Reflections on the Economy of Asean Countries in the Face of the Covid-19 Pandemic

This article discusses the Economic Reflections of Asean countries in facing the Covid-19 Pandemic in several Asean countries, namely Vietnam, Malaysia and Indonesia. Vietnam's economic growth was victorious, the economies of various countries in other Southeast Asian regions were battered by the corona virus. The process of economic growth is influenced by two kinds of factors, namely economic factors and non-economic factors. Economic factors, which are none other than production factors, are the main force affecting economic growth. Malaysia has proven to the world community that its country is capable of managing its economy even in challenging circumstances. He quoted the IMF as global economy recorded negative growth and in Indonesia it seems that contraction in income activities in some income classes is affected. In the second quarter there is a slowdown, then in the third quarter the savings are enormous. It could be that consumption, which has been a factor in economic growth, will be a challenge. In an effort to maintain economic stability during the Covid-19 pandemic. This reflects that the economies of ASEAN countries, even in the world, are currently under the same pressure due to the Covid-19 virus pandemic, the world economy this year will experience a recession.

A Topology-Awareload Balancing Scheme in Data Center Networks

Datacenter networks are playing vital role to accommodate huge amount of data transmission such as in Giga/Tera bytes on multiple links. With this inevitable data transmission, some uncertainties like dynamic traffic behaviour, topology asymmetry and link failure, are major issues faced by Datacenter which result in poor performance. To handle such link failures in Datacenter network, load balancing scheme should be accurate especially path sensing and timely responses to mitigate the fallouts. Different solutions have been proposed to overcome these issues. Some of the proposed techniques are unaware about path conditions. They reroute at fixed data rate blindly. Others were capable for sensing the path condition but rerouting and adjusting the load balancing is very slow which degrade the performance. One of the good technqiue for solving the load balacing problem in Datacenter networks where multipath exits for higher data rate (parallel transmisson). That research required hardware changes, particularly for acqiuring accorate congestion feedback from end host and taking adaptiving decision for load balancing. Thus they can?t react timely to these uncertainties which results in reasonable performance degradation; especially in the worst situation to detect some issues like randomly packets drop as well as throughput of the channel. In this research, a solution has been proposed which focusses on two things (1) accurate timely acknowledgement of packet delivery, (2) Current load on each link. In our proposed work there is no need of hardware changes. We have achieved accurate response of acknowledgments of each packet delivery. This proposed scheme have been implemented using NS3 simulator. The results has been compared with the other existing solutions.