面向物联网应用的能效感知路由

能量采集被认为是基于大型无线传感网络(WSNs)应用的物联网(IoT)的关键技术。为此,针对基于WSNs的IoT应用,提出能量采集感知路由(EHARA)。EHARA路由引用延长退避机制,并结合能量预测策略定义链路成本变量。然后,再利用链路成本变量建立路由表,进而选择传输数据包的最佳转发路由。仿真结果表明,相比于随机性最小路径恢复时间(R-MPRT)路由,提出的EHARA路由极大地提高了网络寿命和能量效率。     

多跳无线传感器网络的高效中继节点快速选择算法

针对多跳无线传感器网络数据收集协议中继转发节点选择算法效率不高的问题,提出了一种能量有效的中继节点快速选择 (EERNFS)算法.EERNFS算法利用分时共享信道的方法维护网络同步和更新节点的邻居信息,使节点在每个网络侦听/睡眠周期依赖一定的概率同步激活唤醒,确保了网络节点瞬时连通度的稳定和一致;基于网络节点的地理优先级、节点价值和链路质量的分布式估计,EERNFS算法采用竞争的方法选择中继转发节点, 使用乘性增加时间窗口的方法,分解候选中继节点间的竞争.理论分析和模拟实验结果表明,EERNFS算法在能效、数据传递的平均时延、分组到达率等网络性能指标上显著优于FFS和GeRaF算法,极大地延长了网络的寿命.     

一种环境感知的无线Mesh网络自适应QoS路径选择算法

本文针对如何改善无线多跳Mesh网络的服务质量,满足无线多媒体业务对数据传输的带宽、时延、抖动的要求等问题,研究了一种基于无线信道状态和链路质量统计的MAC层最大重传次数的自适应调整算法。该算法通过对无线Mesh网络的无线信道环境的动态感知,利用分层判断法区分无线分组丢失的主要原因是无线差错还是网络拥塞导致,实时调整MAC层的最佳重传次数,降低无线网络中的分组冲突概率。基于链路状态信息的统计和最大重传策略,提出了一种启发式的基于环境感知的QoS路由优化机制HEAOR。该算法通过动态感知底层链路状态信息,利用灰色关联分析法自适应选择最优路径,在不增加系统复杂度的基础上,减少链路误判概率,提高传输效率。NS2仿真结果表明,HEAOR算法能有效减少重路由次数,降低链路失效概率,提高网络的平均吞吐率。本文提出的方法不仅能够优化MAC层的重传,而且通过发现跨层设计的优化参数实现对路径的优化选择。      

双向协作OFDM系统中基于能量定价的功率分配与中继选择算法

该文研究双向两跳协作多中继正交频分复用(OFDM)系统的网络寿命优化问题。由于网络寿命最大化的问题无法直接求解,该文提出一种基于对各节点能量定价的次优算法,即将各子载波的功率分配,中继及源节点选择进行分步优化。首先利用拉格朗日法求解两个方向上的源与各中继节点配对时的最优功率分配,使得网络在满足一定吞吐量和发送功率限制的前提下,消耗能量总价值最小;然后在所有可能的配对中选择每个方向最优的中继节点;最后选择损耗能量价值较小的数据流方向。分别考虑了源与目的节点间有无直接链路两种场景,在有直接链路场景下分析了最大比值合并(MRC)和选择合并(SC)两种分集方式对功率优化的影响。仿真结果表明,该文提出算法的网络寿命比已有算法有显著提高。     

一种基于能量感知的节点独立多径路由协议

在综合最小电池代价路由和最小最大电池代价路由优点的基础上,提出一种新的能量感知路由策略,从理论上推导最佳路径条数,并在DSDV路由协议的基础上设计基于该策略的独立多径路由协议EA-MDSDV。仿真结果表明,相比DSDV协议,EA-MDSDV可以较大地提高数据包的递交率,提高网络可靠性;相比非能量保护下的多径路由协议,EA-MDSDV可以保护低能节点的电池能量,延长网络寿命。     

无人机辅助车联网的网络传输链路优化

无人机(UAV)通信技术的快速发展与智能车联网应用需求的极速增长促进了无人机辅助车联网系统的产生与发展。在无人机辅助车联网系统中,如何节省能量的同时最大化系统性能对于能量有限的节点十分重要。基于此,本文主要考虑无人机辅助车联网通信过程中如何选择最优的通信网络链路,从而最大化能量效率的问题。首先建立通信网络链路选择问题为混合整数规划问题,然后提出基于能量效率最大化的网络传输链路优化算法获得最优的传输链路及对应的能量分配,最后通过数值实验仿真验证了所提算法的有效性。     

无线传感器网络基于多元簇首的分簇数据收集算法

为了提高数据收集可靠性和延长网络生命周期,该文提出基于多元簇首的分簇数据收集算法。算法将网络划分为大小相等的栅格,由每个栅格中的节点各自构成一个簇,根据节点失效概率从每个栅格中选出多个簇首,并由同一栅格中的多个簇首协作完成栅格中节点的数据收集任务。此外,算法还采取了一些降低能量开销的措施。仿真实验结果表明,与现有相关算法相比,该算法具有较高的数据收集可靠性,并能够显著延长网络生命周期。     

基于冗余筛选管控评估机制的移动传感网超宽带稳定传输算法

为了优化WSN网络的数据传输特性,设计了基于冗余筛选管控评估的移动WSN超宽带稳定传输算法。基于冗余传输调度机制对区域予以初次分割,通过能量评估方式快速达到区域聚类稳定生存效果,结合构建区域节点能量阈值的方法提高聚类冗余效率,以降低超宽带条件下的节点受限概率。采用区域边界控制方式,通过优化骨干节点剩余能量的方式增强骨干节点工作效率,降低因骨干节点而导致的区域传输抖动,确保中继传输节点性能最佳,以降低链路抖动现象。通过骨干节点能力对传输节点予以甄选,从而提升网络链路传输能力,进一步降低抖动现象对传输性能带来的不利影响。仿真实验表明,所提算法具有更低的网络链路累计抖动频次及更好的网络传输带宽。     

基于接收信噪比和网络寿命的最优中继选择

为了增大网络寿命,降低误符号率,优化无直传链路协作通信系统的性能,本文提出基于接收信噪比和网络寿命的最优中继选择算法。由于网络寿命的问题无法直接求解,将其转化为中继节点剩余能量与目的节点达到接收信噪比门限时发射功率的比值。首先计算各个中继在目的节点的接收信噪比,将大于信噪比门限加入候选中继,然后依次计算候选中继的联合优化函数值并排序,值最大者即为最优中继。理论推导了系统误符号率的上下界,仿真表明理论值与仿真值较为吻合,验证了系统在保证较低误符号率的基础上延长了网络寿命。     

弹性光网络中基于安全性感知的差异化虚拟光网络的映射策略

针对虚拟环境下底层网络中光纤的概率性故障,传统的100%保护至少需要配置一条保护路径,造成资源冗余度高和虚拟网络请求接受率低的问题,该文提出一种基于安全性感知的差异化虚拟光网络的映射(SA-DVNM)策略,在链路发生故障时为差异化虚拟网络请求提供安全保证。在SA-DVNM策略中,设计了一个综合考虑物理节点对之间跳数和相邻带宽大小的节点权重式避免链路映射过长,并提出路径频谱资源使用均衡的链路映射机制,最小化瓶颈链路的数量。当单路径传输失败时,SA-DVNM策略设计允许路径分割的资源分配机制,为保障时延敏感业务的安全性,SA-DVNM策略在路由选择中设计了基于时延差优化的多路径路由频谱分配方法。仿真结果表明该文所提策略在概率故障环境中能够降低带宽阻塞率,提高频谱资源利用率和虚拟光网络接受率。     

DABPR: a large-scale internet of things-based data aggregation back pressure routing for disaster management

In this paper, we propose a data aggregation back pressure routing (DABPR) scheme, which aims to simultaneously aggregate overlapping routes for efficient data transmission and prolong the lifetime of the network. The DABPR routing algorithm is structured into five phases in which event data is sent from the event areas to the sink nodes. These include cluster-head selection, maximization of event detection reliability, data aggregation, scheduling, and route selection with multi attributes decision making metrics phases. The scheme performs data aggregation on redundant data at relay nodes in order to decrease both the size and rate of message exchanges to minimize communication overhead and energy consumption. The proposed scheme is assessed in terms of packet delivery, network lifetime, ratio, energy consumption, and throughput, and compared with two other well-known protocols, namely “information-fusion-based role assignment (InFRA)” and “data routing for in-network aggregation (DRINA)”, which intrinsically are cluster and tree-based routing schemes designed to improve data aggregation efficiency by maximizing the overlapping routes. Meticulous analysis of the simulated data showed that DABPR achieved overall superior proficiency and more reliable performance in all the evaluated performance metrics, above the others. The proposed DABPR routing scheme outperformed its counterparts in the average energy consumption metric by 64.78% and 51.41%, packet delivery ratio by 28.76% and 16.89% and network lifetime by 42.72% and 20.76% compared with InFRA and DRINA, respectively.

     

Topology control in the presence of jammers for wireless sensor networks

In this paper, the problem of ensuring packet delivery ratio and high network lifetime in wireless sensor networks in the presence of single or multiple jammers is studied using single‐leader‐multiple‐followers Stackelberg game theory. A topology control scheme is proposed, in which the sink node, which acts as the leader, identifies the set of jamming affected nodes. On the other hand, the sensor nodes, which act as followers, need to decide an optimum transmission power level, while ensuring an optimal set of neighbor nodes covered. A scheme, named TC‐JAM, for ensuring packet delivery ratio, while avoiding jammers and increasing network lifetime in wireless sensor networks, is proposed. In existing literatures, the sensor nodes are envisioned to be equipped with multiple interfaces, while having access for multiple channels. However, in TC‐JAM, the sensor nodes have simple hardware with single interface for communication, ie, the sensor nodes have single channel for communication. Additionally, in the proposed scheme, TC‐JAM, each sensor node has a provision to vary its transmission power according to the chosen strategies. Using TC‐JAM, the energy consumption of the overall network reduces by up to 62%, and the network lifetime increases by 56% to 73%.     

Load balancing clustering and routing for IoT-enabled wireless sensor networks

Internet of things (IoT) devices are equipped with a number of interconnected sensor nodes that relies on ubiquitous connectivity between sensor devices to optimize information automation processes. Because of the extensive deployments in adverse areas and unsupervised nature of wireless sensor networks (WSNs), energy efficiency is a significant aim in these networks. Network survival time can be extended by optimizing its energy consumption. It has been a complex struggle for researchers to develop energy-efficient routing protocols in the field of WSNs. Energy consumption, path reliability and Quality of Service (QoS) in WSNs became important factors to be focused on enforcing an efficient routing strategy. A hybrid optimization technique presented in this paper is a combination of fuzzy c-means and Grey Wolf optimization (GWO) techniques for clustering. The proposed scheme was evaluated on different parameters such as total energy consumed, packet delivery ratio, packet drop rate, throughput, delay, remaining energy and total network lifetime. According to the results of the simulation, the proposed scheme improves energy efficiency and throughput by about 30% and packet delivery ratio and latency by about 10%, compared with existing protocols such as Chemical Reaction Approach based Cluster Formation (CHRA), Hybrid Optimal Based Cluster Formation (HOBCF), GWO-based clustering (GWO-C) and Cat Swarm Optimization based Energy-Efficient Reliable sectoring Scheme with prediction algorithms (P_CSO_EERSS). The study concludes that the protocol suitable for creating IoT monitoring system network lifetime is an important criteria.     

The Impact of Deployment Pattern and Routing Scheme on the Lifetime in Multi-Sink Wireless Sensor Network

Extensive use of sensor and actuator networks in many real-life applications introduced several new performance metrics at the node and network level. Since wireless sensor nodes have significant battery constraints, therefore, energy efficiency, as well as network lifetime, are among the most significant performance metrics to measure the effectiveness of given network architecture. This work investigates the performance of an event-based data delivery model using a multipath routing scheme for a wireless sensor network with multiple sink nodes. This routing algorithm follows a sink initiated route discovery process with the location information of the source nodes already known to the sink nodes. It also considers communication link costs before making decisions for packet forwarding. Carried out simulation compares the network performance of a wireless sensor network with a single sink, dual sink, and multi sink networking approaches. Based on a series of simulation experiments, the lifetime aware multipath routing approach is found appropriate for increasing the lifetime of sensor nodes significantly when compared to other similar routing schemes. However, energy-efficient packet forwarding is a major concern of this work; other network performance metrics like delay, average packet latency, and packet delivery ratio are also taken into the account.

     

IGBDD: Intelligent Grid Based Data Dissemination Protocol for Mobile Sink in Wireless Sensor Networks

Lifetime and energy efficiency are important factors in the design of wireless sensor network. A critical issue during data collection is the formation of energy holes near the sink. Sensors which are located near the sink have to participate in relaying data on behalf of other sensors and thus their energy will be depleted very quickly. Mobile sink movement yields the significant performance gained by decreasing the amount of energy consumption. In this paper, we propose an Intelligent Grid Based Data Disseminating protocol for mobile sink in wireless sensor networks. We have utilized a virtual grid as the protocol’s substructure. In our proposed method, cell heads (CHs) will be selected based on the locations of virtual cross points (CPs) and CPs selection is needless to transfer any required data between neighbor nodes. We have optimized CPs selection using linear programming technique in order to increase network lifetime. By selecting the CHs based on our proposed algorithm, data will be disseminated toward the sink. Our data dissemination protocol is simple and has low overhead to construct and maintain. Also, we have presented a new method for sink location update which leads to the least cost in data transfer. Simulation results illustrate that by utilizing hierarchical functionality and selecting appropriate CPs and consequently selecting CHs, energy consumption will be decreased in comparison with other presented methods which directly lead to network lifetime increment. Also by determining an optimal cell size, packet delivery rate will be improved noticeably.     

DEC-MAC: delay- and energy-aware cooperative medium access control protocol for wireless sensor networks

This paper deals with two critical issues in wireless sensor networks: reducing the end-to-end packet delivery delay and increasing the network lifetime through the use of cooperative communications. Here, we propose a delay- and energy-aware cooperative medium access control (DEC-MAC) protocol, which trades off between the packet delivery delay and a node’s energy consumption while selecting a cooperative relay node. DEC-MAC attempts to balance the energy consumption of the sensor nodes by taking into account a node’s residual energy as part of the relay selection metric, thus increasing the network’s lifetime. The relay selection algorithm exploits the process of elimination and the complementary cumulative distribution function for determining the most optimal relay within the shortest time period. Our numerical analysis demonstrates that the DEC-MAC protocol is able to determine the optimal relay in no more than three mini slots. Our simulation results show that the DEC-MAC protocol improves the end-to-end packet delivery latency and the network lifetime significantly compared to the state-of-the-art protocols, LC-MAC and CoopMAC.     

Dynamic region‐based mobile multicast

Traditional mobile multicast schemes have higher multicast tree reconfiguration cost or multicast packet delivery cost. Two costs are very critical because the former affects the service disruption time during handoff while the latter affects the packet delivery delay. Although the range‐based mobile multicast (RBMoM) scheme and its similar schemes offer the trade‐off between two costs to some extent, most of them do not determine the size of service region, which is critical to the network performance. Hence, we propose a dynamic region‐based mobile multicast (DRBMoM) to dynamically determine the optimal service region for reducing the multicast tree reconfiguration and multicast packet delivery costs. DRBMoM provides two versions: (i) the per‐user version, named DRBMoM‐U, and (ii) the aggregate‐users version, named DRBMoM‐A. Two versions have different applicability, which are the complementary technologies for pursuing efficient mobile multicast. Though having different data information and operations, two versions have the same method for finding the optimal service region. To that aim, DRBMoM models the users' mobility with arbitrary movement directional probabilities in 2‐D mesh network using Markov Chain, and predicts the behaviors of foreign agents' (FAs') joining in a multicast group. DRBMoM derives a cost function to formulate the average multicast tree reconfiguration cost and the average multicast packet delivery cost, which is a function of service region. DRBMoM finds the optimal service region that can minimize the cost function. The simulation tests some key parameters of DRBMoM. In addition, the simulation and numerical analyses show the cost in DRBMoM is about 22∼50% of that in RBMoM. At last, the applicability and computational complexity of DRBMoM and its similar scheme are analyzed. Copyright © 2010 John Wiley & Sons, Ltd.     

Packet‐level‐based traffic aggregation to optimize NDN content delivery

In recent years, named data networking (NDN) has been accepted as the most popular future paradigm and attracted much attention, of which the routing model contains interest forwarding and content delivery. However, interest forwarding is far from the bottleneck of routing optimization; instead, the study on content delivery can greatly promote routing performance. Although many proposals on content delivery have been investigated, they have not considered packet‐level caching and deep traffic aggregation, which goes against the performance optimization of content delivery. In this paper, we propose a packet‐level‐based traffic aggregation (PLTA) scheme to optimize NDN content delivery. At first, the packet format is devised, and data plane development kit (DPDK) is used to ensure same size for each packet. Then, the whole delivery scheme with traffic aggregation consideration is presented. The simulation is driven by the real YouTube dataset over Deltacom, NSFNET, and CERNET topologies, and the experimental results demonstrate that the proposed PLTA has better delivery performance than three baselines in terms of cache hit ratio, delivery delay, network load, and energy efficiency.     

Betweenness centrality based connectivity aware routing algorithm for prolonging network lifetime in wireless sensor networks

Network lifetime is the key design parameter for wireless sensor network protocols. In recent years, based on energy efficient routing techniques numerous methods have been proposed for enhancing network lifetime. These methods have mainly considered residual energy, number of hops and communication cost as route selection metrics. This paper introduces a method for further improvement in the network lifetime by considering network connectivity along with energy efficiency for the selection of data transmission routes. The network lifetime is enhanced by preserving highly connected nodes at initial rounds of data communication to ensure network connectivity during later rounds. Bassed on the above mentioned concept, a connectivity aware routing algorithm: CARA has been proposed. In the proposed algorithm, connectivity factor of a node is calculated on the basis of Betweenness centrality of a node and energy efficient routes are found by using fuzzy logic and ant colony optimization. The simulation results show that the proposed algorithm CARA performs better than other related state-of-the-art energy efficient routing algorithms viz. FML, EEABR and FACOR in terms of network lifetime, connectivity, energy dissipation, load balancing and packet delivery ratio.     

Mobility-Based Backbone Formation in Wireless Mobile Ad-hoc Networks

In this paper, the well-known network backbone formation problem is modeled as the stochastic min-degree constrained minimum spanning tree (md-MST) problem, where the link duration is associated with the edge weight. Then, a decentralized learning automata-based algorithm is proposed to form the most stable backbone of the wireless mobile ad hoc network (MANET) by finding a near optimal solution to the stochastic md-MST problem of the network topology graph. The proposed method significantly decreases the network overhead and shortens the network delay by reducing the number of intermediate forwarding hosts. It also extends the backbone lifetime by selection of the links with the maximum expected duration. The convergence of the proposed algorithm to the most stable network backbone is proven on the basis of the Martingale theorem. Several simulation experiments are conducted to investigate the efficiency of the proposed backbone formation algorithm. Numerical results show the superiority of the proposed method over the existing methods in terms of the backbone lifetime, end-to-end delay, backbone size, packet delivery ratio, and control message overhead.