Service level

About: Service level is a research topic. Over the lifetime, 7647 publications have been published within this topic receiving 126093 citations. The topic is also known as: service level.

A quantitative view on how RFID can improve inventory management in a supply chain

Abstract: Radio-frequency identification (RFID) as an emerging technology has generated an enormous amount of interest in the supply chain arena. There are a number of theoretical advantages of RFID technology. Inventory can be tracked more accurately in real time, resulting in reduced processing time and labour. More significantly, the complete visibility of accurate inventory data throughout the entire supply chain, from the manufacturing shop floor to warehouses to retail stores, brings opportunities for transformation and improvement in various processes of the supply chain. In this study, we investigate how these advantages can be utilised to improve the inventory performance of a supply chain. We identify the relevant results in the existing supply chain literature, and model the impact of RFID using computer simulation when we cannot find existing results. Our study provides a comprehensive view and some new insights on the potential benefits of RFID in terms of inventory reduction and service level improvement.

Resource-level QoS metric for CPU-based guarantees in cloud providers

Abstract: Success of Cloud computing requires that both customers and providers can be confident that signed Service Level Agreements (SLA) are supporting their respective business activities to their best extent. Currently used SLAs fail in providing such confidence, especially when providers outsource resources to other providers. These resource providers typically support very simple metrics, or metrics that hinder an efficient exploitation of their resources. In this paper, we propose a resource-level metric for specifying finegrain guarantees on CPU performance. This metric allows resource providers to allocate dynamically their resources among the running services depending on their demand. This is accomplished by incorporating the customer's CPU usage in the metric definition, but avoiding fake SLA violations when the customer's task does not use all its allocated resources. As demonstrated in our evaluation, which has been conducted in a virtualized provider where we have implemented the needed infrastructure for using our metric, our solution presents fewer SLA violations than other CPU-related metrics.

On the Scheduling of Energy-Aware Fault-Tolerant Mixed-Criticality Multicore Systems with Service Guarantee Exploration

Abstract: Advancement of Cyber-Physical Systems has attracted attention to Mixed-Criticality Systems (MCSs), both in research and in industrial designs. As multicore platforms are becoming the dominant trend in MCSs, joint energy and reliability management is a crucial issue. In addition, providing guaranteed service level for low-criticality tasks in critical mode is of great importance. To address these problems, we propose “LETR-MC” scheme that simultaneously supports certification, energy management, fault-tolerance, and guaranteed service level in mixed-criticality multicore systems. In this paper, we exploit task-replication to not only satisfy reliability requirements, but also to improve the QoS of low-criticality tasks in overrun situation. Our proposed LETR-MC scheme determines the number of replicas, and reduces the execution time overlap between the primary tasks and replicas. Moreover, instead of ignoring low-criticality tasks or selectively executing them without any guaranteed service level in overrun mode, it mathematically explores the minimum achievable service guarantee for each low-criticality task in different execution modes, i.e., normal, fault-occurrence, overrun and critical operation modes. We develop novel unified demand bound functions (DBF), along with a DVFS method based on the proposed DBF analysis. Our experimental results show that LETR-MC provides up to 59 percent (24 percent on average) energy saving, and significantly improves the service levels of low-criticality tasks compared to the state-of-the-art schemes.

Cloud Work Bench -- Infrastructure-as-Code Based Cloud Benchmarking

Abstract: In order to optimally deploy their applications, users of Infrastructure-as-a-Service clouds are required to evaluate the costs and performance of different combinations of cloud configurations to find out which combination provides the best service level for their specific application. Unfortunately, benchmarking cloud services is cumbersome and error-prone. In this paper, we propose an architecture and concrete implementation of a cloud benchmarking Web service, which fosters the definition of reusable and representative benchmarks. In distinction to existing work, our system is based on the notion of Infrastructure-as-Code, which is a state of the art concept to define IT infrastructure in a reproducible, well-defined, and testable way.