We study scheduling problems in battery-operated computing devices, aiming at schedules with low total energy consumption. While most of the previous work has focused on finding feasible schedules in deadline-based settings, in this paper we are interested in schedules that guarantee good response times. More specifically, our goal is to schedule a sequence of jobs on a variable speed processor so as to minimize the total cost consisting of the power consumption and the total flow time of all the jobs. We first show that when the amount of work, for any job, may take an arbitrary value, then no online algorithm can achieve a constant competitive ratio. Therefore, most of the paper is concerned with unit-size jobs. We devise a deterministic constant competitive online algorithm and show that the offline problem can be solved in polynomial time.

Energy-efficient algorithms for flow time minimization

Novel design of Morlet wavelet neural network for solving second order Lane-Emden equation

Internet of Things (IoT) consists of sensors embed with physical objects that are connected to the Internet and able to establish the communication between them without human intervene applications are industry, transportation, healthcare, robotics, smart agriculture, etc. The communication technology plays a crucial role in IoT to transfer the data from one place to another place through Internet. This paper presents various communication protocols, namely Zigbee, Bluetooth, Near Field Communication (NFC), LoRA, etc. Later, it provides the difference between different communication protocols. Finally, the overall discussion about the communication protocols in IoT.

A Recent Survey on Internet of Things (IoT) Communication Protocols

Multiobjective virtual machine placement mechanisms using nature‐inspired metaheuristic algorithms in cloud environments: A comprehensive review

This paper deals with measuring the Air Quality using MQ135 sensor along with Carbon Monoxide CO using MQ7 sensor. Measuring Air Quality is an important element for bringing awareness to take care of the future generations and for a healthier life. Based on this, Government of India has already taken certain measures to ban Single Stroke and Two Stroke Engine based motorcycles which are emitting high pollution. We are trying to implement a system using IoT platforms like Thingspeak or Cayenne in order to bring awareness to every individual about the harm we are doing to our environment. Already, New Delhi is remarked as the most pollution city in the world recording Air Quality above 300 PPM. We have used easiest platform like Thingspeak and set the dashboard to public such that everyone can come to know the Air Quality at the location where the system is installed. Machine Learning analysis brings us a lot of depth in understanding the information that we obtained from the data. Moreover, we are proviing a reducement of the cost of components versus the state of the art.

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IOT based Air Quality Monitoring System Using MQ135 and MQ7 with Machine Learning Analysis

Resource utilization and energy need to be carefully handled for achieving virtualization in the cloud environment. An important aspect to be considered is that of load balancing, where the workload is distributed so that a particular node does not become overburdened with tasks. Improper load balancing will lead to losses in terms of both memory as well as energy consumption. The resources should be scheduled in a cloud in such a way that users obtain access at any time and with possibly less energy wastage. The proposed algorithm uses an improved Genetic Algorithm that helps reduce overall power consumption as well as performs scheduling of virtual machines so that the nodes are not loaded below or above their capacity. In this case, each chromosome in the population is considered to be a node. Each virtual machine is allocated to a node. The virtual machines on every node correspond to the genes of a chromosome. Crossover and mutation operations have been performed after which optimization techniques have been used to obtain the resulting allocation of tasks. The proposed approach has proved to be competent with respect to earlier approaches in terms of load balancing and resource utilization.

C. Venkatasubbaiah

Papers

Improved Genetic Algorithm for Monitoring of Virtual Machines in Cloud Environment