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. Software-defined networking (SDN) is an emerging paradigm that has become increasingly popular in recent years. The core idea is to separate the control and data planes, allowing the construction of network applications using high-level abstractions that are translated to network devices through a southbound interface. SDN architecture is composed of three layers: 1) infrastructure layer, responsible exclusively for data forwarding; 2) control layer, which maintains the network view and provides core network abstractions; and 3) application layer, which uses abstractions provided by the control layer to implement network applications. SDN provides features, such as flexibility and programmability, that are key enablers to meet current network requirements (e.g., multi-tenant cloud networks and elastic optical networks). However, along with its benefits, SDN also brings new issues. In this survey we focus on issues related to fault management. Different fault management threat vectors are introduced by each layer, as well as by the interface between layers. Nevertheless, besides addressing fault management issues of its architecture, SDN also must handle the same problems faced by legacy networks. However, programmability and centralized management might be used to provide flexibility to deal with those issues. This paper presents an overview of fault management in SDN. The major contributions of this paper are as follows: 1) identification of the main fault management issues in SDN and classification according to the affected layers; 2) survey of efforts that address those issues and classification according to the affected planes, issues concerned, general approaches, and features; an Programmable networks brought by Software Defined Networks (SDN) are perceived by operators as cornerstone to reduce the time to deploy new services, to augment the flexibility and to adapt network resources to customer needs at runtime. However, despite the vulnerabilities identified due to the centralization of the intelligence on SDN, its research is more centered on forwarding traffic and reconfiguration issues, not considering to a great extent the fault management aspects of the control plane. The aim of this paper is to provide SDN with fault management capabilities by using autonomic principles like self-healing mechanisms. We propose a generic self-healing approach that relies on a Bayesian Networks for the diagnosis block and it is applied to a centralized SDN infrastructure to demonstrate its functioning in the presence of faults. Fault tolerant MPI (FTMPI) enables fault tolerance to the MPICH, an open source GPL licensed implementation of MPI standard by Argonne National Laboratory's Mathematics and Computer Science Division. FTMPI is a transparent fault-tolerant environment, based on synchronous checkpointing and restarting mechanism. FTMPI relies on non-multithreaded single process checkpointing library to synchronously checkpoint an application process. Global replicated system controller and cluster node specific node controller monitors and controls check pointing and recovery activities of all MPI applications within the cluster. This work details the architecture to provide fault tolerance mechanism for MPI based applications running on clusters and the performance of NAS parallel benchmarks and parallelized medium range weather forecasting models, P-T80 and P-TI26. The architecture addresses the following issues also: Replicating system controller to avoid single point of failure. Ensuring consistency of checkpoint files based on distributed two phase commit protocol, and robust fault detection hierarchy.