Network Function (NF) deployments suffer from poor link goodput, because popular NFs such as firewalls process only packet headers while receiving and transmitting complete packets. As a result, unnecessary packet payloads needlessly consume link bandwidth. We introduce PayloadPark, which improves goodput by temporarily parking packet payloads in the stateful memory of dataplane programmable switches. PayloadPark forwards only packet headers to NF servers, thereby saving bandwidth between the switch and the NF server. PayloadPark is a transparent in-network optimization that complements existing approaches for optimizing NF performance on end-hosts.

Constraint-based techniques can solve challenging problems arising in highly diverse applications. This paper considers the problem of virtual data center (VDC) allocation, an important, emerging challenge for modern data center operators. To address this problem, we introduce Netsolver, a system for VDC allocation that is based on constraint solving. Netsolver represents a major improvement over existing approaches: it is sound, complete, and scalable, providing support for end-to-end, multi-path bandwidth guarantees across all the layers of hosting infrastructure, from servers to top-of-rack switches to aggregation switches to access routers. Netsolver scales to realistic data center sizes and VDC topologies, typically requiring just seconds to allocate VDCs of 5–15 virtual machines to physical data centers with 1000+ servers, maintaining this efficiency even when the data center is nearly saturated. In many cases, Netsolver can allocate 150%−300% as many total VDCs to the same physical data center as previous methods. Finally, we show how Netsolver can be extended with additional optimization constraints, such as VM affinity and hotspot minimization, demonstrating the flexibility of our approach. The performance and flexibility of Netsolver are made possible by our formalization of the VDC allocation problem in terms of multi-commodity flows, and the corresponding efficient handling of network flow problems in the underlying constraint solvers. This shows the importance of supporting flow-based constraints, which are more mature in ILP- vs. SMT-based constraint solving.

Recent advances in network function virtualization have prompted the research community to consider data-center-scale deployments. However, existing tools, such as E2 and SOL, limit VNF chain allocation to rack-scale and provide limited support for management of allocated chains.

We propose VNF chain abstraction to decouple a tenant's view of the VNF chain from the cloud provider's implementation. We motivate the benefits of such an abstraction for the cloud provider as well as the tenants, and outline the challenges a cloud provider needs to address to make the chain abstraction practical. We describe the design requirements and report on our initial prototype.

Constraint-based techniques can solve challenging problems arising from highly diverse applications. This paper considers the problem of virtual data center (VDC) allocation, an important, emerging challenge for modern data center operators. To solve this problem, we introduce NETSOLVER, which is based on the general-purpose constraint solver MONOSAT. NETSOLVER represents a major improvement over existing approaches: it is sound, complete, and scalable, providing support for end-to-end, multi-path bandwidth guarantees across all the layers of hosting infrastructure, from servers to top-of-rack switches to aggregation switches to access routers. NETSOLVER scales to realistic data center sizes and VDC topologies, typically requiring just seconds to allocate VDCs of 5–15 virtual machines to physical data centers with 1000+ servers, maintaining this efficiency even when the data center is nearly saturated. In many cases, NETSOLVER can allocate 150%−300% as many total VDCs to the same physical data center as previous methods. Essential to our solution efficiency is our formulation of VDC allocation using monotonic theories, illustrating the practical value of the recently proposed SAT modulo monotonic theories approach.

As virtualization technology matured, the concept of virtual network environment has emerged. Because of the flexibility of virtualization, the cloud computing services can serve various needs of its customers more efficiently. However, in some of virtual network provisioning algorithms decisions are made without any consideration of underlying network. In this paper, we are focusing on cross stratum optimization opportunities, e.g., combined optimization of resources in the application and network stratums, and proposing and an efficient and optimized provisioning algorithm. We propose a CSO-aware provisioning algorithm and show its benefits over traditional resource allocation.

Cloud computing promises to reshape the way IT service is produced and consumed by virtualizing computing resources. As if cloud providers offer virtualized CPU and storage resources via machine virtualization and distributed storage technologies respectively, the providers wish to offer to their customers' virtual networks running on the cloud. With cloud-based virtual networks (CVNs), cloud customers (often, corporate customers) can easily build new sites, effectively expanding their enterprise networks into the cloud and thus leveraging the entire benefits of cloud computing (agility, manageability, low cost, etc.). In this paper, we identify core requirements and objectives for managing CVNs. We then define a high-level autonomic CVN-management framework by demarcating between the customer and provider with CVN Management Interface (CMI). Finally we propose an open-flow based autonomic cloud data center management solution based on CVN management framework.

In this paper, we introduce the target scenario of our HELISCOPE project with the emphasis on the four modes for flying-camera task. We also explain the control points that are considered as the interfaces where the on-flight embedded software and mechanical implementation of the unmanned helicopter are contacted for the autopilot necessarily used in performing such as various modes of flying-camera tasks. Being related to real-time issues, we are developing a real-time S/W platform based on TMO (time-triggered and message-triggered object) scheme. We, in this paper, explain the clues in becoming to use the TMO mode with the survey of other on-flight real-time S/W platform researches.