A recent study characterizing failures in computer networks shows that transient single element (node link) failures are the dominant failures in large communication networks like the Internet. Thus, having the routing paths globally recomputed on a failure does not pay off since the failed element recovers fairly quickly, and the recomputed routing paths need to be discarded. In this paper, we present the first distributed algorithm that computes the alternate paths required by some "proactive recovery schemes" for handling transient failures. Our algorithm computes paths that avoid a failed node, and provides an alternate path to a particular destination from an upstream neighbor of the failed node. With minor modifications, we can have the algorithm compute alternate paths that avoid a failed link as well. To the best of our knowledge all previous algorithms proposed for computing alternate paths are centralized, and need complete information of the network graph as input to the algorithm.
A popular approach of tackling the issues related to transient failures of network elements is that of using proactive recovery schemes . These schemes typically work by precomputing alternate paths at the network setup time for the failure scenarios, and then using these alternate paths to re-route the traffic when the failure actually occurs. Also, the information of the failure is suppressed in the hope that the failure is transient and the failed element will recover shortly. The local rerouting based solutions proposed in @cite_5 @cite_16 @cite_10 @cite_12 @cite_0 fall into this category.
@cite_0 @cite_5 @cite_16 @cite_10 @cite_12
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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. As the failure frequency is increasing with the components count in modern and future supercomputers, resilience is becoming critical for extreme scale systems. The association of failure prediction with proactive checkpointing seeks to reduce the effect of failures in the execution time of parallel applications. Unfortunately, proactive checkpointing does not systematically avoid restarting from scratch. To mitigate this issue, failure prediction and proactive checkpointing can be coupled with periodic checkpointing. However, blind use of these techniques does not always improves system efficiency, because everyone of them comes with a mix of overheads and benefits. In order to study and understand the combination of these techniques and their improvement in the system's efficiency, we developed: (i) a prototype combining state of the art failure prediction, fast proactive checkpointing and preventive checkpointing; (ii) a mathematical model that reflects the expected computing efficiency of the combination and computes the optimal checkpointing interval in this context; (iii) a discrete event simulator to evaluate the computing efficiency of the combination for system parameters corresponding to the current and projected large scale HPC systems. We evaluate our proposed technique on a large supercomputer (i.e. TSUBAME2) with production-level HPC applications and we show that failure prediction, proactive and preventive checkpointing can be coupled successfully, imposing only about 2 to 6 of overhead in comparison with preventive checkpointing only. Moreover, our model-based simulations show that the optimal solution improves the computing efficiency up to 30 in comparison with classic periodic checkpointing. We show that the prediction recall has a much higher impact on execution efficiency than the prediction precision. This result suggests that researchers on failure prediction algorithms should focus on improving the recall. We also show that the combination of these techniques can significantly improve (by a factor 2, for a particular configuration) the mean time between failures (MTBF) perceived by the application. Single node failures represent more than 85 of all node failures in the today's large communication networks such as the Internet. Also, these node failures are usually transient. Consequently, having the routing paths globally recomputed does not pay off since the failed nodes recover fairly quickly, and the recomputed routing paths need to be discarded. Instead, we develop algorithms and protocols for dealing with such transient single node failures by suppressing the failure (instead of advertising it across the network), and routing messages to the destination via alternate paths that do not use the failed node. We compare our solution to that of Ref. [11] wherein the authors have presented a "Failure Insensitive Routing" protocol as a proactive recovery scheme for handling transient node failures. We show that our algorithms are faster by an order of magnitude while our paths are equally good. We show via simulation results that our paths are usually within 15 of the optimal for randomly generated graph with 100-1000 nodes. Built upon a shared wireless medium, wireless network is particularly vulnerable to jamming attacks. The ability to recover from attacks and maintain an acceptable level of service degradation is a crucial aspect in the design of a wireless network. To address this issue, this paper investigates the network restoration solutions via the joint design of traffic rerouting, channel re-assignment, and scheduling. Efficient routing and channel assignment schemes can relieve the interference caused by both the normal network nodes and the jamming nodes. Therefore, based on the necessary conditions of schedulability, we first formulate the optimal network restoration problem as linear programming problem, which gives an upper bound on the achievable network throughput. After we solve the LP problems, we have a set of flows assigned to edges that have been assigned to different channels. And based on the LP solutions, we provide a greedy scheduling algorithm using dynamic channel assignment, which schedules both the network traffic and the jamming traffic. In particular, we consider two strategies, namely global restoration and local restoration, which can support a range of tradeoffs between the restoration latency and network throughput after restoration. To quantitatively evaluate the impact of jamming attacks during and after restoration, we define two performance degradation indices, transient disruption index (TDI) and throughput degradation index (THI). Finally, extensive performance evaluations are performed to study the impact of various jamming scenarios in a multi-hop multi-channel wireless network.