基于微积分的最优参数负载均衡机制

T. Chomsiri, D. Pansa
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引用次数: 1

摘要

本研究利用预装在服务器上的代理软件读取服务器资源信息并将信息发送给负载均衡器的技术,对负载均衡器机制进行了改进。这种技术为负载平衡器提供了可靠的最新信息,因为如果这些信息(例如活动连接)是由负载平衡器估计或统计的,那么它可能会有一些错误或与真实信息不匹配。此外,管理员将每个服务器的权重放在负载平衡器上可能会无意中产生偏差。使用这种技术,将传入请求调度到服务器的“计划制定”将有效地运行。实现用于读取资源信息并将其发送到服务器的代理很容易。同样,创建计划制定功能的算法并不难,因为它类似于其他现有的负载平衡算法。因此,本研究的主要问题是每次制定计划的时间间隔应该是多少。这是因为太宽的时间间隔会使系统反应缓慢。因此,整体效率将会下降。同样,时间间隔过窄也会导致整体效率的下降。这是因为负载均衡器必须使用几乎所有的CPU时间来制定调度计划。因此,寻找最佳的时间间隔值是本研究的主要重点。该方法的重点在于发现能给网络带来最高总效率P的最优时间间隔w。我们首先在$P =$ ${f(w)}$项中给出总效率的函数,然后对函数进行微分得到其导数函数。因此,我们可以在P达到最大值的点上找到最优w。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Load Balancer Mechanism using Optimal Parameter based on Calculus
This research proposes improvement of load balancer mechanism using technique that agent software preinstalled on servers has to read server resource information and send the information to load balancer. This technique provides reliable and up-to-date information to the load balancer because if the information, e.g. active connections, is estimated or counted by load balancer, it may have some errors or be not match with the real information. Also, putting weights of each server to the load balancer by an administrator may have unintentionally bias. With this technique, ‘plan making’ for dispatching incoming requests to servers will operate efficiently. Implementing the agent for reading and sending resource information to the server can be done easily. Similarly, an algorithm to create the plan making function is not hard because it is similar to other existing load balancing algorithms. Therefore, the main problem for this research is that how much of time interval between each plan making should be appropriate. This is because too wide of time interval can make slow reaction of system. Consequently, the overall efficiency will be dropped. Likewise, too narrow of time interval can bring the drop of overall efficiency as well. This is because the load balancer has to use almost of all its CPU time to make a dispatching plan. Thus, investigating to find the best value of time interval is the main focus of this research. Highlight of the proposed method is discovering the optimal time interval ‘w’ which can bring the highest overall efficiency ‘P’ to the network. We firstly present the function of overall efficiency in the term $P =$ ${f(w)}$ and then differentiate the function to obtain its derivative function. Consequently, we can discover the optimal ‘w’ at the point that ‘P’ can reach to its maximum.
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