Keping Yu

A Key Management Scheme for Secure Communications of Information Centric Advanced Metering Infrastructure in Smart Grid

The Advanced Metering Infrastructure (AMI) is the core component in Smart Grid. The cyber security is one of the major concerns and challenges should be prior considered. The Information Centric Networking (ICN) is a promising architecture for the future Internet that disseminates content based on named data instead of named hosts. It will be involved into Smart Grid because its excellent congestion control and self-security can enable more scalable, secure, collaborative and pervasive networking. This paper aims at proposing an Information Centric AMI (ICN-AMI) structure and a novel key management scheme (KMS) for a large number of smart meters (SMs) in this system to ensure confidentiality, integrality and authentication. To validate the scheme, the security analysis, comparisons and NDNsim simulation are done to demonstrate that the proposed ICN-KMS is possible solution for ICN-AMI system.

Energy Efficiency Scheme with Cellular Partition Zooming for Massive MIMO Systems

Massive Multiple-Input Multiple-Output (Massive MIMO) has been realized as a promising technology element for 5G wireless mobile communications, in which Spectral Efficiency (SE) and Energy Efficiency (EE) are two critical issues. Prior estimates have indicated that 57% energy consumption of cellular system comes from the operator, mostly used to feed the base station (BS). Yet previously, the User Equipment(UE) is focused on while studying the EE issue instead of BS. In this case, in this paper, an EE scheme that focuses on the optimization of BS energy consumption is proposed. Apart from the previous studies, which divides the coverage area by circuit section, the coverage area is divided by fan section with the help of Propagation theory for zoom in or zoom out. In the proposal, transmission model and parameters related to EE is deduced first. Afterwards, the Cellular Partition Zooming (CPZ) scheme is proposed where the BS can zoom in to maintain the coverage area or zoom out to save the energy. Comprehensive simulation results demonstrate that CPZ presents better EE performance with negligible impact on the transmission rate.

CCN-AMI: Performance evaluation of content-centric networking approach for advanced metering infrastructure in smart grid

Advanced Metering Infrastructure (AMI), as the totality of systems and networks to measure, collect, store, analyze, and use energy usage data, is supposed to the key component that should be preferentially constructed for smart grid. In the meanwhile, content-centric networking (CCN) is perceived as a promising approach where the content itself becomes the core of communication instead of the address or location in the future internet research. Based on its caching advantage, it is widely believed that CCN can effectively reduce the AMI network bandwidth. This paper aims to apply the CCN approach on AMI system, which is called CCN-AMI. To the best of our knowledge, this is the first attempt to distribute contents or requests based on CCN in AMI system. Moreover, a simulation-based performance evaluation is employed to evaluate the effectiveness of the proposed CCN-AMI approach in traffic control for developing AMI system in smart grid.

Outage Probability Analysis of NOMA within Massive MIMO Systems

A Pseudo Double Scattering Channel (PDSC) Matrix assumption is proposed here for the downlink Non- Orthogonal Multiple Access (NOMA) within the massive Multi-Input Multi-Output (MIMO) systems. Afterwards, the outage probability analysis of such a system is investigated. That is, with the aid of random matrix and statistics theories, the Cumulative Probability Distribution (CDF) and also the outage probability performance are addressed. After that, the mathematics derivations obtained here are verified through numerical simulation results, wherein we further find out that with antenna number increasing, the system outage probability performance is reduced.

Content distribution in Information Centric Network: Economic incentive analysis in game theoretic approach

The contributions of this paper are twofold. Firstly, we analyze the decision making problem of caching contents by the network players of Information Centric Networking (ICN) from a game theoretic perspective. We also mention a possible content distribution model for ICN. By our proposed game theory, different network players can find the optimality taking into consideration which benefits them with optimum revenue. Secondly, we present a solution for Live Streaming Media broadcast in ICN and analyze the economic part with a decision tree. We believe, our paper clearly shows the economic incentives for major network players which can stand as a motivation to achieve the faster accommodation of ICN architecture. Besides, we identify some standardization issue in ICN architecture and we emphasize on the need for a common standard for content routers (CR) so that as a node in the ICN, CR ensure scalable content delivery as well as its functionalities match with the Internet open standard philosophy.

A Context-Aware Green Information-Centric Networking Model for Future Wireless Communications

This research proposes a novel wireless information-centric networking (ICN) architecture, namely, Context-Aware Green ICN Model (CAGIM), which can adapt the power consumption of network nodes to optimized values according to the associated link utilization. The power adaption in ICN nodes is conducted through dynamically adjusting the link-rate corresponding to content popularity and traffic load to reduce wasteful energy consumption. Moreover, we propose a smart popularity-based caching strategy, called distinguished caching scheme (DCS), with the introduction of hot and cold-caching partitions of ICN node’s cache storage for popular and non-popular content objects, respectively. DCS improves the content diversity of the cache storage by adjusting, for each content, the number of chunks to be cached at ICN nodes based on its type and popularity level. DCS thus can further decrease the network system power consumption, thanks to its improved cache hit that reduces network traffic load. Toward the goal of realizing a context-aware green wireless network system with efficient content delivery, we also design a Wi-Fi Direct based scheme as an alternative approach to minimize power consumption and latency by sharing essential/important content objects via direct communications with power-saving mechanisms in the case that wireless local area network connections are not available. The evaluation results show that CAGIM can improve network efficiency by reducing both hop-count and power consumption considerably compared with existing wireless network systems with different well-known caching schemes. This proposal enables a flexible and efficient content delivery mechanism for future networks with various real-life scenarios, like Green building, Green company, and Green campus content accesses.

An Intelligent Content Prefix Classification Approach for Quality of Service Optimization in Information-Centric Networking

This research proposes an intelligent classification framework for quality of service (QoS) performance improvement in information-centric networking (ICN). The proposal works towards keyword classification techniques to obtain the most valuable information via suitable content prefixes in ICN. In this study, we have achieved the intelligent function using Artificial Intelligence (AI) implementation. Particularly, to find the most suitable and promising intelligent approach for maintaining QoS matrices, we have evaluated various AI algorithms, including evolutionary algorithms (EA), swarm intelligence (SI), and machine learning (ML) by using the cost function to assess their classification performances. With the goal of enabling a complete ICN prefix classification solution, we also propose a hybrid implementation to optimize classification performances by integration of relevant AI algorithms. This hybrid mechanism searches for a final minimum structure to prevent the local optima from happening. By simulation, the evaluation results show that the proposal outperforms EA and ML in terms of network resource utilization and response delay for QoS performance optimization.

Self-Optimization of Handover Parameters for Long-Term Evolution with Dual Wireless Mobile Relay Nodes

In recent years, train passengers have been transferring increasing amounts of data using mobile devices. Wireless networks with mobile relay nodes support broadband wireless communications for passengers of such vehicles using backhaul links. However, the mobility management entity reuses the handover of existing user equipment, resulting in the handover of the Long-Term Evolution network being unsuitable for user equipment within the cabins of vehicles traveling at high speed. In this paper, we propose a self-optimizing handover hysteresis scheme with dual mobile relay nodes for wireless networks in high-speed mobile environments. The proposed mechanism tunes the hysteresis and cell individual offset handover parameters based on the velocity of the vehicle and the handover performance indicator, which affects the handover triggering decision and performance. The results of simulations conducted in which the performance of the proposed scheme was compared to that of an existing scheme show that the proposed scheme can reduce the number of radio link failures and service interruptions during handover procedures.

Naming scheme using NLP machine learning method for network weather monitoring system based on ICN

The market for IoT devices has been expanding rapidly for several years, and many fields are anticipating further demand in the future. However, together with this expansion, increased communication failures are expected, and solutions to prevent them are needed. Here, we aim to solve communication problems using a new network, called the CCN x (Contents Centric Networking), which is one of the leading ICN (Information Centric Networking) solutions. Our system was constructed by assuming the case of a weather monitoring IoT application in which large data communications were very likely to occur. In this paper, we propose a technique for distributing meteorological data gathered with a weather observation device and 4K camera by ICN, and caching content with a new Naming scheme using machine learning.

A game-theoretical green networking approach for information-centric networks

In order to address the energy issue and enhance the feasibility of Information-Centric Networking (ICN) in the case of access networks, this research proposes a novel Green ICN design which can adapt power consumption of network devices to their optimized real-time link-utilizations based on content popularity levels. We utilize dynamic ALR (Adaptive Link Rate) based scheme for content nodes to provide efficient content delivery as a realistic approach for the economically viable green network We also develop a game-theoretical model to study the interaction between an ISP and a network equipment company in the context of green networking. Specifically, we present the system concept and some demonstration results of game-based Green ICN model to analyze the economic incentives of players. Moreover, we discuss ICN deployment and standardization challenges, then show that the proposal is robust, easy to deploy and practically relevant for the network players.