This paper proposes a dynamic adaptive coscheduling modelDASIC to take advantage of excess available resources in anetwork of workstations (NOW). Besides coscheduling related subtasksdynamically, DASIC can scale up or down the process space dependingupon the number of available processors on an NOW. Based on thedynamic idle processor group (IPG), DASIC employs three modules: thecoscheduling module, the scalable scheduling module and the loadbalancing module, and uses six algorithms to achieve scalability. Asimplified DASIC was also implemented, and experimental results arepresented in this paper, which show that it can maximize systemutilization, and achieve task parallelism as much as possible.