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检索条件"任意字段=13th International Conference on Distributed Computing and Internet Technology, ICDCIT 2017"

共 228 条记录，以下是41-50 订阅

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Design ideas and Empirical Analysis of Building Equipment Monitoring System Based on Cloud computing technology 45

Design ideas and Empirical Analysis of Building Equipment Mo...

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45th IEEE Annual Computers, Software, and Applications conference, COMPSAC 2021

作者： Wenjie, Wang Jiangsu Vocational Institute of Architectural Technology Xuzhou221116 China

ISBN: (纸本)9781665424639

In this paper, a complete monitoring platform based on distributed application system is designed for cloud computing environment, which is used to capture the resource utilization and load capacity of distributed application nodes. With the help of manual configuration strategy, cloud computing resources can be dynamically scheduled and the elastic computing ability of cloud computing environment can be fully utilized by application. It focuses on the creation of access credentials, storage services, MSSQL and Azure database services, cloud services and the access control of cloud platform. Finally, taking an actual building project as an example, the monitoring principle and function of the latest BAS after supplement and modification are implemented in the weak construction drawing to verify the effectiveness of the improved work. © 2021 IEEE.

关键词： Cloud computing

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An Request Offloading and Scheduling Approach Base on Particle Swarm Optimization Algorithm in IoT-Fog Networks 13

An Request Offloading and Scheduling Approach Base on Partic...

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13th IEEE international conference on Communication Software and Networks (ICCSN)

作者： Ju, Chengen Ma, Yue Yin, Zhenyu Zhang, Feiqing Chinese Acad Sci Shenyang Inst Comp Technol Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Liaoning Key Lab Domest Ind Control Platform Tech Shenyang 110168 Peoples R China

ISBN: (纸本)9781665431828

In Industrial internet of things environment, the requests from the terminal devices are usually processed by the fog servers. However, due to the limited hardware resources and software resources, the fog server may be in a high load state in some time. In this case, some real-time requests may not be processed in time, which will affect the performance of the network. Hence, we propose a request offloading and scheduling approach to improve the performance of the net in processing the requests. Considering the influence of the distance between the devices on wireless communication, and the different deadlines of requests, we sort the terminal devices, and add the deadline of the request and the communication distance between the devices into the offloading and scheduling algorithm. these methods not only consider the real-time nature of requests, but also minimizes the average processing delay of requests. Finally, the simulation results prove that the proposed method is verified with efficacy.

关键词： industrial internet of things fog computing network request offloading and scheduling particle swarm optimization

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Vulnerability Classification for Detecting threats in Cloud Environments Against DDoS Attacks

Vulnerability Classification for Detecting Threats in Cloud ...

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international conference on Communication Systems and Network Technologies (CSNT)

作者： V. Esther Jyothi N. Sampreeth Chowdary Department of Computer Applications Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada India Department of Computer Science and Engineering P.V.P. Siddhartha Institute of Technology Vijayawada India

ISBN: (数字)9798350305463

ISBN: (纸本)9798350305470

In order to secure data, infrastructure, and services from potential attacks, cloud security is a wide issue that includes any combination of policies, technologies, and procedures. the cloud has substantially different security needs than traditional settings. Because of its dynamic nature and low client infrastructure ownership, the cloud has decreased traditional security architecture. internet connectivity and distant servers are used in cloud computing to manage data and applications. It provides users with on-demand software, bandwidth, and dynamic virtualized resources through the internet and ensures that its adapters will share in various financial advantages. the utilization of hardware, software licenses, and system maintenance is decreased for the benefit of the customers. the protocol known as SOAP or Simple Object Access Protocol, it enables communication between various web-based services. Extensible Mark-up Language (XML) and Hyper Text Transport Protocol (HTTP) are both used to develop SOAP communications. A cloud web service that uses HTTP and XML might be bringing down by the new type of distributed Denial of Service (DDoS) attacks. HTTP and XML Denial of Service (DoS) attacks provide a serious security risk to cloud computing. the Hypertext Extensible-Denial of Service (HX-DoS) attack, which causes the cloud service provider's communication channel to get blocked and go down, is made up of purposefully transmitted HTTP and XML messages. Differentiating between suitable and improper communications is necessary to solve the issue of HX-DoS attacks against cloud web services. To decide and place the packets on the side of the victim, the reconstruct and drop technique is utilized. Detection rate, accuracy, and precision were the performance parameters used to evaluated the model's performance.

关键词： Transport protocols Cloud computing Computational modeling Software as a service XML Denial-of-service attack HTTP

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FDO-ABE: A Fully Decentralized Lightweight Access Control Architecture for Mobile Edge computing 6

FDO-ABE: A Fully Decentralized Lightweight Access Control Ar...

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6th IEEE international conference on Computer and Communication Systems, ICCCS 2021

作者： Zhang, Zhishuo Huang, Guanjie Hu, Sunqiang Zhang, Wei Wu, Yi Qin, Zhiguang Chengdu China Canberra Australia

ISBN: (纸本)9780738126043

Attribute-based encryption (ABE) is an emergent cryptographic primitive introduced in recent years. Due to its fine-grained access policy, ABE has been widely used in cloud security to build an attribute-based access control architecture. As a promising edge technology, Mobile Edge computing (MEC), introduced for the internet of Mobile things (IoMT), provides the high quality services for the end-users with mobile IoT devices. In MEC, the data is stored and processed isolately and independently in fog nodes or cloudlets located at the edge of the internet in the vicinity of the mobile users. But in most existing ABE schemes, researchers only consider there is a single data storage in the system. So this makes the existing ABE scheme not applicable for the MEC with distributed micro data storages. To solve this prominent challenge in traditional ABE, in this paper, we propose a fully decentralized outsourced ABE scheme (FDO-ABE) acted as the access control architecture for the MEC. Our FDO-ABE scheme, based on the non-interactive multi-authority ABE (NI-MA-ABE) scheme, not only supports the multi attribute authorities (AAs) in generating the multi attribute-based private keys for user, but also provides the independent and isolated ciphertext storage for the distributed cloudlets or fog nodes. What's more, to offload the computational intensive tasks from mobile devices, we design an efficient outsourced decryption (oDec) algorithm for our FDO-ABE scheme. By using our oDec algorithm, the complex operations in decryption phase can be transmitted from mobile IoT devices to the cloudlets. Summing up, our FDO-ABE scheme is more suitable as an access control model for MEC. © 2021 IEEE.

关键词： Mobile edge computing

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Path planning and model design for internet plus technology innovation and entrepreneurship training 4

Path planning and model design for internet plus technology ...

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4th international conference on Advanced Electronic Materials, Computers and Software Engineering, AEMCSE 2021

作者： Zeng, Wenying Li, Binning Zhuhai China Guangdong Polytechnic of Science and Technology School of Management Engineering Guangzhou China

ISBN: (纸本)9781665415965

Technological development and industrial upgrading need innovation, and internet plus technology provides the carrier for entrepreneurship. Talent is still the key factor, and the improvement of innovation and entrepreneurship ability needs the help of internal and external forces and multiple resources. the paper proposes the training model of internet plus technology innovation and entrepreneurship, which includes multiple space time, multiple carrier and multilevel collaboration, and the countermeasures to incorporate everything. internet plus technology innovation and entrepreneurship training needs to integrate resources, manpower, material resources, technology, and other factors. Based on the introduction of internet plus technology, we should establish platform, curriculum resources, teamwork and other collaborative promotion, and switch offline and online flexibly, push on demand and system learning in parallel, promote each other through theory and practice, form innovative and entrepreneurial talents training and personalized talent training, and create new talents. Integrated innovative personnel training mechanism. the innovation of this paper is to put forward the training of integrating innovation and entrepreneurship in various forms, levels and directions, integrating internet plus technology and platform, carrying out creative design, innovation training, entrepreneurship support, specialized integration and integration of government, school and enterprise resources, and establishing a normal operation mechanism. Finally, practice scheme, approach and path are proposed to form an complete system framework to cultivate creative and entrepreneur talents. © 2021 IEEE.

关键词： Engineering education

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Resource Scheduling for Tasks of a Workflow in Cloud Environment 16th

Resource Scheduling for Tasks of a Workflow in Cloud Environ...

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16th international conference on distributed computing and internet technology (icdcit)

作者： Karmakar, Kamalesh Das, Rajib K. Khatua, Sunirmal Univ Calcutta Comp Sci & Engn Kolkata India

ISBN: (纸本)9783030369873;9783030369866

In recent days most of the enterprises and communities adopt cloud services to deploy their workflow-based applications due to the inherent benefits of cloud-based services. these workflow-based applications are mainly compute-intensive. the major issues of workflow deployment in a cloud environment are minimizing execution time (makespan) and monetary cost. As cloud service providers maintain adequate infrastructural resources, workflow scheduling in the cloud environment becomes a non-trivial task. Hence, in this paper, we propose a scheduling technique where monetary cost is reduced, while workflow gets completed within its minimum makespan. To analyze the performance of the proposed algorithm, the experiment is carried out in WorkflowSim and compares the results with the existing well-known algorithms, Heterogeneous Earliest Finish Time (HEFT) and Dynamic Heterogeneous Earliest Finish Time (DHEFT). In all the experiments, the proposed algorithm outperforms the existing ones.

关键词： Cloud computing Workflow scheduling Monetary cost Makespan

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AttentionFunc: Balancing FaaS Compute across Edge-Cloud Continuum with Reinforcement Learning 23

AttentionFunc: Balancing FaaS Compute across Edge-Cloud Cont...

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Proceedings of the 13th international conference on the internet of things

作者： Kexin Li Stefan Nastic Laboratory of Intelligent Collaborative Computing University of Electronic Science and Technology of China China Distributed System Group TU Wien Austria

ISBN: (纸本)9798400708541

Serverless computing is emerging as a promising paradigm to manage compute in Edge-Cloud continuum. However, distributing and balancing the computational load (serverless functions) across the continuum remains a significant challenge. In this paper, we introduce AttentionFunc – a novel framework for decentralized and efficient function offloading and computation balancing in the Edge-Cloud continuum. the AttentionFunc framework strives to introduce a fully decentralized decision-making model that accounts for the multi-objective nature of serverless workflows, the limitations of shared resources in the Edge-Cloud environment, and the dynamic behaviors such as resource contentions or cooperations among serverless functions. In addition, AttentionFunc incorporates an innovative multi-agent offloading model based on the Markov Decision Process (MDP), designed to minimize functions’ execution time and costs. the application of MDP allows the framework to efficiently address these issues using deep reinforcement learning approaches, with an aim to significantly improve function completion latency. Furthermore, AttentionFunc pioneers an attention-based optimization mechanism for multi-agent deep reinforcement learning. this mechanism permits DRL agents to reach a consensus with minimal coordination information, leading to substantial reductions in communication and computation overhead. We evaluate AttentionFunc and compare it against select relevant state-of-the-art approaches. Our experiments and simulations show that AttentionFunc outperforms state-of-the-art approaches in terms of 1) the completion latency (up to 44.2% reduction), 2) the function success rate (up to 43.3% increase). Additionally, we provide the results of many experiments with different MEC scenarios to highlight the components of our approach that influence the results. We conclude that our approach reduces the low-latency challenge faced by most offloading models and improves the successful comple

关键词： Edge-Cloud computing continuum FaaS Multi-agent reinforcement learning serverless functions offloading

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Dynamic Task Offloading with Minority Game for internet of Vehicles in Cloud-Edge computing 13

Dynamic Task Offloading with Minority Game for Internet of V...

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13th IEEE international conference on Services computing (SCC) / 13th IEEE international conference on Web Services (ICWS)

作者： Shen, Bowen Xu, Xiaolong Dai, Fei Qi, Lianyong Zhang, Xuyun Dou, Wanchun Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing Peoples R China Southwest Forestry Univ Sch Big Data & Intelligence Engn Kunming Yunnan Peoples R China Qufu Normal Univ Sch Informat Sci & Engn Jining Shandong Peoples R China Macquarie Univ Dept Comp Sydney NSW Australia Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9781728187860

With the advent of the internet of Vehicles (IoV), drivers are now provided with diverse time-sensitive vehicular services that usually require a large scale of computation. As civilian vehicles are generally insufficient in computational resources, their service requests are offloaded to cloud data centers and edge computing devices (ECDs) with ample computational resources to enhance the quality of service (QoS). However, ECDs are often overloaded with excessive service requests. In addition, as the network conditions and service compositions are complicated and dynamic, the centralized control of ECDs is hard to achieve. To tackle these challenges, a dynamic task offloading method with minority game (MG) in cloud-edge computing, named DOM, is proposed in this paper. Technically, MG is an effective tool with a distributed mechanism which can minimize the dependency on centralized control in resource allocation. In the MG, reinforcement learning (RL) is applied to optimize the distributed decision-making of participants. Finally, with a real-world dataset of IoV services, the effectiveness and adaptability of DOM are evaluated.

关键词： Dynamic Task Offloading Edge computing Game theory Reinforcement Learning

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A Large Scale IoT Botnet Attack Detection Using Ensemble Learning 14th

A Large Scale IoT Botnet Attack Detection Using Ensemble Lea...

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12th international Advanced computing conference, IACC 2022

作者： Jwalin, B. Saravanan, S. Department of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham Banglore India

ISBN: (纸本)9783031356438

the escalation of the newer technology called internet of things (IoT), introduced numerous benefits to people. However, it has also raised the risk of cybercriminal attacks. For instance, it has allowed criminals to access confidential information and launch distributed Denial of Service (DDoS) attacks. Most frequent type of attacks that are carried out is botnets, which are designed to take over a device’s memory and computation. the shortfall of security platform for these devices, can make them vulnerable to exploitation. As connected devices and huge network traffic data rocket in number, it has become more challenging for companies to concentrate on safeguards. In this paper, we propose to implement ensemble algorithms specifically Random Forest and Gradient Boosted Decision Tree (GBDT) that can identify botnet attacks. the research is conducted on a complete N_BaIoT dataset as more data leads to better decisions. We deployed an Apache Spark, a big data technology platform, five nodes cluster to process the complete N_BaIoT dataset. through the experiments, both the GBDT and Random Forest can produce impressive results. With respect to accuracy, GBDT and Random Forest resulted in 99.24% and 99.8% respectively. However, in terms of time elapsed, GBDT can outperform Random Forest by 12 s. Overall, the GBDT model proved effective in finding malicious data from diverse IoT devices with astounding accuracy and a noteworthy time. © 2023, Springer Nature Switzerland AG.

关键词： Botnet

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distributed Packets Scheduling Technique for Cognitive Radio internet of things Based on Discrete Permutation Particle Swarm Optimization 13

Distributed Packets Scheduling Technique for Cognitive Radio...

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2020 IEEE Congress on Cybermatics: 13th IEEE international conferences on internet of things, ithings 2020, 16th IEEE international conference on Green computing and Communications, GreenCom 2020, 13th IEEE international conference on Cyber, Physical and Social computing, CPSCom 2020 and 6th IEEE international conference on Smart Data, SmartData 2020

作者： Tarek, Dina Benslimane, Abderrahim Darwish, M. Kotb, Amira M. Faculty of Computers and Information Cairo University Information Technology Department Cairo Egypt LIA/CERI University of Avignon Avignon France

ISBN: (纸本)9781728176475

Integrating Cognitive Radio Networks with internet of things, which is called Cognitive Radio internet of things (CRIoT), is considered to be a breakthrough for the IoT spectrum scarcity problem. Some IoT applications can be controlled in a centralized manner while others needs a distributed manner. this depends on the nature and the architecture of the deployed IoT application. this paper proposes a distributed scheduling protocol to be applied on IoT for traffic control. three distributed access strategies are examined;classical round robin and two proposed ones named vertex cover and enhanced round robin. they are used along with the centralized scheduling protocol (SDP-PSO) proposed by the authors in [1], to produce a distributed scheduling protocol. Dealing with this scheduling as an optimization problem;an objective fitness function is formulated, so that the fog node responsible to schedule at a time interval will formulate an allocation scheme for packets at itself. Using fairness index, average queuing delay and percentage of dropped packets as performance metrics, the performance evaluations of the three access strategies show that classical round robin performs better in case of using small number of fog node. However vertex cover performs better only in all other cases. Enhanced round robin performance is in the middle between the two other protocols. © 2020 IEEE.

关键词： internet of things

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