亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Agile Support Vector Machine for Energy-efficient Resource Allocation in IoT-oriented Cloud using PSO

计算机科学 负载平衡(电力) 云计算 供应 虚拟机 粒子群优化 分布式计算 元启发式 资源配置 支持向量机 机器学习 人工智能 计算机网络 操作系统 几何学 数学 网格
作者
Muhammad Junaid,Adnan Sohail,Fadi Al‐Turjman,Rashid Ali
出处
期刊:ACM Transactions on Internet Technology [Association for Computing Machinery]
卷期号:22 (1): 1-35 被引量:4
标识
DOI:10.1145/3433541
摘要

Over the years cloud computing has seen significant evolution in terms of improvement in infrastructure and resource provisioning. However the continuous emergence of new applications such as the Internet of Things (IoTs) with thousands of users put a significant load on cloud infrastructure. Load balancing of resource allocation in cloud-oriented IoT is a critical factor that has a significant impact on the smooth operation of cloud services and customer satisfaction. Several load balancing strategies for cloud environment have been proposed in the past. However the existing approaches mostly consider only a few parameters and ignore many critical factors having a pivotal role in load balancing leading to less optimized resource allocation. Load balancing is a challenging problem and therefore the research community has recently focused towards employing machine learning-based metaheuristic approaches for load balancing in the cloud. In this paper we propose a metaheuristics-based scheme Data Format Classification using Support Vector Machine (DFC-SVM), to deal with the load balancing problem. The proposed scheme aims to reduce the online load balancing complexity by offline-based pre-classification of raw-data from diverse sources (such as IoT) into different formats e.g. text images media etc. SVM is utilized to classify “n” types of data formats featuring audio video text digital images and maps etc. A one-to-many classification approach has been developed so that data formats from the cloud are initially classified into their respective classes and assigned to virtual machines through the proposed modified version of Particle Swarm Optimization (PSO) which schedules the data of a particular class efficiently. The experimental results compared with the baselines have shown a significant improvement in the performance of the proposed approach. Overall an average of 94% classification accuracy is achieved along with 11.82% less energy 16% less response time and 16.08% fewer SLA violations are observed.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
hgsgeospan完成签到,获得积分10
5秒前
直率的笑翠完成签到 ,获得积分10
12秒前
hgs完成签到,获得积分10
17秒前
17秒前
MchemG应助科研通管家采纳,获得10
38秒前
JamesPei应助科研通管家采纳,获得10
38秒前
隐形曼青应助科研通管家采纳,获得10
39秒前
Kevin完成签到,获得积分10
1分钟前
1分钟前
辉哥发布了新的文献求助10
1分钟前
1分钟前
1分钟前
董可以发布了新的文献求助10
1分钟前
英俊的铭应助董可以采纳,获得10
1分钟前
curtain完成签到,获得积分10
2分钟前
大个应助科研通管家采纳,获得10
2分钟前
MchemG应助科研通管家采纳,获得10
2分钟前
所所应助科研通管家采纳,获得10
2分钟前
科研通AI2S应助科研通管家采纳,获得10
2分钟前
2分钟前
落寞书易完成签到 ,获得积分10
2分钟前
2分钟前
现实的小霸王完成签到,获得积分10
3分钟前
3分钟前
Xw完成签到,获得积分10
3分钟前
科研通AI5应助迷人问兰采纳,获得10
3分钟前
Hello应助LSH970829采纳,获得10
3分钟前
Xw发布了新的文献求助10
3分钟前
寒冷的应助核桃采纳,获得30
4分钟前
wen发布了新的文献求助10
4分钟前
隐形曼青应助科研通管家采纳,获得10
4分钟前
科研通AI2S应助科研通管家采纳,获得10
4分钟前
MchemG应助科研通管家采纳,获得10
4分钟前
wen完成签到,获得积分10
4分钟前
4分钟前
4分钟前
4分钟前
yar应助wen采纳,获得10
4分钟前
核桃发布了新的文献求助30
4分钟前
迷人问兰发布了新的文献求助10
4分钟前
高分求助中
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3990084
求助须知:如何正确求助?哪些是违规求助? 3532108
关于积分的说明 11256447
捐赠科研通 3271016
什么是DOI,文献DOI怎么找? 1805171
邀请新用户注册赠送积分活动 882270
科研通“疑难数据库(出版商)”最低求助积分说明 809228