Quality Of Service Trade-offs Research Articles

Electric vehicle charging network design with capacity and service considerations

Electric Vehicles (EVs) have a critical role in the future of sustainable transportation systems. Recently, improving the infrastructure for EVs has been a major focus of organizations around the world, such as local and federal governments, energy companies, and automotive original equipment manufacturers. In this article, we present a service network design framework to improve the infrastructure for EVs with quality of service constraints taken into consideration. We present a novel charging station location model with capacity allocation. The model maximizes the EV traffic flow captured and minimizes the average service time for drivers. The model formulation allows for assessing capacity and quality of service trade-offs, and operational insights are presented to reflect drivers’ expectations. We demonstrate an application for the solution approach on a real road network and evaluate the performance based on both computational efficiency and solution quality. Our results highlight how charging times at stations affect the quality of service in the whole service system by quantifying the improvements in flow coverage while reducing waiting times. The value of faster chargers in increasing coverage and reducing the average waiting times is also highlighted in relation to a service provider’s budget constraints.

Enterprise applications cloud rightsizing through a joint benchmarking and optimization approach

Migrating an application to the cloud environment requires non-functional properties consideration such as cost, performance and Quality of Service (QoS). Given the variety and the plethora of cloud offerings in addition with the consumption-based pricing models currently available in the cloud market, it is extremely complex to find the optimal deployment that fits the application requirements and provides the best QoS and cost trade-offs. In many cases the performance of these service offerings may vary depending on the congestion level, provider policies and how the application types that are intended to be executed upon them use the computing resources. A key challenge for customers before moving to Cloud is to know application behavior on cloud platforms in order to select the best-suited environment to host their application components in terms of performance and cost. In this paper, we propose a combined methodology and a set of tools that support the design and migration of enterprise applications to Cloud. Our tool chain includes: (i) the performance assessment of cloud services based on cloud benchmark results, (ii) a profiler/classifier mechanism that identifies the computing footprint of an arbitrary application and provides the best matching with a cloud service solution in terms of performance and cost, (iii) and a design space exploration tool, which is effective in identifying the deployment of minimum costs taking into account workload changes and providing QoS guarantees.

Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance

With the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be considered, notably the communication bandwidth constraints. Existing approaches for target tracking using a camera network typically utilize target handover mechanisms between cameras, or combine results from 2D trackers in each camera into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks typically associated with 2D tracking. In this paper, we present an approach for tracking multiple targets directly in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera along with the target models are used in a probabilistic tracker to estimate the target state. We introduce four variations of our base tracker that incur different computational and communication costs on each node and result in different tracking accuracy. We demonstrate the effectiveness of our proposed trackers by comparing their performance to a 3D tracker that fuses the results of independent 2D trackers. We also present performance analysis of the base tracker along Quality-of-Service (QoS) and Quality-of-Information (QoI) metrics, and study QoS vs. QoI trade-offs between the proposed tracker variations. Finally, we demonstrate our tracker in a real-life scenario using a camera network deployed in a building.

Energy–QoS Trade-Offs in Mobile Service Selection

An attractive advantage of mobile networks is that their users can gain easy access to different services. In some cases, equivalent services could be fulfilled by different providers, which brings the question of how to rationally select the best provider among all possibilities. In this paper, we investigate an answer to this question from both quality-of-service (QoS) and energy perspectives by formulating an optimisation problem. We illustrate the theoretical results with examples from experimental measurements of the resulting energy and performance.

Quality-of-service trade-off analysis for wireless sensor networks

Quality of Service (QoS) support for wireless sensor networks (WSN) is a fairly new topic that is gaining more and more interest. This paper introduces a method for determining the node configurations of a WSN such that application-level QoS constraints are met. This is a complex task, since the search space is typically extremely large. The method is based on a recent algebraic approach to Pareto analysis, that we use to reason about QoS trade-offs. It features an algorithm that keeps the working set of possible configurations small, by analysing parts of the network in a modular fashion, and meanwhile discarding configurations that are inferior to other configurations. Furthermore, we give WSN models for two different applications, spatial mapping and target tracking, in which QoS trade-offs are made explicit. Test results for these applications and a heterogeneous WSN combining these two applications show that the models are accurate and that the method is scalable and thus practically usable for WSN, even with large numbers of nodes. Details are given on how to efficiently implement the algorithm.

On the Customization of Components: A Rule-Based Approach

Realizing the quality-of-service (QoS) requirements for a software system continues to be an important and challenging issue in software engineering. A software system may need to be updated or reconfigured to provide modified QoS capabilities. These changes can occur at development time or at runtime. In component-based software engineering, software systems are built by composing components. When the QoS requirements change, there is a need to reconfigure the components. Unfortunately, many components are not designed to be reconfigurable, especially in terms of QoS capabilities. It is often labor-intensive and error-prone work to reconfigure the components, as developers need to manually check and modify the source code. Furthermore, the work requires experienced senior developers, which makes it costly. The limitations motivate the development of a new rule-based semiautomated component parameterization technique that performs code analysis to identify and adapt parameters and changes components into reconfigurable ones. Compared with a number of alternative QoS adaptation approaches, the proposed rule-based technique has advantages in terms of flexibility, extensibility, and efficiency. The adapted components support the reconfiguration of potential QoS trade-offs among time, space, quality, and so forth. The proposed rule-based technique has been successfully applied to two substantial libraries of components. The F-measure or balanced F-score results for the validation are excellent, that is, 94 percent. Index Terms-Performance measures, rule-based processing, representations.

Constructing Multilevel Metadata Networks for Sharing Dispersed and Transient Information in a Mobile Environment

An intelligent multi-user mechanism has been prototyped at the Information System Collaboratory of the Pennsylvania State University, which is capable of resolving global queries with differing and overlapping information needs, spatial scalability and temporal assumptions. The sources of information for this prototype are mechanical damage monitoring sensors embedded in equipment at plant sites, on-board ships or aircrafts, archived historical and diagnostic databases like those available through NALCOMIS (NAVMASSO document J-004 EM-001C, 1995) logistics and maintenance databases at depots, interactive electronic technical manuals stored in databases, dynamic models of damage, and models of operational performance. The concept-of-operation includes mobile access to this information by equipment maintainers on-board ships, aircrafts and other mobile platforms. Real-time interoperation of these system components and databases, under dynamic equipment operating conditions of thermo-mechanical and environmental stress, requires complex interactions of internal representations of sensor data, performance requirements, resources and equipment models, with rich semantics. To support such interactions, following the work of Bright, Hurson and Pakzad (Bright, Hurson, and Pakzad, Transactions on Database Systems, Vol. 19, No. 2, pp. 212–253, 1994) local schema terms of available data sources are organized as the leaf nodes in a semantic network of metadata. The physical nodes of the network are partitioned into a top-down multi-level search control structure of increasing precision and decreasing semantic aggregation. Each physical node supports search through all lower layers of metadata in connected tree configurations. The resulting multilayered semantic network is modeled as a Thesaurus of terms T and relationships R. A relationship in R may be crisp or fuzzy. The DTIC (Defense Technical Information Center) thesaurus for equipment maintenance was used as a starting point in this work. It was further enhanced by application specific terms and endowed with a distance function. This distance function is used to formulate user adaptable Graphic User Interfaces (GUI) for making quality of service tradeoffs in the resolution of global queries. Step-by-step construction of the thesaurus as a multilevel metadata network, its scalability, dynamic adaptation through usage, and tolerance of semantic imprecision in query resolution are discussed in this paper. Furthermore, performance metrology for evaluating quality of service in global query resolution is also developed (Phoha, in Proceedings of the NIST Workshop on Advancing Measurements and Testing for Information Technology, Gaithersburg, MD, Oct. 1998). This work was funded by DARPA for the past four years under grant DE-FC36-94G010064, for establishing a National Information Infrastructure Testbed for Electronic Commerce in equipment health monitoring, failure diagnosis and prognosis services.

Quality of service (QoS) metrics for continuous media

This paper presents quality of service (QoS) metrics for continuity and synchronization specifications in continuous media (CM). Proposed metrics specify continuity and synchronization, with tolerable limits on average and bursty defaults from perfect continuity, timing and synchronization constraints. These metrics can be used in a distributed environment for resource allocation. Continuity specification of a CM stream consists of its sequencing, display rate and drift profiles. The sequencing profile of a CM stream consists of tolerable aggregate and consecutive frame miss ratios. Rate profiles specify the average rendition rate and its variation. Given a rate profile, the ideal time unit for frame display is determined as an offset from the beginning of the stream. Drift profile specifies the average and bursty deviation of schedules for frames from such fixed points in time. Synchronization requirements of a collection of CM streams are specified by mixing, rate and synchronization drift profiles. Mixing profiles specify vectors of frames that can be displayed simultaneously. They consist of average and bursty losses of synchronization. Rate profiles consist of average rates and permissible deviations thereof. Synchronization drift profiles specify permissible aggregate and bursty time drifts between schedules of simultaneously displayable frames. It is shown that rate profiles of a collection of synchronized streams is definable in terms of rate profiles of its component streams. It is also shown that mixing and drift profiles of a collection of streams are non-definable in terms of sequencing and drift profiles of its constituents. An important consequence of the mutual independence of synchronization and continuity specification is that, in a general purpose platform with limited resources, synchronized display of CM streams may require QoS tradeoffs. An algorithm that makes such tradeoffs is presented as a proof of applicability of our metrics in a realistic environment.