Service level objective

About: Service level objective is a research topic. Over the lifetime, 7894 publications have been published within this topic receiving 218701 citations.

System for selective communication connection based on transaction pricing signals

Abstract: A communications network in which user equipment is provided with a selecting device which communicates with a pricing device in service provider equipment. When communications or other services are required, the selection circuit polls a plurality of service providers, and the pricing circuit of each service provider generates a price signal indicating the level of price for its services. The selection circuit then selects a service provider, based on price (and also other factors such as quality of service).

ARIA: automatic resource inference and allocation for mapreduce environments

Abstract: MapReduce and Hadoop represent an economically compelling alternative for efficient large scale data processing and advanced analytics in the enterprise. A key challenge in shared MapReduce clusters is the ability to automatically tailor and control resource allocations to different applications for achieving their performance goals. Currently, there is no job scheduler for MapReduce environments that given a job completion deadline, could allocate the appropriate amount of resources to the job so that it meets the required Service Level Objective (SLO). In this work, we propose a framework, called ARIA, to address this problem. It comprises of three inter-related components. First, for a production job that is routinely executed on a new dataset, we build a job profile that compactly summarizes critical performance characteristics of the underlying application during the map and reduce stages. Second, we design a MapReduce performance model, that for a given job (with a known profile) and its SLO (soft deadline), estimates the amount of resources required for job completion within the deadline. Finally, we implement a novel SLO-based scheduler in Hadoop that determines job ordering and the amount of resources to allocate for meeting the job deadlines.We validate our approach using a set of realistic applications. The new scheduler effectively meets the jobs' SLOs until the job demands exceed the cluster resources. The results of the extensive simulation study are validated through detailed experiments on a 66-node Hadoop cluster.

Medical insurance verification and processing system

Abstract: A medical claim verification and processing system reads a medical information card (MEDICARD) to determine a patient's background medical and insurance information. The validity of the card is rapidly determined by accessing a central brokerage computer. A local service provider enters into a local terminal the medical and MEDICARD information services provided or to be provided to the patient by using a patient service code and transmits this information to a central brokerage computer. The central brokerage computer converts the patient service code input by the service provider or MEDICARD into a particular service code for the patient's insurance carrier. This service code is then utilized to determine the insurance claim payment for that particular patient service. The claim payment amount for the medical service is then transmitted back to the local entry terminal for use by the service provider and patient. The service provider and patient can then determine the amount of payment which will be made for the particular insurance claim. The provider can then prepare an electronic claim form and, together with the patient's and/or the provider's determination whether or not the assignment provision of the insurance claim will be invoked, the electronic claim form is then transmitted to a central brokerage computer which in turn transmits the claim form to the appropriate insurance carrier. The patient's insurance carrier processes the claim form, and, based upon the assignment decision, transfers the payment check to the patient or makes an electronic funds transfer to an account for the service provider, the patient or a central brokerage computer.

Antecedents to satisfaction with service recovery

Abstract: Building on disconfirmation theory, equity theory and affect‐balance theory, considers antecedents to satisfaction with service recovery. A theoretical model is proposed and tested empirically based on a cross‐sectional national sample of 201 dissatisfied customers complaining of services. The results suggest that perceived performance of service recovery has an impact on equity. Second, disconfirmation of expectations of service recovery and perceived fairness of outcome of service recovery have an impact on satisfaction with service recovery. Finally, negative affect caused by the initial service failure does not have an impact on satisfaction with service recovery.