Multipath energy balancing for clustered wireless sensor networks

In wireless sensor networks, sensors at different locations in the field use different energy levels to propagate sensing data back to the sink or base station. This causes unbalanced energy usage among sensors and also lowers the network lifetime. Currently there are several techniques to mitigate this problem, such as deploying multiple sinks, adding more sensors on heavy traffic areas, or managing the size of clusters depending on the distance from sensor to sink. In this paper, we propose a distributed algorithm and protocol called Multipath Energy Balancing (MEB) to mitigate unbalanced energy usage in clustered wireless sensor networks using multi-path and multi-hop, with a transmission power control approach. The network field is divided into regions, where the ratio of inter-region transmission traffic from all cluster head sensors in one region to other cluster head sensors in the two regions in front can be pre-computed and pre-programmed into the sensors to ease sensor deployment. To further prolong network lifetime, we also present a simple heuristic algorithm to procrastinate cluster formation and routing. Simulation results show that MEB can balance energy much better than Energy-efficient Clustering (EC) and Balancing Energy Consumption (BEC) solutions. It also has a longer network lifetime than EC and BEC protocols, especially when the required cluster size is small. Procrastinating cluster formation and routing also can further improve the network lifetime.

     

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.

     

On Prolonging the Lifetime for Wireless Video Sensor Networks

This paper investigates strategies for prolonging the system lifetime for wireless video sensor networks, by adopting a mobile sink and solar-powered video sensors. Issues of tracking moving objects in wireless video sensor networks are studied, and the effectiveness of adopting a mobile sink is evaluated. This paper applies a power-rate-distortion analysis framework, which provides a theoretical fundamental to quantify various properties of wireless video sensor networks. The performance of wireless video sensor networks is evaluated with a mobile sink versus a static sink, under different cluster sizes and number of sensors. Comparisons of network lifetime, tracking error, video distortion, are also covered in this paper. In addition, this paper also evaluates the performance of solar-powered video sensors under an unequal layered clustering topology.     

ECRP: an energy-aware cluster-based routing protocol for wireless sensor networks

Energy conservation is the main issue in wireless sensor networks. Many existing clustering protocols have been proposed to balance the energy consumption and maximize the battery lifetime of sensor nodes. However, these protocols suffer from the excessive overhead due to repetitive clustering resulting in high-energy consumption. In this paper, we propose energy-aware cluster-based routing protocol (ECRP) in which not only the cluster head (CH) role rotates based on energy around all cluster members until the end of network functioning to avoid frequent re-clustering, but also it can adapt the network topology change. Further, ECRP introduces a multi-hop routing algorithm so that the energy consumption is minimized and balanced. As well, a fault-tolerant mechanism is proposed to cope up with the failure of CHs and relay nodes. We perform extensive simulations on the proposed protocol using different network scenarios. The simulation results demonstrate the superiority of ECRP compared with recent and relevant existing protocols in terms of main performance metrics.

     

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.     

基于TinyOS的无线传感器网络LEACH算法的改进

LEACH协议是无线传感器网络中最流行的分簇路由协议之一.针对LEACH算法簇分布不均匀以及网络能耗不均衡等问题提出了一种高效节能多跳路由算法.在簇建立阶段,新算法根据网络模型计算出最优簇头间距值,调整节点通信半径以控制簇的大小,形成合理网络拓扑结构;在数据传输阶段,簇头与基站之间采用多跳的通信方式,降低了节点能耗.在TinyOS操作系统下,使用nesC语言设计实现了LEACH-EEMH算法.基于TOSSIM平台的仿真结果表明,新算法较LEACH算法在均衡网络能耗、延长网络寿命方面具有显著优势.     

Distributed fuzzy logic based energy‐aware and coverage preserving unequal clustering algorithm for wireless sensor networks

In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency.     

Energy efficient path selection for mobile sink and data gathering in wireless sensor networks

Mobile sink (MS) has drawn significant attention for solving hot spot problem (also known as energy hole problem) that results from multihop data collection using static sink in wireless sensor networks (WSNs). MS is regarded as a potential solution towards this problem as it significantly reduces energy consumption of the sensor nodes and thus enhances network lifetime. In this paper, we first propose an algorithm for designing efficient trajectory for MS, based on rendezvous points (RPs). We next propose another algorithm for the same problem which considers delay bound path formation of the MS. Both the algorithms use k-means clustering and a weight function by considering several network parameters for efficient selection of the RPs by ensuring the coverage of the entire network. We also propose an MS scheduling technique for effective data gathering. The effectiveness of the proposed algorithms is demonstrated through rigorous simulations and comparisons with some of the existing algorithms over several performance metrics.     

Energy Efficient Clustering Scheme (EECS) for Wireless Sensor Network with Mobile Sink

The participants in the Wireless Sensor Network (WSN) are highly resource constraint in nature. The clustering approach in the WSN supports a large-scale monitoring with ease to the user. The node near the sink depletes the energy, forming energy holes in the network. The mobility of the sink creates a major challenge in reliable and energy efficient data communication towards the sink. Hence, a new energy efficient routing protocol is needed to serve the use of networks with a mobile sink. The primary objective of the proposed work is to enhance the lifetime of the network and to increase the packet delivered to mobile sink in the network. The residual energy of the node, distance, and the data overhead are taken into account for selection of cluster head in this proposed Energy Efficient Clustering Scheme (EECS). The waiting time of the mobile sink is estimated. Based on the mobility model, the role of the sensor node is realized as finite state machine and the state transition is realized through Markov model. The proposed EECS algorithm is also been compared with Modified-Low Energy Adaptive Clustering Hierarchy (MOD-LEACH) and Gateway-based Energy-Aware multi-hop Routing protocol algorithms (M-GEAR). The proposed EECS algorithm outperforms the MOD-LEACH algorithm by 1.78 times in terms of lifetime and 1.103 times in terms of throughput. The EECS algorithm promotes unequal clustering by avoiding the energy hole and the HOT SPOT issues.     

Fuzzy-based unequal clustering protocol for underwater wireless sensor networks

Underwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy-based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi-hop and inter-cluster routing. The FBUCP is compared with the LEACH-UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH-UWSN, CDBR, and FBCA.     

Novel chemical reaction optimization based unequal clustering and routing algorithms for wireless sensor networks

Energy conserving of sensor nodes is the most crucial issue in the design of wireless sensor networks (WSNs). In a cluster based routing approach, cluster heads (CHs) cooperate with each other to forward their data to the base station (BS) via multi-hop routing. In this process, CHs closer to the BS are burdened with heavier relay traffic and tend to die prematurely which causes network partition is popularly known as a hot spot problem. To mitigate the hot spot problem, in this paper, we propose unequal clustering and routing algorithms based on novel chemical reaction optimization (nCRO) paradigm, we jointly call these algorithms as novel CRO based unequal clustering and routing algorithms (nCRO-UCRA). In clustering, we partition the network into unequal clusters such that smaller size clusters near to the sink and larger size clusters relatively far away from the sink. For this purpose, we develop the CH selection algorithm based on nCRO paradigm and assign the non-cluster head sensor nodes to the CHs based on derived cost function. Then, a routing algorithm is presented which is also based on nCRO based approach. All these algorithms are developed with the efficient schemes of molecular structure encoding and novel potential energy functions. The nCRO-UCRA is simulated extensively on various scenarios of WSNs and varying number of sensors and the CHs. The results are compared with some existing algorithms and original CRO based algorithm called as CRO-UCRA to show the superiority in terms of various performance metrics like residual energy, network lifetime, number of alive nodes, data packets received by the BS and convergence rate.     

Clustering with Load Balancing-Based Routing Protocol for Wireless Sensor Networks

In this paper we propose a routing protocol based on clustering (IGP-C Protocol) to extend the lifetime in the context of wireless sensor networks while optimizing other resources (memory and processor). Firstly, a clustering algorithm and a load balancing technique are used together in order to reap the benefits of both approaches. The proposed clustering algorithm with load balancing (CALB Algorithm) is a fully distributed algorithm performed by each sensor and requires only communication with its immediate neighbors. Secondly, an Improved Gossiping Protocol (IGP) is proposed to extend the CALB algorithm to the data routing. The simulation results demonstrate the better and promising performances of the IGP-C protocol compared with the other protocols proposed in the literature. The IGP-C protocol allows a better distribution of energy, memory and processing capabilities of cluster-heads and reduces the number of clusters consisting of a single sensor along with the number of iterations. This demonstrates the effectiveness of the cluster-heads election process which improves the load balancing in the wireless sensors network in terms of cluster-heads load and clusters size. Furthermore, the proposed routing strategy builds around the clustering algorithm, is effective since it reduces the data transmission delay and prolongs the network lifetime.     

A Sink-Oriented Layered Clustering Protocol for Wireless Sensor Networks

Clustering is an effective technique to prolong network lifetime for energy-constrained wireless sensor networks. Due to the many-to-one traffic pattern in a multi-hop network, the nodes closer to the sink also help to relay data for those farther away from the sink, and hence they consume much more energy and tend to die faster. This paper proposes a sink-oriented layered clustering (SOLC) protocol to better balance energy consumption among nodes with different distances to the sink. In SOLC, the sensor field is divided into concentric rings, and the SOLC protocol consists of intra-ring clustering and inter-ring routing. We compute the optimal ring width and the numbers of cluster heads in different rings to balance energy consumption between intra-cluster data processing and inter-cluster data relaying. Cluster heads in a ring closer to the sink has smaller sizes than those in the rings farther away from the sink, and hence they can spend less energy for intra-cluster data processing and more energy for inter-cluster data relay. Simulation results show that the SOLC protocol can outperform several existing clustering protocols in terms of improved network lifetime.     

一种无线传感器网络全连通群的休眠调度算法

该文针对无线传感器网络的覆盖性和连通性问题,在假设传感器节点地理位置信息已知的条件下,设计了一种包含全连通群的建立和维护以及群内节点休眠调度的全新算法。该算法采用保证群内节点彼此一跳可达的全连通群分群方法,以及分布式节能的休眠调度策略,最大程度上减少传感器网络的能量消耗,延长了网络寿命。仿真结果表明:该算法能较好地保证无线传感器网络的覆盖性和连通性,且能耗较低。     

An image processing inspired mobile sink solution for energy efficient data gathering in wireless sensor networks

Wireless Networks - This paper presents a gradient-based multi-hop clustering protocol combined with a mobile sink (MS) solution for efficient data gathering in wireless sensor networks. The main...     

Visualization of dynamic fault tolerance rerouting for data traffic in wireless sensor network

In wireless sensor network environments, a phenomenon of data concentration may occur in one or certain sensor nodes in the process of transmitting sensing data from a source sensor node to a sink node. In this case, the overhead that occurs in the sensor node affects the performance of the entire sensor network. In addition, in the sensor network, excessive sensing data traffic or data loss may occur depending on the variability of the topology of the sensor network. In this paper, visualization for dynamic rerouting is designed and implemented, which visibly provides packet movement routes between sensor nodes and transmitted packet traffic transmission capacity to Geography Markup Language‐based maps having GPS coordinate information. A mechanism for the visualization for dynamic rerouting to detect sensing data overheads and sensor node faults occurring in sensor networks and dynamically rerouting of data is proposed. In addition, information on rerouting route paths from source sensors to sink nodes is visually provided. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive directed evolved NSGA2 based node placement optimization for wireless sensor networks

Wireless sensor network (WSN) is a wireless network composed of a large number of static or mobile sensors in a self-organizing and multi-hop manner. In WSN research, node placement is one of the basic problems. In view of the coverage, energy consumption and the distance of node movement, an improved multi-objective optimization algorithm based on NSGA2 is proposed in this paper. The proposed algorithm is used to optimize the node placement of WSN. The proposed algorithm can optimize both the node coverage and lifetime of WSN while also considering the moving distance of nodes, so as to optimize the node placement of WSN. The experiments show that the improved NSGA2 has improvements in both searching performance and convergence speed when solving the node placement problem.

     

基于LEACH路由协议的混合光无线传感网络研究

分析了基于低功耗自适应分簇(LEACH)路由协议的无线传感网络(WSN)在不同拓扑形状下的生命周期,并改进了长方形拓扑形状的路由协议。进而针对WSN在某些场合能量有限、易受干扰和安全性差等缺点,在长方形区域中引入分布式光纤传感结构。将传感光纤铺设在环境复杂和外界电磁波干扰大的监测区域,从而提高整个传感网络的生命周期和可靠性。理论分析和仿真结果表明,改进的拓扑和协议在提高可靠性的同时,有效地延长了光WSN的生存时间,性能优于传统LEACH协议。     

SERP: secure energy-efficient routing protocol for densely deployed wireless sensor networks

In this paper, we present secure energy-efficient routing protocol (SERP) for densely deployed wireless sensor networks which aims to achieve robust security for transmitted sensor readings with an energy-efficient network backbone. When the sensors with limited energy budgets are deployed in hazardous environment, ensuring energy efficiency and security of the sensor readings becomes a crucial task. Here, we address how to deal with such a deployment scenario. Our protocol ensures secure transmission of data from the source sensors to the base station in a way that it can best utilize the available amount of energy in the network. We use one-way hash chain and pre-stored shared secret keys for ensuring data transmission security. In SERP, first, a sink rooted tree structure is created as the backbone of the network. This energy-efficient network structure is used for authenticated and encrypted data delivery from the source sensors to the base station. To introduce data freshness, SERP includes an optional key refreshment mechanism which could be applied depending on the application at hand. Our analysis and simulation results show that SERP provides a good level of confidentiality and authenticity of data that are transmitted from the sensors to the base station. It also helps for energy-efficient structuring of the network so that the maximum lifetime of the network could be achieved.     

Load balancing techniques for lifetime maximizing in wireless sensor networks

Energy consumption has been the focus of many studies on Wireless Sensor Networks (WSN). It is well recognized that energy is a strictly limited resource in WSNs. This limitation constrains the operation of the sensor nodes and somehow compromises the long term network performance as well as network activities. Indeed, the purpose of all application scenarios is to have sensor nodes deployed, unattended, for several months or years.This paper presents the lifetime maximization problem in “many-to-one” and “mostly-off” wireless sensor networks. In such network pattern, all sensor nodes generate and send packets to a single sink via multi-hop transmissions. We noticed, in our previous experimental studies, that since the entire sensor data has to be forwarded to a base station via multi-hop routing, the traffic pattern is highly non-uniform, putting a high burden on the sensor nodes close to the base station.In this paper, we propose some strategies that balance the energy consumption of these nodes and ensure maximum network lifetime by balancing the traffic load as equally as possible. First, we formalize the network lifetime maximization problem then we derive an optimal load balancing solution. Subsequently, we propose a heuristic to approximate the optimal solution and we compare both optimal and heuristic solutions with most common strategies such as shortest-path and equiproportional routing. We conclude that through the results of this work, combining load balancing with transmission power control outperforms the traditional routing schemes in terms of network lifetime maximization.