一种基于冗余度的无线传感器网络节能策略

在无线传感器网络中,传感节点由于采用电池供电,因此寿命有限。如何有效节省传感器节点的能量,延长网络的使用寿命,一直是广泛研究的焦点。文章提出一种适用于高冗余度布置的无线传感器网络结构中,节省传感器节点能量消耗的方法-接续调度法。该方法通过协调点对小区域内节点的调度,使区域内节点依次分时段工作。通过这种接续调度,避免了节点间的冲突和串扰,达到延长整体网络寿命的效果。     

Energy-Efficient Routing Algorithm Based on Unequal Clustering and Connected Graph in Wireless Sensor Networks

Clustering and multi-hop routing algorithms substantially prolong the lifetime of wireless sensor networks (WSNs). However, they also result in the energy hole and network partition problems. In order to balance the load between multiple cluster heads, save the energy consumption of the inter-cluster routing, in this paper, we propose an energy-efficient routing algorithm based on Unequal Clustering Theory and Connected Graph Theory for WSN. The new algorithm optimizes and innovates in two aspects: cluster head election and clusters routing. In cluster head election, we take into consideration the vote-based measure and the transmission power of sensor nodes when to sectionalize these nodes into different unequal clusters. Then we introduce the connected graph theory for inter-cluster data communication in clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads. Simulation results show that, this new algorithm balances the energy consumption among sensor nodes, relieves the influence of energy-hole problem, improve the link quality, achieves a substantial improvement on reliability and efficiency of data transmission, and significantly prolongs the network lifetime.     

Sink Node Placement Strategies for Wireless Sensor Networks

In wireless sensor networks (WSNs), all the data collected by the sensor nodes are forwarded to a sink node. Therefore, the placement of the sink node has a great impact on the energy consumption and lifetime of WSNs. This paper investigates the energy-oriented and lifetime-oriented sink node placement strategies in the single-hop and multiple-hop WSNs, respectively. The energy-oriented strategy considers only the minimizing of the total energy consumption in the networks, while the lifetime-oriented strategy focuses much more on the lifetime of the nodes which consume energy fastest. Using a routing-cost based ant routing algorithm, we evaluate the performances of different placement strategies in the networks. Simulation results show that the networks with lifetime-oriented strategy achieve a significant improvement on network lifetime.     

Balance energy-efficient and real-time with reliable communication protocol for wireless sensor network

In many wireless sensor network applications, it should be considered that how to trade off the inherent conflict between energy efficient communication and desired quality of service such as real-time and reliability of transportation. In this paper, a novel routing protocols named balance energy-efficient and real-time with reliable communication (BERR) for wireless sensor networks (WSNs) are proposed, which considers the joint performances of real-time, energy efficiency and reliability. In BERR, a node, which is preparing to transmit data packets to sink node, estimates the energy cost, hop count value to sink node and reliability using local information gained from neighbor nodes. BERR considers not only each sender’ energy level but also that of its neighbor nodes, so that the better energy conditions a node has, the more probability it will be to be chosen as the next relay node. To enhance real-time delivery, it will choose the node with smaller hop count value to sink node as the possible relay candidate. To improve reliability, it adopts retransmission mechanism. Simulation results show that BERR has better performances in term of energy consumption, network lifetime, reliability and small transmitting delay.     

Clustering and multi-hop routing with power control in wireless sensor networks

Clustering routing protocols excel in several aspects of wireless sensor networks (WSNs). This article proposes a clustering and multihop routing protocol (CMRP). In CMRP, a node independently makes its decision to compete for becoming a cluster head or join a cluster, according to its residual energy and average broadcast power of all its neighbors. To minimize the power consumption of the cluster head, CMRP sends the data in a power-aware multihop manner to the base station (BS) through a quasi-fixed route (QFR). In addition, CMRP presents a transmission power control algorithm with dynamic intercluster neighbor position estimation (DCNPE) to save energy. Simulation results show that the performance of CMRP is better than the hybrid, energy-efficient, distributed clustering approach (HEED). In the best case, CMRP increases the sensor network lifetime by 150.2%.     

Secure coverage-preserving node scheduling scheme using energy prediction for wireless sensor networks

With the fast development of the micro-electro-mechanical systems(MEMS),wireless sensor networks(WSNs)have been extensively studied.Most of the studies focus on saving energy consumption because of restricted energy supply in WSNs.Cluster-based node scheduling scheme is commonly considered as one of the most energy-efficient approaches.However,it is not always so efficient especially when there exist hot spot and network attacks in WSNs.In this article,a secure coverage-preserved node scheduling scheme for WSNs based on energy prediction is proposed in an uneven deployment environment.The scheme is comprised of an uneven clustering algorithm based on arithmetic progression,a cover set partition algorithm based on trust and a node scheduling algorithm based on energy prediction.Simulation results show that network lifetime of the scheme is 350 rounds longer than that of other scheduling algorithms.Furthermore,the scheme can keep a high network coverage ratio during the network lifetime and achieve the designed objective which makes energy dissipation of most nodes in WSNs balanced.     

Energy Efficiency Routing with Node Compromised Resistance in Wireless Sensor Networks

For the energy limited wireless sensor networks, the critical problem is how to achieve the energy efficiency. Many attackers can consume the limited network energy, by the method of capturing some legal nodes then control them to start DoS and flooding attack, which is difficult to be detected by only the classic cryptography based techniques with common routing protocols in wireless sensor networks (WSNs). We argue that under the condition of attacking, existing routing schemes are low energy-efficient and vulnerable to inside attack due to their deterministic nature. To avoid the energy consumption caused by the inside attack initiated by the malicious nodes, this paper proposes a novel energy efficiency routing with node compromised resistance (EENC) based on Ant Colony Optimization. Under our design, each node computes the trust value of its 1-hop neighbors based on their multiple behavior attributes evaluation and builds a trust management by the trust value. By this way, sensor nodes act as router to achieve dynamic and adaptive routing, where the node can select much energy efficiency and faithful forwarding node from its neighbors according to their remaining energy and trust values in the next process of data collection. Simulation results indicate that the established routing can bypass most compromised nodes in the transmission path and EENC has high performance in energy efficiency, which can prolong the network lifetime.     

无线传感器网络能量高效混合MAC算法

针对无线传感器网络MAC协议中存在的能耗问题,提出了能量高效的无线传感器网络混合MAC(EEH-MAC)算法,采用基于TDMA机制的时槽系数动态调整簇内节点的时槽大小来降低数据的传输时延;同时,对部分不需要数据传输的节点不分配时槽来减少能耗;按簇内节点剩余能量系数形成时槽分配顺序来减少状态转换的能耗;在簇头之间采用CSMA/CA机制的随机分配策略进行通信.仿真结果表明,EEH-MAC协议能有效减少能耗并延长网络生命周期.     

Throughput Evaluation of a Novel Scheme to Mitigate the Congestion over WSNs

In recent years, due to fast development of wireless sensor networks (WSNs), the numbers of nodes are increasing, and their scope of applications is continuously expanding, including environmental monitoring, military and smart home applications. The power supply, memory and computing power of wireless sensor nodes are greatly hampered in WSNs so that the WSNs are classified as a task-oriented framework. This study focused on exploring problems caused by traffic congestion on the WSNs with a large amount of flow, such as packet loss, bandwidth reduction, and waste of energy on the sensor nodes. On the other hand, a cooperative strong node mechanism is presented and named as Cooperative Strong Node Mechanism, in which a threshold is set to determine whether the node traffic is over or not. When the load exceeds, the privilege of corresponding sensor nodes is upgraded so that it can command its child nodes to change the transmission path to distribute the traffic effectively. Furthermore, when the traffic exceeds preset overall network flow, new sensor nodes are added in the network to relieve the traffic. This novel proposed mechanism can not only increase network throughput and effectively prevent the occurrence from congestion problems, but is suitable for a variety of routing protocols.     

DR-NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time-series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.     

基于遗传聚类的无线传感器负载均衡路由算法

通常的无线传感器分簇网络存在节点负载不均衡的问题。为均衡各节点能量消耗,延长网络生存周期,将K均值算法与遗传算法相结合,提出一种负载均衡的无线传感器网络路由算法,算法利用遗传算法的全局寻优能力以克服传统K均值算法的局部性和对初始中心的敏感性,实现了传感器网络节点自适应成簇与各节点负载均衡。仿真实验表明,该算法显著延长了网络寿命,相对于其他分簇路由算法,其网络生存时间延长了约43%。     

DUCR: Distributed unequal cluster‐based routing algorithm for heterogeneous wireless sensor networks

Designing energy efficient communication protocols for wireless sensor networks (WSNs) to conserve the sensors' energy is one of the prime concerns. Clustering in WSNs significantly reduces the energy consumption in which the nodes are organized in clusters, each having a cluster head (CH). The CHs collect data from their cluster members and transmit it to the base station via a single or multihop communication. The main issue in such mechanism is how to associate the nodes to CHs and how to route the data of CHs so that the overall load on CHs are balanced. Since the sensor nodes operate autonomously, the methods designed for WSNs should be of distributed nature, i.e., each node should run it using its local information only. Considering these issues, we propose a distributed multiobjective‐based clustering method to assign a sensor node to appropriate CH so that the load is balanced. We also propose an energy‐efficient routing algorithm to balance the relay load among the CHs. In case any CH dies, we propose a recovery strategy for its cluster members. All our proposed methods are completely distributed in nature. Simulation results demonstrate the efficiency of the proposed algorithm in terms of energy consumption and hence prolonging the network lifetime. We compare the performance of the proposed algorithm with some existing algorithms in terms of number of alive nodes, network lifetime, energy efficiency, and energy population.     

Multi-factor and Distributed Clustering Routing Protocol in Wireless Sensor Networks

One of important issues in wireless sensor networks is how to effectively use the limited node energy to prolong the lifetime of the networks. Clustering is a promising approach in wireless sensor networks, which can increase the network lifetime and scalability. However, in existing clustering algorithms, too heavy burden of cluster heads may lead to rapid death of the sensor nodes. The location of function nodes and the number of the neighbor nodes are also not carefully considered during clustering. In this paper, a multi-factor and distributed clustering routing protocol MFDCRP based on communication nodes is proposed by combining cluster-based routing protocol and multi-hop transmission. Communication nodes are introduced to relay the multi-hop transmission and elect cluster heads in order to ease the overload of cluster heads. The protocol optimizes the election of cluster nodes by combining various factors such as the residual energy of nodes, the distance between cluster heads and the base station, and the number of the neighbor nodes. The local optimal path construction algorithm for multi-hop transmission is also improved. Simulation results show that MFDCRP can effectively save the energy of sensor nodes, balance the network energy distribution, and greatly prolong the network lifetime, compared with the existing protocols.     

无线传感器网络中利用随机网络编码的低能耗可靠机会路由

无线传感器网络中节点大多采用电池供电,让节点以低能耗将采集的数据传递到信宿,对无线传感器网络有效运行极为重要.该文提出了能量有效的可靠机会路由EROR（Energy-efficient Reliable Opportunistic Routing）,它利用结合节点剩余能量和链路上收发双方的总能耗的转发代价,选择转发节点集合（简称“转发集”）、主转发节点和协助转发节点,让节点调节发射功率并利用随机线性编码把数据包分片编码发送到转发集,进而以多跳方式把数据可靠低能耗地传递到信宿.仿真结果表明：在网络生存时间和能耗方面,EROR比已有路由策略CodePower更优.     

LSAPSP: Load distribution‐based slot allocation and path establishment using optimized substance particle selection in sensor networks

Sensor node energy conservation is the primary design parameters in wireless sensor networks (WSNs). Energy efficiency in sensor networks directly prolongs the network lifetime. In the process of route discovery, each node cooperates to forward the data to the base station using multi‐hop routing. But, the nodes nearer to the base station are loaded more than the other nodes that lead to network portioning, packet loss and delay as a result nodes may completely loss its energy during the routing process. To rectify these issues, path establishment considers optimized substance particle selection, load distribution, and an efficient slot allocation scheme for data transmission between the sensor nodes in this paper. The selection of forwarders and conscious multi‐hop path is selected based on the route cost value that is derived directly by taking energy, node degree and distance as crucial metrics. Load distribution based slot allocation method ensures the balance of data traffic and residual energy of the node in areal‐time environment. The proposed LSAPSP simulation results show that our algorithm not only can balance the real‐time environment load and increase the network lifetime but also meet the needs of packet loss and delay.     

无线传感器网络自适应目标跟踪节点调度算法

在无线传感器网络中,设计合理的节点调度算法是提高网络感知能力、降低系统能耗的关键。在分析节点能耗模型的基础上,针对移动目标跟踪型网络应用,提出一种高能效的无线传感器网络自适应节点调度算法ANSTT。该算法根据节点对移动目标的感知能力,以及节点的相对剩余能量水平,自动调整节点工作模式。仿真实验表明,ANSTT算法在维持低感知延时、高目标感知率的同时,可有效降低系统能耗,延长网络寿命。     

A boolean spider monkey optimization based energy efficient clustering approach for WSNs

Wireless sensor network (WSN) consists of densely distributed nodes that are deployed to observe and react to events within the sensor field. In WSNs, energy management and network lifetime optimization are major issues in the designing of cluster-based routing protocols. Clustering is an efficient data gathering technique that effectively reduces the energy consumption by organizing nodes into groups. However, in clustering protocols, cluster heads (CHs) bear additional load for coordinating various activities within the cluster. Improper selection of CHs causes increased energy consumption and also degrades the performance of WSN. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for long run operation of WSN. Clustering a network with proper load balancing is an NP-hard problem. To solve such problems having vast search area, optimization algorithm is the preeminent possible solution. Spider monkey optimization (SMO) is a relatively new nature inspired evolutionary algorithm based on the foraging behaviour of spider monkeys. It has proved its worth for benchmark functions optimization and antenna design problems. In this paper, SMO based threshold-sensitive energy-efficient clustering protocol is proposed to prolong network lifetime with an intend to extend the stability period of the network. Dual-hop communication between CHs and BS is utilized to achieve load balancing of distant CHs and energy minimization. The results demonstrate that the proposed protocol significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.     

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.     

Energy-efficient data sensing and routing in unreliable energy-harvesting wireless sensor network

Energy-harvesting wireless sensor network (WSN) is composed of unreliable wireless channels and resource-constrained nodes which are powered by solar panels and solar cells. Energy-harvesting WSNs can provide perpetual data service by harvesting energy from surrounding environments. Due to the random characteristics of harvested energy and unreliability of wireless channel, energy efficiency is one of the main challenging issues. In this paper, we are concerned with how to decide the energy used for data sensing and transmission adaptively to maximize network utility, and how to route all the collected data to the sink along energy-efficient paths to maximize the residual battery energy of nodes. To solve this problem, we first formulate a heuristic energy-efficient data sensing and routing problem. Then, unlike the most existing work that focuses on energy-efficient data sensing and energy-efficient routing respectively, energy-efficient data sensing and routing scheme (EEDSRS) in unreliable energy-harvesting wireless sensor network is developed. EEDSRS takes account of not only the energy-efficient data sensing but also the energy-efficient routing. EEDSRS is divided into three steps: (1) an adaptive exponentially weighted moving average algorithm to estimate link quality. (2) an distributed energetic-sustainable data sensing rate allocation algorithm to allocate the energy for data sensing and routing. According to the allocated energy, the optimal data sensing rate to maximize the network utility is obtained. (3) a geographic routing with unreliable link protocol to route all the collected data to the sink along energy-efficient paths. Finally, extensive simulations to evaluate the performance of the proposed EEDSRS are performed. The experimental results demonstrate that the proposed EEDSRS is very promising and efficient.     

Self-Recommendation Mechanism in Trust Calculation Among Nodes in WSN

This paper proposes a node self-recommendation mechanism which is effective in trust calculation model in wireless sensor networks (WSNs). The mechanism has little practical sense to cable and wireless network among which nodes’ resources, especially energy, are almost unlimited; furthermore it may bring some security risk to networks on the contrary. But as to WSNs where nodes’ resources are strictly limited, a node can express its intension of participating communication to its neighbors by using the mechanism according to its current running state and predefined strategies. This mechanism is useful to save nodes’ energy, balance network load and prolong network lifetime ultimately. The paper focuses on self-recommendation value expression, calculation and synthesis method. Application method of the mechanism is also discussed. Simulation results show that using trust calculation model cooperatively with self-recommendation mechanism can protect low energy nodes effectively and balance energy consumption among adjacent nodes without weakening malicious node identification function of the trust model.