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Performance Modeling and Design of Computer Systems
Tackling the questions that systems designers care about, this book brings queueing theory decisively back to computer science. The book is written with computer scientists and engineers in mind and is full of examples from computer systems, as well as manufacturing and operations research. Fun and readable, the book is highly approachable, even for undergraduates, while still being thoroughly rigorous and also covering a much wider span of topics than many queueing books. Readers benefit from a lively mix of motivation and intuition, with illustrations, examples and more than 300 exercises – all while acquiring the skills needed to model, analyze and design large-scale systems with good performance and low cost. The exercises are an important feature, teaching research-level counterintuitive lessons in the design of computer systems. The goal is to train readers not only to customize existing analyses but also to invent their own.
eBook
A Review of Monitoring Technologies for Solar PV Systems Using Data Processing Modules and Transmission Protocols: Progress, Challenges and Prospects
Solar photovoltaic (PV) is one of the prominent sustainable energy sources which shares a greater percentage of the energy generated from renewable resources. As the need for solar energy has risen tremendously in the last few decades, monitoring technologies have received considerable attention in relation to performance enhancement. Recently, the solar PV monitoring system has been integrated with a wireless platform that comprises data acquisition from various sensors and nodes through wireless data transmission. However, several issues could affect the performance of solar PV monitoring, such as large data management, signal interference, long-range data transmission, and security. Therefore, this paper comprehensively reviews the progress of several solar PV-based monitoring technologies focusing on various data processing modules and data transmission protocols. Each module and transmission protocol-based monitoring technology is investigated with regard to type, design, implementations, specifications, and limitations. The critical discussion and analysis are carried out with respect to configurations, parameters monitored, software, platform, achievements, and suggestions. Moreover, various key issues and challenges are explored to identify the existing research gaps. Finally, this review delivers selective proposals for future research works. All the highlighted insights of this review will hopefully lead to increased efforts toward the enhancement of the monitoring technologies in future sustainable solar PV applications.
Journal Article
Energy-efficient priority encoding strategies using machine learning based hybrid MAC protocol for wireless sensor networks
In the present work, a Priority-Aware Periodic Hybrid MAC protocol ($$Pa^2HMAC$$) is proposed to achieve intelligent, energy-efficient, and priority-based data transmission in Wireless Sensor Networks (WSNs). WSNs frequently encounter challenges in efficiently managing heterogeneous traffic—such as event-driven, periodic, and emergency data—while maintaining low latency and reduced energy consumption. Traditional MAC protocols rely on static scheduling, lacking the adaptability needed to handle critical or time-sensitive data under varying network conditions, leading to packet delays, energy wastage, and reduced responsiveness. The proposed$$Pa^2HMAC$$protocol integrates a machine learning-based priority encoding mechanism that evaluates data transmission priorities based on three key factors: data priority, emergency data, and buffer overflow. It operates in two distinct modes—Normal and Priority—to dynamically adapt to changing network requirements. In Normal mode, sensor nodes transmit data using either TDMA or BMA schemes depending on traffic type, while the central controller optimally determines sampling rates for periodic data. When emergency or high-priority conditions occur, the system switches to Priority mode to ensure timely and reliable data delivery. Simulation results demonstrate that the proposed$$Pa^2HMAC$$outperforms existing TDMA, EA-TDMA, EBMA, and ASHMAC protocols in terms of energy efficiency, and latency reduction, thereby offering a robust framework for priority-aware, energy-efficient communication in WSNs.
Journal Article
Optimized Energy Management Model on Data Distributing Framework of Wireless Sensor Network in IoT System
Data Dissemination is an essential transmitting method for a sensor network to the end-users across any set of interconnected frameworks. WSN is often used within an IoT system, in other words. As in a mesh network, a wide collection of sensors can collect data individually and send data to the web via an IoT system through a router. The conventional defined solution for data dissemination in Wireless Sensor Networks (WSN) does not include the wide range of new applications built on the Internet of Things (IoT)systems. Hence, it is observed that searching for an appropriate transmission link while distributing data with optimized utilization of energy is a significant challenge in the IoT communication infrastructure. Therefore, in this paper, an Optimized Energy Management Model for Data Dissemination (OEM-DD) framework has been proposed to optimize energy during data transmission efficiently across all sensor network nodes in the IoT system. The efficiency of the data dissemination across an interconnected network has been achieved by introducing a Non-adaptive routing approach in which data is distributed effectively from a single source to various points. Besides, Non-adaptive routing involves the dispersed collaboration system and the priority task planning principle combined with an integer framework for the efficient energy processing and grouping of data in the sensor’s network. Optimization of the energy management model through Non-adaptive routing allows low power consumption and minimal energy usage for each sensor node in the IoT system to improve the transfer and handling of data in severe interruption. The experimental results show that the suggested model enhances the data transmission rate of 96.33% with less energy consumption of 20.11% in WSN, which is the subset of IoT systems.
Journal Article
A Secure, Energy- and SLA-Efficient (SESE) E-Healthcare Framework for Quickest Data Transmission Using Cyber-Physical System
Due to advances in technology, research in healthcare using a cyber-physical system (CPS) opens innovative dimensions of services. In this paper, the authors propose an energy- and service-level agreement (SLA)-efficient cyber physical system for E-healthcare during data transmission services. Furthermore, the proposed phenomenon will be enhanced to ensure the security by detecting and eliminating the malicious devices/nodes involved during the communication process through advances in the ad hoc on-demand distance vector (AODV) protocol. The proposed framework addresses the two security threats, such as grey and black holes, that severely affect network services. Furthermore, the proposed framework used to find the different network metrics such as average qualifying service set (QSS) paths, mean hop and energy efficiency of the quickest path. The framework is simulated by calculating the above metrics in mutual cases i.e., without the contribution of malevolent nodes and with the contribution of malevolent nodes over service time, hop count and energy constraints. Further, variation of SLA and energy shows their expediency in the selection of efficient network metrics.
Journal Article