4 research outputs found

    Optimal Service Provisioning in IoT Fog-based Environment for QoS-aware Delay-sensitive Application

    Full text link
    This paper addresses the escalating challenges posed by the ever-increasing data volume, velocity, and the demand for low-latency applications, driven by the proliferation of smart devices and Internet of Things (IoT) applications. To mitigate service delay and enhance Quality of Service (QoS), we introduce a hybrid optimization of Particle Swarm (PSO) and Chemical Reaction (CRO) to improve service delay in FogPlan, an offline framework that prioritizes QoS and enables dynamic fog service deployment. The method optimizes fog service allocation based on incoming traffic to each fog node, formulating it as an Integer Non-Linear Programming (INLP) problem, considering various service attributes and costs. Our proposed algorithm aims to minimize service delay and QoS degradation. The evaluation using real MAWI Working Group traffic data demonstrates a substantial 29.34% reduction in service delay, a 66.02% decrease in service costs, and a noteworthy 50.15% reduction in delay violations compared to the FogPlan framework

    Aesthetic choices: Defining the range of aesthetic views in interactive digital media including games and 3D virtual environments (3D VEs)

    Get PDF
    Defining aesthetic choices for interactive digital media such as games is a challenging task. Objective and subjective factors such as colour, symmetry, order and complexity, and statistical features among others play an important role for defining the aesthetic properties of interactive digital artifacts. Computational approaches developed in this regard also consider objective factors such as statistical image features for the assessment of aesthetic qualities. However, aesthetics for interactive digital media, such as games, requires more nuanced consideration than simple objective and subjective factors, for choosing a range of aesthetic features. From the study it was found that the there is no one single optimum position or viewpoint with a corresponding relationship to the aesthetic considerations that influence interactive digital media. Instead, the incorporation of aesthetic features demonstrates the need to consider each component within interactive digital media as part of a range of possible features, and therefore within a range of possible camera positions. A framework, named as PCAWF, emphasized that combination of features and factors demonstrated the need to define a range of aesthetic viewpoints. This is important for improved user experience. From the framework it has been found that factors including the storyline, user state, gameplay, and application type are critical to defining the reasons associated with making aesthetic choices. The selection of a range of aesthetic features and characteristics is influenced by four main factors and sub-factors associated with the main factors. This study informs the future of interactive digital media interaction by providing clarity and reasoning behind the aesthetic decision-making inclusions that are integrated into automatically generated vision by providing a framework for choosing a range of aesthetic viewpoints in a 3D virtual environment of a game. The study identifies critical juxtapositions between photographic and cinema-based media aesthetics by incorporating qualitative rationales from experts within the interactive digital media field. This research will change the way Artificial Intelligence (AI) generated interactive digital media in the way that it chooses visual outputs in terms of camera positions, field-view, orientation, contextual considerations, and user experiences. It will impact across all automated systems to ensure that human-values, rich variations, and extensive complexity are integrated in the AI-dominated development and design of future interactive digital media production

    Service level agreement specification for IoT application workflow activity deployment, configuration and monitoring

    Get PDF
    PhD ThesisCurrently, we see the use of the Internet of Things (IoT) within various domains such as healthcare, smart homes, smart cars, smart-x applications, and smart cities. The number of applications based on IoT and cloud computing is projected to increase rapidly over the next few years. IoT-based services must meet the guaranteed levels of quality of service (QoS) to match users’ expectations. Ensuring QoS through specifying the QoS constraints using service level agreements (SLAs) is crucial. Also because of the potentially highly complex nature of multi-layered IoT applications, lifecycle management (deployment, dynamic reconfiguration, and monitoring) needs to be automated. To achieve this it is essential to be able to specify SLAs in a machine-readable format. currently available SLA specification languages are unable to accommodate the unique characteristics (interdependency of its multi-layers) of the IoT domain. Therefore, in this research, we propose a grammar for a syntactical structure of an SLA specification for IoT. The grammar is based on a proposed conceptual model that considers the main concepts that can be used to express the requirements for most common hardware and software components of an IoT application on an end-to-end basis. We follow the Goal Question Metric (GQM) approach to evaluate the generality and expressiveness of the proposed grammar by reviewing its concepts and their predefined lists of vocabularies against two use-cases with a number of participants whose research interests are mainly related to IoT. The results of the analysis show that the proposed grammar achieved 91.70% of its generality goal and 93.43% of its expressiveness goal. To enhance the process of specifying SLA terms, We then developed a toolkit for creating SLA specifications for IoT applications. The toolkit is used to simplify the process of capturing the requirements of IoT applications. We demonstrate the effectiveness of the toolkit using a remote health monitoring service (RHMS) use-case as well as applying a user experience measure to evaluate the tool by applying a questionnaire-oriented approach. We discussed the applicability of our tool by including it as a core component of two different applications: 1) a contextaware recommender system for IoT configuration across layers; and 2) a tool for automatically translating an SLA from JSON to a smart contract, deploying it on different peer nodes that represent the contractual parties. The smart contract is able to monitor the created SLA using Blockchain technology. These two applications are utilized within our proposed SLA management framework for IoT. Furthermore, we propose a greedy heuristic algorithm to decentralize workflow activities of an IoT application across Edge and Cloud resources to enhance response time, cost, energy consumption and network usage. We evaluated the efficiency of our proposed approach using iFogSim simulator. The performance analysis shows that the proposed algorithm minimized cost, execution time, networking, and Cloud energy consumption compared to Cloud-only and edge-ward placement approaches
    corecore