Hierarchical Power Management Architecture and Optimal Local Control Policy for Energy Efficient Networks

Yifei Wei,Xiao-jun Wang,Leonardo Fialho,Roberto Bruschi,Olga Ormond,Martin Collier 한국통신학회 2016 Journal of communications and networks Vol.18 No.4

Since energy efficiency has become a significant concernfor network infrastructure, next-generation network devices areexpected to have embedded advanced power management capabilities. However, how to effectively exploit the green capabilities isstill a big challenge, especially given the high heterogeneity of devicesand their internal architectures. In this paper, we introduce ahierarchical power management architecture (HPMA) which representsphysical components whose power can be monitored andcontrolled at various levels of a device as entities. We use energyaware state (EAS) as the power management setting mode of eachdevice entity. The power policy controller is capable of getting informationon how many EASes of the entity are manageable insidea device, and setting a certain EAS configuration for the entity. Wepropose the optimal local control policy which aims to minimizethe router power consumption while meeting the performance constraints. A first-order Markov chain is used to model the statisticalfeatures of the network traffic load. The dynamic EAS configurationproblemis formulated as aMarkov decision process and solvedusing a dynamic programming algorithm. In addition, we demonstratea reference implementation of the HPMA and EAS conceptin a NetFPGA frequency scaled router which has the ability of togglingamong five operating frequency options and/or turning offunused Ethernet ports.

Flow-table Updating Strategy for Efficient Use of Renewable Energy in Software Defined Wireless Relay Networks

Li Li,Yifei Wei,Mei Song,Xiao-jun Wang 한국통신학회 2017 Journal of communications and networks Vol.19 No.6

Software defined networking (SDN) is revolutionizing thetelecommunication networking industry by providing flexible andefficient management. Because of energy cost and environmentalconcerns, green networking technologies are being developed to increasingenergy efficiency and making use of renewable energy, forboth wired and wireless networks. Relay nodes (RNs) are widelyused in wireless networks to increasing energy efficiency as well asthe network coverage. In this paper, we consider an SDN-enabledwireless relay network, in which the relay nodes are powered by renewableenergy. In the beginning, all the users can connect to a BSor an RN in the most energy efficient way, however, the availabilityof renewable energy is unpredictable, and users connected to anRN will have to be handed over to base stations (BSs) when there isnot enough renewable energy to power the RN. There are also occasionswhen an RN harvested more renewable energy than requiredto server the users connected to it, in these cases users connectedto BS or other RNs can be transferred to connect through this RN,otherwise the harvested surplus renewable energy will be wastedas it cannot be stored.We transform the problem of optimizing theuse of harvested renewable energy into a flow-table managementproblem. A model of harvested renewable energy available for RNsis built first, then we propose a dynamic flow-table updating strategy(DFTUS), which is driven by the availability of renewable energy,to maximize the use of the harvested renewable energy andthus minimize the use of traditional energy. DFTUS can be integratedas an application on top of an SDN controller. Simulationresults show that DFTUS can make more efficient use of renewableenergy thus make the overall relay network more energy efficientcompared with other routing strategies such as the capacity limitedstrategy (CLS) and the optimal path strategy (OPS).

Coral‑Like NiFe2O4/C Composite as the High‑Performance Anode Material for Lithium‑Ion Batteries

Shanshan Bao,Yifei Xiao,Junfeng Li,Bo Yue,Yanjun Li,Wenxian Sun,Lei Liu,Yi Huang,Li Wang,Peicong Zhang,Xuefei Lai 대한금속·재료학회 2020 ELECTRONIC MATERIALS LETTERS Vol.16 No.3

In this work, we fabricated NiFe2O4/C composite with a coral-like structure through co-precipitation approach followed bythermal decomposition. The composite with a large surface area of 162.1 m2 g−1 and an average pore size of 11.8 nm wasobtained. The porous structure in the composite derived from oxalate can Effectively accommodate the volume changesof NiFe2O4 during the cycling processes. When used as anode materials, the initial charge and discharge capacities of thecomposite were 926.7 and 1277.7 mAh g−1 at 100 mA g−1. After 50 cycles, the reversible capacity of NiFe2O4/C could stillremain at 892.4 mAh g−1. Even at a current density of 2000 mA g−1, the reversible capacity still reached 523.3 mAh g−1. The results showed that the synergy between NiFe2O4 and carbon improved the electrochemical performance, and the porouscomposite could stabilize the structure of the electrode.

Deep Local Multi-level Feature Aggregation Based High-speed Train Image Matching

Jun-Liang Chen,Xiang Li,Yifei Wei,Xiao-jun Wang 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.5

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

Data Access Control Scheme Based on Blockchain and Outsourced Verifiable Attribute-Based Encryption in Edge Computing

Chao Ma,Xiaojun Jin,Song Luo,Yifei Wei,Xiao-jun Wang 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.7

The arrival of the Internet of Things and 5G technology enables users to rely on edge computing platforms to process massive data. Data sharing based on edge computing refines the efficiency of data collection and analysis, saves the communication cost of data transmission back and forth, but also causes the privacy leakage of a lot of user data. Based on attribute-based encryption and blockchain technology, we design a fine-grained access control scheme for data in edge computing, which has the characteristics of verifiability, support for outsourcing decryption and user attribute revocation. User attributes are authorized by multi-attribute authorization, and the calculation of outsourcing decryption in attribute encryption is completed by edge server, which reduces the computing cost of end users. Meanwhile, We implemented the user's attribute revocation process through the dual encryption process of attribute authority and blockchain. Compared with other schemes, our scheme can manage users' attributes more flexibly. Blockchain technology also ensures the verifiability in the process of outsourcing decryption, which reduces the space occupied by ciphertext compared with other schemes. Meanwhile, the user attribute revocation scheme realizes the dynamic management of user attribute and protects the privacy of user attribute.