Reliability of Computer Systems and Networks Fault Tolerance, Analysis, and Design

Rupe, Jason

doi:10.1080/07408170304426

Cited by 7 publications

(19 citation statements)

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“…System reliability is defined as the probability that the system operates without failure in the interval [0, t], given that the system was performing correctly at time 0 [22]. In contrast, service reliability, which we denote by R min , refers to the minimum reliability among all nodes (aggregators).…”

Section: Solving the Control Plane Deployment Problem With Reliamentioning

confidence: 99%

“…We initiate the master problem with a set of paths κ * ⊆ κ (lines 1-3), Algorithm 5. Then, we begin a repetitive process for adding new paths: 1) solve the master problem 2 and obtain values of the duals of the constraints imposed on edges and flows (lines 11-12); 2) identify the new paths K f as the paths that violate dual constraint (14 in Section III-E) (lines 13-17), while satisfying requirements due to delay and backlog constraints (line 18); 3) add the new potential path to the subset κ * and repeat the process again (line [19][20][21][22][23][24]. The process is repeated until no new paths can be found, or the maximum number of iterations is reached, or the object value does not improve with the newly added path (line 7-8).…”

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confidence: 99%

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Fast Deployment of Reliable Distributed Control Planes With Performance Guarantees

et al. 2020

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Current trends strongly indicate a transition towards large-scale programmable networks with virtual network functions. In such a setting, deployment of distributed control planes will be vital for guaranteed service availability and performance. Moreover, deployment strategies need to be completed quickly in order to respond flexibly to varying network conditions. We propose an effective optimization approach that automatically decides on the needed number of controllers, their locations, control regions, and traffic routes into a plan which fulfills control flow reliability and routability requirements, including bandwidth and delay bounds. The approach is also fast: the algorithms for bandwidth and delay bounds can reduce the running time at the level of 50x and 500x, respectively, compared to state-of-the-art and direct solvers such as CPLEX. Altogether, our results indicate that computing a deployment plan adhering to predetermined performance requirements over network topologies of various sizes can be produced in seconds and minutes, rather than hours and days. Such fast allocation of resources that guarantees reliable connectivity and service quality is fundamental for elastic and efficient use of network resources. INDEX TERMS Software-defined networking, distributed control plane, controller placement problem, latency, reliability, routability, optimization. V K possible ways to map them on the network. For each mapping, there are K V possible ways of defining control regions.

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Section: Solving the Control Plane Deployment Problem With Reliamentioning

confidence: 99%

mentioning

confidence: 99%

Fast Deployment of Reliable Distributed Control Planes With Performance Guarantees

et al. 2020

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“…According to [25], the reliability of a system is defined as the probability that the system operates without failure in the interval [0, t], given that the system was performing correctly at time 0. In this section, we describe our optimization approach that targets at service reliability.…”

Section: Control Plane Optimizationmentioning

confidence: 99%

Flexible distributed control plane deployment

Liu¹,

Steinert²,

Kostić

2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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For large-scale programmable networks, flexible deployment of distributed control planes is essential for service availability and performance. However, existing approaches only focus on placing controllers whereas the consequent control traffic is often ignored. In this paper, we propose a black-box optimization framework offering the additional steps for quantifying the effect of the consequent control traffic when deploying a distributed control plane. Evaluating different implementations of the framework over real-world topologies shows that close to optimal solutions can be achieved. Moreover, experiments indicate that running a method for controller placement without considering the control traffic, cause excessive bandwidth usage (worst cases varying between 20.1%-50.1% more) and congestion, compared to our approach.

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“…Reliability is represented by Eq. (1), where T is a random variable that represents the time for occurrence of defects in the system [3,4].…”

Section: Basic Conceptsmentioning

confidence: 99%

“…The major problem with this assignment is the estimation of the number of redundant equipment and the choice of the type of redundancy that must be considered to guarantee the quality of the service offered. The estimation of the type and number of redundant equipment should also consider the cost of the quantitative of each type of redundancy mechanism attributed to the components of the cloud computing [3,4].…”

Section: Introductionmentioning

confidence: 99%

Modeling Strategies to Improve the Dependability of Cloud Infrastructures

Sousa¹,

Lins²

2018

Dependability Engineering

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Cloud computing presents some challenges that need to be overcome, such as planning infrastructures that maintain availability when failure events and repair activities occur. Cloud infrastructure planning that addresses the dependability aspects is an essential activity because it ensures business continuity and client satisfaction. Redundancy mechanisms cold standby, warm standby and hot standby can be allocated to components of the cloud infrastructure to maintain the availability levels agreed in service level agreement (SLAs). Mathematical formalisms based on state space such as stochastic Petri nets and based on combinatorial as reliability block diagrams can be adopted to evaluate the dependability of cloud infrastructures considering the allocation of different redundancy mechanisms to its components. This chapter shows the adoption of the mathematical formalisms stochastic Petri nets and reliability block diagrams to dependability evaluation of cloud infrastructures with different redundancy mechanisms.

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Reliability of Computer Systems and Networks Fault Tolerance, Analysis, and Design

Cited by 7 publications

References 0 publications

Fast Deployment of Reliable Distributed Control Planes With Performance Guarantees

Fast Deployment of Reliable Distributed Control Planes With Performance Guarantees

Flexible distributed control plane deployment

Modeling Strategies to Improve the Dependability of Cloud Infrastructures

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