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International Workshop on Quality of Service

作者： Xinhou Wang Kezhi Wang Song Wu Sheng Di Kun Yang Hai Jin Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China University of Essex UK Argonne National Laboratory USA

Nowadays, by integrating the cloud radio access network (C-RAN) with the mobile cloud computing (MCC) technology, mobile service provider (MSP) can efficiently handle the increasing mobile traffic and enhance the capabilities of mobile users' devices to provide better quality of service (QoS). But the power consumption has become skyrocketing for MSP as it gravely affects the profit of MSP. Previous work often studied the power consumption in C-RAN and MCC separately while less work had considered the integration of C-RAN with MCC. In this paper, we present a unifying framework for optimizing the power-performance tradeoff of MSP by jointly scheduling network resources in C-RAN and computation resources in MCC to minimize the power consumption of MSP while still guaranteeing the QoS for mobile users. Our objective is to maximize the profit of MSP. To achieve this objective, we first formulate the resource scheduling issue as a stochastic problem and then propose a Resource onlIne sCHeduling (RICH) algorithm using Lyapunov optimization technique to approach a time average profit that is close to the optimum with a diminishing gap (1/V) for MSP while still maintaining strong system stability and low congestion to guarantee the QoS for mobile users. With extensive simulations, we demonstrate that the profit of RICH algorithm is 3.3× (18.4×) higher than that of active (random) algorithm.

关键词： Mobile communication Servers Power demand Cloud computing Mobile computing Quality of service Dynamic scheduling

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Dynamic SDN Controller Assignment in Data Center Networks: Stable Matching with Transfers

Dynamic SDN Controller Assignment in Data Center Networks: S...

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Annual IEEE International Conference on Computer Communications

作者： Tao Wang Fangming Liu Jian Guo Hong Xu Key Laboratory of Services Computing Technology and System Ministry of Education School of Computer Science and Technology Huazhong University of Science and Technology NetX Lab @ City University of Hong Kong

ISBN: (纸本)9781467399548

Software defined networking is becoming increasingly prevalent in data center networks for its programmability that enables centralized network configuration and management. However, since switches are statically assigned to controllers, traffic dynamics cause load imbalance among the controllers. As a result, some controllers are not fully utilized, while switches connected to overloaded controllers may experience long response times. In this paper, we consider dynamic controller assignment so as to minimize the average response time of the control plane. We formulate this problem as a stable matching problem with transfers, and propose a hierarchically two-phase algorithm that integrates key concepts from both matching theory and coalitional games to solve it efficiently. Theoretical analysis proves that our algorithm converges to a near-optimal Nash stable solution within tens of iterations. Extensive simulations show that our approach reduces response time by about 86%, and achieves better load balancing among controllers compared to static assignment.

关键词： Controllers Reaction Time control surfaces Switches data center unbalanced load programmability

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Improving the memory efficiency of in-memory mapreduce based HPC systems 1

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： Pei, Cheng Shi, Xuanhua Jin, Hai Services Computing Technology and System Laboratory Cluster and Grid Computing Laboratory School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

In-memory cluster computing systems based MapReduce, such as Spark, have made a great impact in addressing all kinds of big data problems. Given the overuse of memory speed, which stems from avoiding the latency caused by disk I/O operations, some process designs may cause resource inefficiency in traditional high performance computing (HPC) systems. Hash-based shuffle, particularly large-scale shuffle, can significantly affect job performance through excessive file operations and unreasonable use of memory. Some intermediate data unnecessarily overflow to the disk when memory usage is unevenly distributed or when memory runs out. Thus, in this study, Write Handle Reusing is proposed to fully utilize memory in shuffle file writing and reading. Load Balancing Optimizer is introduced to ensure the even distribution of data processing across all worker nodes, and Memory-Aware Task Scheduler that coordinates concurrency level and memory usage is also developed to prevent memory spilling. Experimental results on representative workloads demonstrate that the proposed approaches can decrease the overall job execution time and improve memory efficiency. © Springer International Publishing Switzerland 2015.

关键词： MapReduce

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Public auditing for secure data storage in cloud through a third party auditor using modern ciphertext 11

Public auditing for secure data storage in cloud through a t...

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11th International Conference on Information Assurance and Security, IAS 2015

作者： Hussien, Zaid Alaa Jin, Hai Abduljabbar, Zaid Ameen Yassin, Ali A. Hussain, Mohammed Abdulridha Abbdal, Salah H. Zou, Deqing Cluster and Grid Computing Laboratory Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China University of Basrah Basrah Iraq

ISBN: (纸本)9781467387156

Outsourced data in cloud and computation results are not always trustworthy because data owners lack physical possession and control over the data as a result of virtualization, replication, and migration techniques. Protecting outsourced data from security threats has become a challenging and potentially formidable task in cloud computing;hence, many schemes have focused on ameliorating this problem and on enabling public auditability for cloud data storage security. These schemes drop into two categories: total computation cost and burden on client side. Researchers have used bilinear map technology with public key cryptography. Although this technology is highly efficient, computation time is long and overhead cost is high. The client needs to perform numerous computations to ensure the integrity of data storage. To reduce auditing cost, we propose an efficient and robust scheme to maintain data integrity in cases that involve public auditing. Our scheme adopts modern cipher cryptography with a cryptographic hash function. We consider allowing a third party auditor to preprocess data on behalf of cloud users before uploading them to cloud service providers and then verifying data integrity afterward. Our proposed scheme has important security characteristics, such as privacy, key management, low cost computation, key exchange, low overhead cost, no burden on client side, inability of cloud service providers to create correct verifier respond without data, and one-time key. Finally, efficiency analysis shows that our scheme is faster and more cost-efficient than the bilinear map-based scheme. © 2015 IEEE.

关键词： Public key cryptography

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MR-COF: A genetic MapReduce configuration optimization framework 15th

MR-COF: A genetic MapReduce configuration optimization frame...

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： Liu, Chao Zeng, Deze Yao, Hong Hu, Chengyu Yan, Xuesong Fan, Yuanyuan Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan430074 China China Services Computing Technology and System Lab and Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319271392

Hadoop/MapReduce has emerged as a de facto programming framework to explore cloud-computing resources. Hadoop has many configuration parameters, some of which are crucial to the performance of MapReduce jobs. In practice, these parameters are usually set to default or inappropriate values. This severely limits system performance (e.g., execution time). Therefore, it is essential but also challenging to investigate how to automatically tune these parameters to optimize MapReduce job performance. In this paper, we propose an automatic MapReduce configuration optimization framework named as MR-COF. By monitoring and analyzing the runtime behavior, the framework adopts a cost-based performance prediction model that predicts the MapReduce job performance. In addition, we design a genetic search algorithm which iteratively tunes parameters in order to find out the best one. Testbed-based experimental results show that the average MapReduce job performance is increased by 35% with MR-COF compared to the default configuration. © Springer International Publishing Switzerland 2015.

关键词： MapReduce

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Optimization of asynchronous graph processing on GPU with hybrid coloring model 2015

Optimization of asynchronous graph processing on GPU with hy...

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20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015

作者： Shi, Xuanhua Liang, Junling Di, Sheng He, Bingsheng Jin, Hai Lu, Lu Wang, Zhixiang Luo, Xuan Zhong, Jianlong Services Computing Technology and System Lab. Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology China Argonne National Laboratory United States School of Computer Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781450332057

Modern GPUs have been widely used to accelerate the graph processing for complicated computational problems regarding graph theory. Many parallel graph algorithms adopt the asynchronous computing model to accelerate the iterative convergence. Unfortunately, the consistent asynchronous computing requires locking or the atomic operations, leading to significant penalties/overheads when implemented on GPUs. To this end, coloring algorithm is adopted to separate the vertices with potential updating conflicts, guaranteeing the consistency/correctness of the parallel processing. We propose a light-weight asynchronous processing framework called Frog with a hybrid coloring model. We find that majority of vertices (about 80%) are colored with only a few colors, such that they can be read and updated in a very high degree of parallelism without violating the sequential consistency. Accordingly, our solution will separate the processing of the vertices based on the distribution of colors.

关键词： Graphics processing unit

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Fine-grained and heterogeneous proxy re-encryption for secure cloud storage

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Chinese Science Bulletin 2014年第32期59卷 4201-4209页

作者： Peng Xu Hongwu Chen Deqing Zou Hai Jin Services Computing Technology and System Laboratory Cluster and Grid Computing Laboratory School of Computer Science and Technology Huazhong University of Science and Technology

Cloud is an emerging computing *** has drawn extensive attention from both academia and *** its security issues have been considered as a critical obstacle in its rapid *** data owners store their data as plaintext in cloud,they lose the security of their cloud data due to the arbitrary accessibility,specially accessed by the un-trusted *** order to protect the confidentiality of data owners’cloud data,a promising idea is to encrypt data by data owners before storing them in ***,the straightforward employment of the traditional encryption algorithms can not solve the problem well,since it is hard for data owners to manage their private keys,if they want to securely share their cloud data with others in a fine-grained *** this paper,we propose a fine-grained and heterogeneous proxy re-encryption(FHPRE)system to protect the confidentiality of data owners’cloud *** applying the FH-PRE system in cloud,data owners’cloud data can be securely stored in cloud and shared in a fine-grained ***,the heterogeneity support makes our FH-PRE system more efficient than the previous ***,it provides the secure data sharing between two heterogeneous cloud systems,which are equipped with different cryptographic primitives.

关键词：安全问题数据存储加密算法细粒度异构代理计算模式数据共享

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When smart grid meets geo-distributed cloud: An auction approach to datacenter demand response

When smart grid meets geo-distributed cloud: An auction appr...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Zhi Zhou Fangming Liu Zongpeng Li Hai Jin Key Laboratory of Services Computing Technology and System Huazhong University of Science and Technology China Department of Computer Science University of Calgary Canada

Datacenter demand response is envisioned as a promising tool for mitigating operational stability issues faced by smart grids. It enables significant potentials in peak load reduction and facilitates the incorporation of distributed generation. Monetary refund from the smart grid can also alleviate the cloud's burden in escalating electricity cost. However, the current demand response paradigm is inefficient towards incentivizing a cloud that runs over geo-distributed datacenters. Leveraging auction theory, this work presents an efficient incentive mechanism to elicit demand response from geo-distributed clouds. To determine the winning bids and their corresponding payments, the cloud that acts as the auctioneer needs to solve a set of winner determination problems that are highly challenging. By integrating techniques from the Gibbs sampling method and the alternating direction method of multipliers, we propose a decentralized algorithm for each datacenter to make autonomous decisions on winning bid selection and workload management, striking a balance among the economic efficiency, truthfulness and the computational efficiency. Through extensive trace-driven evaluations, we demonstrate that our incentive mechanism constitutes a win-win mechanism for both the geo-distributed cloud and the smart grid.

关键词： Smart grids Load management Power demand Servers Cost accounting Conferences Computers

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Public auditing for secure data storage in cloud through a third party auditor using modern ciphertext

Public auditing for secure data storage in cloud through a t...

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International Symposium on Information Assurance and Security (IAS)

作者： Zaid Alaa Hussien Hai Jin Zaid Ameen Abduljabbar Ali A. Yassin Mohammed Abdulridha Hussain Salah H. Abbdal Deqing Zou Cluster and Grid Computing Laboratory Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Cluster and Grid Computing Laboratory Huazhong University of Science and Technology Wuhan China University of Basrah Basrah Iraq

ISBN: (纸本)9781467387163

Outsourced data in cloud and computation results are not always trustworthy because data owners lack physical possession and control over the data as a result of virtualization, replication, and migration techniques. Protecting outsourced data from security threats has become a challenging and potentially formidable task in cloud computing; hence, many schemes have focused on ameliorating this problem and on enabling public auditability for cloud data storage security. These schemes drop into two categories: total computation cost and burden on client side. Researchers have used bilinear map technology with public key cryptography. Although this technology is highly efficient, computation time is long and overhead cost is high. The client needs to perform numerous computations to ensure the integrity of data storage. To reduce auditing cost, we propose an efficient and robust scheme to maintain data integrity in cases that involve public auditing. Our scheme adopts modern cipher cryptography with a cryptographic hash function. We consider allowing a third party auditor to preprocess data on behalf of cloud users before uploading them to cloud service providers and then verifying data integrity afterward. Our proposed scheme has important security characteristics, such as privacy, key management, low cost computation, key exchange, low overhead cost, no burden on client side, inability of cloud service providers to create correct verifier respond without data, and one-time key. Finally, efficiency analysis shows that our scheme is faster and more cost-efficient than the bilinear map-based scheme.

关键词： Cloud computing Cryptography Memory Metadata Outsourcing Protocols

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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