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A Method for Privacy-preserving in IoT-SDN Integration Environment 16

A Method for Privacy-preserving in IoT-SDN Integration Envir...

引用

16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Gheisari, Mehdi Wang, Guojun Chen, Shuhong Seyfollahi, Ali Guangzhou Univ Sch Comp Sci & Technol Guangzhou 510006 Guangdong Peoples R China Islamic Azad Univ Tabriz Branch Dept Comp Engn Tabriz Iran

ISBN: (纸本)9781728111414

IoT aim is connecting all objects around the world with each other through the Internet. there are a large number of devices in the IoT that each one produces data over time. We can not publish the original data, without any process, due to the possibility of sensitive data disclosure. A networking paradigm that provisions network management flexibility and easier manipulation of the network called "Software Defined networking" (SDN) recently emerged. through observations, we have found existing solutions are in lack of flexibility in management while preserving-privacy. In this paper, at first, we propose a platform for integration of IoT with SDN. then, we propose a method for solving the data privacy issue on top of it. Instead of having one static rule for all IoT devices, in our solution, each device can apply six possible privacy-preserving rules. During the time, the privacy method that each device should apply changes. We show the striking flexibility of our architecture so that management of data would be more efficient along with we are able to preserve the privacy of produced data in an acceptable level, finding original data would be a tough task.

关键词： Internet of things IoT-SDN VPN VLAN Encryption Privacy-preserving Software Defined networking Aggregation

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Saranyu: Using Smart Contracts and Blockchain for Cloud Tenant Management 11

<i>Saranyu</i>: Using Smart Contracts and Blockchain for Clo...

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11th IEEE international conference on Cloud computing (CLOUD) Part of the IEEE World Congress on Services

作者： Nayak, Sambit Narendra, Nanjangud C. Shukla, Anshu Kempf, James Ericsson Res Bangalore Bangalore Karnataka India Ericsson Res Santa Clara CA USA

ISBN: (纸本)9781538672358

While blockchains and smart contracts are primarily known for their use as the technologies underlying cryptocurrencies like Bitcoin and Ethereum, these technologies also have applicability in other areas. In this paper, we present an application of smart contracts running on a permissioned distributed ledger (essentially a private blockchain where only credentialed participants are allowed to read and write) to managing tenant and service accounts in a cloud computing data center. the system is called Saranyu and it supports four services: identity management, authentication, authorization, and charging. Identity management and authentication are handled using client-generated public/private key pairs in the usual fashion. Authorization is handled as a contract from a grantee of service access rights to a recipient which is a tenant or other service. Charging is supported by Saranyu integration with payment gateways for payments related to service resource usage. We describe an implementation of Saranyu on top of the Quorum blockchain system. We believe the security, non-repudiation, tamper-resistance, and easy transaction history access brought by blockchain technology will increase transparency and trust in cloud tenant and service management and that the fundamentally distributed nature of the blockchain will make Saranyu an excellent match with developing distributed cloud architectures.

关键词： Contracts Cloud computing Authorization Public key Electronic mail Data centers"

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Cymbalo: An Efficient Graph Processing Framework for Machine Learning 16

Cymbalo: An Efficient Graph Processing Framework for Machine...

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16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Tian, Xinhui Xie, Biwei Zhan, Jianfeng Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781728111414

Due to the growth of data scale, distributed machine learning has become more important than ever. Some recent work, like TuX(2), show promising prospect in dealing with distributed machine learning by leveraging the power of graph computation, but still leave some key problems unsolved. In this paper, we propose Cymbalo, a new distributed graph processing framework for large-scale machine learning algorithms. To satisfy the specific characteristics of machine learning, Cymbalo employs a heterogeneity-aware data model, a hybrid computing model and a vector-aware programming model, to ensure small memory footprint, good computation efficiency and expressiveness. the experiment results show that Cymbalo outperforms Spark by 2.4x-3.2x, and PowerGraph by up to 5.8x. Moreover, Cymbalo can also outperform Angel, a recent parameter server system, by 1.6x-2.1x.

关键词： Large-scale machine learning Graph computation distributed processing Spark

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Evaluation of Production Serverless computing Environments 11

Evaluation of Production Serverless Computing Environments

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11th IEEE international conference on Cloud computing (CLOUD) Part of the IEEE World Congress on Services

作者： Lee, Hyungro Satyam, Kumar Fox, Geoffrey C. Indiana Univ Sch Informat Comp & Engn Bloomington IN 47405 USA

ISBN: (纸本)9781538672358

Serverless computing provides a small runtime container to execute lines of codes without infrastructure management which is similar to Platform as a Service (PaaS) but a functional level. Amazon started the event-driven compute named Lambda functions in 2014 with a 25 concurrent limitation, but it now supports at least a thousand of concurrent invocation to process event messages generated by resources like databases, storage and system logs. Other providers, i.e., Google, Microsoft, and IBM offer a dynamic scaling manager to handle parallel requests of stateless functions in which additional containers are provisioning on new compute nodes for distribution. However, while functions are often developed for microservices and lightweight workload, they are associated with distributed data processing using the concurrent invocations. We claim that the current serverless computing environments can support dynamic applications in parallel when a partitioned task is executable on a small function instance. We present results of throughput, network bandwidth, a file I/O and compute performance regarding the concurrent invocations. We deployed a series of functions for distributed data processing to address the elasticity and then demonstrated the differences between serverless computing and virtual machines for cost efficiency and resource utilization.

关键词： FaaS Serverless Event-driven computing Amazon Lambda Google Functions Microsoft Azure Functions IBM OpenWhisk

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Towards a unified description language for simulations in cloud environments 11

Towards a unified description language for simulations in cl...

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11th IEEE/ACM international conference on Utility and Cloud computing (UCC-Companion) / 5th IEEE/ACM international conference on Big Data computing, Applications and Technologies (BDCAT)

作者： Weiss, Nils Preisler, thomas Renz, Wolfgang Hamburg Univ Appl Sci Fac Engn & Comp Sci Berliner Tor 7 D-20099 Hamburg Germany

ISBN: (纸本)9781728103594

In recent years, cloud infrastructures evolved into a flexible technology for computationally intense simulations. Container-based clouds provide scalability to scientists who develop large-scale distributed simulations, particularly when developed in microservice architecture. Automating configuration and deployment of such distributed simulations on container as a service (CaaS) platforms is a challenge that we approach in this paper. We will present a novel concept for a descriptive language, that allows for convenient execution and management of distributed simulations on cloud infrastructures using heterogeneous models run on CaaS platforms, supplemented by a software framework to implement functionality. this language will allow for reproducible simulation results and a reduction of necessary configuration for structural layers by providing an interface towards the simulation system. the configuration, deployment, conduction, roll-back and result collection of the simulation will be handled by the framework provided for this domain specific language (DSL).

关键词： Cloud computing Containers DSL Computational modeling Software Tools Computer architecture

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Radix: Enabling High-throughput Georeferencing for Phenotype Monitoring over Voluminous Observational Data 16

Radix: Enabling High-throughput Georeferencing for Phenotype...

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16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Roselius, Maxwell Pallickara, Sangmi Lee Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)9781728111414

Remote sensing of plant traits and their environment facilitates non-invasive, high-throughput monitoring of the plant's physiological characteristics. Effective ingestion of these sensing data into a storage subsystem while georeferencing phenotyping setups is key to providing timely access to scientists and modelers. In this study, we propose RADIX, a high-throughput distributed data ingestion framework with support for fine-grained georeferencing. Our methodology includes a novel spatial indexing scheme, the nested hash grid, for fine-grained georeferencing of data while conserving memory footprints and ensuring acceptable latency. We include empirical evaluations performed on a commodity machine cluster with up to 1TB of data. Our benchmarks demonstrate the efficacy of our approach.

关键词： high-throughput georeferencing distributed analytics High-throughput phenotyping. data ingestion sensor data

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Asynchronous group-based ADMM algorithm under efficient communication structure 16

Asynchronous group-based ADMM algorithm under efficient comm...

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16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Zhou, Jianhui Lei, Yongmei Shanghai Univ Sch Comp Engn & Sci Shanghai Peoples R China

ISBN: (纸本)9781728111414

Alternating direction method of multipliers (ADMM) has been recognized as an efficient approach for solving many large-scale machine learning problems. However, the ADMM under master-slave mode suffers from several limitations, e.g., can't make full use of multi-core cluster environment and single master load is too heavy, resulting in huge time overhead. In this paper, we propose a hierarchical communication structure. Since intra-node communications mostly use shared memory, we divide the processes of the same node into one group, the processes within the group synchronize communication, and each group communicate asynchronously with the master. Combining this structure with the ADMM algorithm, a hierarchical asynchronous group-based ADMM algorithm (HAG-ADMM) is proposed. theoretical analysis and experiments show that the hierarchical communication structure can improve the communication efficiency of the algorithm and has no effect on the convergence.

关键词： distributed optimization ADMM asynchronous hierarchical communication structure group-based ADMM parallel computing

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Contract-Based Demand Response Model for High Performance computing Systems 16

Contract-Based Demand Response Model for High Performance Co...

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16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Ahmed, Kishwar Bull, Jesse Liu, Jason Florida Int Univ Miami FL 33199 USA

ISBN: (纸本)9781728111414

High-performance computing (HPC) systems can consume substantial electricity during their operation, and consequently incur significant energy cost. Demand response is a scheme adopted by energy consumers to reduce energy use during the high load periods upon request from the power grid. In this paper, we propose a demand response model to allow both HPC operators and HPC users to jointly reduce the energy consumption. We apply the contract theory, originated from economics for studying the contractual arrangements among economic actors, and design a reward mechanism to ensure participation of both HPC operators and HPC users in the demand response program. We perform both analytical and simulation studies of our proposed approach. Our analyses show that our contract-based demand response model is both feasible (in ensuring both individual rationality and incentive compatibility) and optimal. the trace-based simulation demonstrates the practicality of the proposed approach.

关键词： Demand Response Energy Efficiency Contract theory High-Performance computing

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Acinonyx: Dynamic Flow Scheduling for Virtual Machine Migration in SDN-enabled Clouds 16

Acinonyx: Dynamic Flow Scheduling for Virtual Machine Migrat...

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16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Toosi, Adel Nadjaran Buyya, Rajkumar Monash Univ Fac Informat Technol Clayton Vic Australia Univ Melbourne Sch Comp & Informat Syst Parkville Vic Australia

ISBN: (纸本)9781728111414

Cloud providers rely on virtualization technology for efficient data center management and service delivery. Live Virtual Machine (VM) Migration is one of the critical features of this technology enabling cloud providers to relocate VMs between servers without disrupting applications currently running on it. One of the key challenges of VM live migration is that it creates elephant flows over the network links connecting the source to destination servers due to the transfer of the entire memory and possibly disks of the VM. In this paper, we leverage software -defined networking (SDN) and propose a dynamic flow scheduling approach called Acinonyx. Our solution is designed to minimize the negative impact of live VM migration on data center network traffic and reduce migration time in cloud data centers with multiple network paths between servers. Acinonyx adaptively installs flow entries on the switches of the shortest path with the lowest congestion and redirects VM migration traffic to the appropriate path. We describe the implementation of the proposed solution over our testbed environment, where we use OpenStack for managing commodity servers and OpenDaylight SDN controller for managing the OpenFlow switches. Our experimental results show that Acinonyx can significantly reduce the migration time of VMs while improving the overall network throughput for other VM communications.

关键词： Software-defined networking Cloud computing Dynamic Flow Scheduling Live VM Migration OpenDaylight OpenStack

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A Patient Centric Agent Assisted Private Blockchain on Hyperledger Fabric for Managing Remote Patient Monitoring

A Patient Centric Agent Assisted Private Blockchain on Hyper...

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international conference on Electrical and Computer Engineering (ICECE)

作者： Md. Anwar Hussen Wadud T. M. Amir-Ul-Haque Bhuiyan Md Ashraf Uddin Md. Motiur Rahman Mawlana Bhashani Science and Technology University Bangladesh Institute of Information and Communication Technology Bangladesh University of Engineering and Technology Internet Commerce Security Laboratory Federation University Australia Australia

ISBN: (数字)9781665422543

ISBN: (纸本)9781665446617

Recently, during the COVID-19 situation, the requirement and importance of tracking patients from a remote location have increased significantly. Most patients now prefer to obtain their doctor's care and check their health status through their mobile phone call, Skype, Facebook Messenger, or other online resources. there is, however, a major concern about the privacy of patients when using online resources. Patients usually choose to keep their information confidential, which should be only accessible to authorized individuals. the most current remote patient monitoring system is organization-centric and patient's privacy and security rely on healthcare providers' mercy. Blockchain technologies have attracted the attention of researchers for designing eHealth applications to provide patients with secure and privacy-preserving health services. Blockchain researchers have recently proposed some models for remote patient monitoring systems. However, most of those researchers have applied public blockchains where health data is available to all participants with the property of data tamper-proof. In this paper, we propose a novel remote patient monitoring model using a decentralized private blockchain to protect patient's privacy and increase the system's efficiency. the private blockchain will be implemented on Hyperledger Fabric where a Patient-centric Agents (PCA) manage patient's data and coordinate authorization to form a secure channel to transmit data to the private blockchain. A hybrid consensus by combining Proof of Integrity (PoI) and Proof of Validity (PoV) is used to protect data privacy and integrity when retrieving data from a blockchain-based cloud database. Finally, the Merkle Tree algorithm was used for data processing and authentication when collecting data and uploading it to a cloud database.

关键词： Patient monitoring Privacy distributed ledger Databases Social networking (online) Blockchain Fabrics

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