Energy Efficient Handover for Heterogeneous Networks: A Non-Cooperative Game Theoretic Approach

Wireless Personal Communications - The small cell technology is considered as a key technology for 5G networks. The capacity expansion and coverage extension are both achieved through this...     

一种构建CORBA Trader服务集群的方法

OMG的Trader服务是分布对象的“中介”服务，在大规模分布环境下，对Trader服务的需求日益显得迫切．单一节点的Trader服务其本身会变成分布应用的性能瓶颈．本文提出了一种基于一致性Hash方法的Cache节点定位算法和Trader Cache集群框架，并对该框架的负载均衡能力和请求响应能力进行了测试。     

Reconfigurable Carry Look-Ahead Adder Trading Accuracy for Energy Efficiency

The modern portable devices exhibiting multimedia applications demand higher energy efficient signal processing due to limited battery size. The approximate adders have shown a remarkable energy-efficiency over the accurate adders for error tolerant applications. In this paper, three novel approximate carry look-ahead adder (ACLA) architectures are proposed. These approximate ACLAs are achieved by simplifying the Boolean expression of carry generation logic such that the probability of error is small while eliminating number of logic gates. Further, a novel accuracy reconfigurable CLA (Re-CLA) that provides desired quality/accuracy in the given energy budget is proposed. The post layout synthesis results using Synopsys IC Compiler of the proposed adders are computed and analysed against the existing adders. These results demonstrate 37.67%, 18.21%, 18.14% and 15.92% reduction in energy consumption by the proposed 8-bit ACLA-I, -II, -III and -IV adders respectively over the existing approximate adder. Further, the proposed 8-bit and 16-bit Re-CLAs require only 1.92% and 7.08% more energy over the existing CLA for achieving accuracy reconfigurability. Finally, the synthesis results of the Gaussian smoothing filters embedded with the proposed adders show higher energy efficiency with acceptable image quality over the state-of-the-art adder architectures.

     

Power Control for Cognitive Radio Networks: A Game Theoretic Approach

In communication industry one of the most rapidly growing area is wireless technology and its applications. The efficient access to radio spectrum is a requirement to make this communication feasible for the users that are running multimedia applications and establishing real-time connections on an already overcrowded spectrum. In recent times cognitive radios (CR) are becoming the prime candidates for improved utilization of available spectrum. The unlicensed secondary users share the spectrum with primary licensed user in such manners that the interference at the primary user does not increase from a predefined threshold. In this paper, we propose an algorithm to address the power control problem for CR networks. The proposed solution models the wireless system with a non-cooperative game, in which each player maximize its utility in a competitive environment. The simulation results shows that the proposed algorithm improves the performance of the network in terms of high SINR and low power consumption.

     

Computing Optimal Max-Min Fair Resource Allocation for Elastic Flows

In this paper, we consider the max-min fair resource allocation problem as applied to elastic flows. We are interested in computing the optimal max-min fair rate allocation. The proposed approach is a linear programming based one and allows the computation of optimal routing paths with regard to max-min fairness, in stable and known traffic conditions. We consider non-bounded access rates, but we show how the proposed approach can handle the case of upper-bounded access rates. A proof of optimality and some computational results are also presented     

Energy Optimal Control for Steel Rolling

This paper describes the application of optimal control theory to a practical example, that of minimum energy consumption in steel rolling. In a steel plant, heavy reversing rollers are continually starting and braking. The driving motor operates mainly in the dynamic state thus consuming a large amount of energy. This paper analyzes the process of dynamic energy consumption, and further, applies the optimal control theory to minimize this. Both theoretical analysis and experimental results are encouraging.     

Cooperative Anti-Jamming and Interference Mitigation for UAV Networks: A Local Altruistic Game Approach

To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer...     

博弈模型在传感器网络安全中的应用

入侵检测是传感器网络安全的重要研究内容,论文基于博弈论中的非合作模型提出了一种新型传感器网络入侵检测方案。该方案用一种只有两个参与者(攻击者和传感器网络)的非零非合作博弈模型来描述传感器网络中入侵检测问题,并证明了这个博弈模型可以达到纳什均衡,据此可以制定一个防御策略有效地提高入侵被检测到的概率。模拟试验证明这一模型是有效可行的。     

Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT

Peer-to-peer(P2P) spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT). However, implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges. In this paper, we exploit consortium blockchain and Directed Acyclic Graph(DAG) to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT, named spectrum-energy chain,where a set ...     

LFM信号的一种最优滤波算法

本文提出了一种基于分数阶傅立叶变换的LFM信号的最优滤波算法.首先由线性最小均方误差估计的正交条件出发,得到了连续分数阶傅立叶域上的等效Wiener滤波算子的求解方法;在此基础上,进一步给出了滤波算子的离散化算法.分析及数值仿真的结果表明,这一算法不仅在性能上接近普通的Wiener滤波器,而且计算简单,便于实现.     

Optimal Energy Delivery by a Brain Pacemaker for Cerebellar Control of After-Discharge

In recent years, electrical stimulation of the cerebellum has been used successfully to control epileptic seizure activity in man. This paper deals with the minimization of the energy transferred from a brain pacemaker to the cerebellum. Reducing this energy may reduce considerably the damage done to the brain tissue, and will probably prolong the life of an implanted power source used to energize such a pacer. Using an electrical model for stainless steel electrodes imbedded in brain tissue, it is shown theoretically that an exponentially increasing stimulating pulse can reduce the energy for inhibition of after-discharge activity by at least 30 percent compared to the corresponding quantity obtained for a rectangular waveform. Preliminary in vivo tests of this theory have been conducted in cats. Electrically induced after-discharge activity was obtained by stimulating the sensorymotor cortex. Three different waveshapes (rectangular, triangular, and exponentially increasing) were applied to the cerebellum, and the minimum energy required to inhibit the elicited after-discharge was found for various pulsewidths, repetition rates, and train lengths. The preliminary data indicate that nonrectangular waveforms require less energy than the rectangular waveshape to achieve threshold inhibition of after-discharge activity.     

Resource Allocation for Network Security Risk Assessment:A Non-Cooperative Differential Game Based Approach

In this paper, we propose a non-cooperative differential game theory based resource allocation approach for the network security risk assessment. For the risk assessment, the resource will be used for risk assess, including response cost and response negative cost. The whole assessment process is considered as a differential game for optimal resource control. The proposed scheme can be obtained through the Nash Equilibrium. It is proved that the game theory based algorithm is applicable and the optimal resource level can be achieved based on the proposed algorithm.     

Optimal Scheduling of Air Conditioners for Energy Efficiency

Energy saving is one of the most important research hotspots, by which operational expenditure and CO₂ emission can be reduced. Optimal cooling capacity scheduling in addition to temperature control can improve energy efficiency. The main contribution of this work is modeling the telecommunication building for the fabric cooling load to schedule the operation of air conditioners. The time series data of the fabric cooling load of the building envelope is taken by simulation by using Energy Plus, Building Control Virtual Test Bed (BCVTB), and Matlab. This pre-computed data and other internal thermal loads are used for scheduling in air conditioners. Energy savings obtained for the whole year are about 4% to 6% by simulation and the field study, respectively.     

Optimal Power Control in Cooperative Relay Networks Based on a Differential Game

In this paper, the optimal power control problem in a cooperative relay network is investigated and a new power control scheme is proposed based on a non‐cooperative differential game. Optimal power allocated to each node for a relay is formulated using the Nash equilibrium in this paper, considering both the throughput and energy efficiency together. It is proved that the non‐cooperative differential game algorithm is applicable and the optimal power level can be achieved.     

Distributed Optimal Contention Window Control for Elastic Traffic in Single-Cell Wireless LANs

This paper presents a theoretical study on distributed contention window control algorithms for achieving arbitrary bandwidth allocation policies and efficient channel utilization. By modeling different bandwidth allocation policies as an optimal contention window assignment problem, the authors design a general and fully distributed contention window control algorithm, called general contention window adaptation (GCA), and prove that it converges to the solution of the contention window assignment problem. By examining the stability of GCA, we identify the optimal stable point that maximizes channel utilization and provide solutions to control the stable point near the optimal point. Due to the generality of GCA, this work provides a theoretical foundation to analyze existing and design new contention window control algorithms.     

致力绿色能源,领航技术发展——访艾默生网络能源中国区总裁付恒科

付恒科,毕业于西安电子科技大学并获得硕士学位,2006年在哈佛大学完成了总经理的高级管理课程。2001年10月在艾默生以7.5亿美元并购华为下属的安圣电气公司之后,付恒科被任命为艾默生网络能源中国公司的常务副总裁和市场总裁,现任艾默生网络能源有限公司中国区总裁,负责艾默生网络能源公司在中国的市场规划与全面的业务发展,包括公司战略规划、市场研究以及艾默生网络能源旗下各产品在国内外的拓展、销售以及服务。付恒科先生于1999年1月至2001年10月期间在华为技术下属的安圣电气公司任职,历任市场总裁、公司常务副总裁、公司代总裁,并兼任华为技术代理商管理部部长和华为技术对外合作事务委员会主任,负责安圣电气的市场规划与发展、安圣电气的公司规划与发展。在他的带领下,安圣电气成功地取得了在中国通信行业直销市场的优势领先地位。