to make sure that the data will be received without delay. We test how we can invest buffer space that can be used efficiently to reduce delays between source and destination, avoiding loss of high-priority data packets. The results are presented in three stages. First, we show how to obtain the greatest possible reduction in rate variability when the surgeon begins an operation using live streaming. Second, the proposed algorithm reduces congestion on the determined path used for the online surgery. Third, we have evaluated the affection of optimal smoothing algorithm on the network parameters such as peak-to-mean ratio and delay to optimize m-QoS. We propose a new Smart-Rout Control algorithm (s-RCA) for creating a virtual smart path between source and destination to transfer the required data traffic between them, considering the number of hops and link delay. This provides a reliable connection that can be used in healthcare surgery to guarantee that all instructions are received without any delay, to be executed instantly. This idea can improve m-QoS in distance surgery, with trusted paths. The new s-RCA can be adapted with an existing routing protocol to track the primary path and monitor emergency packets received in node buffers, for direct forwarding via the demand path, with extended features.
Cloud computing technology has proved to be an important technological solution, especially for small and medium- sized businesses (SMEs), by providing many opportunities for companies to enhance their operations, reduce cost, improve scalability and flexibility, and make more efficient use of technology. Despite its benefits, most SMEs are still hesitant about adopting cloud computing. The purpose of this study is to assess the factors that influence cloud computing adoption among SMEs in Jordan. This study does so by developing a research model based on the Technology Organization Environment (TOE) and Diffusion of Innovation (DOI) .These theories overlap in terms of the characteristics that strengthen the explanation of adoption. An online questionnaire was used to collect data from 244 SMEs registered in Jordan. A multiple regression test was implemented to examine the proposed model. The results indicate that seven factors significantly affect cloud computing adoption among SMEs. Among these factors, cost reduction was found to be the strongest predictor, while the weakest predictor was firm size. However, the firm’s scope insignificantly influenced cloud computing adoption among SMEs in Jordan. This finding could provide insights for SMEs decision- makers when it comes to adopting cloud computing. In addition, it provides insights for practitioners in terms of recognizing the important factors that encourage or prevent SMEs from adopting cloud computing.
The performances of the routing protocols are important since they compute the primary path between source and destination. In addition, routing protocols need to detect failure within a short period of time when nodes move to start updating the routing table in order to find a new primary path to the destination. Meantime, loss of packets and end-to-end delays will increase thereby reducing throughput and degrading the performance of the network. This paper proposes a new algorithm, DBRT (Driven Backup Routing Table), to improve the existing proactive protocols such as DSDV (Destination Sequenced Distance Vector) protocol by creating a backup routing table to provide multiple alternative routes. The DBRT algorithm identifies adjacent nodes for each node in the same range and then selects one of these as a backup next hop according to the available path to the destination. The results show that loss of data packets, throughput and end-to-end delay times between source and destination are improved. The results show that the new protocol does not degrade the network's performance despite sending extra messages to construct and update the new backup routing table. Simulations (using an NS2 simulator) are undertaken to demonstrate the difference between using a DSDV protocol with or without the proposed schema.
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