Variable length dynamic addressing based on network traffic distribution in wireless sensor networks

In this paper,a novel dynamic addressing scheme for wireless sensor networks(WSNs)is proposed by using variable length coding.A WSN is typically composed of numerous tiny energy-constrained sensor nodes with limited information processing and data storage capabilities;thus,the energy-efficient strategy is the key issue in designing protocols for WSN.Traditional addressing strategies adopt flat addressing(static and uniform addresses)for sensor nodes.However,the proposed variable length dynamic addressing(VLDA)for sensor nodes is based on the fact that different nodes in the network have uneven traffic loads.Therefore,nodes with more data to receive or send are allocated with shorter addresses.Whether a node is busy or not is determined by the network traffic distribution(NTD),which is defined as the number of data packets each node has received or sent in a period of time.Sensor nodes’energy is saved by VLDA scheme;hence,the wireless sensor network’s lifetime is extended.In the simulation,a 20%improvement has been achieved through the addressing scheme compared to traditional flat addressing.

Benefits Analysis of Beam Hopping in Satellite Mobile System with Unevenly Distributed Traffic

Satellite mobile system and space-airground integrated network have a prominent superiority in global coverage which plays a critical role in remote and non-land regions, as well as emergency communications. However, due to the gradual angle attenuations of the satellite antennas, it is difficult to achieve full frequency multiplex among different beams as terrestrial 5G network. Multi-color frequency reuse is widely adopted in both academic and industry. Beam hopping scheme has attracted the attention of researchers recently due to the allocation flexibility. In this paper, we focus on analyzing the performance benefits of beam hopping compared with multi-color frequency reuse scheme in non-uniform user and traffic distributions in satellite system. Aerial networks are also introduced to form a space-airground integrated network for coverage enhancement,and the capacity improvement is analyzed. Besides,additional improved techniques are provided to make comprehensive analysis and comparisons. Theoretical analysis and simulation results indicate that the beam hopping scheme has a prominent superiority in the system capacity compared with the traditional multicolor frequency reuse scheme in both satellite mobile system and future space-air-ground integrated network.

Future Vision on Artificial Intelligence Assisted Green Energy Efficiency Network

To meet the key performance requirement of the 5G network and the demand of the growing number of mobile subscribers,millions of base stations are being constructed.5G New Radio is designed to enable denser network deployments,which raises significant concerns about network energy consumption.Machine learning(ML),as a kind of artificial intelligence(AI)technologies,can enhance network optimization performance and energy efficiency.In this paper,we propose AI/ML-assisted energy-saving strategies to achieve optimal performance in terms of cell shutdown duration and energy efficiency.To realize network intelligence,we put forward the concept of intrinsic AI,which integrates AI into every aspect of wireless communication networks.

A novel fractional uplink power control framework for self-organizing networks

Internet of things and network densification bring significant challenges to uplink management.Only depending on optimization algorithm enhancements is not enough for uplink transmission.To control intercell interference,Fractional Uplink Power Control(FUPC)should be optimized from network-wide perspective,which has to find a better traffic distribution model.Conventionally,traffic distribution is geographic-based,and ineffective due to tricky locating efforts.This paper proposes a novel uplink power management framework for Self-Organizing Networks(SON),which firstly builds up pathloss-based traffic distribution model and then makes the decision of FUPC based on the model.PathLoss-based Traffic Distribution(PLTD)aggregates traffic based on the propagation condition of traffic that is defined as the pathloss between the position generating the traffic and surrounding cells.Simulations show that the improvement in optimization efficiency of FUPC with PLTD can be up to 40%compared to conventional GeoGraphic-based Traffic Distribution(GGTD).

Pedestrian walking characteristics at stairs according to width change for application of piezoelectric energy harvesting

This work aims at finding pedestrian walking characteristics at U-type stairs according to the width change of stairs and appropriate spot for installing piezoelectric energy harvesting.The number of pedestrian at two kinds of stairs(one is stairs with 1.5 m in width and the other is stairs with 3 m in width) was estimated by calculating the number of steps on the stairs by a zone which is divided into 30 cm×30 cm.The result shows high density in the middle in the case of narrow stairs but traffic is concentrated on stair inside(pillar side) in stairs with large width.In conclusion,the location for installation of piezoelectric energy harvesting system should be considered differently on stairs width and the number of installation depends on total expected traffic and the expected traffic for a device.

Effect of traffic restriction on atmospheric particle concentrations and their size distributions in urban Lanzhou, Northwestern China

During the 2012 Lanzhou International Marathon, the local government made a significant effort to improve traffic conditions and air quality by implementing traffic restriction measures. To evaluate the direct effect of these measures on urban air quality, especially particle concentrations and their size distributions, atmospheric particle size distributions （0.5-20μm） obtained using an aerodynamic particle sizer （model 3321, TSI, USA） in June 2012 were analyzed. It was found that the particle number, surface area and volume concentrations for size range 0.5-10 μm were （15.0±2.1） cm-3, （11.8±2.6） μm2/cm3 and （1.9±0.6） μm2/cm3, respectively, on the traffic-restricted day （Sunday）, which is 63.2%, 53.0% and 47.2% lower than those on a normal Sunday. For number and surface area concentrations, the most affected size range was 0.5-0.7 and 0.5-0.8 μm, respectively, while for volume concentration, the most affected size ranges were 0.5-0.8, 1.7-2.0 and 5.0-5.4 μm. Number and volume concentrations of particles in size range 0.5-1.0μm correlated well with the number of non-CNG （Compressed Natural Gas） powered vehicles, while their correlation with the number of CNG-powered vehicles was very low, suggesting that reasonable urban traffic controls along with vehicle technology improvements could play an important role in improving urban air quality.

A new traffic allocation algorithm in Ad hoc networks

A dynamic traffic distribution algorithm based on the minimization product of packet delay and packet energy consumption is proposed. The algorithm is based on packet delay and energy consumption in allocating traffic, which can optimize the network performance. Simulation demonstrated that the algorithm could dynamically adjust to the traffic distribution between paths, which can minimize the product of packet delay and energy consumption in mobile Ad hoc networks.

TIFAflow: Enhancing Traffic Archiving System with Flow Granularity for Forensic Analysis in Network Security

The archiving of Internet traffic is an essential function for retrospective network event analysis and forensic computer communication. The state-of-the-art approach for network monitoring and analysis involves storage and analysis of network flow statistic. However, this approach loses much valuable information within the Internet traffic. With the advancement of commodity hardware, in particular the volume of storage devices and the speed of interconnect technologies used in network adapter cards and multi-core processors, it is now possible to capture 10 Gbps and beyond real-time network traffic using a commodity computer, such as n2disk. Also with the advancement of distributed file system （such as Hadoop, ZFS, etc.） and open cloud computing platform （such as OpenStack, CloudStack, and Eucalyptus, etc.）, it is practical to store such large volume of traffic data and fully in-depth analyse the inside communication within an acceptable latency. In this paper, based on well- known TimeMachine, we present TIFAflow, the design and implementation of a novel system for archiving and querying network flows. Firstly, we enhance the traffic archiving system named TImemachine＋FAstbit （TIFA） with flow granularity, i.e., supply the system with flow table and flow module. Secondly, based on real network traces, we conduct performance comparison experiments of TIFAflow with other implementations such as common database solution, TimeMachine and TIFA system. Finally, based on comparison results, we demonstrate that TIFAflow has a higher performance improvement in storing and querying performance than TimeMachine and TIFA, both in time and space metrics.

考虑双重不确定性的公交时刻表分布鲁棒优化模型

城市公交系统由于受外界干扰,其需求和运行环境在时空上呈现高度不确定性,给日常运营组织带来了巨大挑战.为增强公交系统对于客流需求和运行场景双重不确定性的应对能力,提出一种权衡服务质量和服务鲁棒性的单一线路时刻表优化方法.方法采用离散场景集刻画需求的不确定性,并以滞留人数的期望值和条件风险值最小化为目标,综合考虑多方面约束,构建多场景耦合的分布鲁棒优化模型(DRO).为方便模型求解,运用模糊集描述场景发生概率的不确定性,再借助对偶理论和常规线性化方法将原模型转化为等价的混合整数线性规划形式.最后通过实际案例对方法进行分析,结果表明:等价转换得到的线性形式可由GUROBI优化软件快速求得最优解;DRO模型所得时刻表能有效应对双重不确定性;随着不确定性的上升,分布鲁棒优化方法相较于传统随机规划方法体现出更强的鲁棒性,可以切实改善公交系统运营的稳定性.

Optimization of listening time of S-MAC for wireless sensor networks

In wireless sensor networks, sensor nodes are usually battery-operated computing and sensing devices, hence operations are limited by the initially equipped batteries, which are hard to be recharged or replaced. ：In this sense, saving energy consumption becomes significant. As most energy waste is from the always-on wireless interface, S-MAC is suggested to reduce energy consumption by introducing periodic listen/sleep scheme. However, when designing the listening time, S-MAC fails to consider the traffic distribution factor. In this article, an optimization for this scheme is proposed based on the distribution model. Evaluations show that the optimized S-MAC achieves considerable improvement in energy and latency.