E-mail, WWW, FTP, BT and QQlive, etc. axe used more and more universal because the advantage of Internet, but the data-omitting phenomenon is a headache problem. In this paper, we consider the problem of allocating a ...E-mail, WWW, FTP, BT and QQlive, etc. axe used more and more universal because the advantage of Internet, but the data-omitting phenomenon is a headache problem. In this paper, we consider the problem of allocating a large number of independent, unequal-sized loads exchanged between servers and clients or between themselves when there are data-omitting, and we describe the dynamic load balancing problems by intro- ducing some parameters αij, we use an undirected graph to model the platform, where servers （CPU time, disk memory） can have different speeds of computation and communication. Because the number of loads is large, we focus on the question of determining the optimal dynamic load balancing scheduling strategy （splittable strategy） for each processor （the fraction of time spent computing and the fraction of time spent communication with each neighbor）. We show that finding the optimal dynamic load balancing state can be solved using a linear programming approach by adding more constrains and, thus, in polynomial time. And make the execute time minimization.展开更多
基金This work is supported by National Natural Science Foundation of China （1067108） Scientific and technological project of Hubei province （2006AA412C27） Science Foundation of Three Gorges University （604401）.
文摘E-mail, WWW, FTP, BT and QQlive, etc. axe used more and more universal because the advantage of Internet, but the data-omitting phenomenon is a headache problem. In this paper, we consider the problem of allocating a large number of independent, unequal-sized loads exchanged between servers and clients or between themselves when there are data-omitting, and we describe the dynamic load balancing problems by intro- ducing some parameters αij, we use an undirected graph to model the platform, where servers （CPU time, disk memory） can have different speeds of computation and communication. Because the number of loads is large, we focus on the question of determining the optimal dynamic load balancing scheduling strategy （splittable strategy） for each processor （the fraction of time spent computing and the fraction of time spent communication with each neighbor）. We show that finding the optimal dynamic load balancing state can be solved using a linear programming approach by adding more constrains and, thus, in polynomial time. And make the execute time minimization.
