20-02-2012, 05:39 PM
help me sir.
my seminar is on this month(date:22).
20-02-2012, 05:39 PM
help me sir. my seminar is on this month(date:22).
03-03-2012, 10:45 PM
plz send me client side load balancer using cloud ppt it is important for me plz send to my email mujeebmca12[at]gmail.com.plzz
06-05-2012, 12:23 PM
I want ppt about client side load balancing using cloud computing.
30-06-2012, 06:11 PM
Client-side Load Balancer using Cloud
Client-side Load Balancer.pdf (Size: 170.69 KB / Downloads: 73) ABSTRACT Web applications' trac demand uctuates widely and un- predictably. The common practice of provisioning a xed capacity would either result in unsatised customers (un- derprovision) or waste valuable capital investment (overpro- vision). By leveraging an infrastructure cloud's on-demand, pay-per-use capabilities, we nally can match the capacity with the demand in real time. This paper investigates how we can build a large-scale web server farm in the cloud. INTRODUCTION An infrastructure cloud, such as Amazon's EC2/S3 ser- vices [2], promises to fundamentally change the economics of computing. First, it provides a practically unlimited in- frastructure capacity (e.g., computing servers, storage or network) on demand. Instead of grossly over-provisioning upfront due to uncertain demands, users can elastically pro- vision their infrastructure resources from the provider's pool only when needed. Second, the pay-per-use model allows users to pay for the actual consumption instead of for the peak capacity. Third, a cloud infrastructure is much larger than most enterprise data centers. PRIOR WORK There are well established techniques to scale a web server farm in an owned infrastructure. We will brie y visit them here and point out their limitations if deployed in cloud. Load Balancer A standard way to scale web applications is by using a hardware-based load balancer [5]. The load balancer as- sumes the IP address of the web application, so all com- munication with the web application hits the load balancer rst. The load balancer is connected to one or more iden- tical web servers in the back-end. Depending on the user session and the load on each web server, the load balancer forwards packets to dierent web servers for processing. The hardware-based load balancer is designed to handle high- level of load, so it can easily scale. DNS Load Balancing Another well established technique is DNS aliasing [10]. When a user browses to a domain (e.g., www.website.com), the browser rst asks its local DNS server for the IP address (e.g., 209.8.231.11), then, the browser contacts the IP ad- dress. In case the local DNS server does not have the IP address information for the asked domain, it contacts other DNS servers that have the information, which will eventu- ally be the original DNS server that the web server farm directly manages. The original DNS server can hand out dierent IP addresses to dierent requesting DNS servers so that the load could be distributed out among the servers sitting at each IP address. Layer 2 Optimization In an enterprise where one can fully control the infras- tructure, we can apply layer 2 optimization techniques to build a scalable web server farm that does not impose all drawbacks discussed above: expensive hardware, single per- formance bottleneck, and lack of adaptiveness. There are several variations of layer 2 optimization. One way, referred to as direct web server return [4], is to have a set of web servers, all have the same IP address, but dif- ferent layer 2 addresses (MAC address). A browser request may rst hit one web server, which may in turn load balance the request to other web servers. However, when replying to a browser request, any web server can directly reply. By removing the constraint that all replies have to go through the same server, we can achieve higher scalability. This tech- nique requires the ability to dynamically change the map- ping between an IP address and a layer 2 address at the router level. Cloud Components’ Performance Characteristics We have run an extensive set of performance tests on a number of cloud components to understand their perfor- mance limits. The results are reported in a technical re- port [11] and they are not reproduced here due to space limitations (we do not cite it to facilitate double-blind re- view). A few key observations from the performance study motivated our design. They are listed as follows.
03-09-2012, 04:15 PM
hi plz send the ppt for client side load balancer using cloud
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