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This paper presents resource management techniques for allocatingcommunication and computational resources in a distributed stream processingplatform. The platform is designed to exploit the synergy of two classes ofnetwork connections -- dedicated and opportunistic. Previous studies weconducted have demonstrated the benefits of such bi-modal resource organizationthat combines small pools of dedicated computers with a very large pool ofopportunistic computing capacities of idle computers to serve high throughputcomputing applications. This paper extends the idea of bi-modal resourceorganization into the management of communication resources. Since distributedstream processing applications demand large volume of data transmission betweenprocessing sites at a consistent rate, adequate control over the networkresources is important to assure a steady flow of processing. The system modelused in this paper is a platform where stream processing servers at distributedsites are interconnected with a combination of dedicated and opportunisticcommunication links. Two pertinent resource allocation problems are analyzed indetails and solved using decentralized algorithms. One is the mapping of thestream processing tasks on the processing and the communication resources. Theother is the adaptive re-allocation of the opportunistic communication linksdue to the variations in their capacities. Overall optimization goal is highertask throughput and better utilization of the expensive dedicated links. Theevaluation demonstrates that the algorithms are able to exploit the synergy ofbi-modal communication links towards achieving the optimization goals.

Decentralized Management of Bi-modal Network Resources in a Distributed Stream Processing Platform