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.
Refs. @cite_5 @cite_0 present protocols based on local re-routing for dealing with transient single link and single node failures respectively. They demonstrate via simulations that the recovery paths computed by their algorithm are usually within 15 the theoretically optimal alternate paths.
@cite_0 @cite_5
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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. We investigate the single link failure recovery problem and its application to the alternate path routing problem for ATM networks, and the k-replacement edges for each edge of a minimum cost spanning tree. Specifically, given a 2-connected graph G, a specified node s, and a shortest paths tree Ts = e1, e2, . . . , eni1 of s, where ei = (xi, yi) and xi = parentTs(yi), find a shortest path from yi to s in the graph G for 1 · i · n i 1. We present an O(m + n log n) time algorithm for this problem and a linear time algorithm for the case when all weights are equal. When the edge weights are integers, we present an algorithm that takes O(m + Tsort(n)) time, where Tsort(n) is the time required to sort n integers. We establish a lower bound of ­(min(m p n, n 2 )) for the directed version of our problem under the path comparison model, where Ts is the shortest paths destination tree of s. We show that any solution to the single link recovery problem can be adapted to solve the alternate path routing problem in ATM networks. Our technique for the single link failure recovery problem is adapted to find the k-replacement edges for the tree edges of a minimum cost spanning tree in O(m + n log n) time. 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. 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. Node failures are inevitable in distributed storage systems (DSS). To enable efficient repair when faced with such failures, two main techniques are known: Regenerating codes, i.e., codes that minimize the total repair bandwidth; and codes with locality, which minimize the number of nodes participating in the repair process. This paper focuses on regenerating codes with locality, using pre-coding based on Gabidulin codes, and presents constructions that utilize minimum bandwidth regenerating (MBR) local codes. The constructions achieve maximum resilience (i.e., optimal minimum distance) and have maximum capacity (i.e., maximum rate). Finally, the same pre-coding mechanism can be combined with a subclass of fractional-repetition codes to enable maximum resilience and repair-by-transfer simultaneously. 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. A new distributed algorithm is presented for dynamically determining weighted shortest paths used for message routing in computer networks. The major features of the algorithm are that the paths defined do not form transient loops when weights change and the number of steps required to find new shortest paths when network links fail is less than for previous algorithms. Specifically, the worst case recovery time is proportional to the largest number of hops h in any of the weighted shortest paths. For previous loop-free distributed algorithms this recovery time is proportional to h2. 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. For restoration in the case of single link failures in meshed networks several strategies can be considered: link restoration, path restoration and path restoration with link-disjunct route. In terms of spare capacity requirement path restoration is found to be most attractive. These results are obtained by using two general optimisation techniques (simulated annealing and integer linear programming). Both techniques have each their own features; their applicability depends on the size and type of the problem. Application to WDM fibre networks is discussed. Due to the highly dynamic topology and absence of any fixed infrastructure, stability of selected path is of prime importance in ad hoc networks. The frequent route failure and high control overhead in routing protocols lead to degraded system performance. This paper proposes a stability based distributed adaptive routing protocol for ad hoc networks, which uses the worst case lifetime of wireless links, which is obtained by linear regression of the variation of distance between nodes as the routing metric. An efficient beaconing mechanism, load balancing, pro-active and reactive route reconfiguration mechanisms are also studied with the protocol. The protocol is supported with simulation using GloMoSim. This paper presents and evaluates two principles for wireless routing protocols. The first is datapath validation: data traffic quickly discovers and fixes routing inconsistencies. The second is adaptive beaconing: extending the Trickle algorithm to routing control traffic reduces route repair latency and sends fewer beacons. We evaluate datapath validation and adaptive beaconing in CTP Noe, a sensor network tree collection protocol. We use 12 different testbeds ranging in size from 20--310 nodes, comprising seven platforms, and six different link layers, on both interference-free and interference-prone channels. In all cases, CTP Noe delivers > 90 of packets. Many experiments achieve 99.9 . Compared to standard beaconing, CTP Noe sends 73 fewer beacons while reducing topology repair latency by 99.8 . Finally, when using low-power link layers, CTP Noe has duty cycles of 3 while supporting aggregate loads of 30 packets minute. Mobile ad hoc networks are characterized by multi-hop wireless links, absence of any cellular infrastructure, and frequent host mobility. Design of efficient routing protocols in such networks is a challenging issue. A class of routing protocols called on-demand protocols has recently attracted attention because of their low routing overhead. The on-demand protocols depend on query floods to discover routes whenever a new route is needed. Such floods take up a substantial portion of network bandwidth. We focus on a particular on-demand protocol, called dynamic source routing, and show how intelligent use of multipath techniques can reduce the frequency of query floods. We develop an analytic modeling framework to determine the relative frequency of query floods for various techniques. Results show that while multipath routing is significantly better than single path routing, the performance advantage is small beyond a few paths and for long path lengths. It also shows that providing all intermediate nodes in the primary (shortest) route with alternative paths has a significantly better performance than providing only the source with alternate paths. 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 studies the capacity and flow assignment problem arising in the design of self-healing asynchronous transfer mode (ATM) networks using the virtual path concept. The problem is formulated here as a linear programming problem which is solved using standard methods. The objective is to minimize the spare capacity cost for the given restoration requirement. The spare cost depends on the restoration strategies used in the network. We compare several restoration strategies quantitatively in terms of spare cost, notably: global versus failure-oriented reconfiguration, path versus link restoration, and state-dependent versus state-independent restoration. The advantages and disadvantages of various restoration strategies are also highlighted. Such comparisons provide useful guidance for real network design. Further, a new heuristic algorithm based on the minimum cost route concept is developed for the design of large self-healing ATM networks using path restoration. Numerical results illustrate that the heuristic algorithm is efficient and gives near-optimal solutions for the spare capacity allocation and flow assignment for tested examples. This paper deals with a distributed adaptive routing strategy which is very simple and effective, and is free of a ping-pong-type looping in the presence of network failures. Using the number of time intervals required for a node to recover from a network failure as the measure of network's adaptability, performance of this strategy and the ARPANET's previous routing strategy (APRS) is comparatively analyzed without resorting to simulation. Formulas of the exact number of time intervals required for failure recovery under both strategies are also derived. We show that i)the performance of the strategy is always better than, or at least as good as, that of APRS, and ii) network topology has significant effects on the performance of both strategies. 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. We revisit in this paper the resilience problem of routing traffic in a parallel link network model with a malicious player using a game theoretic framework. Consider that there are two players in the network: the first player wishes to split its traffic so as to minimize its average delay, which the second player, i.e., the malicious player, tries to maximize. The first player has a demand constraint on the total traffic it routes. The second player controls the link capacities: it can decrease by some amount the capacity of each link under a constraint on the sum of capacity degradation. We first show that the average delay function is convex both in traffic and in capacity degradation over the parallel links and thus does not have a saddle point. We identify best responses strategies of each player and compute both the max-min and the min-max values of the game. We are especially interested in the min max strategy as it guarantees the best performance under worst possible link capacity degradation. It thus allows to obtain routing strategies that are resilient and robust. We compare the results of the min-max to those obtained under the max-min strategies. We provide stable algorithms for computing both max-min and min-max strategies as well as for best responses. Routing protocols using the distributed Bellman-Ford (DBF) algorithm converge very slowly to the correct routes when link costs increase, and in the case when a set of link failures results in a network partition, DBF simply fails to converge, a problem which is commonly referred to as the count-to-infinity problem. We present the first distance-vector routing algorithm, MDVA, that uses a set of loop-free invariants to prevent the count-to-infinity problem. MDVA, in addition, computes multipaths that are loop-free at every instant. In our earlier work we shows how such loop-free multipaths can be used in traffic load-balancing and minimizing delays, which otherwise are impossible to perform in current single-path routing algorithms. Jamming attacks are especially harmful to the reliability of wireless communication, as they can effectively disrupt communication between any node pairs. Existing jamming defenses primarily focus on repairing connectivity between adjacent nodes. In this paper, we address jamming at the network level and focus on restoring the end-to-end data delivery through multipath routing. As long as all paths do not fail concurrently, the end-to-end path availability is maintained. Prior work in multipath selection improves routing availability by choosing node-disjoint paths or link-disjoint paths. However, through our experiments on jamming effects using MicaZ nodes, we show that disjointness is insufficient for selecting fault-independent paths. Thus, we address multipath selection based on the knowledge of a path's availability history. Using Availability History Vectors (AHVs) of paths, we present a centralized AHV-based algorithm to select fault-independent paths, and a distributed AHV-based routing protocol built on top of a classic routing algorithm in ad hoc networks. Our extensive simulation results validate that both AHV-based algorithms are effective in overcoming the jamming impact by maximizing the end-to-end availability of the selected paths. 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.