Abstract Middleboxes have become a vital part of modern networks by providing services such as load balancing, optimization of network traffic, and content filtering. A sequence of middleboxes comprising a logical service is called a Service Function Chain (SFC) . In this context, the main issues are to maintain an acceptable level of network path survivability and a fair allocation of the resource between different demands in the event of faults or failures. In this paper, we focus on the problems of traffic engineering, failure recovery, fault prevention, and SFC with reliability and energy consumption constraints in Software Defined Networks (SDN). These types of deployments use Fog computing as an emerging paradigm to manage the distributed small-size traffic flows passing through the SDN-enabled switches (possibly Fog Nodes). The main aim of this integration is to support service delivery in real-time, failure recovery, and fault-awareness in an SFC context. Firstly, we present an architecture for Failure Recovery and Fault Prevention called FRFP; this is a multi-tier structure in which the real-time traffic flows pass through SDN-enabled switches to jointly decrease the network side-effects of flow rerouting and energy consumption of the Fog Nodes. We then mathematically formulate an optimization problem called the Optimal Fog-Supported Energy-Aware SFC rerouting algorithm (OFES) and propose a near-optimal heuristic called Heuristic OFES (HFES) to solve the corresponding problem in polynomial time. In this way, the energy consumption and the reliability of the selected paths are optimized, while the Quality of Service (QoS) constraints are met and the network congestion is minimized. In a reliability context, the focus of this work is on fault prevention; however, since we use a reallocation technique, the proposed scheme can be used as a failure recovery scheme. We compare the performance of HFES and OFES in terms of energy consumption, average path length, fault probability, network side-effects, link utilization, and Fog Node utilization. Additionally, we analyze the computational complexity of HFES. We use a real-world network topology to evaluate our algorithm. The simulation results show that the heuristic algorithm is applicable to large-scale networks.
The available literature ranges from the joint problem of fault-aware distributing and routing the traffic flows content in SDNs NFVs infrastructure @cite_22 @cite_10 to the problem of fault detection and recovery solutions in SDNs NFVs @cite_14 @cite_19 . In detail, in @cite_10 the authors analyze the fault tolerance over SDN. They present a discussion about fault tolerance and failure happening in the OpenFlow (OF) protocol that is applied in SDNs. Specifically, they propose a link node failure detection and failure recovery method in the data plane that can be controlled through the controller. However, they do not present any discussion about the application plane side-effect and do not cover the SFC fault-awareness.
@cite_19 @cite_14 @cite_10 @cite_22
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When dealing with node or link failures in Software Defined Networking (SDN), the network capability to establish an alternative path depends on controller reachability and on the round trip times (RTTs) between controller and involved switches. Moreover, current SDN data plane abstractions for failure detection (e.g. OpenFlow "Fast-failover") do not allow programmers to tweak switches' detection mechanism, thus leaving SDN operators still relying on proprietary management interfaces (when available) to achieve guaranteed detection and recovery delays. We propose SPIDER, an OpenFlow-like pipeline design that provides i) a detection mechanism based on switches' periodic link probing and ii) fast reroute of traffic flows even in case of distant failures, regardless of controller availability. SPIDER can be implemented using stateful data plane abstractions such as OpenState or Open vSwitch, and it offers guaranteed short (i.e. ms) failure detection and recovery delays, with a configurable trade off between overhead and failover responsiveness. We present here the SPIDER pipeline design, behavioral model, and analysis on flow tables' memory impact. We also implemented and experimentally validated SPIDER using OpenState (an OpenFlow 1.3 extension for stateful packet processing), showing numerical results on its performance in terms of recovery latency and packet losses. One of the main concerns on SDN is relative to its ability to quickly react to network failures, while limiting both the control-plane overhead and the additional forwarding state kept by data-plane devices. Despite its practical importance, this concern is often overlooked in OpenFlow-based proposals. In this paper, we propose a new architecture, called IBSDN, in which a distributed routing protocol flanks OpenFlow to improve network robustness, reaction to failures, and controller scalability. In deeply exploring this idea, we complement our architecture with data-plane triggered mechanisms that improve its efficiency. We prove that the resulting solution ensures robustness for any combination of topological failures, and quickly reduces the path stretch. Finally, experimenting with a prototype implementation, we show that our approach is practical and overcomes the main limitations of previous work. A reliable and scalable mechanism to provide protection against a link or node failure has additional requirements in the context of SDN and OpenFlow. Not only it has to minimize the load on the controller, but it must be able to react even when the controller is unreachable. In this paper we present a protection scheme based on precomputed backup paths and inspired by MPLS “crankback” routing, that guarantees instantaneous recovery times and aims at zero packet-loss after failure detection, regardless of controller reachability, even when OpenFlow's “fast-failover” feature cannot be used. The proposed mechanism is based on OpenState, an OpenFlow extension that allows a programmer to specify how forwarding rules should autonomously adapt in a stateful fashion, reducing the need to rely on remote controllers. We present the scheme as well as two different formulations for the computation of backup paths. We consider the problem of routing in a delay tolerant network (DTN) in the presence of path failures. Previous work on DTN routing has focused on using precisely known network dynamics, which does not account for message losses due to link failures, buffer overruns, path selection errors, unscheduled delays, or other problems. We show how to split, replicate, and erasure code message fragments over multiple delivery paths to optimize the probability of successful message delivery. We provide a formulation of this problem and solve it for two cases: a 0 1 (Bernoulli) path delivery model where messages are either fully lost or delivered, and a Gaussian path delivery model where only a fraction of a message may be delivered. Ideas from the modern portfolio theory literature are borrowed to solve the underlying optimization problem. Our approach is directly relevant to solving similar problems that arise in replica placement in distributed file systems and virtual node placement in DHTs. In three different simulated DTN scenarios covering a wide range of applications, we show the effectiveness of our approach in handling failures.