Machine learning for cloud management - Kumar, Jitendra; Singh, Ashutosh Kumar; Mohan, Anand; Buyya, Rajkumar 1970- (CRC Press, Taylor & Francis Group, 2022)
Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- List of Figures -- List of Tables -- Preface -- Author -- Abbreviations -- Chapter 1: Introduction -- 1.1. CLOUD COMPUTING -- 1.2. CLOUD MANAGEMENT -- 1.2.1. Workload Forecasting -- 1.2.2. Load Balancing -- 1.3. MACHINE LEARNING -- 1.3.1. Artificial Neural Network -- 1.3.2. Metaheuristic Optimization Algorithms -- 1.3.3. Time Series Analysis -- 1.4. WORKLOAD TRACES -- 1.5. EXPERIMENTAL SETUP &amp -- EVALUATION METRICS -- 1.6. STATISTICAL TESTS -- 1.6.1. Wilcoxon Signed-Rank Test -- 1.6.2. Friedman Test -- 1.6.3. Finner Test -- Chapter 2: Time Series Models -- 2.1. AUTOREGRESSION -- 2.2. MOVING AVERAGE -- 2.3. AUTOREGRESSIVE MOVING AVERAGE -- 2.4. AUTOREGRESSIVE INTEGRATED MOVING AVERAGE -- 2.5. EXPONENTIAL SMOOTHING -- 2.6. EXPERIMENTAL ANALYSIS -- 2.6.1. Forecast Evaluation -- 2.6.2. Statistical Analysis -- Chapter 3: Error Preventive Time Series Models -- 3.1. ERROR PREVENTION SCHEME -- 3.2. PREDICTIONS IN ERROR RANGE -- 3.3. MAGNITUDE OF PREDICTIONS -- 3.4. ERROR PREVENTIVE TIME SERIES MODELS -- 3.4.1. Error Preventive Autoregressive Moving Average -- 3.4.2. Error Preventive Autoregressive Integrated Moving Average -- 3.4.3. Error Preventive Exponential Smoothing -- 3.5. PERFORMANCE EVALUATION -- 3.5.1. Comparative Analysis -- 3.5.2. Statistical Analysis -- Chapter 4: Metaheuristic Optimization Algorithms -- 4.1. SWARM INTELLIGENCE ALGORITHMS IN PREDICTIVE MODEL -- 4.1.1. Particle Swarm Optimization -- 4.1.2. Firefly Search Algorithm -- 4.2. EVOLUTIONARY ALGORITHMS IN PREDICTIVE MODEL -- 4.2.1. Genetic Algorithm -- 4.2.2. Differential Evolution -- 4.3. NATURE INSPIRED ALGORITHMS IN PREDICTIVE MODEL -- 4.3.1. Harmony Search -- 4.3.2. Teaching Learning Based Optimization -- 4.4. PHYSICS INSPIRED ALGORITHMS IN PREDICTIVE MODEL -- 4.4.1. Gravitational Search Algorithm