Cloud computing is summed up as a different model for allowing favorable, network as per demand to use shared devices of computational resources which are collected and then released with marginal management effort or interaction with any client or any service provider. Cloud computing is a well-known technology in the pasture of information technology that provides computing as a service. In cloud computing environment the resources are provisioned on the basis of demand, as and when required. A large number of cloud users can request a number of cloud services at the same time. Due to increase in the usage of cloud computing there is a need for a efficient and effective resource allocation algorithm which can be used for proper usage of the resources and also check that the resource is not wastage. In this we propose a priority based resource allocation algorithm which can be used for proper allocation of resources and also the resources are allocated efficiently and effectively. In this paper, two strategies are proposed for the purpose of optimum resource allocation in which the first approach uses the concept of specification matching and second uses the concept of priority based approach. In the first approach, different types of resources (virtual machine) are allocated by taking three parameters into consideration: processing element, main memory, and network bandwidth. In the second approach, one parameter is considered namely: Priority. In both strategies, users are allowed to submit the parameters during cloudlet submission. The user inserted parameters will then be considered while allocating resources to them. The objectives of this research are to improve utilization of resources and reduce the request loss.
Lambda Architecture in Big Data Computing
The evolution of the technologies in Big Data in the last decade has presented a history of battles with growing data volume. An increasing number of systems are being built to handle the Volume, Velocity, Variety, Veracity, Validity, and Volatility of Big Data and help gain new insights and make better business decisions. A well-designed big data architecture must handle the 6 V’s of Big Data, save your company money, and help predict future trends.
Lambda (λ) Architecture
The Lambda Architecture λis an emerging paradigm in Big Data computing. The name lambda architecture is derived from a functional point of view of data processingi.e. all data processing is understood as the application of a function to all data.
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A survey on various resource allocation policies in cloud computing environmenteSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A survey on various resource allocation policies in cloud computing environmenteSAT Journals
Abstract Cloud computing is bringing a revolution in computing environment replacing traditional software installations, licensing issues into complete on-demand services through internet. In Cloud computing multiple cloud users can request number of cloud services simultaneously. So there must be a provision that all resources are made available to requesting user in efficient manner to satisfy their need. Resource allocation is based on quality of service and service level agreement. In cloud computing environment, to allocate resources to the user there are several methods but provider should consider the efficient way to guarantee that the applications’ requirements are attended to correctly and satisfy the user’s need This paper survey different resource allocation policies used in cloud computing environment. Keywords: Cloud computing, Resource allocation
Cloud computing is the fastest emerging technology and a novel buzzword in the field of IT domain that offer distinct services, applications and focuses on providing sustainable, reliable, scalable and virtualized resources to its consumer. The main aim of cloud computing is to enhance the use of distributed resources to achieve higher throughput and resource utilization in large-scale computation problems. Scheduling affects the efficiency of cloud and plays a significant role in cloud computing to create high performance environment. The Quality of Service (QoS) requirements of user application define the scheduling of resources. Numbers of researchers have tried to solve these scheduling problems using different QoS based scheduling techniques. In this paper, a detail analysis of resource scheduling methodology is presented, with different types of scheduling based on soft computing techniques, their comparisons, benefits and results are discussed. Major finding of this paper helps researchers to decide suitable approach for scheduling user’s applications considering their QoS requirements.
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Dynamic Resource Provisioning with Authentication in Distributed DatabaseEditor IJCATR
Data center have the largest consumption amounts of energy in sharing the power. The public cloud workloads of different
priorities and performance requirements of various applications [4]. Cloud data center have capable of sensing an opportunity to present
different programs. In my proposed construction and the name of the security level of imperturbable privacy leakage rarely distributed
cloud system to deal with the persistent characteristics there is a substantial increases and information that can be used to augment the
profit, retrenchment overhead or both. Data Mining Analysis of data from different perspectives and summarizing it into useful
information is a process. Three empirical algorithms have been proposed assignments estimate the ratios are dissected theoretically and
compared using real Internet latency data recital of testing methods
Time Efficient VM Allocation using KD-Tree Approach in Cloud Server Environmentrahulmonikasharma
Cloud computing is an incipient and quickly evolving model, with new expenses and capabilities being proclaimed frequently. The increases of user on cloud with the expansion of variety of services, with that the complete allocation of resource with the minimum latent time for Virtual machine is necessary. To allocate this virtual cloud computing resources to the cloud user is a key technical issue because user demand is dynamic in nature that required dynamic allocation of resource too. To improve the allocation there must be a correct balanced algorithmic scheduling for Resource Allocation Technique. The aim of this work is to allocate resource to scientific experiment request coming from multiple users, wherever customized Virtual machines (VM) are aloft in applicable host out there in cloud. Therefore, properly programmed scheduling cloud is extremely vital and it’s significant to develop efficient scheduling methods for appropriately allocation of VMs into physical resource. The planned formulas minimize the time interval quality so as of O (Log n) by adopting KD-Tree.
A latency-aware max-min algorithm for resource allocation in cloud IJECEIAES
Cloud computing is an emerging distributed computing paradigm. However, it requires certain initiatives that need to be tailored for the cloud environment such as the provision of an on-the-fly mechanism for providing resource availability based on the rapidly changing demands of the customers. Although, resource allocation is an important problem and has been widely studied, there are certain criteria that need to be considered. These criteria include meeting user’s quality of service (QoS) requirements. High QoS can be guaranteed only if resources are allocated in an optimal manner. This paper proposes a latency-aware max-min algorithm (LAM) for allocation of resources in cloud infrastructures. The proposed algorithm was designed to address challenges associated with resource allocation such as variations in user demands and on-demand access to unlimited resources. It is capable of allocating resources in a cloud-based environment with the target of enhancing infrastructure-level performance and maximization of profits with the optimum allocation of resources. A priority value is also associated with each user, which is calculated by analytic hierarchy process (AHP). The results validate the superiority for LAM due to better performance in comparison to other state-of-the-art algorithms with flexibility in resource allocation for fluctuating resource demand patterns.
Lambda Architecture in Big Data Computing
The evolution of the technologies in Big Data in the last decade has presented a history of battles with growing data volume. An increasing number of systems are being built to handle the Volume, Velocity, Variety, Veracity, Validity, and Volatility of Big Data and help gain new insights and make better business decisions. A well-designed big data architecture must handle the 6 V’s of Big Data, save your company money, and help predict future trends.
Lambda (λ) Architecture
The Lambda Architecture λis an emerging paradigm in Big Data computing. The name lambda architecture is derived from a functional point of view of data processingi.e. all data processing is understood as the application of a function to all data.
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A survey on various resource allocation policies in cloud computing environmenteSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A survey on various resource allocation policies in cloud computing environmenteSAT Journals
Abstract Cloud computing is bringing a revolution in computing environment replacing traditional software installations, licensing issues into complete on-demand services through internet. In Cloud computing multiple cloud users can request number of cloud services simultaneously. So there must be a provision that all resources are made available to requesting user in efficient manner to satisfy their need. Resource allocation is based on quality of service and service level agreement. In cloud computing environment, to allocate resources to the user there are several methods but provider should consider the efficient way to guarantee that the applications’ requirements are attended to correctly and satisfy the user’s need This paper survey different resource allocation policies used in cloud computing environment. Keywords: Cloud computing, Resource allocation
Cloud computing is the fastest emerging technology and a novel buzzword in the field of IT domain that offer distinct services, applications and focuses on providing sustainable, reliable, scalable and virtualized resources to its consumer. The main aim of cloud computing is to enhance the use of distributed resources to achieve higher throughput and resource utilization in large-scale computation problems. Scheduling affects the efficiency of cloud and plays a significant role in cloud computing to create high performance environment. The Quality of Service (QoS) requirements of user application define the scheduling of resources. Numbers of researchers have tried to solve these scheduling problems using different QoS based scheduling techniques. In this paper, a detail analysis of resource scheduling methodology is presented, with different types of scheduling based on soft computing techniques, their comparisons, benefits and results are discussed. Major finding of this paper helps researchers to decide suitable approach for scheduling user’s applications considering their QoS requirements.
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Dynamic Resource Provisioning with Authentication in Distributed DatabaseEditor IJCATR
Data center have the largest consumption amounts of energy in sharing the power. The public cloud workloads of different
priorities and performance requirements of various applications [4]. Cloud data center have capable of sensing an opportunity to present
different programs. In my proposed construction and the name of the security level of imperturbable privacy leakage rarely distributed
cloud system to deal with the persistent characteristics there is a substantial increases and information that can be used to augment the
profit, retrenchment overhead or both. Data Mining Analysis of data from different perspectives and summarizing it into useful
information is a process. Three empirical algorithms have been proposed assignments estimate the ratios are dissected theoretically and
compared using real Internet latency data recital of testing methods
Time Efficient VM Allocation using KD-Tree Approach in Cloud Server Environmentrahulmonikasharma
Cloud computing is an incipient and quickly evolving model, with new expenses and capabilities being proclaimed frequently. The increases of user on cloud with the expansion of variety of services, with that the complete allocation of resource with the minimum latent time for Virtual machine is necessary. To allocate this virtual cloud computing resources to the cloud user is a key technical issue because user demand is dynamic in nature that required dynamic allocation of resource too. To improve the allocation there must be a correct balanced algorithmic scheduling for Resource Allocation Technique. The aim of this work is to allocate resource to scientific experiment request coming from multiple users, wherever customized Virtual machines (VM) are aloft in applicable host out there in cloud. Therefore, properly programmed scheduling cloud is extremely vital and it’s significant to develop efficient scheduling methods for appropriately allocation of VMs into physical resource. The planned formulas minimize the time interval quality so as of O (Log n) by adopting KD-Tree.
A latency-aware max-min algorithm for resource allocation in cloud IJECEIAES
Cloud computing is an emerging distributed computing paradigm. However, it requires certain initiatives that need to be tailored for the cloud environment such as the provision of an on-the-fly mechanism for providing resource availability based on the rapidly changing demands of the customers. Although, resource allocation is an important problem and has been widely studied, there are certain criteria that need to be considered. These criteria include meeting user’s quality of service (QoS) requirements. High QoS can be guaranteed only if resources are allocated in an optimal manner. This paper proposes a latency-aware max-min algorithm (LAM) for allocation of resources in cloud infrastructures. The proposed algorithm was designed to address challenges associated with resource allocation such as variations in user demands and on-demand access to unlimited resources. It is capable of allocating resources in a cloud-based environment with the target of enhancing infrastructure-level performance and maximization of profits with the optimum allocation of resources. A priority value is also associated with each user, which is calculated by analytic hierarchy process (AHP). The results validate the superiority for LAM due to better performance in comparison to other state-of-the-art algorithms with flexibility in resource allocation for fluctuating resource demand patterns.
A SURVEY ON RESOURCE ALLOCATION IN CLOUD COMPUTINGijccsa
Cloud computing is an on-demand service resource which includes applications to data centers on a
pay-per-use basis. In order to allocate these resources properly and satisfy users’ demands, an efficient
and flexible resource allocation mechanism is needed. Due to increasing user demand, the resource
allocating process has become more challenging and difficult. One of the main focuses of research
scholars is how to develop optimal solutions for this process. In this paper, a literature review on proposed
dynamic resource allocation techniques is introduced.
A SURVEY ON RESOURCE ALLOCATION IN CLOUD COMPUTINGijccsa
Cloud computing is an on-demand service resource which includes applications to data centers on a
pay-per-use basis. In order to allocate these resources properly and satisfy users’ demands, an efficient
and flexible resource allocation mechanism is needed. Due to increasing user demand, the resource
allocating process has become more challenging and difficult. One of the main focuses of research
scholars is how to develop optimal solutions for this process. In this paper, a literature review on proposed
dynamic resource allocation techniques is introduced.
A Survey on Resource Allocation in Cloud Computingneirew J
Cloud computing is an on-demand service resource which includes applications to data centers on a
pay-per-use basis. In order to allocate these resources properly and satisfy users’ demands, an efficient
and flexible resource allocation mechanism is needed. Due to increasing user demand, the resource
allocating process has become more challenging and difficult. One of the main focuses of research
scholars is how to develop optimal solutions for this process. In this paper, a literature review on proposed
dynamic resource allocation techniques is introduced.
Hybrid Based Resource Provisioning in CloudEditor IJCATR
The data centres and energy consumption characteristics of the various machines are often noted with different capacities.
The public cloud workloads of different priorities and performance requirements of various applications when analysed we had noted
some invariant reports about cloud. The Cloud data centres become capable of sensing an opportunity to present a different program.
In out proposed work, we are using a hybrid method for resource provisioning in data centres. This method is used to allocate the
resources at the working conditions and also for the energy stored in the power consumptions. Proposed method is used to allocate the
process behind the cloud storage.
ABSTRACT
Cloud computing utilizes large scale computing infrastructure that has been radically changing the IT landscape enabling remote access to computing resources with low service cost, high scalability , availability and accessibility. Serving tasks from multiple users where the tasks are of different characteristics with variation in the requirement of computing power may cause under or over utilization of resources.Therefore maintaining such mega-scale datacenter requires efficient resource management procedure to increase resource utilization. However, while maintaining efficiency in service provisioning it is necessary to ensure the maximization of profit for the cloud providers. Most of the current research works aims at how providers can offer efficient service provisioning to the user and improving system performance. There are comparatively fewer specific works regarding resource management which also deals with the economic section that considers profit maximization for the provider. In this paper we represent a model that deals with both efficient resource utilization and pricing of the resources. The joint resource management model combines the work of user assignment, task scheduling and load balancing on the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, task scheduling, load balancing and pricing that works on group based resources offering reduction in task execution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost is calculated over a time interval involving the number of served customer at this time and the amount of resources used within this time
GROUP BASED RESOURCE MANAGEMENT AND PRICING MODEL IN CLOUD COMPUTINGijcsit
Cloud computing utilizes large scale computing infrastructure that has been radically changing the IT landscape enabling remote access to computing resources with low service cost, high scalability , availability and accessibility. Serving tasks from multiple users where the tasks are of different characteristics with variation in the requirement of computing power may cause under or over utilization of resources.Therefore maintaining such mega-scale datacenter requires efficient resource management procedure to increase resource utilization. However, while maintaining efficiency in service provisioning it is necessary to ensure the maximization of profit for the cloud providers. Most of the current research works aims at how providers can offer efficient service provisioning to the user and improving system performance. There are comparatively fewer specific works regarding resource management which also deals with the economic section that considers profit maximization for the provider. In this paper we represent a model that deals with both efficient resource utilization and pricing of the resources. The joint resource management model combines the work of user assignment, task scheduling and load balancing on the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, task scheduling, load balancing and pricing that works on group based resources offering reduction in task execution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost is calculated over a time interval involving the number of served customer at this time and the amount of resources used within this time.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
An Efficient Cloud Scheduling Algorithm for the Conservation of Energy throug...IJECEIAES
Method of broadcasting is the well known operation that is used for providing support to different computing protocols in cloud computing. Attaining energy efficiency is one of the prominent challenges, that is quite significant in the scheduling process that is used in cloud computing as, there are fixed limits that have to be met by the system. In this research paper, we are particularly focusing on the cloud server maintenance and scheduling process and to do so, we are using the interactive broadcasting energy efficient computing technique along with the cloud computing server. Additionally, the remote host machines used for cloud services are dissipating more power and with that they are consuming more and more energy. The effect of the power consumption is one of the main factors for determining the cost of the computing resources. With the idea of using the avoidance technology for assigning the data center resources that dynamically depend on the application demands and supports the cloud computing with the optimization of the servers in use.
THE EFFECT OF THE RESOURCE CONSUMPTION CHARACTERISTICS OF CLOUD APPLICATIONS ...ijccsa
Auto scaling is a service provided by the cloud service provider that allows provision of temporary
resources to the subscriber’s systems to prevent overloading. So far, many methods of auto scaling have
been proposed and applied. Among them, solutions based on low-level metrics are commonly used in
industry systems. Resource statistics are the basis for detecting overloading situation and making
additional resources in a timely manner. However, the effectiveness of these methods depends very much
on the accuracy of the overload calculation from low-level metrics. Overloading is mentioned in solutions
that usually favor a shortage of CPU resources. However, the demand for resources comes from the
application running on that each application has the characteristics of demanding different resource types,
with different CPU, memory, I/O ratios so it can not just be statistically on CPU consumption. The point of
view here is that even though based on low level resources, the source for calculation and forecasting is the
characteristic of the resource needs of the application. In this paper, we will develop an empirical model to
assess the effect of the application's resource consumption characteristics on the efficiency of the lowmetricauto scaling solutions and propose an auto scaling solution that is calculated based on statistics of
different types of resources. The results of the simulations show that the proposed solution based on
multiple resources is more positive.
THE EFFECT OF THE RESOURCE CONSUMPTION CHARACTERISTICS OF CLOUD APPLICATIONS ...ijccsa
Auto scaling is a service provided by the cloud service provider that allows provision of temporary resources to the subscriber’s systems to prevent overloading. So far, many methods of auto scaling have been proposed and applied. Among them, solutions based on low-level metrics are commonly used in industry systems. Resource statistics are the basis for detecting overloading situation and making additional resources in a timely manner. However, the effectiveness of these methods depends very much on the accuracy of the overload calculation from low-level metrics. Overloading is mentioned in solutions that usually favor a shortage of CPU resources. However, the demand for resources comes from the application running on that each application has the characteristics of demanding different resource types, with different CPU, memory, I/O ratios so it can not just be statistically on CPU consumption. The point of view here is that even though based on low level resources, the source for calculation and forecasting is the characteristic of the resource needs of the application. In this paper, we will develop an empirical model to assess the effect of the application's resource consumption characteristics on the efficiency of the lowmetricauto scaling solutions and propose an auto scaling solution that is calculated based on statistics of different types of resources. The results of the simulations show that the proposed solution based on multiple resources is more positive.
Similar to Optimum Resource Allocation using Specification Matching and Priority Based Method in Cloud (20)
Data Mining is a significant field in today’s data-driven world. Understanding and implementing its concepts can lead to discovery of useful insights. This paper discusses the main concepts of data mining, focusing on two main concepts namely Association Rule Mining and Time Series Analysis
A Review on Real Time Integrated CCTV System Using Face Detection for Vehicle...rahulmonikasharma
We are describes the technique for real time human face detection and counting the number of passengers in vehicle and also gender of the passengers.The Image processing technology is very popular,now at present all are going to use it for various purpose. It can be applied to various applications for detecting and processing the digital images. Face detection is a part of image processing. It is used for finding the face of human in a given area. Face detection is used in many applications such as face recognition, people tracking, or photography. In this paper,The webcam is installed in public vehicle and connected with Raspberry Pi model. We use face detection technique for detecting and counting the number of passengers in public vehicle via webcam with the help of image processing and Raspberry Pi.
Considering Two Sides of One Review Using Stanford NLP Frameworkrahulmonikasharma
Sentiment analysis is a type of natural language processing for tracking the mood of the public about a particular product or a topic and is useful in several ways. Polarity shift is the most classical task which aims at classifying the reviews either positive or negative. But in many cases, in addition to the positive and negative reviews, there still many neutral reviews exist. However, the performance sometimes limited due to the fundamental deficiencies in handling the polarity shift problem. We propose an Improvised Dual Sentiment Analysis (IDSA) model to address this problem for sentiment classification. We first propose a novel data expansion technique by creating sentiment-reversed review for each training and test review. We develop a corpus based method to construct a pseudo-antonym dictionary. It removes DSA’s dependency on an external antonym dictionary for review reversion. We conduct a range of experiments and the results demonstrates the effectiveness of DSA in addressing the polarity shift in sentiment classification. .
A New Detection and Decoding Technique for (2×N_r ) MIMO Communication Systemsrahulmonikasharma
The requirements of fifth generation new radio (5G- NR) access networks are very high capacity and ultra-reliability. In this paper, we proposed a V-BLAST2 × N_r MIMO system that is analyzed, improved, and expected to achieve both very high throughput and ultra- reliability simultaneously.A new detection technique called parallel detection algorithm is proposed. The performance of the proposed algorithm compared with existing linear detection algorithms. It was seen that the proposed technique increases the speed of signal transmission and prevents error propagation which may be present in serial decoding techniques. The new algorithm reduces the bit error probability and increases the capacity simultaneouslywithout using a standard STC technique. However, it was seen that the BER of systems using the proposed algorithm is slightly higher than a similar system using only STC technique. Simulation results show the advantages of using the proposed technique.
Broadcasting Scenario under Different Protocols in MANET: A Surveyrahulmonikasharma
A wireless network enables people to communicate and access applications and information without wires. This provides freedom of movement and the ability to extend applications to different parts of a building, city, or nearly anywhere in the world. Wireless networks allow people to interact with e-mail or browse the Internet from a location that they prefer. Adhoc Networks are self-organizing wireless networks, absent any fixed infrastructure. broadcasting of data through proper channel is essential. Various protocols are designed to avoid the loss of data. In this paper an overview of different broadcast protocols are discussed.
Sybil Attack Analysis and Detection Techniques in MANETrahulmonikasharma
Security is important for many sensor network applications. A particularly harmful attack against sensor and ad hoc networks is known as the Sybil attack [6], where a node Illegitimately claims multiple identities.Mobility cause a main problem when we talk about security in Mobile Ad-hoc networks. It doesn’t depend on fixed architecture, the nodes are continuously moving in a random fashion. In this article we will focus on identifying the Sybil attack in MANET. It uses air medium for communication so it is more prone to the attack. Sybil attack is one in which single node present multiple fake identities to other nodes, which cause destruction.
A Landmark Based Shortest Path Detection by Using A* and Haversine Formularahulmonikasharma
In 1900, less than 20 percent of the world populace lived in cities, in 2007, fair more than 50 percent of the world populace lived in cities. In 2050, it has been anticipated that more than 70 percent of the worldwide population (about 6.4 billion individuals) will be city tenants. There's more weight being set on cities through this increment in population [1]. With approach of keen cities, data and communication technology is progressively transforming the way city regions and city inhabitants organize and work in reaction to urban development. In this paper, we create a nonspecific plot for navigating a route throughout city A asked route is given by utilizing combination of A* Algorithm and Haversine equation. Haversine Equation gives least distance between any two focuses on spherical body by utilizing latitude and longitude. This least distance is at that point given to A* calculation to calculate minimum distance. The method for identifying the shortest path is specify in this paper.
Processing Over Encrypted Query Data In Internet of Things (IoTs) : CryptDBs,...rahulmonikasharma
Internet of Things (IoT) is the developing technologies that would be the biggest agents to modify the current world. Machine-to-machine communications perform with virtual, mobile and instantaneous connections. In IoT system, it consists of data-gathering sensors various other household devices. Intended for protecting IoT system, the end-to-end secure communication is a necessary measure to protect against unauthorized entities (e.g., modification attacks and eavesdropping,) and the data unprotected on the Cloud. The most important concern hereby is how to preserve the insightful information and to provide the privacy of user data. In IoT, the encrypted data computing is based on techniques appear to be promising approaches. In this paper, we discuss about the recent secure database systems, which are capable to execute SQL queries over encrypted data.
Quality Determination and Grading of Tomatoes using Raspberry Pirahulmonikasharma
In India cultivation of tomatoes is carried out by traditional methods and techniques. Today tremendous improvement in field of agriculture technologies and products can be seen. The tomatoes affect the overall production drastically. Image processing technique can be key technique for finding good qualities of tomatoes and grading. This work aimed to study different types of algorithms used for quality grading and sorting of fruit from the acquire image. In previous years several types of techniques are applied to analyses the good quality fruits. A simple system can be implemented using Raspberry pi with computer vision technology and image processing algorithms.
Comparative of Delay Tolerant Network Routings and Scheduling using Max-Weigh...rahulmonikasharma
Network management and Routing is supportively done by performing with the nodes, due to infrastructure-less nature of the network in Ad hoc networks or MANET. The nodes are maintained itself from the functioning of the network, for that reason the MANET security challenges several defects. Routing process and Scheduling is a significant idea to enhance the security in MANET. Other than, scheduling has been recognized to be a key issue for implementing throughput/capacity optimization in Ad hoc networks. Designed underneath conventional (LT) light tailed assumptions, traffic fundamentally faces Heavy-tailed (HT) assumption of the validity of scheduling algorithms. Scheduling policies are utilized for communication networks such as Max-Weight, backpressure and ACO, which are provably throughput optimality and the Pareto frontier of the feasible throughput region under maximal throughput vector. In wireless ad-hoc network, the issue of routing and optimal scheduling performs with time varying channel reliability and multiple traffic streams. Depending upon the security issues within MANETs in this paper presents a comparative analysis of existing scheduling policies based on their performance to progress the delay performance in most scenarios. The security issues of MANETs considered from this paper presents a relative analysis of existing scheduling policies depend on their performance to progress the delay performance in most developments.
DC Conductivity Study of Cadmium Sulfide Nanoparticlesrahulmonikasharma
The dc conductivity of consolidated nanoparticle of CdS has been studied over the temperature range from 303 K to 523 K and the conductivity has been found to be much larger than that of single crystals.
A Survey on Peak to Average Power Ratio Reduction Methods for LTE-OFDMrahulmonikasharma
OFDM (Orthogonal Frequency Division Multiplexing) is generally preferred for high data rate transmission in digital communication. The Long-Term Evolution (LTE) standards for the fourth generation (4G) wireless communication systems. Orthogonal Frequency Division Multiple Access (OFDMA) and Single Carrier Frequency Division Multiple Access (SC-FDMA) are the two multiple access techniques which are generally used in LTE.OFDM system has a major shortcoming of high peak to average power ratio (PAPR) value. This paper explains different PAPR reduction techniques and presents a comparison of the various techniques based on theoretical results. It also presents a survey of the various PAPR reduction techniques and the state of the art in this area.
IOT Based Home Appliance Control System, Location Tracking and Energy Monitoringrahulmonikasharma
Home automation has been a dream of sciences for so many years. It could wind up conceivable in twentieth century simply after power all family units and web administrations were begun being utilized on across the board level. The point of home robotization is to give enhanced accommodation, comfort, vitality effectiveness and security. Vitality checking and protection holds prime significance in this day and age in view of the irregularity between control age and request observing frameworks accessible in the market. Ordinarily, customers are disappointed with the power charge as it doesn't demonstrate the power devoured at the gadget level. This paper shows the outline and execution of a vitality meter utilizing Arduino microcontroller which can be utilized to gauge the power devoured by any individual electrical apparatus. The primary expectation of the proposed vitality meter is to screen the power utilization at the gadget level, transfer it to the server and build up remote control of any apparatus. So we can screen the power utilization remotely and close down gadgets if vital. The car segment is additionally one of the application spaces where vehicle can be made keen by utilizing "IOT". So a vehicle following framework is additionally executed to screen development of vehicles remotely.
Thermal Radiation and Viscous Dissipation Effects on an Oscillatory Heat and ...rahulmonikasharma
An anticipated outcome that is intended chapter is to investigate effects of magnetic field on an oscillatory flow of a viscoelastic fluid with thermal radiation, viscous dissipation with Ohmic heating which bounded by a vertical plane surface, have been studied. Analytical solutions for the quasi – linear hyperbolic partial differential equations are obtained by perturbation technique. Solutions for velocity and temperature distributions are discussed for various values of physical parameters involving in the problem. The effects of cooling and heating of a viscoelastic fluid compared to the Newtonian fluid have been discussed.
Advance Approach towards Key Feature Extraction Using Designed Filters on Dif...rahulmonikasharma
In fast growing database repository system, image as data is one of the important concern despite text or numeric. Still we can’t replace test on any cost but for advancement, information may be managed with images. Therefore image processing is a wide area for the researcher. Many stages of processing of image provide researchers with new ideas to keep information safe with better way. Feature extraction, segmentation, recognition are the key areas of the image processing which helps to enhance the quality of working with images. Paper presents the comparison between image formats like .jpg, .png, .bmp, .gif. This paper is focused on the feature extraction and segmentation stages with background removal process. There are two filters, one is integer filter and second one is floating point Filter, which is used for the key feature extraction from image. These filters applied on the different images of different formats and visually compare the results.
Alamouti-STBC based Channel Estimation Technique over MIMO OFDM Systemrahulmonikasharma
The examination on various looks into on MIMO STBC framework in order to accomplish the higher framework execution is standard that the execution of the remote correspondence frameworks can be improved by usage numerous transmit and get radio wires, that is normally gathered on the grounds that the MIMO procedure, and has been incorporated. The Alamouti STBC might be a promising because of notice the pick up inside the remote interchanges framework misuse MIMO. To broaden the code rate and furthermore the yield of the symmetrical zone time square code for more than 4 transmit reception apparatuses is examined. The outlined framework is beated once forced with M-PSK (i.e upto 32-PSK) regulation. The channel estimation examine in these conditions.
Empirical Mode Decomposition Based Signal Analysis of Gear Fault Diagnosisrahulmonikasharma
A vibration investigation is about the specialty of searching for changes in the vibration example, and after that relating those progressions back to the machines mechanical outline. The level of vibration and the example of the vibration reveal to us something about the interior state of the turning segment. The vibration example can let us know whether the machine is out of adjust or twisted. Al-so blames with the moving components and coupling issues can be distinguished. This paper shows an approach for equip blame investigation utilizing signal handling plans. The information has been taken from college of ohio, joined states. The investigation has done utilizing MATLAB software.
This paper discusses a new algorithm of a univariate method, which is vitally important to develop a short-term load forecasting module for planning and operation of distribution system. It has many applications including purchasing of energy, generation and infrastructure development etc. We have discussed different time series forecasting approaches in this paper. But ARIMA has proved itself as the most appropriate method in forecasting of the load profile for West Bengal using the historical data of the year of 2017. Auto Regressive Integrated Moving Average model gives more accuracy level of load forecast than any other techniques. Mean Absolute Percentage Error (MAPE) has been calculated for the mentioned forecasted model.
Impact of Coupling Coefficient on Coupled Line Couplerrahulmonikasharma
The coupled line coupler is a type of directional coupler which finds practical utility. It is mainly used for sampling the microwave power. In this paper, 3 couplers A,B & C are designed with different values of coupling coefficient 6dB,10dB & 18dB respectively at a frequency of 2.5GHz using ADS tool. The return loss, isolation loss & transmission loss are determined. The design & simulation is done using microstrip line technology.
Design Evaluation and Temperature Rise Test of Flameproof Induction Motorrahulmonikasharma
The ignition of flammable gases, vapours or dust in presence of oxygen contained in the surrounding atmosphere may lead to explosion. Flameproof three phase induction motors are the most common and frequently used in the process industries such as oil refineries, oil rigs, petrochemicals, fertilizers, etc. The design of flameproof motor is such that it allows and sustain explosion within the enclosure caused by ignition of hazardous gases without transmitting it to the external flammable atmosphere. The enclosure is mechanically strong enough to withstand the explosion pressure developed inside it. To prevent an explosion due to hot spot on the surface of the motor, flameproof induction motors are subjected to heat run test to determine the maximum surface temperature and temperature class with respect to the ignition temperature of the surrounding flammable gas atmosphere. This paper highlights the design features of flameproof motors and their surface temperature classification for different sizes.
Water billing management system project report.pdfKamal Acharya
Our project entitled “Water Billing Management System” aims is to generate Water bill with all the charges and penalty. Manual system that is employed is extremely laborious and quite inadequate. It only makes the process more difficult and hard.
The aim of our project is to develop a system that is meant to partially computerize the work performed in the Water Board like generating monthly Water bill, record of consuming unit of water, store record of the customer and previous unpaid record.
We used HTML/PHP as front end and MYSQL as back end for developing our project. HTML is primarily a visual design environment. We can create a android application by designing the form and that make up the user interface. Adding android application code to the form and the objects such as buttons and text boxes on them and adding any required support code in additional modular.
MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software. It is a stable ,reliable and the powerful solution with the advanced features and advantages which are as follows: Data Security.MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
An Approach to Detecting Writing Styles Based on Clustering Techniquesambekarshweta25
An Approach to Detecting Writing Styles Based on Clustering Techniques
Authors:
-Devkinandan Jagtap
-Shweta Ambekar
-Harshit Singh
-Nakul Sharma (Assistant Professor)
Institution:
VIIT Pune, India
Abstract:
This paper proposes a system to differentiate between human-generated and AI-generated texts using stylometric analysis. The system analyzes text files and classifies writing styles by employing various clustering algorithms, such as k-means, k-means++, hierarchical, and DBSCAN. The effectiveness of these algorithms is measured using silhouette scores. The system successfully identifies distinct writing styles within documents, demonstrating its potential for plagiarism detection.
Introduction:
Stylometry, the study of linguistic and structural features in texts, is used for tasks like plagiarism detection, genre separation, and author verification. This paper leverages stylometric analysis to identify different writing styles and improve plagiarism detection methods.
Methodology:
The system includes data collection, preprocessing, feature extraction, dimensional reduction, machine learning models for clustering, and performance comparison using silhouette scores. Feature extraction focuses on lexical features, vocabulary richness, and readability scores. The study uses a small dataset of texts from various authors and employs algorithms like k-means, k-means++, hierarchical clustering, and DBSCAN for clustering.
Results:
Experiments show that the system effectively identifies writing styles, with silhouette scores indicating reasonable to strong clustering when k=2. As the number of clusters increases, the silhouette scores decrease, indicating a drop in accuracy. K-means and k-means++ perform similarly, while hierarchical clustering is less optimized.
Conclusion and Future Work:
The system works well for distinguishing writing styles with two clusters but becomes less accurate as the number of clusters increases. Future research could focus on adding more parameters and optimizing the methodology to improve accuracy with higher cluster values. This system can enhance existing plagiarism detection tools, especially in academic settings.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Top 10 Oil and Gas Projects in Saudi Arabia 2024.pdf
Optimum Resource Allocation using Specification Matching and Priority Based Method in Cloud
1. International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169
Volume: 5 Issue: 7 77 – 84
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Optimum Resource Allocation using Specification Matching and Priority Based
Method in Cloud
Akhil Chaurasia
Department of Computer Science and Engineering
Sant Longowal Institute of Engineering and Technology
Deemed University, Longowal, Sangrur, India
e-mail:akhilchaurasia47@gmail.com
Jaspal Singh
Department of Computer Science and Engineering
Sant Longowal Institute of Engineering and Technology
Deemed University, Longowal, Sangrur, India
e-mail:safrisoft@yahoo.com
Abstract— Cloud computing is summed up as a different model for allowing favorable, network as per demand to use shared devices of
computational resources which are collected and then released with marginal management effort or interaction with any client or any service
provider. Cloud computing is a well-known technology in the pasture of information technology that provides computing as a service. In cloud
computing environment the resources are provisioned on the basis of demand, as and when required. A large number of cloud users can request a
number of cloud services at the same time. Due to increase in the usage of cloud computing there is a need for a efficient and effective resource
allocation algorithm which can be used for proper usage of the resources and also check that the resource is not wastage. In this we propose a
priority based resource allocation algorithm which can be used for proper allocation of resources and also the resources are allocated efficiently
and effectively. In this paper, two strategies are proposed for the purpose of optimum resource allocation in which the first approach uses the
concept of specification matching and second uses the concept of priority based approach. In the first approach, different types of resources
(virtual machine) are allocated by taking three parameters into consideration: processing element, main memory, and network bandwidth. In the
second approach, one parameter is considered namely: Priority. In both strategies, users are allowed to submit the parameters during cloudlet
submission. The user inserted parameters will then be considered while allocating resources to them. The objectives of this research are to
improve utilization of resources and reduce the request loss.
Keywords- cloud computing, specification matching , priority
__________________________________________________*****_________________________________________________
I. INTRODUCTION
Cloud computing “refers to both the applications delivered as
services over the Internet, and the hardware and system
software in the data centres that provide those services”,
according to Armbrust et al.[1], and “is a utility oriented
distributed computing system consisting of a collection of
inter-connected and virtualized computers that are
dynamically provisioned and presented as one or more unified
computing resource(s) based on service-level agreements
established through negotiation between the service provider
and consumers” according to Buyya et al. [2]. Cloud
computing can be considered as an extension of grid
computing. One of the main characteristics of cloud
computing is on-demand self-service. That means Cloud
computing characteristically has provision for on-demand IT
resource allocation and instantaneous scalability. Unlike Grid
computing that typically provides persistent and permanent
use of all available IT resources, the cloud computing is very
specific on the consumer's demand, based on his current
computing requirements and therefore eliminates over-
provisioning of available IT resources.
The organizations can save the huge amount of expense by
avoiding build and manage large data centers for in-house
applications or data storage. The consumers of the cloud
computing do not have to own the IT infrastructure and
therefore need not care about the maintenance of servers and
networks in the cloud. They just pay for services on demand
that is based on the running of application instances normally
varying depending upon the use of Internet bandwidth, a
number of instances of action and amount of data transferred
at a specific time.
There are a variety of background activities in cloud
computing such as allocation of virtual machines (VMs), load
sharing, load balancing, process migration, and shared
memory access etc. which are completely abstracted from the
users view [3]. If the workload is shared by all the available
resources, it is known as load sharing. An even distribution of
workload on available resources is called load balancing [4].
One of the elementary aspects of virtualization technologies
engaged in cloud environments is resource consolidation and
managing. Using hypervisors inside a bunch environment
allows for a number of standalone physical machines to be
consolidated to a virtualized situation, thereby need less
Physical Machine (PM) physical resources than ever before.
The perception of Cloud computing has not only adjusted the
field of distributed systems but also fundamentally changed
how businesses consume computing today. While Cloud
computing offers many advanced features, it still has some
shortcomings such as the moderately high working cost for
both public and private Clouds. Better resource allocation is
depends on maneuver over utilization of physical machines
and virtual machines [5].
In this paper, we present an efficient resource allocation
technique that will help cloud owner to reduce wastage of
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resources and to achieve maximum profit. Efficient resource
allocation in the cloud is a very challenging task as it needs to
satisfy both the user‟s requirements and server‟s performance
equally. Resource allocation in cloud computing environment
is defined as the assignment of available resources such as
CPU, memory, storage, network bandwidth etc in an economic
way. It is the main part of resource management. Yet, an
important problem that must be addressed effectively in the
cloud is how to manage Quality of Services (QoS) and
maintain Service Level Agreement (SLA) for cloud users that
share cloud resources.
The proposed policy based resource allocation strategy
provides maximized resource utilization and reduced
completion time of user requests. Four parameters are used by
the proposed approach for resource allocation to user requests
namely: Processing Element (PE), Main Memory (RAM),
Network Bandwidth (BW) and Priority (P). CloudSim-3.0.3
simulator is used for the purpose of simulation of results and
to analyze the behavior of proposed work.
The rest of this paper is organized as: Section II describes
different related works regarding allocation policies in a cloud
environment and about the parameters which have been used
by the researchers. Section III proposes a policy based
resource allocation approach (PRAA), by taking four
parameters into consideration for allocation of the resources.
Section IV describes the simulation evaluations on CloudSim,
which confirms the effectiveness of the proposed approach.
Section V presents the conclusions and future scope.
II. RELATED WORK
Garima et al .[6] proposed a priority based earliest deadline
first algorithm with task migration. The algorithm that
discussed in this paper used two job scheduling algorithm one
is priority based and second is the earliest deadline first
scheduling algorithm. The tasks were scheduled on the basis of
priority and high priority task gets scheduled first. The earliest
deadline first scheduling algorithm had scheduled the tasks
according to their deadline. The task having earliest deadline
get scheduled first and then the other tasks having the earliest
deadline will be scheduled next. The tasks were scheduled pre-
emptively and preemptable tasks would be migrated to the
other virtual machine.
Pawar and Wagh [7] had been present dynamic resource
allocation for preemptable task execution in the cloud. The
proposed priority based algorithm which considered multiple
SLA parameters such as memory, network bandwidth, and
required CPU time. In order to achieve the agreed SLA
objective, the proposed algorithm dynamically provisioned the
resources by preempting the low priority task with high priority
task.
Natasha and Gill [8] proposed a priority based resource
allocation method for handling a situation where two or more
requests at a particular instance of time had the same priority.
The work flow of this model was discussed in three stages. In
stage I, initial parametric values were generated such as
attaching priority to the request of Cloud user and the user
requests were sorted in descending order based the priority.
After priority assigned, requests with same priority were
grouped into a group known as an open group. A ready queue
was generated for all the requests which were in open group
and had not been executed yet in stage II. In stage III, grouped
requests were executed. A threshold value of available
resources was set and when the load needed by one or more
requests in ready queue exceed the threshold limit; request
should wait in the waiting queue.
Santhosh and Ravichandran [9] proposed a scheduling
algorithm with pre-emptive execution to overcome the non-
pre-emptive scheduling limitations. In non-pre-emptive
scheduling, if any high priority task arrived and wait because
of unavailability of the virtual machine then system
performance degrades. In this work, When a high priority task
arrived in between execution of other task and the deadline of
the task which was about to miss then the task would be
migrated to another virtual machine. This work was compared
with traditional EDF and other non-pre-emptive scheduling
algorithms. The results show that response time was reduced
and overall system performance was improved.
K C Gouda et al. [10] proposed a priority based resource
allocation approach which allocates the resource with
minimum wastage and provides maximum profit in a dynamic
cloud environment. This algorithm used different parameters
like cost, time, no.of processors request etc. This priority
algorithm decides the allocation sequence for different task
requested by the different user after considering the priority
based on some optimum threshold decided by the cloud service
provider.
Walsh et al. [11], proposed a general two-layer architecture
that uses utility functions, adopted in the context of dynamic
and autonomous resource allocation, which consists of local
agents and global arbiter. The responsibility of local agents is
to calculate utilities for given current or forecasted workloads
and range of resources, for each AE and results, are transfer to
the global arbiter. Where global arbiter computer near-optimal
configuration of resources based on the results provided by the
local agents. In global arbiter, the new configurations applied
by assigning new resources to the AEs and the new
configuration computed either at the end of fixed control
intervals or in an event triggered manner or anticipated SLA
violation.
Wazir Y. O. et al. [12] proposed a new approach for dynamic
autonomous resource management in the computing cloud. In
this paper, the author‟s contribution is two-fold. First,
distributed architecture is adopted where resource management
is decomposed into independent tasks, each of which is
performed by Autonomous Node Agents that are tightly
coupled with the physical machines in a data center. Second,
the Autonomous Node Agents carry out configurations in
parallel through Multiple Criteria Decision Analysis using the
PROMETHEE method. This approach is potentially more
feasible in large data centers than centralized approaches.
Savani and Amar [13] proposed a priority based resource
allocation algorithm which can be used for proper allocation of
resources effectively. In this algorithm, the resources in the
cloud are allocated according to the priority which is assigned
to each user request.
Zhen Xiao [14] presents design and implementation of an
automated resource management system that can avoid
overload in the system while minimizing numbers of servers
being used, it introduces the concept of skewness measure the
convent utilization of the server and improves utilization of
servers of multidimensional resource constraints.
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Gaganjot and Sugandhi [15] proposed a preemptive priority
based job scheduling algorithm in green cloud computing
(PPJSGC). In this paper a green energy efficient scheduling
algorithm which makes the use of preemptive priority job
scheduling algorithm in cloud computing. This algorithm
focuses on reducing the power cost. The computing server is
selected on the basis of which satisfies the minimum resource
requirement of a job as per the best fit. Resources are allocated
based on the best allocation scheme. This method creates a
balanced between energy consumption and a load of the server.
This paper focuses on to design such an algorithm that
minimizes the carbon footprints and maximizes the resources
according to the suitability of the servers.
Dorian Minarolli and Bernd Freisleben [16] represents a VM
resource allocation in cloud computing via multi agent fuzzy
control, it focused on line grained dynamic resource allocation
of VM locally on each physical machine of a cloud provider
and consider memory and CPU as a resource that can be
managed. Fuzzy control is used to minimize a global utility
function as n a hill climbing heuristic implemented over fuzzy
rules. The problem considers is how to resource of a cloud
provider should be reallocated to VM dynamically where
workload changes to keep the performance according to SLA's.
Kazuki and Shin-ichi [17] proposed an optimal resource
allocation algorithm with limited energy power consumption.
Three parameters were taken into consideration to allocate
resources: processing element, network bandwidth, and electric
power consumption. The maximum numbers of the request
were processed by this approach. Total consumption of electric
power was reduced by aggregating requests being processed in
multiple areas.
Swachil and Upendra [18] proposed an improvement Priority
based Job Scheduling Algorithm in Cloud Computing using
Iterative Method. Improved priority based job scheduling
algorithm uses an iterative method to find priority of jobs and
resources and also finds priority of jobs to achieve better
performance. The proposed scheduling algorithm consists of
three levels of priorities: scheduling level (goal), resources
level (attributes) and jobs level (alternatives). Scheduling level
is the goal to be achieved by the scheduler, resources level are
the attributes that are available to achieve the desired goal and
the last level is the job level which are the available
alternatives from which the best job should be scheduled first.
This algorithm has better makespan and consistency than the
other algorithm like priority based job scheduling algorithm
and prioritized round robin algorithm.
Satveer and Birmohan [19] proposed an Optimum Resource
Allocation Approach (ORAA) in cloud computing. In this
paper, different types of resources (virtual machine) are
allocated by taking three parameters into consideration:
processing element, main memory, and network bandwidth.
Users are allowed to submit the parameters during job
submission. The user inserted parameters will then be
considered while allocating resources to them. The objective of
this paper is to make optimum resource allocation and achieve
efficient utilization of resources over public cloud.
Jiayin Li [20] presents a resource optimization mechanism in
heterogeneous IaaS federate multi cloud systems, that enable
preemptable task scheduling with resource allotment model,
cloud system model, local mapping, and energy consumption,
and application model. It is suitable for autonomic future in
cloud and VMs. The proposed online dynamic algorithms for
resource allocation and task scheduling. In proposed cloud
resource phenomenal every data center has a manager server,
the communication and resource allotment scheme works
between various servers of each data center for share
workloads among multiple data servers. The workload sharing
makes a large resource pool of flexible and cheaper resources
to resource allocation.
It has been observed from the literature that the strategies used
by the researchers provide a scope for improvement in resource
allocation. To eradicate the limitations of work done by the
researchers, a new priority based policy for resource allocation
has been proposed in this paper.
III. PROPOSED WORK
This paper proposes a method to handle the cloudlet requests
by managing resources using priority based approach for
resource allocation. The proposed approach is used to attain
better utilization of resources and reduced completion time of
user requests by means of optimized allocation of resources at
the virtual machine level. The Cloud parameters basically
represent the different types of resource: four parameters have
been chosen because of its dynamic nature. In the proposed
work, users give the parameter values during request
submission and these parameters are then be considered while
allocating VMs. The demand for any of these resources may
differ from user to user and hence are allocated dynamically.
The information about VMs with different parameters is
maintained by the data center broker in the form of resource
matrices and the VMs are allocated to the user at run time with
the help of these resource matrices. These matrices contain
merely two values either „1‟ or „0‟. Here '1' indicates that the
virtual machine of specific configuration is available and '0'
indicates its unavailability.
At the starting of the approach, to acquire some service, user
sends the request for resource allocation; the broker checks for
the available VM to process that request. When the request
with required parameter values arrives, it starts searching a
VM that fulfils its requirement with the help of the matrices
maintained by the broker. If a virtual instance of required type
exists, the arrived user request will be allocated to that VM.
After allocating all matching VMs to the user requests, the
broker will check unallocated user requests and available VMs
in the datacenter. Here the priority parameter submit by user is
used. The values of priority parameter submitted by user are
assumed. If user gives priority value '1' which represents the
priority of PE type of resource required most by the user. In
this condition, the broker search for the available VM which
has PE value equal or more than required by the user and
allocate to the user request. Accordingly, priority value '2'
represents the RAM type of resource and '3' represents the BW
type of resource. If the user gives priority value '0', then broker
will allocate any available VM to the user request without
checking any specification of the VM. So according to this
allocation of resources, all of the user requests will get
computing resource without waiting in waiting queue if VM
with any configuration is available. To check the availability
of matching VMs in the data center the essential condition is
as follows:
Z1[k1p][VMi]=1 (1)
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p ϵ U and i ϵ J
Where U is a set of PEs having “a” types and J is set of VMs.
The availability of first parameter that is PE is measured with
the help of a matrix of dimension (a × j ). If the value of
corresponding equation 1 is „1‟, that means requisite resource
can be assigned to the request and if that value is „0‟, which
means no resource can fulfil the requirement of the user
request.
Z2[k2q][VMi]=1 (2)
q ϵ V and i ϵ J
Where V is a set of RAMs having “b” types and J is set of
VMs. Similarly, in order to check the availability of the
second parameter that is different types of RAM, matrix of
dimension ( b × j ) is used and
Z3[k3r][ VMi]=1 (3)
r ϵ W and i ϵ J
Where W is a set of BWs having “c” types and J is set of
VMs. To check the availability of the third parameter that is
the BW, a third matrix of dimension ( c × j ) is maintained,
where PE, RAM, and BW are three parameters of a request
that is send by the user to achieve a required type of service.
In the above matrices Z1, Z2 and Z3, the type of PE is
represented by k1, and it may vary from 1 to a, k2 represents
the types of RAM and it may vary from 1 to b, and k3
represents the different kind of BW and it may vary from 1 to
c.
When a user demand for a service with the requisite
parameters, the availability of service is determined with the
help of three resource matrices and each matrix will return a
set of VM Ids namely T1, T2 and T3. The common VM Ids
between T1, T2 and T3 are taken into a set T and these VM
Ids can fulfil the requirement of request of a user. One of the
VM Ids from set T is assigned to the request.
In the proposed approach, if all of three equations must be
satisfied at the same time, then a VM Id returned. If the
service is unattainable, that means VM with the required
configuration does not exist. Once a VM is allocated to a
request, the value of that VM in all three matrices is reset. For
the resource allocation based on the priority, at a time only one
condition must be satisfied like when priority is for PE then,
Equation 1 only checked. Accordingly, Equation 2 checked for
priority of RAM type of resource and Equation 3 will be
checked for the priority of BW type of resource.
In the proposed approach, the space shared policy of
CloudSim-3.0.3 simulator has been chosen over time shared
policy to achieve the concept of load balancing of individual
VM in the data center. The workload on a single virtual
machine is balanced efficiently with the help of fair allocation
of resources and space-shared policy of VM. The proposed
approach which inculcates the above benefits is described in
following algorithm.
Algorithm1: Optimum Resource Allocation (VMs, CRs)
Begin
1. Initialize CloudletRequest-Completed
2. Formulate matrices Z1, Z2, Z3 for parameters PE,
RAM, BW.
3. Update VM-List (based on VM parameters)
4. Update CR-List (based on CR parameters )
5. Repeat for i = 1 to length (CR-List)
a. Call SMA (VM-List, CR-List)
b. Call Update (VM-List, Request-Completed,
CR-List)
6. If (Request-Completed != CR-List && VM-List !=
Null)
Repeat for i = 1 to length (CR-List != Request-
Completed)
a. Call PBRAA (VM-List, CR-List)
b. Call Update (VM-List, Request-Completed,
CR-List)
End
Algorithm2: SMA (VM-List, CR-List)
Begin
1. For Id = 1 to length (VM-List)
if (Z1 [Cloudlet-List.PE] [Id] and
Z2 [Cloudlet-List.RAM] [Id] and
Z3 [Cloudlet-List.BW] [Id] = available)
2. Allocate VM to CR (from VM-List)
3. Call Update (VM-List, CloudletRequest-Completed,
CR-List)
End
Algorithm3: PBRAA (VM-List, CR-List)
Begin
1. For Id = 1 to length (VM-List)
If (CR.P = 1 && Z1 [CR-List.PE] [Id] = Available)
Allocate VM to CR (from VM-List)
Else if (CR.P = 2 && Z2 [CR-List.RAM] [Id] =
Available)
Allocate VM to CR (from VM-List)
Else if (CR.P = 3 && Z3 [CR-List.BW] [Id] =
Available)
Allocate VM to CR (from VM-List)
Else if (CR.P = 0 && Z1 [CR-List.PE] [Id] =
Available || Z2 [CR-
List.RAM] [Id] = Available || Z3 [CR-List.BW] [Id]
= Available)
Allocate VM to CR (from VM-List)
2. Call Update (VM-List, CloudletRequest-Completed,
CR-List)
End
Algorithm4: Update (VM-List, CloudletRequest-
Completed, CR-List)
Begin
1. If (CloudletRequest-Completed = True)
Set (Z1 [CR.PE] [Id] and Z2
[CR-List.RAM] [Id] and Z3
[CR-List.BW] [Id] = 1)
Else
(Z1 [CR-List.PE] [Id] and
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Z2 [CR-List.RAM] [Id] and
Z3 [CR-List.BW] [Id] = 0)
2. Update VM-List
3. Update CR-List
End
Figure 1. Dataflow Diagram of Proposed Method
The proposed algorithm in this chapter takes O (m2
* n2
) time
and O (n2
) space to process all the Cloudlets in the virtual
Cloud in worst case where n is the number of virtual machines
and m is the number of Cloudlets.
IV. RESULT AND DISCUSSION
For the purpose of simulation, the CloudSim-3.0.3 simulation
toolkit has been used in the proposed work as the primary
objective of this toolkit is to provide a generalized and
extensible simulation framework that enables seamless
modeling, simulation, and experimentation of emerging Cloud
computing infrastructures and application [26].
The Cloud service system with proposed policy is shown in
figure 4.1. Only one data center is considered in the public
Cloud. There are different types of user requests and VMs in
this CloudSim-3.0.3 environment. A new broker policy is
implemented for resource allocation in which space-shared
policy is used by Cloudlets on VMs. The value of parameters
PE, RAM, and BW that a user can submit in its request are
listed in table 4.1 and the values of Priority parameter is listed
in table 4.2
TABLE 4.1 The values of Three Parameters
S.N. Type PE RAM BW
(No. of
Cores) ( in MB) ( in Mbps)
1 1 1 Core 1024 1000
2 2 2 Core 2048 2000
3 3 4 Core 4096 4000
4 4 8 Core 8192 8000
TABLE 4.2 The Values of Priority Parameter
S. No. Value of Priority (P) Demand for
Parameter
(Resource Type)
1 0 Any available VM
2 1 PE type of resource
3 2 RAM type of resource
4 3 BW type of resource
In this simulation environment, three different VM-sets in
which VM-set 1 consist of ten VMs and VM-set 2 consist of
eleven VMs and VM-set 3 consist of twelve VMs. Three
different data-sets in which each data-set consist of ten or
twelve user requests are created. All three data-sets are
executed on VM-sets separately which confirms the simulation
results. The specifications of the VMs in VM-sets and
specifications of cloudlet requests in data-sets are listed in
table 4.3 and table 4.4 respectively
The proposed approach for allocation of resources has been
verified with the help of three datasets. The Cloudlets
requested by the users of dissimilar types due to variation in
input parameters and these are allocated to the three VM-sets.
Table 4.5, Table 4.6 and table 4.7 show the number of
requests that has been accepted using matching method and
using priority separately, to provide the services, and this is
because a machine with required configuration has been
found.
As a result of this exact matching and by using priority given
by user, a mapping has been performed between the requests
and the virtual machines. In other words, user requests have
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been assigned to the virtual machine so as to get its required
service. Sometimes, if there is no available virtual machine
and in case a virtual machine is available, which does not
fulfils the need of user request, then only a request will be
unallocated. Using this information about user requests, the
average utilization of virtual machines has been calculated.
TABLE 4.3 The Specifications of Virtual Machines
S. N.
VMs
VM Set 1 VM Set 2 VM Set 3
PE
Type
RAM
Type
BW
Type
PE
Type
RAM
Type
BW
Type
PE
Type
RAM
Type
BW
Type
1 VM 0 Type 1 Type 1 Type 1 Type 1 Type 2 Type 1 Type 1 Type 2 Type 1
2 VM 1 Type 2 Type 2 Type 2 Type 1 Type 2 Type 2 Type 1 Type 2 Type 2
3 VM 2 Type 2 Type 1 Type 2 Type 2 Type 1 Type 2 Type 2 Type 1 Type 2
4 VM 3 Type 4 Type 4 Type 8 Type 4 Type 2 Type 2 Type 2 Type 2 Type 2
5 VM 4 Type 2 Type 4 Type 4 Type 2 Type 4 Type 2 Type 2 Type 4 Type 2
6 VM 5 Type 4 Type 8 Type 2 Type 2 Type 8 Type 4 Type 2 Type 4 Type 4
7 VM 6 Type 4 Type 4 Type 4 Type 8 Type 4 Type 4 Type 4 Type 4 Type 4
8 VM 7 Type 8 Type 4 Type 8 Type 4 Type 8 Type 2 Type 4 Type 8 Type 4
9 VM 8 Type 8 Type 8 Type 8 Type 8 Type 8 Type 8 Type 8 Type 8 Type 8
10 VM 9 Type 8 Type 4 Type 8 Type 4 Type 8 Type 2 Type 8 Type 8 Type 2
11 VM10 - - - Type 4 Type 1 Type 8 Type 4 Type 1 Type 8
12 VM 11 - - - - - - Type 8 Type 4 Type 8
TABLE 4.4 The Specification of Cloudlet Request
CR Id Data Set 1 Data Set 2 Data Set 3
PE
Type
RAM
Type
BW
Type
P PE
Type
RAM
Type
BW
Type
P PE
Type
RAM
Type
BW
Type
P
0 1 2 1 0 1 2 1 0 1 2 1 1
1 1 2 2 0 1 2 3 2 1 2 1 0
2 2 1 2 0 2 2 2 1 1 2 2 3
3 2 3 2 0 2 2 3 3 2 1 2 0
4 2 3 3 0 2 3 3 2 2 3 2 2
5 3 4 2 0 3 4 2 1 2 3 3 0
6 3 3 3 0 3 3 3 0 2 3 3 1
7 3 2 3 0 3 2 4 1 3 3 3 0
8 4 3 4 0 4 3 4 0 3 4 2 3
9 4 4 3 0 4 3 3 2 4 4 4 0
10 4 4 4 0 4 4 1 3 4 4 2 2
11 4 4 2 0 4 4 3 1 4 1 2 2
TABLE 4.5 The Result on VM Set 1
Data Set No. of CR No. of VMs Allocation of User Requests Average Utilization (Pu)
(In %)Using
Matching
Method
Using
Priority
Unallocated
Requests
01 12 10 10 00 02 100.00
02 12 10 05 05 02 90.00
03 12 10 08 02 02 95.00
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TABLE 4.6 The Results on VM Set 2
Data Set No. of CR No. of VMs Allocation of User Requests Average Utilization (Pu)
(In %)Using
Matching
Method
Using
Priority
Unallocated
Requests
01 12 11 09 01 01 90.00
02 12 11 05 06 00 100.00
03 12 11 08 03 00 95.00
TABLE 4.7 The Results on VM Set 3
Data Set No. of CR No. of VMs Allocation of User Requests Average Utilization (Pu)
(In %)Using
Matching
Method
Using
Priority
Unallocated
Requests
01 12 12 09 03 00 100.00
02 12 12 06 05 01 85.34
03 12 12 07 05 00 90.00
It has been observed, the proposed approach has achieved an
average utilization of 100% for dataset 1 on VM Set 1, VM
Set 2 and on VM Set 3. Dataset 2 and Dataset 3 also
achieved nearly 90% to 95 % average utilizations on VM
sets. In the table 4.6 and 4.7, there is case in which one
cloudlet request is unallocated when a VM is available in
VM set. It is because; the resource priority given by user
can‟t fulfill using available VM.
V. CONCLUSION
The optimum resource allocation using configuration
matching and priority approach is used for the purpose to
improve the resource utilization and to reduce the
completion time of user requests. Basically, this approach is
proposed to eradicate the limitations of scheduling of
resources of optimum allocation. At the time when priority
given to the resources, there has a situation where there are
available computing resources with miss-matched
configuration to serve the user request, but the resource is
not allocated to the request. In this situation, the request loss
is more and utilization of resources is somehow not
maximized as well. So, to eliminate this limitation of that
situation this method of optimum allocation of resource by
using SMA and priority is proposed.
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