Service-level agreement | EPFL Graph Search

A service-level agreement (SLA) is an agreement between a service provider and a customer. Particular aspects of the service – quality, availability, responsibilities – are agreed between the service provider and the service user. The most common component of an SLA is that the services should be provided to the customer as agreed upon in the contract. As an example, Internet service providers and telcos will commonly include service level agreements within the terms of their contracts with customers to define the level(s) of service being sold in plain language terms. In this case, the SLA will typically have a technical definition of mean time between failures (MTBF), mean time to repair or mean time to recovery (MTTR); identifying which party is responsible for reporting faults or paying fees; responsibility for various data rates; throughput; jitter; or similar measurable details. Overview A service-level agreement is an agreement between two or more parties,

An Accountability Interface for the Internet

Olga Irzak

The Internet provides no information on the fate of transmitted packets, and end systems cannot determine who is responsible for dropping or delaying their traffic. As a result, they cannot verify that their ISPs are honoring their service level agreements, nor can they react to adverse network conditions appropriately. While current probing tools provide some assistance in this regard, they only give feedback on probes, not actual traffic. Moreover, service providers could, at any time, render their network opaque to such tools. We propose an explicit accountability interface, through which ISPs can pro-actively supply feedback to traffic sources on loss and delay, at administrative-domain granularity. Notably, our interface is resistant to ISP lies and can be implemented with a modest NetFlow modification. On our Click-based prototype, playback of real traces from a Tier-1 ISP reveals less than 2% bandwidth overhead. Finally, our proposal benefits not only end systems, but also ISPs, who can now control the amount and quality of information revealed about their internals.

2007

Loss and Delay Accountability for the Internet

Olga Irzak

The Internet provides no information on the fate of transmitted packets, and end systems cannot determine who is responsible for dropping or delaying their traffic. As a result, they cannot verify that their ISPs are honoring their service level agreements, nor can they react to adverse network conditions appropriately. While current probing tools provide some assistance in this regard, they only give feedback on probes, not actual traffic. Moreover, service providers could, at any time, render their network opaque to such tools. We propose "AudIt," an explicit "accountability interface," through which ISPs can pro-actively supply feedback to traffic sources on loss and delay, at administrative-domain granularity. Notably, our interface is resistant to ISP lies and can be implemented with a modest NetFlow modification. On our Click-based prototype, playback of real traces from a Tier-1 ISP reveals less than 2% bandwidth overhead. Finally, our proposal benefits not only end systems, but also ISPs, who can now control the amount and quality of information revealed about their internals.

2007

Limiting the impact of supply chain disruptions in the face of distributional uncertainty in demand

René Yves Glogg, Ralf Seifert, Anna Timonina-Farkas

Service-level requirements play a crucial role in eliminating stock-outs in a production pipeline. However, delivering a specific service level can become an unattainable goal given the various uncertainties influencing both the production pipeline and customer demand and causing the manufacturer to adapt the initial strategy in response to disruptions. Such deviations from optimality frequently result in unexpected (and potentially very high) costs and are complex to manage. On the one hand, the manufacturer can use a robust or distributionally robust approach to prepare for the worst-case disruption, ensuring that the realized cost will be lower than the estimated cost with high probability. On the other hand, this solution may lead to overly conservative production schedules. In this article, we take a different approach and develop a bilevel stochastic optimization model with chance constraints, which allows us to make the production more predictable in the event of disruptions by driving costs and optimal schedules closer to the benchmark for each scenario considered. We introduce doubly probabilistic service-level requirements to account for two interdependent layers of uncertainty, that is, production disruptions and distributional uncertainties in customer demand. This allows us to make high-quality production decisions with only a limited understanding of the demand pattern. Approximating the problem for a numerical solution, we guarantee tight optimality gaps for high service levels and propose an efficient solution scheme, combining robust scenario reduction with a customized Benders decomposition procedure. In the managerial section, we use the Omegax Swatch MoonSwatches example to demonstrate that a desirable doubly probabilistic service level can be attained for disruptions with a drop in demand. In the case of disruptions followed by a peak in demand, one can tighten the optimality gaps if the service level is reduced.

WILEY2022

Limiting the impact of supply chain disruptions in the face of distributional uncertainty in demand

René Yves Glogg, Ralf Seifert, Anna Timonina-Farkas

WILEY2022