Showing papers on "Service level published in 2010"

Minimizing Electricity Cost: Optimization of Distributed Internet Data Centers in a Multi-Electricity-Market Environment

Abstract: The study of Cyber-Physical System (CPS) has been an active area of research. Internet Data Center (IDC) is an important emerging Cyber-Physical System. As the demand on Internet services drastically increases in recent years, the power used by IDCs has been skyrocketing. While most existing research focuses on reducing power consumptions of IDCs, the power management problem for minimizing the total electricity cost has been overlooked. This is an important problem faced by service providers, especially in the current multi-electricity market, where the price of electricity may exhibit time and location diversities. Further, for these service providers, guaranteeing quality of service (i.e. service level objectives-SLO) such as service delay guarantees to the end users is of paramount importance. This paper studies the problem of minimizing the total electricity cost under multiple electricity markets environment while guaranteeing quality of service geared to the location diversity and time diversity of electricity price. We model the problem as a constrained mixed-integer programming and propose an efficient solution method. Extensive evaluations based on real-life electricity price data for multiple IDC locations illustrate the efficiency and efficacy of our approach.

Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centers

Abstract: The rapid growth in demand for computational power driven by modern service applications combined with the shift to the Cloud computing model have led to the establishment of large-scale virtualized data centers. Such data centers consume enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions. Dynamic consolidation of virtual machines (VMs) and switching idle nodes off allow Cloud providers to optimize resource usage and reduce energy consumption. However, the obligation of providing high quality of service to customers leads to the necessity in dealing with the energy-performance trade-off. We propose a novel technique for dynamic consolidation of VMs based on adaptive utilization thresholds, which ensures a high level of meeting the Service Level Agreements (SLA). We validate the high efficiency of the proposed technique across different kinds of workloads using workload traces from more than a thousand PlanetLab servers.

Low level Metrics to High level SLAs - LoM2HiS framework: Bridging the gap between monitored metrics and SLA parameters in cloud environments

Abstract: Cloud computing represents a novel on-demand computing approach where resources are provided in compliance to a set of predefined non-functional properties specified and negotiated by means of Service Level Agreements (SLAs). In order to avoid costly SLA violations and to timely react to failures and environmental changes, advanced SLA enactment strategies are necessary, which include appropriate resource-monitoring concepts. Currently, Cloud providers tend to adopt existing monitoring tools, as for example those from Grid environments. However, those tools are usually restricted to locality and homogeneity of monitored objects, are not scalable, and do not support mapping of low-level resource metrics e.g., system up and down time to high-level application specific SLA parameters e.g., system availability. In this paper we present a novel framework for managing the mappings of the Low-level resource Metrics to High-level SLAs (LoM2HiS framework). The LoM2HiS framework is embedded into FoSII infrastructure, which facilitates autonomic SLA management and enforcement. Thus, the LoM2HiS framework detects future SLA violation threats and can notify the enactor component to act so as to avert the threats. We discuss the conceptual model of the LoM2HiS framework, followed by the implementation details. Finally, we present the first experimental results and a proof of concept of the LoM2HiS framework.

Dynamic proportional share scheduling in Hadoop

Abstract: We present the Dynamic Priority (DP) parallel task scheduler for Hadoop. It allows users to control their allocated capacity by adjusting their spending over time. This simple mechanism allows the scheduler to make more efficient decisions about which jobs and users to prioritize and gives users the tool to optimize and customize their allocations to fit the importance and requirements of their jobs. Additionally, it gives users the incentive to scale back their jobs when demand is high, since the cost of running on a slot is then also more expensive. We envision our scheduler to be used by deadline or budget optimizing agents on behalf of users. We describe the design and implementation of the DP scheduler and experimental results. We show that our scheduler enforces service levels more accurately and also scales to more users with distinct service levels than existing schedulers.

Cost modelling techniques for availability type service support contracts: a literature review and empirical study

Abstract: The traditional distinction between manufacturing and services, both in relation to products and indeed, the actual companies themselves, is getting blurred. Increasingly services are becoming a major part of the company offerings in manufacturing sector. In order to compete in a transformed environment, companies need to assess the cost of their service offerings properly to stay competitive. The research in this paper is focused on enhancing existing knowledge in cost estimation models for availability type support service contracts that focus on equipment availability targets and predefined service levels. Most of the current studies concentrate on product cost estimation rather than on services. The difficulty of this task lies in properly estimating the costs of activities during the long lasting contracts, which in some cases may reach even several decades. The paper first reports the existing knowledge in cost estimating techniques through detailed review of literature and presents the key cost assessment techniques that can be used in estimating the cost of service contracts over its entire life-cycle. The paper investigates different availability type support contracts in defence sector and reports the cost assessment techniques used in practice. The paper presents an integrated framework for costing availability type service contracts based on the literature and practice. The gaps in cost modelling of availability type service contracts and areas for further research are identified.

Service-Level Differentiation in Many-Server Service Systems via Queue-Ratio Routing

Abstract: Motivated by telephone call centers, we study large-scale service systems with multiple customer classes and multiple agent pools, each with many agents. To minimize staffing costs subject to service-level constraints, where we delicately balance the service levels (SLs) of the different classes, we propose a family of routing rules called fixed-queue-ratio (FQR) rules. With FQR, a newly available agent next serves the customer from the head of the queue of the class (from among those he is eligible to serve) whose queue length most exceeds a specified proportion of the total queue length. The proportions can be set to achieve desired SL targets. The FQR rule achieves an important state-space collapse (SSC) as the total arrival rate increases, in which the individual queue lengths evolve as fixed proportions of the total queue length. In the current paper we consider a variety of service-level types and exploit SSC to construct asymptotically optimal solutions for the staffing-and-routing problem. The key assumption in the current paper is that the service rates depend only on the agent pool.

Transparent Header Modification for Reducing Serving Load Based on Current and Projected Usage

Abstract: A method and system for dynamically altering the delivery of web content to end users based on server load. Responsive to receiving a client request for web content, utilization metrics are collected from each device involved in delivering the web content. A device load level is determined for each device based on the utilization metrics, a system load level is determined for a subset of the devices having the same device type based on the device load levels, and a service level to provide to the client is determined based on the system load level. The request header is modified to specify the service level to provide to the client, wherein the service level indicates the web content variant to deliver. The request is sent with the modified header to a selected device which serves the web content according to the service level to the client.

Automated service level management of applications in cloud computing environment

Abstract: Automated service level management of applications can include automated deployment, monitoring, forecasting, and/or predicting based on a plurality of service levels comprising application level, application server platform level, virtual machine level, and/or infrastructure level, and optimizations at multiple levels using a plurality of techniques including automated dynamic application migration. Automated deployment of applications in a cloud computing environment using deployment descriptors comprises receiving values for service level parameters for an application, creating a deployment descriptor based on the parameters, identifying application servers that satisfy the deployment descriptors, and deploying the application to the identified application servers. Automated dynamic migration of applications in a cloud computing environment comprises deciding to migrate an application, obtaining application resource requirements, identifying application server candidates, selecting an application server from one of the candidates, and migrating the application.

Multi-functional landscapes in semi arid environments: implications for biodiversity and ecosystem services

Abstract: Synergies between biodiversity conservation objectives and ecosystem service management were investigated in the Succulent Karoo biome (83,000 km2) of South Africa, a recognised biodiversity hotspot Our study complemented a previous biodiversity assessment with an ecosystem service assessment Stakeholder engagement and expert consultation focussed our investigations on surface water, ground water, grazing and tourism as the key services in this region The key ecosystem services and service hotspots were modelled and mapped The congruence between these services, and between biodiversity priorities and ecosystem service priorities, were assessed and considered in relation to known threats Generally low levels of overlap were found between these ecosystem services, with the exception of surface and ground water which had an 80% overlap The overlap between ecosystem service hotspots and individual biodiversity priority areas was generally low Four of the seven priority areas assessed have more than 20% of their areas classified as important for services In specific cases, particular service levels could be used to justify the management of a specific biodiversity priority area for conservation Adopting a biome scale hotspot approach to assessing service supply highlighted key management areas However, it underplayed local level dependence on particular services, not effectively capturing the welfare implications associated with diminishing and limited service provision We conclude that regional scale (biome level) approaches need to be combined with local level investigations (municipal level) Given the regional heterogeneity and varied nature of the impacts of drivers and threats, diverse approaches are required to steer land management towards sustainable multifunctional landscape strategies

Genetic Algorithm for Bus Frequency Optimization

Abstract: In this paper, a bilevel programming model for the bus frequency design is presented, which determines the optimal bus frequencies aiming to minimize the total travel time of passengers subject to the constraint on the overall fleet size of each company by accounting for the route choice behaviors of the users. The objective of the lower level is to assign transit trips to bus route network based on optimal strategy. In the upper level, bus frequencies of routes are optimized as a result of passenger assignment. An iterative approach, which consists of a genetic algorithm and a label-marking method, is used to solve the bilevel model. Finally, the model and the algorithms are illustrated with two test examples. The results show that the optimization can improve the local service level of one company, and the proper integration of several companies probably improves the efficiency of resources and the service level of the whole transit system.

Periodic review inventory-control for perishable products under service-level constraints

Abstract: Food retail inventory management faces major challenges by uncertain demand, perishability, and high customer service level requirements. In this paper, we present a method to determine dynamic order quantities for perishable products with limited shelf-life, positive lead time, FIFO or LIFO issuing policy, and multiple service level constraints. In a numerical study, we illustrate the superiority of the proposed method over commonly suggested order-up-to-policies. We show that a constant-order policy might provide good results under stationary demand, short shelf-life, and LIFO inventory depletion.

Crowdsourcing service-level network event monitoring

Abstract: The user experience for networked applications is becoming a key benchmark for customers and network providers. Perceived user experience is largely determined by the frequency, duration and severity of network events that impact a service. While today's networks implement sophisticated infrastructure that issues alarms for most failures, there remains a class of silent outages (e.g., caused by configuration errors) that are not detected. Further, existing alarms provide little information to help operators understand the impact of network events on services. Attempts to address this through infrastructure that monitors end-to-end performance for customers have been hampered by the cost of deployment and by the volume of data generated by these solutions.We present an alternative approach that pushes monitoring to applications on end systems and uses their collective view to detect network events and their impact on services - an approach we call Crowdsourcing Event Monitoring (CEM). This paper presents a general framework for CEM systems and demonstrates its effectiveness for a P2P application using a large dataset gathered from BitTorrent users and confirmed network events from two ISPs. We discuss how we designed and deployed a prototype CEM implementation as an extension to BitTorrent. This system performs online service-level network event detection through passive monitoring and correlation of performance in end-users' applications.

Systems and methods for managing multi-level service level agreements in cloud-based networks

Abstract: Embodiments relate to systems and methods for managing multi-level service level agreements (SLAs) in cloud-based networks. A resource managing module can manage resources in the cloud-based networks in response to the detection of one or more triggering events. In embodiments, the triggering events can be changeovers in time periods, or meeting or exceeding thresholds associated with end user operation of the resources in the cloud-based networks. The multi-level SLAs can specify how to adjust the resources in the cloud-based networks in response to the detection of the triggering events. The resource managing module can adjust applicable resources in the cloud-based networks as specified by the multi-level SLAs.

A cloud agency for SLA negotiation and management

Abstract: Resources management facilities, based on service level agreements, are needed in the Cloud in order to negotiate a collection of inter-connected and virtualized computers between resource providers and consumers. In this paper we present the architectural design of a system named Cloud Agency which aims to respond to this need and to offer added value to the existing Cloud services. This system is in charge to broker the collection of Cloud resources from different providers that fulfills at the best the requirements of user's applications. The user is able to delegate to the Agency the necessary checks of the agreement fulfilment, the monitoring of resource utilization and eventually necessary re-negotiations.

The budget constrained r-interdiction median problem with capacity expansion

Abstract: In this article, we elaborate on a budget constrained extension of the r-interdiction median problem with fortification (RIMF). The objective in the RIMF is to find the optimal allocation of protection resources to a given service system consisting of p facilities so that the disruptive effects of r possible attacks to the system are minimized. The defender of the system needs to fortify q facilities of the present system to offset the worst-case loss of r non-fortified facilities due to an interdiction in which the attacker’s objective is to cause the maximum possible disruption in the service level of the system. The defender-attacker relationship fits a bilevel integer programming (BIP) formulation where the defender and attacker take on the respective roles of the leader and the follower. We adopt this BIP formulation and augment it with a budget constraint instead of a predetermined number of facilities to be fortified. In addition, we also assume that each facility has a flexible service capacity, which can be expanded at a unit cost to accommodate the demand of customers who were serviced by some other interdicted facility before the attack. First, we provide a discrete optimization model for this new facility protection planning scenario with a novel set of closest assignment constraints. Then, to tackle this BIP problem we use an implicit enumeration algorithm performed on a binary tree. For each node representing a different fortification scheme, the attacker’s problem is solved to optimality using Cplex 11. We report computational results obtained on a test bed of 96 randomly generated instances. The article concludes with suggestions for future research.

Taxi intelligent comprehensive supervision and service system

Abstract: The invention relates to a taxi intelligent comprehensive supervision and service system which comprises a taxi vehicle intelligent service system and a taxi comprehensive supervision service and operation analysis system. The taxi vehicle intelligent service system is connected with the taxi comprehensive supervision service and operation analysis system through a wireless network and sends on and off duty signing data of a driver, operation detail data, service evaluation data, passenger volume investigation and statistics data and alarm data to the taxi comprehensive supervision service and operation analysis system in real time; and the taxi comprehensive supervision service and operation analysis system receives and carries out mining analysis on the data and sends terminal control data, driver service quality star-level data, dynamic check data and public information data to the taxi vehicle intelligent service system, therefore, the invention can enhance the scientificity of industry management and decision and strengthen the supervision of a taxi industry, thereby enhancing the service level and the passenger satisfaction of the taxi industry.

Alternate risk measures for emergency medical service system design

Abstract: The stochastic nature of emergency service requests and the unavailability of emergency vehicles when requested to serve demands are critical issues in constructing valid models representing real life emergency medical service (EMS) systems. We consider an EMS system design problem with stochastic demand and locate the emergency response facilities and vehicles in order to ensure target levels of coverage, which are quantified using risk measures on random unmet demand. The target service levels for each demand site and also for the entire service area are specified. In order to increase the possibility of representing a wider range of risk preferences we develop two types of stochastic optimization models involving alternate risk measures. The first type of the model includes integrated chance constraints (ICCs ), whereas the second type incorporates ICCs and a stochastic dominance constraint. We develop solution methods for the proposed single-stage stochastic optimization problems and present extensive numerical results demonstrating their computational effectiveness.

Cloud Broker and Procurement System and Method

Abstract: A cloud broker and procurement system and method is closed. In particular embodiments, the method includes receiving an offer of a computing resource from each of a plurality of providers. The method further includes receiving, from each of the plurality of providers, a service level agreement associated with each respective offered computing resource. Additionally, the method includes normalizing each of the service level agreements associated with the offered computing resources. The method further includes receiving a request from a requesting computer for a computing resource and selecting, based at least in part on the normalized service level agreements, one of the providers to provide the requested computing resource. The method also includes transmitting a service match indicator to the client, wherein the service match indicator indicates a time at which the offered computing resource will be utilized, and utilizing the computing resource on the selected provider.

The impact of service encounter quality in service evaluation: evidence from a business‐to‐business context

Abstract: Purpose – This paper aims to examine the impact of service encounter quality within a service evaluation model. The conceptual model seeks to incorporate the following constructs: service encounter quality, service quality, customer satisfaction, perceived value, loyalty to the firm and loyalty to the employees.Design/methodology/approach – A conceptual model was developed based on a comprehensive literature review. A questionnaire was developed with item measures that captures the constructs in the conceptual model. A survey of business customers was undertaken, and a response rate of 18.6 per cent was obtained. The data are analysed via confirmatory factor analysis and structural equation modelling.Findings – Service encounter quality is directly related to customer satisfaction and service quality perceptions, and indirectly to perceived value and loyalty. The paper offers insights into the specifics of business‐to‐business service dynamics by examining the role of service quality, satisfaction, value ...

Out-of-Stock: Reactions, Antecedents, Management Solutions, and a Future Perspective

Abstract: In today’s competitive environment, service-oriented retailers are faced with one important question: How can we deliver good service levels to our customers, while becoming more cost efficient at the same time? Superior levels of service to customers are necessary to differentiate these retailers from the strongly priceoriented chains, such as Aldi, Lidl, ASDA, Wal-Mart, and Colruyt. One key differentiator of service retailers is their assortment. In general, service retailers offer more national brands than discounters, and also a wider variety of products. However, offering more variety in products and brands has two important consequences. First, retailers are confronted with more costs in the supply chain, due to higher inventory, procurement, handling, and warehouse costs. Second, more variety also increases the probability that out-of-stocks (OOS) may occur, which may lead to customer dissatisfaction and (temporary) store disloyalty. As service retailers strive to compete with discounters on service, OOS can severely jeopardize their competitive position in the consumers’ mind.

Service-Level Agreements for Electronic Services

Abstract: The potential of communication networks and middleware to enable the composition of services across organizational boundaries remains incompletely realized. In this paper, we argue that this is in part due to outsourcing risks and describe the possible contribution of Service-Level Agreements (SLAs) to mitigating these risks. For SLAs to be effective, it should be difficult to disregard their original provisions in the event of a dispute between the parties. Properties of understandability, precision, and monitorability ensure that the original intent of an SLA can be recovered and compared to trustworthy accounts of service behavior to resolve disputes fairly and without ambiguity. We describe the design and evaluation of a domain-specific language for SLAs that tend to exhibit these properties and discuss the impact of monitorability requirements on service-provision practices.

SLA-driven planning and optimization of enterprise applications

Abstract: We propose a model-based methodology to size and plan enterprise applications subject to Service Level Agreements (SLAs). Our approach is illustrated using a real-world Enterprise Resource Planning (ERP) application, namely SAP ERP. Firstly, we develop a closed queueing network model with finite capacity regions describing the SAP ERP application performance and show that this model is effective and robust in capturing measured response times and utilizations. Secondly, we propose an analytical cost model that jointly accounts for fixed hardware costs and dynamic operational costs related to power consumption.Based on the developed performance and cost models, we propose to use multi-objective optimization to find the Pareto-optimal solutions that describe the best trade-off solutions between conflicting performance and cost-saving goals. Experimental validation demonstrates the accuracy of the proposed models and shows that the attained Pareto-optimal solutions can be efficiently used by service providers for SLA-driven planning decisions, thus making a strong case in favor of the applicability of our methodology for deployment decisions subject to different SLA requirements.

SLA validation in layered cloud infrastructures

Abstract: Cloud computing brings in a novel paradigm to foster ITbased service economy in scalable computing infrastructures by allowing guaranteed on-demand resource allocation with flexible pricing models. Scalable computing infrastructures not only require autonomous management abilities but also the compliance to users' requirements through Service Level Agreements (SLAs). Such infrastructures should automatically respond to changing components, workload, and environmental conditions as well as prevent violations of agreed SLAs. The essential requirements for SLA-based orchestration of services include agile component-based infrastructure to support these orchestrations; proactive validation of SLAs to prevent violations; and business enabling requirements including trust, privacy and breach management to address penalty enforcement, renegotiation and recovery. In this paper we outline a systematic approach that weaves together three different SLA management models, which cater the above mentioned issues by localizing and addressing them at different but interrelated scopes pertaining to resource, infrastructure, and business domains. In our framework Cloud components (e.g., meta negotiator, broker, automatic service deployer) are loosely coupled using SLAs and can be exchanged on demand considering current load, systems failures, and the whole Cloud ecosystem. Thereafter, SLAs are validated based on high level goals (e.g., business rules, VO policies) ensuring trust, privacy, and breach management in layered Cloud infrastructures.

Leveraging Smart-Meters for Initiating Application Migration across Clouds for Performance and Power-Expenditure Trade-Offs

Abstract: Smart meters, introduced by smart grid technologies, enable power distribution companies to price electricity differently for different times of the day. Such dynamic pricing schemes help the power companies to modulate the aggregate demand of electricity based on the supply. Accordingly, cloud providers, which are often the largest consumers of electricity, should be able to respond to various dynamic pricing signals called demand response (DR) signals by autonomously moving identified applications to other cloud sites. This paper leverages the recent advancements in cloud migration technologies to 'intelligently' move applications across geographically distributed cloud sites at runtime after a DR signal is received by the cloud provider. This helps minimize the cost incurred by a cloud provider and yet provide adequate service level guarantees as stated in the service level agreements (SLA). The current work develops models and solution schemes for identifying suitable applications for migration and placing such applications on remote cloud sites to take advantages of pricing schemes such as the time-of-use pricing and real time pricing.