This paper studies the resilient routing and (in-band) fast failover mechanisms supported in Software-Defined Networks (SDN). We analyze the potential benefits and limitations of such failover mechanisms, and focus on two main metrics: (1) correctness (in terms of connectivity and loop-freeness) and (2) load-balancing. We make the following contributions. First, we show that in the worst-case (i.e., under adversarial link failures), the usefulness of local failover is rather limited: already a small number of failures will violate connectivity properties under any fast failover policy, even though the underlying substrate network remains highly connected. We then present randomized and deterministic algorithms to compute resilient forwarding sets; these algorithms achieve an almost optimal tradeoff. Our worst-case analysis is complemented with a simulation study.
This work is motivated by the trend towards Software-Defined Networking and in particularly the fast failover mechanism which supports the in-band masking of failures (see Section 5.8 of the OpenFlow 1.1 specification). However, as the convergence time of routing algorithms is often relatively high compared to packet forwarding speeds, ranging from 10s of milliseconds to seconds depending on the network @cite_5 , many networks today incorporate some robustness already in the forwarding tables of a router or switch: Thus, robust routing concepts and link protection schemes have been studied intensively for many years, also outside SDN.
@cite_5
2949817135 1561042325 2027076000 2009508457 2563943708 2557890845 1908662580 2110916358 2146191242 1543942291 1530120774 1966518282 2086002250 2059762964 1561598073 2162076967 2155564629 2101946268 2127699957 2141661023
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. 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. Although Software-Defined Networking and its implementation OpenFlow facilitate managing networks and enable dynamic network configuration, recovering from network failures in a timely manner remains non-trivial. The process of (a) detecting the failure, (b) communicating it to the controller and (c) recomputing the new shortest paths may result in an unacceptably long recovery time. In this paper, we demonstrate that current solutions, employing both reactive restoration or proactive protection, indeed suffer long delays. We introduce a failover scheme with per-link Bidirectional Forwarding Detection sessions and preconfigured primary and secondary paths computed by an OpenFlow controller. Our implementation reduces the recovery time by an order of magnitude compared to related work, which is confirmed by experimental evaluation in a variety of topologies. Furthermore, the recovery time is shown to be constant irrespective of path length and network size. 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. Software defined networks (SDNs) introduced the concept of decoupling control and data planes which is a paradigm shift. The OpenFlow protocol is one of a number of technologies that enables this decoupling and, in effect, commodifies network equipment. As of now, there is still limited work that has been done towards modeling the transit delay across OpenFlow switches experienced by network traffic. In this work we develop a stochastic model for the path latency in Open vSwitch (used together with a POX controller) based on measurements made in experiments performed on three different platforms which include 1) Mininet, 2) MikroTik RouterBoard 750GL and 3) GENI testbed softswitch. We propose a log-normal mix model (LNMM) and show that it offers a R2 value of greater than 0.90 for most of our experiments. We also demonstrate how the M M 1 models proposed in earlier studies is a poor fit. Abstract The energy efficiency of wired networks has received considerable attention over the past decade due to its economic and environmental impacts. However, because of the vertical integration of the control and data planes in conventional networks, optimizing energy consumption in such networks is challenging. Software-defined networking (SDN) is an emerging networking paradigm that decouples the control plane from the data plane and introduces network programmability for the development of network applications. In this work, we propose an energy-aware integral flow-routing solution to improve the energy efficiency of the SDN routing application. We consider discreteness of link rates and pose the routing problem as a mixed integer linear programming (MILP) problem, which is known to be NP complete. The proposed solution is a heuristic implementation of the Benders decomposition method that routes additional single and multiple flows without resolving the routing problem. Performance evaluations demonstrate that the proposed solution achieves a close-to-optimal performance (within 3.27 error) compared to CPLEX on various topologies with less than 0.056 of CPLEX average computation time. Furthermore, our solution outperforms the shortest path algorithm by 24.12 to 54.35 in power savings. We contribute a fast routing algorithm for timetable networks with realistic transfer times. In this setting, our algorithm is the first one that successfully applies precomputation based on node contraction: gradually removing nodes from the graph and adding shortcuts to preserve shortest paths. This reduces query times to 0.5 ms with preprocessing times below 4 minutes on all tested instances, even on continental networks with 30 000 stations. We achieve this by an improved contraction algorithm and by using a station graph model. Every node in our graph has a one-to-one correspondence to a station and every edge has an assigned collection of connections. Also, our graph model does not require parallel edges. Dealing with network failures effectively is a major operational challenge for Internet service providers. Commonly deployed link state routing protocols such as OSPF react to link failures through global (i.e., network-wide) link state advertisements and routing table recomputations, causing significant forwarding discontinuity after a failure. The drawback with these protocols is that they need to trade off routing stability and forwarding continuity. To improve failure resiliency without jeopardizing routing stability, we propose a proactive local rerouting based approach called failure insensitive routing (FIR). The proposed approach prepares for failures using interface-specific forwarding, and upon a failure, suppresses the link state advertisement and instead triggers local rerouting using a backwarding table. In this paper, we prove that when no more than one link failure notification is suppressed, FIR always finds a loop-free path to a destination if one such path exists. We also formally analyze routing stability and network availability under both proactive and reactive approaches, and show that FIR provides better stability and availability than OSPF. Software-defined networking provides flexibility in designing networks by allowing distributed network state to be managed by logically centralized control programs. However, this flexibility brings added complexity, which requires new debugging tools that can provide insights into network behavior. We propose a tool, SDN traceroute, that can query the current path taken by any packet through an SDN-enabled network. The path is traced by using the actual forwarding mechanisms at each SDN-enabled device without changing the forwarding rules being measured. This enables administrators to discover the forwarding behavior for arbitrary Ethernet packets, as well as debug problems in both switch and controller logic. Our prototype implementation requires only a few high-priority rules per device, runs on commodity hardware using only the required features of the OpenFlow 1.0 specification, and can generate traces in about one millisecond per hop. The data center network is increasingly a cost, reliability and performance bottleneck for cloud computing. Although multi-tree topologies can provide scalable bandwidth and traditional routing algorithms can provide eventual fault tolerance, we argue that recovery speed can be dramatically improved through the co-design of the network topology, routing algorithm and failure detector. We create an engineered network and routing protocol that directly address the failure characteristics observed in data centers. At the core of our proposal is a novel network topology that has many of the same desirable properties as FatTrees, but with much better fault recovery properties. We then create a series of failover protocols that benefit from this topology and are designed to cascade and complement each other. The resulting system, F10, can almost instantaneously reestablish connectivity and load balance, even in the presence of multiple failures. Our results show that following network link and switch failures, F10 has less than 1 7th the packet loss of current schemes. A trace-driven evaluation of MapReduce performance shows that F10's lower packet loss yields a median application-level 30 speedup. Recent work has focused on increasing availability in the face of Internet path failures. To date, proposed solutions have relied on complex routing and path-monitoring schemes, trading scalability for availability among a relatively small set of hosts. This paper proposes a simple, scalable approach to recover from Internet path failures. Our contributions are threefold. First, we conduct a broad measurement study of Internet path failures on a collection of 3,153 Internet destinations consisting of popular Web servers, broad-band hosts, and randomly selected nodes. We monitored these destinations from 67 PlanetLab vantage points over a period of seven days, and found availabilities ranging from 99.6 for servers to 94.4 for broadband hosts. When failures do occur, many appear too close to the destination (e.g., last-hop and end-host failures) to be mitigated through alternative routing techniques of any kind. Second, we show that for the failures that can be addressed through routing, a simple, scalable technique, called one-hop source routing, can achieve close to the maximum benefit available with very low overhead. When a path failure occurs, our scheme attempts to recover from it by routing indirectly through a small set of randomly chosen intermediaries. Third, we implemented and deployed a prototype one-hop source routing infrastructure on PlanetLab. Over a three day period, we repeatedly fetched documents from 982 popular Internet Web servers and used one-hop source routing to attempt to route around the failures we observed. Our results show that our prototype successfully recovered from 56 of network failures. However, we also found a large number of server failures that cannot be addressed through alternative routing. Our research demonstrates that one-hop source routing is easy to implement, adds negligible overhead, and achieves close to the maximum benefit available to indirect routing schemes, without the need for path monitoring, history, or a-priori knowledge of any kind. Many DTN routing protocols use a variety of mechanisms, including discovering the meeting probabilities among nodes, packet replication, and network coding. The primary focus of these mechanisms is to increase the likelihood of finding a path with limited information, so these approaches have only an incidental effect on such routing metrics as maximum or average delivery latency. In this paper, we present RAPID , an intentional DTN routing protocol that can optimize a specific routing metric such as worst-case delivery latency or the fraction of packets that are delivered within a deadline. The key insight is to treat DTN routing as a resource allocation problem that translates the routing metric into per-packet utilities which determine how packets should be replicated in the system. We evaluate RAPID rigorously through a prototype of RAPID deployed over a vehicular DTN testbed of 40 buses and simulations based on real traces. To our knowledge, this is the first paper to report on a routing protocol deployed on a real DTN at this scale. Our results suggest that RAPID significantly outperforms existing routing protocols for several metrics. We also show empirically that for small loads RAPID is within 10 of the optimal performance. We consider the problem of optimal scheduling and routing in an ad-hoc wireless network with multiple traffic streams and time varying channel reliability. Each packet transmission can be overheard by a subset of receiver nodes, with a transmission success probability that may vary from receiver to receiver and may also vary with time. We develop a simple backpressure routing algorithm that maximizes network throughput and expends an average power that can be pushed arbitrarily close to the minimum average power required for network stability, with a corresponding tradeoff in network delay. When channels are orthogonal, the algorithm can be implemented in a distributed manner using only local link error probability information, and supports a ''blind transmission'' mode (where error probabilities are not required) in special cases when the power metric is neglected and when there is only a single destination for all traffic streams. For networks with general inter-channel interference, we present a distributed algorithm with constant-factor optimality guarantees. This paper introduces a fast solution procedure to solve 100-node instances of the time-dependent orienteering problem (TD-OP) within a few seconds of computation time. Orienteering problems occur in logistic situations were an optimal combination of locations needs to be selected and the routing between the selected locations needs to be optimized. In the time-dependent variant, the travel time between two locations depends on the departure time at the first location. Next to a mathematical formulation of the TD-OP, the main contribution of this paper is the design of a fast and effective algorithm to tackle this problem. This algorithm combines the principles of an ant colony system (ACS) with a time-dependent local search procedure equipped with a local evaluation metric. Additionally, realistic benchmark instances with varying size and properties are constructed. The average score gap with the known optimal solution on these test instances is only 1.4 with an average computation time of 0.5seconds. An extensive sensitivity analysis shows that the performance of the algorithm is insensitive to small changes in its parameter settings. The task of moving data (i.e., the routing problem) in large-scale sensor networks has to contend with several obstacles, including severe power constraints at each node and temporary, but random, failures of nodes, rendering routing schemes designed for traditional communication networks ineffective. We consider the open problem of finding optimum routes between any fixed source-destination pair in a large-scale network, such that the communication load (i.e., the required power) is distributed among all the nodes, the overall latency is minimized, and the algorithm is decentralized and robust. A recent work addressed this problem in the context of a grid topology and showed how to obtain load-balanced routing, but transmissions are restricted to be among near-neighbors and the overall latency grows linearly with the number of nodes. We show how one can route messages between source and destination nodes along random small-world topologies using a decentralized algorithm. Specifically, nodes make connections independently (based only on the source and destination information in the packets), according to a distribution that guarantees an average latency of O(log sup 2 (N)), while preventing hotspot regions by providing an almost uniform distribution of traffic load over all nodes. Surprisingly, the randomized nature of the network structure keeps the average per-node power consumption almost the same as in the case of a grid topology (i.e., local transmissions), while providing an exponential reduction in latency, resulting in a highly fault-tolerant and stable design capable of working in very dynamic environments. We formulate the delay-tolerant networking routing problem, where messages are to be moved end-to-end across a connectivity graph that is time-varying but whose dynamics may be known in advance. The problem has the added constraints of finite buffers at each node and the general property that no contemporaneous end-to-end path may ever exist. This situation limits the applicability of traditional routing approaches that tend to treat outages as failures and seek to find an existing end-to-end path. We propose a framework for evaluating routing algorithms in such environments. We then develop several algorithms and use simulations to compare their performance with respect to the amount of knowledge they require about network topology. We find that, as expected, the algorithms using the least knowledge tend to perform poorly. We also find that with limited additional knowledge, far less than complete global knowledge, efficient algorithms can be constructed for routing in such environments. To the best of our knowledge this is the first such investigation of routing issues in DTNs. In classical routing strategies for multihop mobile wireless networks packets are routed on a pre-defined route usually obtained by a shortest path routing protocol. In opportunistic routing schemes, for each packet and each hop, the next relay is found by dynamically selecting the node that captures the packet transmission and which is the nearest to the destination. Such a scheme allows each packet to take advantage of the local pattern of transmissions and fadings at any slot and at any hop. The aim of this paper is to quantify and optimize the potential performance gains of such opportunistic routing strategies compared with classical routing schemes. The analysis is conducted under the following lower layer assumptions: the Medium Access (MAC) layer is a spatial version of Aloha which has been shown to scale well for large multihop networks; the capture of a packet by some receiver is determined by the Signal over Interference and Noise Ratio (SINR) experienced by the receiver. The paper contains a detailed simulation study which shows that such time-space opportunistic schemes very significantly outperform classical routing schemes. It also contains a mathematical study where we show how to optimally tune the MAC parameters so as to minimize the average number of time slots required to carry a typical packet from origin to destination on long paths. We show that this optimization is independent of network density. In this paper, we present a framework for analyzing routing performance in delay tolerant networks (DTNs). Differently from previous work, our framework is aimed at characterizing the exact distribution of relevant performance metrics, which is a substantial improvement over existing studies characterizing either the expected value of the metric, or an asymptotic approximation of the actual distribution. In particular, the considered performance metrics are packet delivery delay, and communication cost, expressed as number of copies of a packet circulating in the network at the time of delivery. Our proposed framework is based on a characterization of the routing process as a stochastic coloring process and can be applied to model performance of most stateless delay tolerant routing protocols, such as epidemic, two-hops, and spray and wait. After introducing the framework, we present examples of its application to derive the packet delivery delay and communication cost distribution of two such protocols, namely epidemic and two-hops routing. Characterizing packet delivery delay and communication cost distribution is important to investigate fundamental properties of delay tolerant networks. As an example, we show how packet delivery delay distribution can be used to estimate how epidemic routing performance changes in presence of different degrees of node cooperation within the network. More specifically, we consider fully cooperative, noncooperative, and probabilistic cooperative scenarios, and derive nearly exact expressions of the packet delivery rate (PDR) under these scenarios based on our proposed framework. The comparison of the obtained packet delivery rate estimation in the various cooperation scenarios suggests that even a modest level of node cooperation (probabilistic cooperation with a low probability of cooperation) is sufficient to achieve 2-fold performance improvement with respect to the most pessimistic scenario in which all potential forwarders drop packets. This paper describes two techniques that improve throughput in an ad hoc network in the presence of nodes that agree to forward packets but fail to do so. To mitigate this problem, we propose categorizing nodes based upon their dynamically measured behavior. We use a watchdog that identifies misbehaving nodes and a pathrater that helps routing protocols avoid these nodes. Through simulation we evaluate watchdog and pathrater using packet throughput, percentage of overhead (routing) transmissions, and the accuracy of misbehaving node detection. When used together in a network with moderate mobility, the two techniques increase throughput by 17 in the presence of 40 misbehaving nodes, while increasing the percentage of overhead transmissions from the standard routing protocol's 9 to 17 . During extreme mobility, watchdog and pathrater can increase network throughput by 27 , while increasing the overhead transmissions from the standard routing protocol's 12 to 24 . Existing position-based unicast routing algorithms which forward packets in the geographic direction of the destination require that the forwarding node knows the positions of all neighbors in its transmission range. This information on direct neighbors is gained by observing beacon messages each node sends out periodically. Due to mobility, the information that a node receives about its neighbors becomes outdated, leading either to a significant decrease in the packet delivery rate or to a steep increase in load on the wireless channel as node mobility increases. In this paper, we propose a mechanism to perform position-based unicast forwarding without the help of beacons. In our contention-based forwarding scheme (CBF) the next hop is selected through a distributed contention process based on the actual positions of all current neighbors. For the contention process, CBF makes use of biased timers. To avoid packet duplication, the first node that is selected suppresses the selection of further nodes. We propose three suppression strategies which vary with respect to forwarding efficiency and suppression characteristics. We analyze the behavior of CBF with all three suppression strategies and compare it to an existing greedy position-based routing approach by means of simulation with ns-2. Our results show that CBF significantly reduces the load on the wireless channel required to achieve a specific delivery rate compared to the load a beacon-based greedy forwarding strategy generates.