Clustering-based adaptive low-power subframe configuration with load-aware offsetting in dense heterogeneous networks

Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless networks.In dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when possible to enhance the user throughput and system capacity by increasing the area spectral efficiency.However,because of the transmit power differences in different tiers of HetNets and irregular service demand,a load imbalance typically exists among different serving nodes.To offload more traffic to LPNs and coordinate the Inter-Cell Interference(ICI),Third-Generation Partnership Project(3GPP)has facilitated the development of the Cell Range Expansion(CRE),enhanced Inter-Cell Interference Coordination(eICIC)and Further enhanced ICIC(FeICIC).In this paper,we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe(LPS)approach.Our solution allows the separation of User Association(UA)functions at the User Equipment(UE)and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength(max-RSS)based UA scheme,where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the system.The proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service regions.Results show that our method effectively solves the offloading and interference coordination problems in dense HetNets.

Unweighted Voting Method to Detect Sinkhole Attack in RPL-Based Internet of Things Networks

The Internet of Things(IoT)consists of interconnected smart devices communicating and collecting data.The Routing Protocol for Low-Power and Lossy Networks(RPL)is the standard protocol for Internet Protocol Version 6(IPv6)in the IoT.However,RPL is vulnerable to various attacks,including the sinkhole attack,which disrupts the network by manipulating routing information.This paper proposes the Unweighted Voting Method(UVM)for sinkhole node identification,utilizing three key behavioral indicators:DODAG Information Object(DIO)Transaction Frequency,Rank Harmony,and Power Consumption.These indicators have been carefully selected based on their contribution to sinkhole attack detection and other relevant features used in previous research.The UVM method employs an unweighted voting mechanism,where each voter or rule holds equal weight in detecting the presence of a sinkhole attack based on the proposed indicators.The effectiveness of the UVM method is evaluated using the COOJA simulator and compared with existing approaches.Notably,the proposed approach fulfills power consumption requirements for constrained nodes without increasing consumption due to the deployment design.In terms of detection accuracy,simulation results demonstrate a high detection rate ranging from 90%to 100%,with a low false-positive rate of 0%to 0.2%.Consequently,the proposed approach surpasses Ensemble Learning Intrusion Detection Systems by leveraging three indicators and three supporting rules.

Lossy nodes inference based on end-to-end passive monitoring in wireless sensor networks

This paper presents a passive monitoring mechanism, loss）, nodes inference （LoNI）, to identify loss）, nodes in wireless sensor network using end-to-end application traffic. Given topology dynamics and bandwidth constraints, a space-efficient packet marking scheme is first introduced. The scheme uses a Bloom filter as a compression tool so that path information can bc piggybacked by data packets. Based on the path information, LoNI then adopts a fast algorithm to detect lossy nodes. The algorithm formulates the inference problem as a weighted set-cover problem and solves it using a greedy approach with low complexity. Simulations show that LoNI can locate about 80% of lossy nodes when lossy nodes are rare in the network. Furthermore, LoNI performs better for the lossy nodes near the sink or with higher loss rates.

A low-power Bluetooth-based wireless sensor network and its global confliction-solving impact localization method

During the whole service lifetime of aircraft structures with composite materials,impacts are inevitable and can usually cause severe but barely visible damages.Since the occurrences of impact are random and unpredictable,it is a hotspot direction to develop an online impact monitoring system that can meet strict limitations of aerospace applications including small size,light weight,and low power consumption.Piezoelectric(PZT)sensor,being able to generate impact response signals with no external power and cover a large-scale structure with only a small amount of them,is a promising choice.Meanwhile,for real systems,networks with multiple nodes are normally required to monitor large-scale structures in a global way to identify any impact localization confliction,yet the existing studies are mostly evaluated with single nodes instead of networks.Therefore,in this paper,based on a new low-power node designed,a Bluetooth-based digital impact monitoring PZT sensor network is proposed for the first time with its global confliction-solving impact localization method.Evaluations of the system as a network are researched and analyzed on a complex real aircraft wing box for a global confliction-solving impact localization,showing a satisfying high accuracy.

A low-power high-throughput link splitting router for NoCs

In this paper, we propose a technique for lowering the latency of the communication in a NoC （network on chip）. The technique, which can support two qualities of service （QoS）, i.e., the guaranteed throughput （GT） and best effort （BE）, is based on splitting a wider link into narrower links to increase throughput and decrease latency in the NoC. In addition, to ease the synchronization and reduce the crosstalk, we use the l-of-4 encoding for the smaller buses. The use of the encoding in the proposed NoC architecture considerably lowers the latency for both BE and GT packets. In addition, the bandwidth is increased while the power consumption of the links is reduced.

Towards Interference-Aware ZigBee Transmissions in Heterogeneous Wireless Networks

Cross-technology interference(CTI)from diverse wireless networks such as ZigBee,Bluetooth,and Wi-Fi has become a severe problem in the 2.4 GHz Industrial Scientific and Medical(ISM)band.Especially,low power and lossy networks are vulnerable to the signal interferences from other aggressive wireless networks when they perform low power operations to conserve the energy consumption.This paper presents CoSense,which accurately detects ZigBee signals with a reliable signal correlation scheme in the presence of the CTI.The key concept of CoSense is to reduce false wake-ups of low power listening(LPL)by identifying the pre-defined ZigBee signatures.Our scheme is robust in the coexistence environment of diverse wireless technologies since the signal correlation works well in bad wireless channel conditions.It achieves standard compliance and transparency without any hardware and firmware changes.We have implemented CoSense on the Universal Software Radio Peripheral(USRP)platform to verify its feasibility.The experimental exploration reveals that CoSense significantly reduces the false-positive and false-negative rate under typical setting and the additional overhead is negligible.The results show that our scheme saves much energy by up to 63%in dynamic network interference scenarios where low-power ZigBee transmissions are overwhelmed by strong Wi-Fi signal interferences.

基于DCT自适应量化的频谱数据有损压缩算法

针对由于我国频谱监测设备数量激增产生了海量频谱监测数据的存储和传输难题,提出一种基于DCT自适应量化的频谱数据有损压缩算法。首先将多帧频谱监测数据组合并经过灰度空间映射形成一幅时频图,后将时频图数据矩阵按列三等分,将等分后的数据作为RGB三通道合成一幅彩色图像并对其进行二维DCT变换,利用BP神经网络估计量化阈值后进行量化,最后经过游程编码与二次熵编码完成频谱监测数据的压缩。通过对真实接收机采集的频谱数据的压缩处理,压缩率约为10%,数据恢复后的百分比均方根误差约为11%。实验结果表明,所提算法具有稳定的压缩率和较小的恢复误差,能够有效地对实际采集的频谱数据进行压缩。

基于无线传感网NB-IoT分簇RPL组播路由算法的研究

为了在已有RPL组播路由协议的基础上,改进无线传感网关键转发节点轮换机制,在DAO消息option选项中增加能量剩余参数和转发节点更换阈值后,根据网络规模和组播接收节点数,转发节点轮换阈值,使能量充足的转发节点参与到分组转发中。当节点能量减少到设定的阈值后,切换转发节点,保证各节点的能耗均衡,从而设计出最优转发节点集。通过仿真可知;该算法可以有效控制节点能耗,提高网络节点的平均使用时间,延长网络生存周期。

LOA-RPL:Novel Energy-Efficient Routing Protocol for the Internet of Things Using Lion Optimization Algorithm to Maximize Network Lifetime

Energy conservation is a significant task in the Internet of Things(IoT)because IoT involves highly resource-constrained devices.Clustering is an effective technique for saving energy by reducing duplicate data.In a clustering protocol,the selection of a cluster head(CH)plays a key role in prolonging the lifetime of a network.However,most cluster-based protocols,including routing protocols for low-power and lossy networks(RPLs),have used fuzzy logic and probabilistic approaches to select the CH node.Consequently,early battery depletion is produced near the sink.To overcome this issue,a lion optimization algorithm(LOA)for selecting CH in RPL is proposed in this study.LOA-RPL comprises three processes:cluster formation,CH selection,and route establishment.A cluster is formed using the Euclidean distance.CH selection is performed using LOA.Route establishment is implemented using residual energy information.An extensive simulation is conducted in the network simulator ns-3 on various parameters,such as network lifetime,power consumption,packet delivery ratio(PDR),and throughput.The performance of LOA-RPL is also compared with those of RPL,fuzzy rule-based energyefficient clustering and immune-inspired routing(FEEC-IIR),and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm(RISARPL).The performance evaluation metrics used in this study are network lifetime,power consumption,PDR,and throughput.The proposed LOARPL increases network lifetime by 20%and PDR by 5%–10%compared with RPL,FEEC-IIR,and RISA-RPL.LOA-RPL is also highly energy-efficient compared with other similar routing protocols.

基于TSCH的工业无线网络流量自适应传输调度机制研究

当今LLN网络设备要满足低功耗要求的同时必须支持多种业务数据的传输,所以需要一种动态调度算法提高网络的可靠性。虽然基于IEEE 802.15.4标准的时隙信道跳变(TSCH)技术可以满足LLN的需求,然而现有的TSCH调度算法缺少灵活性。为了解决这一问题,本文提出了基于TSCH的流量感知自适应调度改进算法(Enhanced Adaptive Transmission Scheduling Mechanism,EATSM)。本文通过自相似性采样方法采集各链路流量信息,在准确获取各个邻居链路流量之后进行按权按序为每个邻居链路分配时隙数量与位置,保证传输可靠性的同时又能做到调度灵活性。通过理论分析与实验数据对比,本文提出的EATSM调度算法设计相比较于主流自适应调度算法,数据包投递率为99.57%,提高了0.26个百分点,节点运行占空比为0.34%,减少了0.88个百分点。

FDTD Analysis of Nonuniform Lossy Cascade Multiconductor Transmission Lines

A hybrid algorithm is presented for nonuniform lossy multiconductor transmission lines (MTL) connected by arbitrary linear load networks. The networks are characterized by a state-variable equation which allows a general characterization of dynamic elements in the cascade networks. The method is achieved by the finite difference-time domain (FDTD) algorithm for the MTL, and the skin effect is taken into account, the more accurate method is used to compute the skin effect. And this method is combined with the computation of the nonuniform transmission lines. Finally, several numerical examples are given, these results indicate that: the current of the lossy MTL is smaller than the lossless of the MTL; and when the load networks contain the dynamic element, the transition time of the current is longer than the MTL connected by resistance only.

Design of Wireless Multi-media Sensor Network for Precision Agriculture

To satisfy the needs of modem pre-cision agriculture, a Precision Agriculture Sensing System （PASS） is designed, which is based on wireless multimedia sensor network. Both hardware and software of PASS are tai-lored for sensing in wide farmland without human supervision. A dedicated single-chip sensor node platform is designed specially for wireless multi-media sensor network. To guarantee the bulky data transmission, a bit-map index reliable data transmission mecha-nism is proposed. And a battery-array switch-ing system is design to power the sensor node to elongate the lifetime. The effectiveness and performance of PASS have been evaluated through comprehensive experiments and large-scale real-life deployment.

低功耗有损网络RPL目标函数研究综述

低功耗有损网络(Low-power and Lossy Network, LLN)的RPL(无线传感网络)路由协议因其适用资源受限的网络而受到关注。为了研究如何通过优化目标函数(Objective Function,OF)提高资源利用率,回顾和梳理近几年相关文献中提出的设计方案,从路由度量的角度归纳了两类优化思路,并论述了不同方案的优势与不足之处。研究结果显示,尽管多数针对路由指标的优化可以改善网络质量,均衡能耗,但存在性能指标检测不全、受到环境约束、可拓展性低等问题。针对以上问题,总结了三个无线传感网络路由优化方面值得被关注的要点,期望能为该领域的研究人员提供优化思路。

LLN中移动感知的节能父节点选择算法

针对低功耗有损网络现有移动性支持路由算法中父节点切换频繁、移动检测机制使用不可靠的瞬时路由度量、未考虑链路质量对能耗影响等问题,提出一种基于剩余通信时间(Remaining Communication Time, RCT)的移动感知节能父节点选择算法。首先,为了降低父节点切换次数并节省节点能耗,构建了基于RCT和通信成本的父节点选择函数,移动节点基于该函数值选择下一父节点。其次,为了避免在移动场景下由于瞬时路由度量不可靠而导致的不必要的父节点切换,在算法的移动检测阶段提出一种基于接收信号强度指标(Indicator of Received Signal Strength,RSSI)和RCT值的移动检测机制,父节点需要结合RSSI和RCT两个值来共同判断移动节点是否需要进行父节点切换。理论分析和仿真结果表明,算法在控制开销、网络生存时间、能耗等方面的性能均得到了提升。

BE-RPL:Balanced-load and Energy-efficient RPL

Internet of Things(IoT)empowers imaginative applications and permits new services when mobile nodes are included.For IoT-enabled low-power and lossy networks(LLN),the Routing Protocol for Low-power and Lossy Networks(RPL)has become an established standard routing protocol.Mobility under standard RPL remains a difficult issue as it causes continuous path disturbance,energy loss,and increases the end-to-end delay in the network.In this unique circumstance,a Balanced-load and Energy-efficient RPL(BE-RPL)is proposed.It is a routing technique that is both energy-efficient and mobility-aware.It responds quicker to link breakage through received signal strength-based mobility monitoring and selecting a new preferred parent reactively.The proposed system also implements load balancing among stationary nodes for leaf node allocation.Static nodes with more leaf nodes are restricted from participating in the election for a new preferred parent.The performance of BE-RPL is assessed using the COOJA simulator.It improves the energy use,network control overhead,frame acknowledgment ratio,and packet delivery ratio of the network.

An efficient lossy link localization approach for wireless sensor networks

Network fault management is crucial for a wireless sensor network(WSN) to maintain a normal running state because faults(e.g., link failures) often occur. The existing lossy link localization(LLL) approach usually infers the most probable failed link set first, and then gives the fault hypothesis set. However, the inferred failed link set contains many possible failures that do not actually occur. That quantity of redundant information in the inferred set can pose a high computational burden on fault hypothesis inference, and consequently decreases the evaluation accuracy and increases the failure localization time. To address the issue, we propose the conditional information entropy based redundancy elimination(CIERE), a redundant lossy link elimination approach, which can eliminate most redundant information while reserving the important information. Specifically, we develop a probabilistically correlated failure model that can accurately reflect the correlation between link failures and model the nondeterministic fault propagation. Through several rounds of mathematical derivations, the LLL problem is transformed to a set-covering problem. A heuristic algorithm is proposed to deduce the failure hypothesis set. We compare the performance of the proposed approach with those of existing LLL methods in simulation and on a real WSN, and validate the efficiency and effectiveness of the proposed approach.

基于接收信号强度的安全RPL路由

低功率低损耗网络路由(Routing Protocol for low power and Lossy network,RPL)是无线物联网的典型路由。由于未采用集中安全机制,RPL路由易受女巫攻击。为此,提出基于接收信号强度的防御女巫攻击的RPL路由(RSSI-based against Sybil attack RPL,RSPL)。RSPL路由通过统计接收信号的强度值,并结合邻居节点的观察,估算节点可信度,进而检测攻击节点。同时,利用链路的传输期望次数和链路信任值修改RPL路由中的目标函数,进而阻止攻击节点参与路由。性能分析表明,相比同类算法,提出的RSPL路由降低了检测攻击节点的误检率,提高了数据包传递率。

基于6LoWPAN的物联网寻址策略研究

在6LoWPAN(IPv6 over Low-power Wireless Personal Area Network)的基础上,该文提出应用于物联网的寻址策略,实现基于IEEE 802.15.4协议的底层异构网络与互联网的实时通信。寻址策略包括IPv6地址自动配置和报头压缩。采用的分层地址自动配置策略,首先在底层网络内部允许节点使用16位短地址导出的链路本地地址进行数据分组传输,该链路本地地址需通过执行基于分簇的重复地址检测机制保证唯一性;其次,每个底层网络中的Sink节点通过上层IP路由器获取全球路由前缀,并与接口标识符相结合,形成Sink节点的全球地址,实现底层网络与互联网的数据交换。同时,通过在报头压缩编码中植入链路本地地址和全球地址控制位,提出了一种适用于物联网应用的报头压缩方案IIPHC(IoTs IPv6 Header Compression)。如果地址类型为链路本地地址,则采用简单灵活的IIPHC1方案,如果地址类型为全球地址,则采用相对复杂但有效的IIPHC2方案。仿真及测试结果表明,基于6LoWPAN的物联网寻址策略在网络开销、时延、吞吐量、能耗等性能方面存在一定的优越性。

集中式网络拥塞控制的高效RPL路由协议

针对低功耗有损网络中采用博弈论的网络拥塞控制(game theory based network congestion control protocol,GTNCC)路由算法在路由构建过程中仅仅考虑无线链路质量不能使网络拓扑最优,以及在拥塞控制过程中由拥塞节点的子节点判断是否切换父节点不能快速高效地缓解网络拥塞等问题,提出一种基于多维度量结合的集中式网络拥塞控制(centralized network congestion control based on multi-metrics combination,CNCCMC)路由协议。首先,为了降低网络拥塞发生的概率,CNCCMC路由协议综合考虑了节点剩余能量、缓存占用率、无线链路质量和中继节点当前子节点个数等多维度量完成路由构建;其次,当检测到网络拥塞时,CNCCMC路由协议依据网络拥塞节点进行流量分析和判断的结果采取集中式的方式控制其子节点的切换;最后,在网络拥塞缓解过程中,提出一种"乒乓效应"避免机制。理论分析和仿真结果表明,与GTNCC路由算法相比,CNCCMC路由协议在降低网络拥塞发生的概率、延长网络平均生存寿命和提高网络吞吐量等方面的性能得到了有效提升。

LLN中基于环路避免的高效路由修复算法

针对低功耗有损网络(low power and lossy networks,LLN)中现有路由修复算法存在控制开销冗余、修复时延较大和路由环路等问题,提出一种LLN中基于环路避免的高效路由修复算法(highly-efficient loop-free based repair routing protocol for LLN,HLR-RPL)。该算法提出了3个优化思路:首先,采用一种修正后的面向目的地的有向无循环图(destination oriented directed acyclic graph,DODAG)信息请求消息(DODAG information solicitation amend,DIS-A),使得链路中断通告过程和寻路过程同时进行;其次,提出一种减少控制消息回复机制,避免所有接收到DIS-A消息的节点均回复DODAG信息对象消息;最后,提出一种链路中断节点的子节点切换机制,从而优化了网络拓扑。仿真结果表明,HLR-RPL算法在控制开销和路由修复时延等性能方面优于现有的路由修复算法,且能够彻底避免路由环路的产生。