An Improved DR Algorithm Based on Target Extrapolating in ROIA Cloud Platform

Abstract

Real-time Online Interactive Application (ROIA) is an emerging distributed application recently. ROIA needs a highly robust and efficient architecture to cope with the huge concurrent users. Previous works are almost based on the C/S or P2P mode, and their scalability and resource utilization are relatively low. So we try to take advantage of the cloud computing technologies to achieve higher scalability and resource utilization. However, as ROIA servers focused on several data centers in cloud computing rather than being scattered in many areas, it will increase in part users' network delays and affect their user experiences in ROIA. To cope with this problem, we propose an improved Dead Reckoning (DR) algorithm. Traditional DR algorithm is mostly based on the classic formula of physics to predict, without taking the influence of the user's target under the different situations into account, so there are some limitations. This paper proposes an improved DR algorithm based on target-extrapolating in a cloud platform for ROIA, elaborates the basic idea of the improved algorithm and the computational model formula, and then carries out a simulation experiment. The analyses of the simulation results show that the improved algorithm is superior to traditional one.