In service function chaining, data flows from a particular application or user travel along a pre-defined sequence of network functions. Appropriate service function chaining resource allocation is required to comply with the service level required by the application. In this paper, we introduce a dynamic priority assignment for flows that compete for service using a particular network function in a chain. Using the recent results of the performance metrics of transient birth-death processes, we analyse this priority assignment and develop an optimal strategy for selecting a (cheap) low-or (expensive) high-priority service, given the flow's service level agreement requirements. A decision table can, thus, be created to facilitate the fast, online priority scheduling of newly arriving flows requesting service.
a b s t r a c tPre-congestion notification (PCN) protects inelastic traffic by using feedback on network link loads on and acting upon this accordingly. These actions comprise to admission control and termination of flows. Two PCN architectures have been defined by IETF: the centralized and decentralized PCN architecture. The decentralized PCN architecture has received much attention in the literature whereas the centralized PCN architecture has not. In the decentralized architecture, feedback is sent from the egress nodes to ingress nodes, which then take and apply decisions regarding admission of new flows and/or termination of ongoing flows. Signaling occurs only between ingress and egress nodes.In the centralized architecture these decisions are made at a central node, which requires proper signaling for action and information exchange between the central node and the egress and ingress nodes. This signaling has been suggested by other authors, but is not fully defined yet. Our contribution is twofold. We define signaling in the centralized PCN architecture focussing on flow termination, which completes the definition of the signaling in the centralized PCN architecture. Secondly, we run extensive simulations showing that the proposed signaling works well and that the performances of the centralized PCN and the decentralized PCN architectures are similar. Hence, it is expected that results from existing research on the effectiveness of decentralized PCN are also valid when the centralized PCN architecture is used.
One of the major challenges in next-generation Internet is to allocate services to nodes in the network. This problem, known as theservice placement problem, can be solved by layered graph approach. However, due to the existence of resource bottleneck, the requests are rejected from the beginning in the resource constrained network. In this paper we propose two iterative algorithms for efficient allocation of additional resources in order to improve the ratio of accepted service placement requests. To this end, we (1) introduce a new concept of sensitivity for each service node to locate the bottleneck node, (2) state the problem of allocating additional resources, and (3) use sensitivity to propose a simple iterative algorithm and an utilization-based iterative algorithm for efficient resource allocation. The performance of these two algorithms is evaluated by simulation experiments in a variety of parameter settings. The results show that the proposed algorithms increase request acceptance ratio significantly by allocating additional resources into the bottleneck node and links. The utilization-based iterative algorithm also decreases the long-term cost by making efficient use of additional resources.
This paper is motivated by recent developments in SDN and NFV whereby service functions, distributed over a centralised controlled network, are connected to form a service function chain (SFC). Upon arrival of a new service request a decision has to be made to which one of SFCs the request must be routed. This decision is based on (1) actual state information about the background traffic through the SFC nodes, and (2) a prediction of the fraction of time that the SFC is in overflow during the course of the new flow in the system. In this paper, we propose a new method for assigning an incoming flow to an SFC. For that, we propose and compare two methods: a simple flow-based algorithm and a more refined hybrid flow/packet-based algorithm. By extensive simulations, we show that the simple flow-based algorithm works particularly well if the network is not overloaded upon new flow arrival. Moreover, the results show that the flow/packet-based algorithm enhances the flowbased algorithm as it handles initial overload significantly better. We conclude that the prediction-based SFC selection is a powerful method to meet QoS requirements in a software defined network with varying background traffic. Keywords: Software defined network • Service function chain • Predictive selection • Varying background traffic
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