无线传感器网络模糊逻辑分簇路由协议

在无线传感器网络（Wireless Sensor Network,WSN）中,LEACH协议通过概率模型来选举簇头,由于没有考虑到传感器节点的分布情况和能量剩余等信息,可能会使得部分节点过早死亡.针对这一问题,提出基于模糊逻辑的分簇路由协议（DFLCP）.在预选簇头阶段,根据节点剩余能量等信息利用模糊逻辑计算出节点的竞争半径,使得簇头分布相对均匀;在簇头选举阶段,通过模糊逻辑确定节点成为簇头的概率.仿真结果表明：DFLCP协议可有效控制簇头节点的分布密度和簇的半径,均衡网络负载,延长节点平均生存时间.     

A Novel Heterogeneous Clustering Protocol for Lifetime Maximization of Wireless Sensor Network

The network lifetime of Wireless Sensor Network (WSN) is one of the most challenging issues for any network protocol. The nodes in the network are densely deployed and are provided with limited power supply. The routing strategy is treated as an effective solution to improve the lifetime of the network. The cluster based routing techniques are used in the WSN to enhance the network lifespan and to minimize the energy consumption of the network. In this paper, an energy efficient heterogeneous clustering protocol for the enhancement of the network lifetime is proposed. The proposed protocol uses the sensor energy for the clustering process in a well-organized manner to maximize the lifetime of network. The MATLAB simulator is used for implementing the clustering model of proposed protocol and for measuring the effectiveness of the proposed technique the comparison is performed with the various existing approaches such as Stability Election Protocol, Distributed Energy Efficient Clustering and Adaptive Threshold Energy Efficient cross layer based Routing.

     

Performance enhancement routing protocols for heterogeneous WSNs

One of the main constraints in wireless sensor networks (WSNs) is the energy consumption. To mitigate this limitation and to prolong network life‐time, stability period and throughput, this paper proposes new cluster‐heads selection protocols, they based on Stable Election Protocol (SEP) and Distributed Energy‐Efficient Clustering (DEEC). We first propose Enhanced Zonal‐SEP (EZSEP) and Zonal Threshold‐DEEC (ZTDEEC) protocols, the proposed protocols are based on dividing the network field into certain zones, this will improve the connectivity of the far normal nodes with the base station (BS). Several evaluation metrics are used to compare between the proposed protocols and the conventional ZSEP and TDEEC protocols such as: network stability, instability period, life‐time and throughput. Considering the same total initial energy, the obtained results show that the proposed EZSEP slightly outperforms the conventional ZSEP in terms of network stability, instability period and life‐time, it achieves enormous improvements in terms of throughput as more nodes can transmit direct to BS. On the other hand, the proposed ZTDEEC provides huge improvements in terms of all the evaluation metrics mentioned above. To further improve the network life‐time and network throughput, we propose Threshold‐based EZSEP (TE‐ZSEP) and Enhanced‐ZTDEEC (EZ‐TDEEC) protocols, in these two new protocols we redefine the threshold formula used in EZSEP and ZTDEEC to consider both weighted energy and weighted distance parameters. By combining the idea of dividing the network field into certain zones and the new threshold formula, the proposed TE‐ZSEP and EZ‐TDEEC protocols can effectively improve the energy consumption in heterogeneous WSN and prolong its life‐time as proved by the obtained results.     

基于多级能量阈值的簇头更新策略

簇路由是节省无线传感网络(WSNs)能量的有效策略。簇头的选择是簇路由的关键。然而,传统的簇路由是采用固定周期更新簇头,并没有考虑到簇头的剩余能量。为此,针对稳定簇头选择协议(SEP)进行改进,提出基于多级能量阈值的簇头更新策略,记为I-SEP。I-SEP路由考虑三类节点,这三类节点的初始能量不同。并针对三类节点的能量以及比例,计算它们成为簇头的概率和阈值。同时,每轮计算簇头的剩余能量,只有簇头剩余能量小于预定的阈值,才进行簇头更新,否则原来的簇头仍作为簇头,进而减少了更换簇头所带来的能耗。仿真结果表明,相比于SEP,提出的I-SEP路由有效地降低了能耗,延长了网络寿命。     

EMRP: Evolutionary-based multi-hop routing protocol for wireless body area networks

Routing is one of the main challenges in designing wireless body area networks. Existing routing protocols exhibit some drawbacks for practical networks: First, insufficient criteria (e.g., only energy or distance) are used to select the forwarder nodes. Second, controllable parameters of the protocol are determined manually and no automatic tuning is used. Third, the protocol is not adjusted and optimized based on application specifications. In order to overcome the mentioned drawbacks, an adaptive Evolutionary Multi-hop Routing Protocol (named EMRP) is proposed in this paper. We introduce a multi-objective function based on energy level, distance, estimated path loss and estimated energy consumption for selecting optimal forwarder nodes. The proposed objective function aims to select forwarder nodes with high energy, low communication distance, low path loss and low energy consumption. The controllable parameters of EMRP can be adaptively optimized based on application specifications via genetic algorithm. Simulation results show a significant improvement than the existing technologies in terms of lifetime, path loss, throughput, and energy consumption.     

FUCA: Fuzzy‐based unequal clustering algorithm to prolong the lifetime of wireless sensor networks

Wireless sensor network comprises billions of nodes that work collaboratively, gather data, and transmit to the sink. “Energy hole” or “hotspot” problem is a phenomenon in which nodes near to the sink die prematurely, which causes the network partition. This is because of the imbalance of the consumption of energy by the nodes in wireless sensor networks. This decreases the network's lifetime. Unequal clustering is a technique to cope up with this issue. In this paper, an algorithm, “fuzzy‐based unequal clustering algorithm,” is proposed to prolong the lifetime of the network. This protocol forms unequal clusters. This is to balance the energy consumption. Cluster head selection is done through fuzzy logic approach. Input variables are the distance to base station, residual energy, and density. Competition radius and rank are the two output fuzzy variables. Mamdani method is employed for fuzzy inference. The protocol is compared with well‐known algorithms, like low‐energy adaptive clustering hierarchy, energy‐aware unequal clustering fuzzy, multi‐objective fuzzy clustering algorithm, and fuzzy‐based unequal clustering under different network scenarios. In all the scenarios, the proposed protocol performs better. It extends the lifetime of the network as compared with its counterparts.     

Low end‐to‐end delay fuzzy networking protocol for mobile wireless sensing

Because of the practical limitations of the energy and processing capabilities, the deployment of many Wireless Sensor Networks (WSN) is facing two main challenges of increasing network lifetime and reducing End to End Delay (EED) which become critical when the nodes are mobile and use non‐rechargeable energy sources. One way to help to extend network lifetime is using fuzzy logic in a form of artificial intelligence. To this end we propose a new routing protocol for using mobile WSNs, which holds the nodes in an equal level of energy and decreases energy dissipation of the network. An optimum path is selected based on the cost of each node to increase network lifetime. In order to lessen EED, we also attempt to design a novel zoning‐scheme for the network area. In this scheme, zonation is dynamic and works based on the Data Link (DL) position. The simulation result shows a significant improvement in lifetime and EED by proposed protocol compared with existing protocols. Copyright © 2016 John Wiley & Sons, Ltd.     

A New Method to Find a High Reliable Route in IoT by Using Reinforcement Learning and Fuzzy Logic

Recently, Internet is moving quickly toward the interaction of objects, computing devices, sensors, and which are usually indicated as the Internet of things (IoT). The main monitoring infrastructure of IoT systems main monitoring infrastructure of IoT systems is wireless sensor networks. A wireless sensor network is composed of a large number of sensor nodes. Each sensor node has sensing, computing, and wireless communication capability. The sensor nodes send the data to a sink or a base station by using wireless transmission techniques However, sensor network systems require suitable routing structure to optimizing the lifetime. For providing reasonable energy consumption and optimizing the lifetime of WSNs, novel, efficient and economical schemes should be developed. In this paper, for enhancing network lifetime, a novel energy-efficient mechanism is proposed based on fuzzy logic and reinforcement learning. The fuzzy logic system and reinforcement learning is based on the remained energies of the nodes on the routes, the available bandwidth and the distance to the sink. This study also compares the performance of the proposed method with the fuzzy logic method and IEEE 802.15.4 protocol. The simulations of the proposed method which were carried out by OPNET (Optimum Network performance) indicated that the proposed method performed better than other protocols such as fuzzy logic and IEEE802.15.4 in terms of power consumption and network lifetime.

     

NSMTSEP: Neighbor Supported Modified Threshold Sensitive Stable Election Protocol for WSN

The way by which we select a cluster head critically affects the overall futuristic structure in the network. Cluster head wastes more energy for long distance transmission in the network. Sometimes, due to incomplete information of neighbor nodes, a proper cluster head is not selected and deplete energy quickly. This paper, presents a clustering protocol (NSMTSEP) based on neighbor support. Support of the neighbor node is used to calculate the threshold. Neighbor nodes are labeled based on dynamically changing parameters. The total energetic value of different nodes, cluster heads degree, the summative information of distances of member nodes, etc. is dynamically changing parameters. The label of a node is used to calculate the weight of that particular node. Weight is finally used to formulate equations for threshold calculation. The fundamental target is to increase the stable time, throughput, and network lifespan by reducing the cost incurred in intra-cluster communication. Neighbor supported labeled method is suitable for increasing longevity in the network. NSMTSEP upgrades stability by 8.6%, 36.9% as compared to enhanced threshold sensitive stable election protocol (ETSSEP) and threshold sensitive stable election protocol (TSEP). NSMTSEP is three times more stable than stable election protocol (SEP) and low energy adaptive clustering hierarchy protocol (LEACH). Improvement in the lifespan of NSMTSEP is recorded by 11.98%, 3.43% and 24.9% over ETSSEP, TSEP, and LEACH respectively whereas more than twice in comparison with SEP. The throughput enhanced by 32.2% and 55.7% respectively over TSEP and LEACH, twice over SEP and ETSSEP respectively.

     

Genetic spider monkey‐based routing protocol to increase the lifetime of the network and energy management in WSN

Wireless sensor networks (WSNs) include large distributed nodes in the sensing field. However, the sensor nodes may die due to energy deficiency as they are situated in a hostile environment. Therefore, an energy‐efficient WSN routing protocol is necessary in order to better accommodate the various environmental conditions. In this paper, we have proposed a new Energy‐Efficient Genetic Spider Monkey‐based Routing Protocol (EGSMRP) to improve the stability and lifetime of sensor nodes. The operation of EGSMRP is classified into two stages: (i) setup phase and (ii) steady‐state phase. In the setup phase, GSMO‐based cluster head selection procedure is done. In this phase, the base station utilizes the GSMO algorithm as a device to generate energy‐efficient clusters. Followed with this, the steady‐state phase solves the load balancing issue by utilizing the intracluster data broadcast and dual‐hop intercluster broadcasting algorithm. Thereby, the proposed EGSMRP protocol has shown the energy‐based opportunistic broadcasting with reduced control overhead. Simulation is performed in various conditions to evaluate the effectiveness of the proposed EGSMRP protocol using different metrics such as throughput, control overhead, energy consumption, end‐to‐end delay, and network lifetime. From the simulation results, it was evident that EGSMRP has achieved a higher performance compared to other traditional approaches such as EBAR, MCTRP, IEEMARP, HMCEER, and EFTETRP.     

Modulated relay based stable election protocol for large-scale wireless sensor networks

Internet of things (IoT) applications based on wireless sensor networks (WSNs) have recently gained vast momentum. These applications vary from health care, smart cities, and military applications to environmental monitoring and disaster prevention. As a result, energy consumption and network lifetime have become the most critical research area of WSNs. Through energy-efficient routing protocols, it is possible to reduce energy consumption and extend the network lifetime for WSNs. Using hybrid routing protocols that incorporate multiple transmission methods is an effective way to improve network performance. This paper proposes modulated R-SEP (MR-SEP) for large-scale WSN-based IoT applications. MR-SEP is based on the well-known stable election protocol (SEP). MR-SEP defines three initial energy levels for the nodes to improve the network energy distribution and establishes multi-hop communication between the cluster heads (CHs) and the base station (BS) through relay nodes (RNs) to reduce the energy consumption of the nodes to reach the BS. In addition, MR-SEP reduces the replacement frequency of CHs, which helps increase network lifetime and decrease power consumption. Simulation results show that MR-SEP outperforms SEP, LEACH, and DEEC protocols by 70.2%, 71.58%, and 74.3%, respectively, in terms of lifetime and by 86.53%, 86.68%, and 86.93% in terms of throughput.     

A fuzzy decision scheme for relay selection in cooperative wireless sensor network

In energy‐constrained military wireless sensor networks, minimizing the bit error rate (BER) with little compromise on network lifetime is one of the most challenging issues. This paper presents a new relay selection based on fuzzy logic (RSFL) scheme which provides balance between these parameters. The proposed scheme considers node's residual energy and path loss of the relay‐destination link as the input parameters for the selection of the relay node. The relay node selection by fuzzy logic is based on prioritizing higher residual energy and minimum path loss. To evaluate the performance on wireless sensor network, we compare the proposed scheme with the three existing relay selection strategies, ie, random, maximum residual energy based relay selection (MaxRes), and minimum energy consumption based relay selection (MinEnCon). The simulation results of the proposed scheme in terms of network lifetime, BER, Network Survivability Index (NSI), and average energy of network nodes have been presented and compared with different relay selection schemes. The simulation results show that the proposed RSFL scheme has the lowest BER, moderate network lifetime, average energy, and NSI.     

Intrusion Detection in Mobile Sensor Networks: A Case Study for Different Intrusion Paths

Optimization of energy consumption in the batteries of a sensor node plays an essential role in wireless Sensor networks (WSNs). The longevity of sensor nodes depends on efficiency of energy utilization in batteries. Energy is consumed by sensor nodes in WSNs to perform three significant functions namely data sensing, transmitting and relaying. The battery energy in WSNs depletes mainly due to sampling rate and transmission rate. In the present work, the most important parameters affecting the longevity of network are indentified by modeling the energy consumption. The parameters are expressed as a fuzzy membership function of variables affecting the life time of network. Fuzzy logic is used at multiple levels to optimize the parameters. Network simulator-2 is used for experimentation purpose. The proposed work is also compared with the existing routing protocols like Enhanced Low Duty Cycle, Threshold Sensitive Energy Efficient Sensor Network and Distributed Energy Efficient Adaptive Clustering Protocol with Data Gathering. The proposed solution is found to be more energy efficient and hence ensures longer network lifetime.

     

Stable-Aware Evolutionary Routing Protocol for Wireless Sensor Networks

In real life scenario for wireless sensor networks (WSNs), energy heterogeneity among the sensor nodes due to uneven terrain, connectivity failure, and packet dropping is a crucial factor that triggered the race for developing robust and reliable routing protocols. Prolonging the time interval before the death of the first sensor node, viz. the stability period, is critical for many applications where the feedback from the WSN must be reliable. Although Low Energy Adaptive Clustering Hierarchy (LEACH) and LEACH-like protocols are fundamental and popular clustering protocols to manage the system’s energy and thus to prolong the lifespan of the network, they assume a near to a perfect energy homogeneous system where a node failure, drainage and re-energizing are typically not considered. More recent protocols like Stable Election Protocol (SEP) considers the reverse, i.e., energy heterogeneity, and properly utilizes the extra energy to guarantee a stable and reliable performance of the network system. While paradigms of computational intelligence such as evolutionary algorithms (EAs) have attracted significant attention in recent years to address various WSN’s challenges such as nodes deployment and localization, data fusion and aggregation, security and routing, they did not (to the best of our knowledge) explore the possibility of maintaining heterogeneous-aware energy consumption to guarantee a reliable and robust routing protocol design. By this, a new protocol named stable-aware evolutionary routing protocol (SAERP), is proposed in this paper to ensure maximum stability and minimum instability periods for both homogeneous/heterogeneous WSNs. SAERP introduces an evolutionary modeling, where the cluster head election probability becomes more efficient, to well maintain balanced energy consumption in both energy homogeneous and heterogeneous settings. The performance of SAERP over simulation for 90 WSNs is evaluated and compared to well known LEACH and SEP protocols. We found that SAERP is more robust and always ensures longer stability period and shorter instability period.     

A fuzzy multicriteria decision‐making‐based CH selection and hybrid routing protocol for WSN

One of the famous approaches to decision making is named as multicriteria decision making (MCDM). In order to solve the MCDM issues, a better way is provided by the fuzzy logic. Expendability, cost, maintenance, availability of software, and performance characteristics are such problems considered by the decision. The precise estimation of the pertinent data is one of the vital phases in DM systems. This paper presents a fuzzy MCDM‐based cluster head (CH) selection and hybrid routing protocol to solve the most common issues. In this research article, the generalized intuitionistic fuzzy soft set (GIFSS) approach is utilized to select the optimal CH, and hybrid shark smell optimization (SSO), and a genetic algorithm (GA) is introduced for the effective routing. Initially, the wireless sensor network (WSN) system and energy models are designed, and then the nodes are grouped into several clusters. Next, based on the GIFSS, the CH nodes are selected, and finally, an effective routing is placed based on the hybrid optimizations. The implementation is performed on the NS2 platform, and the performances are evaluated by packet delivery ratio (PDR), delay, packet loss ratio (PLR), network lifetime, bit error rate (BER), energy consumption, throughput, and jitter. The existing approaches named energy centers examining using particle swarm optimization (EC‐PSO), variable dimension‐based PSO (VD‐PSO), energy‐efficient PSO‐based CH selection (PSO‐ECHS), low‐energy adaptive clustering hierarchy‐sugeno fuzzy (LEACH‐SF), SSO, and GA are compared with the proposed strategy. According to the implemented outcomes, it displays the proposed strategy and gives improved outcomes than the others.     

ABC algorithm‐based trustworthy energy‐efficient MIMO routing protocol

This paper introduces artificial bee algorithm (ABC)‐based energy‐efficient protocol with security for the enhancement of lifetime of wireless sensor network. A trustworthy energy‐efficient routing MIMO (TEEM) technique is used by implementing MIMO technique in TEER protocol to isolate malicious nodes and to reduce the fading effects and interference in the network. The performance of ABC‐based trustworthy energy‐efficient MIMO routing (ABC‐TEEM) protocol is analysed. Alive node performance, residual energy, throughput analysis, and pocket loss rate of ABC‐TEEM protocol for WSN are computed and compared with the performance of existing TEEM protocol for various diversity orders.     

太赫兹网络中基于中继的高效双信道MAC协议

现有的太赫兹无线个域网双信道介质访问控制(MAC)协议工作在WiFi和太赫兹信道。由于这两种信道的频率相差极大,导致使用全向天线和定向天线的覆盖范围各不相同,这样便会使节点之间的消息传输成功率大大降低,同时也降低了网络整体的吞吐量。另外,在现有的太赫兹无线网络双信道MAC协议中还存在一定的冗余控制开销,这导致了信道利用率低。基于此,文章提出一种太赫兹无线网络中基于中继的高效双信道MAC协议(HE-BRMAC),HE-BRMAC分为中继辅助和自适应减少控制开销机制。通过这两种机制可达到提高消息传输成功率、提升网络整体吞吐量、减少控制开销和提高信道利用率的效果,尤其当节点数较多时,HE-BRMAC的效果更为显著。     

基于OLSR的Ad Hoc网络功率意识路由协议

针对Ad Hoc网络能量受限的特点,提出了一种基于OLSR的功率意识路由协议.该协议的路由选择策略考虑节点发射功率和剩余寿命,同时尽量选择寿命较长的节点作为MPR节点.针对网络流量的突发性和随机性,采用基于能量流失率的节点寿命预测模型.在兼顾传统路由指标之外,主要考虑数据分组传输成功率和网络维持时间等参数.仿真结果显示,该算法有效地提高了网络吞吐量,延长了网络寿命.     

太赫兹网络中基于中继协作转发的高效双信道MAC协议

针对现有多输入多输出(Multiple-Input Multiple-Output, MIMO)太赫兹通信网络双信道MAC协议存在波束重叠干扰和冗余控制开销等问题,提出了一种太赫兹网络中基于中继协作转发的双信道MAC协议(High Efficiency Dual channel MAC Protocol Based on Relay Cooperative Forwarding in Terahertz Networks, HE-RCFMAC)。HE-RCFMAC协议包含动态帧聚合、基于位置信息自适应协作转发和精简RTS(Request To Send)/CTS(Clear To Send)帧三种机制。经三种机制处理后,可有效提升信道利用率,同时减小控制开销,提高数据传输成功率和整体网络吞吐量。仿真结果表明,所提协议与现有的MIMO太赫兹双信道MAC协议相比,MAC层吞吐量、数据传输成功率和信道利用率分别提升了12.82%、12.28%和8.73%,证明了所提协议的有效性。