Congfeng Jiang

• phd
• Professor (Associate) at Hangzhou Dianzi University

Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster, where the resources can be pooled in order to maximize data center resource utilization. Due to resource competition between batch jobs and online services, co-location frequently impairs the performance of online services. This study presents...

Edge computing and IoT devices have been widely deployed in smart city applications due to the rapid promotion and implementation of 5G communication technology. Limited by power supply and hardware computing capability, applications on edge servers are mostly deployed and run in the form of container micro-services to improve resource utilization....

Cloud services are now well established. Thanks to specific providers’ pioneering work, they offer on-site the benefit of predictability, continuity, and quality of service provided by virtualization technologies. In this context, SDN (Software Defined Networking) aims at providing tenant management of the transmission and various abstractions of t...

Contemporary megawatt-scale data centers have emerged to meet the increasing demand for online cloud services and big data analytics. However, in such large-scale data centers, servers of different generations are installed gradually year by year, making the data center heterogeneous in computing capability and energy efficiency. Furthermore, due t...

Modern data centers typically contain thousands of servers, providing various computing and storage services for users. The strategy to provide reliable and high-performance online services is to over-allocate resources for online services, which results in a waste of cluster resources. Therefore, cloud vendors tend to co-locate online services and...

The increasing demand for big data processing leads to commercial off-the-shelf (COTS) and cloud-based big data analytics services. Giant cloud service vendors provide customized big data processing systems (BDPS), which are more cost-effective for operation and maintenance than self-owned platforms. End users can rent big data analytics services w...

The abstract should briefly summarize the contents of the Server energy consumption of data center is an important issue of energy management. Energy optimization of server is also necessary to reduce energy consumption of data center cooling and power supply, and reduce the operation cost of whole data center. High server energy consumption is mai...

With increasing market competition among commercial cloud computing infrastructures, major cloud service providers are building co-located data centers to deploy online services and offline jobs in the same cluster to improve resource utilization. However, at present, related researches on the characteristics of co-location are still immature. Ther...

Land-use classification is fundamental for environmental and water resource evaluation in coastal plain areas. However, comprehensive remote sensing image-based land-use analysis is challenged by the lack of massive remote sensing images and the massive computing power of large-scale server systems. In this paper, the spatial-temporal land-use chan...

In terms of power and energy consumption, DRAMs play a key role in a modern server system as well as processors. Although power-aware scheduling is based on the proportion of energy between DRAM and other components, when running memory-intensive applications, the energy consumption of the whole server system will be significantly affected by the n...

Edge computing is a new paradigm for providing cloud computing capacities at the edge of network near mobile users. It offers an effective solution to help mobile devices with computation-intensive and delay-sensitive tasks. However, the edge of network presents a dynamic environment with large number of devices, high mobility of the end user, hete...

This paper investigates the security issues and performance optimization of the blockchain. Security has been a hot topic in blockchain technology. Stealing cryptocurrency and disclosing the privacy of transaction process have exposed the vulnerability of blockchain in different degrees. These vulnerabilities not only caused significant losses to t...

With popularity of cloud computing services, more and more tasks and services are deployed on large-scale clusters. As an emerging technology in cloud computing field, containers make virtualization extremely lightweight. However, lack of prediction causes scheduling decisions lag behind the dynamics of clouds. Thus, how to carry out performance pr...

Workload characteristics are vital for both data center operation and job scheduling in co-located data centers, where online services and batch jobs are deployed on the same production cluster. In this paper, a comprehensive analysis is conducted on Alibaba‘s cluster-trace-v2018 of a production cluster of 4034 machines. The findings and insights a...

In this paper, we present a new allocation and resource consolidation system based on a scalability metric. According to cloud computing principles, the end users rent computing and big data analytic services with a pay-as-you-go cost model. However, when users’ data size increases or when the application stresses the memory or requires more comput...

In this article, we provide a concise but systematic review on blockchain-enabled cyber-physical systems (CPS). We dissect various blockchain-enabled CPS as reported in the literature in terms of their operations and the features of blockchain that have been used. We identify key common CPS operations that can be enabled by blockchain, and classify...

Edge computing is an emerging paradigm for the increasing computing and networking demands from end devices to smart things. Edge computing allows the computation to be offloaded from the cloud data centers to the network edge and edge nodes for lower latency, security and privacy preservation. Although energy efficiency in cloud data centers has b...

Currently, many cloud providers deploy their big data processing systems as cloud services, which helps users conveniently manage and process their data in clouds. Among different service providers’ big data processing services, how to evaluate and compare their scalability is an interesting and challenging work. Most traditional benchmark tools fo...

DRAM is a significant source of server power consumption especially when the server runs memory intensive applications. Current power aware scheduling assumes that DRAM is as energy proportional as other components. However, the non-energy proportionality of DRAM significantly affects the power and energy consumption of the whole server system when...

The increasing demand for cloud-based services, such as big data analytics and online e-commerce, leads to rapid growth of large-scale internet data centers. In order to provide highly reliable, cost effective, and high quality cloud services, data centers are equipped with sensors to monitor the operational states of infrastructure hardware, such...

The explosive growth of massive data generation from Internet of Things in industrial, agricultural and scientific communities has led to a rapid increase for data analytics in cloud data centers. The ubiquitous and pervasive demand for near-data processing urges the edge computing paradigm in recent years. Edge computing is promising for less netw...

The explosive growth of massive data generation from Internet of Things in industrial, agricultural and scientific communities has led to a rapid increase in cloud data centers for data analytics. The ubiquitous and pervasive demand for near-data processing urges the edge computing paradigm in recent years. Edge computing is promising for less netw...

Edge computing is an emerging paradigm to meet the ever-increasing computation demands from pervasive devices such as sensors, actuators, and smart things. Though the edge devices can execute complex applications, it is necessary for some applications to migrate to centralized servers. By offloading the computation from the edge nodes to the edge s...

The explosive growth in cloud-based services, big data analytics, and artificial intelligence related services provisioning leads to the rapid growth of construction of large scale Internet data centers (IDCs). Modern IDCs are equipped with various sensors to monitor its healthy operation and maintenance states, such as temperature, thermal distrib...

With the development of virtualization technologies, containers are widely used to provide a light-weight isolated runtime environment. Compared with virtual machines, containers can achieve high resource utilization and provide a more convenient way of sharing, but there are significant security challenges due to potential resource contention amon...

Power consumption is a primary concern in modern servers and data centers. Due to varying in workload types and intensities, different servers may have a different energy efficiency (EE) and energy proportionality (EP) even while having the same hardware configuration (i.e., central processing unit (CPU) generation and memory installation). For exa...

In order to reduce power and energy costs, giant cloud providers now mix online and batch jobs on the same cluster. Although the co-allocation of such jobs improves machine utilization, it challenges the data center scheduler and workload assignment in terms of quality of service, fault tolerance, and failure recovery, especially for latency critic...

Metadata extraction from scholarly PDF documents is the fundamental work of publishing, archiving, digital library construction, bibliometrics, and scientific competitiveness analysis and evaluations. However, different scholarly PDF documents have different layout and document elements, which make it impossible to compare different extract approac...

With the rapid development of the Internet of Things and the ever-increasing demands of advanced services and applications, edge computing is proposed to move the computing and storage resources near the data source, which improves the response time and saves the bandwidth. However, due to the limited available resources and massive privacy-sensiti...

In virtualized sensor networks, virtual machines (VMs) share the same hardware for sensing service consolidation and saving power. For those VMs that reside in the same hardware, frequent interdomain data transfers are invoked for data analytics, and sensor collaboration and actuation. Traditional ways of interdomain communications are based on vir...

The authors propose to use formatting templates and implicit formatting semantics information for automatic metadata identification and segmentation. The pure texts and their corresponding formatting information including line height, font type, and font size, are recognized in parallel to guide metadata identification. The authors use implicit for...

Current cloud data centers are fully virtualized for service consolidation and power/energy reduction. Although virtualization could reduce the real-time power consumption and overall energy consumption, the energy characteristics of hypervisors hosting different workloads have not been well profiled or understood thus far. In this study, we invest...

Modern cloud data centers are virtualized for resource multiplexing and services consolidations. Virtual machines (VMs) residing in the same server cluster share the same hardware resources and power supply while they may have different QoS requirements for their services and applications. Moreover, the power consumption of the server cluster is hi...

Current cloud data centers are fully virtualized for service consolidations and power/energy reduction. Although virtualization could reduce real time power and overall energy consumption, the energy characteristics of hypervisors hosting different workloads are not well profiled and understood. In this paper, we investigate the power and energy ch...

The energy problem is one of the serious problems in the current large-scale storage systems need to be addressed urgently. In order to reduce the energy consumption of cloud storage system, and to meet the performance needs of users, this paper purposed a cloud storage system integrated high availability green gear-shifting mechanism (HGLG): The f...

In this paper we study one prison identification method based on iris image recognition to meet the real-time identification requirements for prison management. The identification method for online real-time acquisition personnel iris image using pre-processing algorithm to improve the quality of image for subsequent feature extraction. Moreover, w...

In this paper we study one prison identification method based on iris image recognition to meet the real-time identification requirements for prison management. The identification method for online real-time acquisition personnel iris image using pre-processing algorithm to improve the quality of image for subsequent feature extraction. Moreover, w...

The energy problem is one of the serious problems in the current large-scale storage systems need to be addressed urgently. In order to reduce the energy consumption of cloud storage system, and to meet the performance needs of users, this paper purposed a cloud storage system integrated green gear-shifting mechanism (GGSC): The frame designed a ne...

In this paper we propose a Hamming Distance Deviation Matching Approach (HDDMA) for Iris recognition. Our HDDMA approach is different from the traditional iris matching method based on Hamming Distance. Firstly we use the odd symmetry Gabor filters with single frequency and two directions to extract iris edge information. Secondly we use zero-cross...

As power density increases with high technology, the high temperature has threatened the system performance, reliability and even system safety. In this paper, we propose a temperature-aware task scheduling approach which combines low-overhead Time-Slice Scaling (TSS) with Alternative Scheduling schemes to reduce temperature. Through fine-grained t...

Main memory accounts for a large and increasing fraction of the energy consumption in multi-core systems. Therefore, it is critical to address the power issue in the memory subsystem. This paper presents a solution to improve memory power efficiency through coordinating page allocation and thread group scheduling (CAS). Under the proposed page allo...

We can view the topology of classical clouds infras-tructures as data centers to which are connected user machines. In these architectures the computations are centered on a subset of machines (the data centers) among the possible ones. In our study, we propose to consider an alternative view of clouds where both users machines and data centers are...

The growing gap between microprocessor speed and DRAM speed is a major problem that computer designers are facing. In order to narrow the gap, it is necessary to improve DRAM's speed and throughput. Moreover, on multi-core platforms, DRAM memory shared by all cores usually suffers from the memory contention and interference problem, which can cause...

As multicore systems are requiring increasing main memory bandwidth and capacity, the processor is no longer the unique dominating energy consumption component, in contrast, main memory is responsible for a large and increasing fraction of the energy consumed by systems. Therefore, improving power efficiency of processor and memory has received a l...

Taking advantage of distributed storage technology and virtualization technology, cloud storage systems provide virtual machine clients customizable storage service. They can be divided into two types: distributed file system and block level storage system. There are two disadvantages in existing block level storage system: Firstly, Some of them ar...

Virtualization is widely used in cloud computing environments to efficiently manage resources, but it also raises several challenges. One of them is the fairness issue of resource allocation among virtual machines. Traditional virtualized resource allocation approaches distribute physical resources equally without taking into account the actual wor...

In this paper we propose different models for the energy consumption in a special existing cloud system named SlapOS. In this cloud, the data center comprises dedicated and volunteer machines, these latter ones are not always available. Our objective is to state how to plan the run of applications for minimizing the global energy consumption, we pr...

In order to solve the urgent issue of the energy consumption in the cloud storage system. An Energy-effective adaptive replication strategy (E2ARS) is proposed in this paper, in which data partition mechanism, minimal replicas determining model, replicas placement strategies and the adaptive gear-shifting mechanism are elaborately designed. We try...

In traditional virtualization systems Virtual Machines (VMs) are usually over-provisioned for guarantying peak performance of hosting applications and thus waste a lot of computing resources. Although virtual machine consolidation can save power consumptions, it also increases the power intensity in a rack and makes the servers more prone to failur...

In virtualized systems, allocation and scheduling of resources shared among multiple virtual machines faces challenges such as autonomy, isolation and high workload dynamics. The multiplexing and consolidation nature of virtualized systems also raise issues such as interference and conflicts among various virtual machine instances. Therefore tradit...

The rapid development of Web 2.0 brings the flourish of web reviews. Traditional web review data extraction methods suffer from poor performance in dealing with massive data. To solve this problem, we propose an effective and efficient approach to extract web reviews based on Hadoop. It overcomes inefficiency when dealing with large-scale data, and...

Multi-core architecture has become prominent in modern processors including personal computers, large scale server systems and embedded systems. While multi core processors provide higher computing performance, they have higher power density and also consume more energy than traditional single core processors. Therefore, Dynamic Frequency Scaling (...

I/O access speed is critical to storage performance in today's distributed file systems. One approach to improve the I/O performance is to use cache scheme. In this paper, we ameliorate the data access patterns in object-based file systems, and propose a novel cache operation strategy and a frequency based replacement strategy based on Ceph. The ca...

Traditional Virtual Machines are over-provisioned to provide peak performance and waste a lot of system resources. In this paper, we propose and implement a placement strategy of Virtual Machines based on workload characteristic-s. In our approach, the virtual machines are placed into various groups after several iterations and matching based on th...

In this paper, we study resource allocation strategy about the virtualized servers. Based on a non-cooperative game theory, we employ bidding model to solve the resource allocation problem in virtualized servers with multiple instances competing for resources. The optimal response function of utility function which we introduced makes every player...

Power consumption has become a critical problem for not only battery powered devices like hand held intelligent devices, but also personal computers and large scale server systems like date centers containing thousands of computers. In such computing systems, processors consume large amount of energy thus power reduction of processors can eventuall...

In virtualization environments, resources are shared across multiple virtual machines(VMs), which results in contentions and even conflicting under heavily loaded or consolidated situations. In order to accommodate as many as service instances while still delivering performance guarantees, resource allocation should be optimized in a just adequate...

In consolidated virtualization systems, hardware resources are shared and multiplexed across multiple virtual machines (VMs) for energy and cost savings, where resources are over-provisioned according to the peak demand of VMs to provide performance guarantees. This over-provisioning manner results in resource waste and contention under heavily loa...

With active deployment of virtualization in large scale data centers and cloud computing environments, allocation and scheduling of virtual and physical resources raise more challenges and may have negative impacts on system performance due to: (1) the isolation between the guest Virtual Machines (VMs) and the Virtual Machines Monitor (VMM), and (2...

In grid environment, jobs may be scheduled to multiple machines across different administrative domains. However, grid security is a main hurdle to make the job scheduling decision secure, reliable and fault tolerant. A security-aware parallel and independent job scheduling algorithm in grid computing environment based on adaptive job replications...

Resource management is one of the main issues in Cloud Computing. In order to improve resource utilization of large Data Centers while delivering services with higher QoS to Cloud Clients, an automatic resource allocation strategy based on market Mechanism (ARAS-M) is proposed. Firstly, the architecture and the market model of ARAS-M are constructe...

In virtualized systems, such as large data centers and cloud computing environments, resources are shared across multiple virtual machines, which results in contentions and conflicting under heavily loaded or consolidated situations. In order to accommodate as many as computing and service capabilities while still delivering performance guarantees,...

Due to various differences in hardware architectures of devices in ubiquitous computing systems, portability and platform-independency become the main challenge for graphics programming in system design. In this paper, we propose an adaptive user interface programming toolkit for system design in ubiquitous computing environment. The toolkit levera...

Virtualization technology enables server and service consolidation to save more power and operational costs of large scale computing systems. However, the consolidation nature of virtualization intensifies the power densities in a rack, thus resulting in higher probability of failures and Service Level Agreements violations under constrained power...

The indoor Real Time Location Systems (RTLS) is attracting more and more attention while a series of challenging problem still exists such as the real-time performance, location precision, and the large amount of disturbance signal brought by complex indoor circumstances. However, existing location estimation technology cannot satisfy the requireme...

Power is becoming a critical resource to large scale server systems and data centers. With active deployment of virtualization technology, power management raise more challenges and have negative impact on system performance due to : (1) the isolation between the guest Virtual Machines (VMs) and the Virtual Machines Manager (VMM), and (2)the indepe...

Conventional hardware based per-component and system-wide power management methods can save more power consumptions if they are in assistance with software-level adaptation. Since the conventional coarsegrained methods are not adaptive to various fluctuating workload in real scenarios, the system performance can be deteriorated greatly if the objec...

With the scale of computing system increases, power consumption has become the major challenge to system performance, reliability and IT management costs. Specifically, system performance and reliability, described by various Quality of Service(QoS) metrics, cannot be guaranteed if the objective is to minimize the total power consumption solely, de...

With the development of the computer technology, the virtual machine has been become the main research topic. Understanding of the current technology and future trends of virtual machine system greatly help to improve the service performance of system. Therefore, we describe the current technology and present the future trends of virtual machine sy...

Typical remote sensing image interpretation consists of large number of long-lived independent computation jobs such as calibration, correction, and transformation and computation. These time consuming jobs are suitable for execution in desktop grid with high performance commodity PCs for its lower cost and high management ability. In this paper, a...

Since more power consumption results in more failures and degradations in system performance, reliability, and power bills, it has been a critical problem for not only large scale server system but also personal computers (PCs). Though much literature has focused on energy management and power budgeting for server systems, power consumption of PCs...

Higher power consumption in data centers results in more heat dissipation, cooling costs and degrades the system reliability. Conventional power reduction techniques such as dynamic voltage/frequency scaling (DVS/DFS) have disadvantages when they are ported to current data centers with virtualization deployments. In this paper, we give a short surv...

Power consumption is becoming a critical and annoying problem to data centers (DCs). Higher power consumption results in more heat dissipation, cooling costs and makes servers more prone to failures. Various excellent workload and application-specific dynamic voltage/frequency scaling (DVS/DFS) algorithms have been proposed and deployed in many com...

Applications such as online virtual fitting room for clothes demand massive computing powers in order to obtain real-time and high fidelity simulation.Computer cluster provides the infrastructure and solution to solve large scale, computation intensive and high throughput problems like fine-grained cloth simulation. In this paper, some key techniqu...