In this paper, we consider a load balancing problem in distributed systems, that has two conflicting objectives: (i) minimizing the users’ expected response time and (ii) minimizing the total monetary cost incurred by each user. To satisfy both the objectives simultaneously, we consider the objectives in an integrated manner and formulate the problem as an optimization problem. We then cast it into a game-theoretic setting and model the load balancing problem as a non-cooperative game. To solve the game, we characterize the best response strategy for each player, and derive a decentralized algorithm called Cost-Aware Load Balancing Algorithm (CALBA). We conduct a rigorous experimental study to demonstrate the effectiveness of CALBA. Further, to establish the effectiveness of CALBA, we compare it with three other load balancing schemes, i.e., MinRT, MinCost, and GPMS, using various system configurations such as varying system size, varying system utilization, and system heterogeneity, across multiple performance indicators. The computational results show that textitCALBA outperforms the competitive schemes by reducing the response time and cost, and unlike others, CALBA produces an allocation of load which guarantees fairness (in terms of response time) between the users. In a nutshell, the results demonstrate the suitability of CALBA in realistic scenarios as it is an adaptable and feasible approach to get a cost-aware load balancing solution.

在本文中，我们考虑了分布式系统中的负载平衡问题，该问题有两个相互矛盾的目标：（i）最小化用户的预期响应时间，以及（ii）最小化每个用户所产生的总货币成本。为了同时满足两个目标，我们以综合的方式考虑目标并将问题表述为优化问题。然后，我们将其转换为博弈论设置，并将负载均衡问题建模为非合作博弈。为了解决游戏中，我们描述了最佳的应对策略为每个球员，并从中获得一个分散的算法称为Ç ost-一个洁具大号OAD乙alancing一个lgorithm（CALBA）。我们进行了严格的实验研究，以证明CALBA的有效性。此外，为了确定CALBA的有效性，我们将其与其他三种负载均衡方案（即MinRT，MinCost和GPMS）进行了比较，并使用了多种系统配置，例如可变的系统大小，可变的系统利用率和系统异构性，跨多个性能指标。计算结果表明，textitCALBA通过减少响应时间和成本，优于竞争方案，而CALBA与其他方案不同产生负载分配，以确保用户之间的公平性（根据响应时间）。简而言之，结果证明了CALBA在现实情况下的适用性，因为它是一种获得成本意识的负载平衡解决方案的适应性和可行方法。