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ACM SIGCOMM Computer Communication Review
A Constraint Language Approach to Matchmaking
RIDE '04 Proceedings of the 14th International Workshop on Research Issues on Data Engineering: Web Services for E-Commerce and E-Government Applications (RIDE'04)
OpenFlow: enabling innovation in campus networks
ACM SIGCOMM Computer Communication Review
Resource Leasing and the Art of Suspending Virtual Machines
HPCC '09 Proceedings of the 2009 11th IEEE International Conference on High Performance Computing and Communications
Rhizoma: a runtime for self-deploying, self-managing overlays
Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware
A network in a laptop: rapid prototyping for software-defined networks
Hotnets-IX Proceedings of the 9th ACM SIGCOMM Workshop on Hot Topics in Networks
Can the production network be the testbed?
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Topology-aware resource allocation for data-intensive workloads
ACM SIGCOMM Computer Communication Review
The Genesis Kernel: a programming system for spawning network architectures
IEEE Journal on Selected Areas in Communications
The Tempest-a practical framework for network programmability
IEEE Network: The Magazine of Global Internetworking
Towards realistic benchmarks for virtual infrastructure resource allocators
APSys'12 Proceedings of the Third ACM SIGOPS Asia-Pacific conference on Systems
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Resource allocation is an increasing challenge for distributed network testbeds as computational and network resources are involved. Testbed designers have moved to a query-based model: clients provide a declarative description of their desired resources, and the provider allocate specific resources to meet the request. In this paper, we describe an new approach to negotiate testbed resources between clients and testbed providers: the clients specify their requests as constraints, and the providers reply with resource allocations expressed also as declarative set of constraints on resources. This gives providers more flexibility in late-binding of resources to requests, and opens up a wide design space to optimize resource allocation for efficiency, cost, utilization, or other metrics. Our simple first experiments suggest that the late-binding of resources enabled by representing resource reservation as constraints achieves better network resource utilization compared to the fixed assignment solution.