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.     

DDRP: An efficient data‐driven routing protocol for wireless sensor networks with mobile sinks

Introduction of mobile sinks into a wireless sensor network can largely improve the network performance. However, sink mobility can cause unexpected changes of network topology, which may bring excessive protocol overhead for route maintenance and may offset the benefit from using mobile sinks. In this paper, we propose an efficient data‐driven routing protocol (DDRP) to address this problem. The design objective is to effectively reduce the protocol overhead for data gathering in wireless sensor networks with mobile sinks. DDRP exploits the broadcast feature of wireless medium for route learning. Specifically, each data packet carries an additional option recording the known distance from the sender of the packet to target mobile sink. The overhearing of transmission of such a data packet will gratuitously provide each listener a route to a mobile sink. Continuous such route‐learning among nodes will provide fresh route information to more and more nodes in the network. When no route to mobile sink is known, random walk routing simply is adopted for data packet forwarding. Simulation results show that DDRP can achieve much lower protocol overhead and longer network lifetime as compared with existing work while preserving high packet delivery ratio. Copyright © 2012 John Wiley & Sons, Ltd.     

Minimum spanning tree–based delay‐aware mobile sink traversal in wireless sensor networks

Energy efficient data collection in a delay‐bound application is a challenging issue for mobile sink–based wireless sensor networks. Many researchers have proposed the concept of rendezvous points (RPs) to design the path for the mobile sink. Rendezvous points are the locations in the network where the mobile sink halts and collects data from the nearby sensor nodes. However, the selection of RPs for the design of path has a significant impact on timely data collection from the network. In this paper, we propose an efficient algorithm for selection of the RPs for efficient design of mobile sink trajectory in delay‐bound applications of wireless sensor networks. The algorithm is based on a virtual path and minimum spanning tree and shown to maximize network lifetime. We perform extensive simulations on the proposed algorithm and compare results with the existing algorithms to demonstrate the efficiency of the proposed algorithm of various performance metrics.     

一种基站可移动传感器网络再编程协议

 本文针对基站可移动传感器网络实现了一再编程协议MovPro.该协议可以将新的二进制程序通过多跳的形式下发到网络内的节点上并使之运行.该协议的大致过程描述为,当基站在网络内移动时,基站将数据发送给它移动轨迹上的节点.节点收到部分二进制代码后通过窗口交换的形式将二进制代码传播到整个网络.MovPro是第一个在基站可移动传感器网络的真实系统.本文通过多种方式减少通信开销,并通过二级存储的方式减少外部flash的写次数.实验表明MovPro适用于基站可移动传感器网络.     

无线传感器网络中移动sink节点的路径规划

在无线传感器网络中,大量感知数据汇集到sink节点的采集方法会导致sink节点附近的节点能量耗尽,造成能量空洞。针对该问题,利用移动的sink节点进行数据收集是一种解决方法,其中移动sink的路径规划成为一个重要的问题。提出了一个移动sink路径规划算法,将无线传感器中随机分布的节点划分为不同的子区域,寻找sink节点移动的最佳转向点,最终得到最优的移动路径,以实现无线传感器网络生命周期最大化。仿真实验表明,与现有方案相比,该算法能显著延长网络的生命周期。     

Energy‐Efficient Quorum‐Based MAC Protocol for Wireless Sensor Networks

The reliability of sensor networks is generally dependent on the battery power of the sensor nodes that it employs; hence it is crucial for the sensor nodes to efficiently use their battery resources. This research paper presents a method to increase the reliability of sensor nodes by constructing a connected dominating tree (CDT), which is a subnetwork of wireless sensor networks. It detects the minimum number of dominatees, dominators, forwarder sensor nodes, and aggregates, as well as transmitting data to the sink. A new medium access control (MAC) protocol, called Homogenous Quorum‐Based Medium Access Control (HQMAC), is also introduced, which is an adaptive, homogenous, asynchronous quorum‐based MAC protocol. In this protocol, certain sensor nodes belonging to a network will be allowed to tune their wake‐up and sleep intervals, based on their own traffic load. A new quorum system, named BiQuorum, is used by HQMAC to provide a low duty cycle, low network sensibility, and a high number of rendezvous points when compared with other quorum systems such as grid and dygrid. Both the theoretical results and the simulation results proved that the proposed HQMAC (when applied to a CDT) facilitates low transmission latency, high delivery ratio, and low energy consumption, thus extending the lifetime of the network it serves.     

Novel service protocol for supporting remote and mobile users in wireless sensor networks with multiple static sinks

A wireless sensor network typically consists of users, a sink, and a number of sensor nodes. The users may be remotely connected to a wireless sensor network and via legacy networks such as Internet or Satellite the remote users obtain data collected by the sink that is statically located at a border of the wireless sensor network. However, in practical sensor network applications, there might be two types of users: the traditional remote users and mobile users such as firefighters and soldiers. The mobile users may move around sensor fields and they communicate with the static sink only via the wireless sensor networks in order to obtain data like location information of victims in disaster areas. For supporting the mobile users, existing studies consider temporary structures. However, the temporary structures are constructed per each mobile user or each source nodes so that it causes large energy consumption of sensor nodes. Moreover, since some of them establish the source-based structure, sinks in them cannot gather collective information like mean temperature and object detection. In this paper, to effectively support both the remote users and the mobile users, we propose a novel service protocol relying on the typical wireless sensor network. In the protocol, multiple static sinks connect with legacy networks and divide a sensor field into the number of the multiple sinks. Through sharing queries and data via the legacy networks, the multiple static sinks provide high throughput through distributed data gathering and low latency through short-hops data delivery. Multiple static sinks deliver the aggregated data to the remote users via the legacy networks. In case of the mobile users, when a mobile user moves around, it receives the aggregated data from the nearest static sink. Simulation results show that the proposed protocol is more efficient in terms of energy consumption, data delivery ratio, and delay than the existing protocols.     

An intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks

Overlapping is one of the topics in wireless sensor networks that is considered by researchers in the last decades. An appropriate overlapping management system can prolong network lifetime and decrease network recovery time. This paper proposes an intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks, called IKOCP. This protocol uses some of the intelligent and knowledge‐based systems to construct a robust overlapping strategy for sensor networks. The overall network is partitioned to several regions by a proposed multicriteria decision‐making controller to monitor both small‐scale and large‐scale areas. Each region is managed by a sink, where the whole network is managed by a base station. The sensor nodes are categorized by various clusters using the low‐energy adaptive clustering hierarchy (LEACH)‐improved protocol in a way that the value of p is defined by a proposed support vector machine–based mechanism. A proposed fuzzy system determines that noncluster heads associate with several clusters in order to manage overlapping conditions over the network. Cluster heads are changed into clusters in a period by a suggested utility function. Since network lifetime should be prolonged and network traffic should be alleviated, a data aggregation mechanism is proposed to transmit only crucial data packets from cluster heads to sinks. Cluster heads apply a weighted criteria matrix to perform an inner‐cluster routing for transmitting data packets to sinks. Simulation results demonstrate that the proposed protocol surpasses the existing methods in terms of the number of alive nodes, network lifetime, average time to recover, dead time of first node, and dead time of last node.     

A frequency‐aware data‐centric mechanism for wireless sensor networks

Wireless sensor networks (WSNs) are characterized by their low bandwidth, limited energy, and largely distributed deployment. To reduce the flooding overhead raised by transmitting query and data information, several data‐centric storage (DCS) mechanisms are proposed. However, the locations of these data‐centric nodes significantly impact the power consumption and efficiency for information queries and storage capabilities, especially in a multi‐sink environment. This paper proposes a novel dissemination approach, which is namely the dynamic data‐centric routing and storage mechanism (DDCRS), to dynamically determine locations of data‐centric nodes according to sink nodes' location and data collecting rate and automatically construct shared paths from data‐centric nodes to multiple sinks. To save the power consumption, the data‐centric node is changed when new sink nodes participate when the WSNs or some queries change their frequencies. The simulation results reveal that the proposed protocol outperforms existing protocols in terms of power conservation and power balancing. Copyright © 2009 John Wiley & Sons, Ltd.     

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.     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

Energy-Aware Data Aggregation for Grid-Based Wireless Sensor Networks with a Mobile Sink

Wireless sensor networks (WSNs) are made up of many small and highly sensitive nodes that have the ability to react quickly. In WSNs, sink mobility brings new challenges to large-scale sensor networks. Almost all of the energy-aware routing protocols that have been proposed for WSNs aim at optimizing network performance while relaying data to a stationary gateway (sink). However, through such contemporary protocols, mobility of the sink can make established routes unstable and non-optimal. The use of mobile sinks introduces a trade-off between the need for frequent rerouting to ensure optimal network operation and the desire to minimize the overhead of topology management. In this paper, in order to reduce energy consumption and minimize the overhead of rerouting frequency, we propose an energy-aware data aggregation scheme (EADA) for grid-based wireless sensor networks with a mobile sink. In the proposed scheme, each sensor node with location information and limited energy is considered. Our approach utilizes location information and selects a special gateway in each area of a grid responsible for forwarding messages. We restrict the flooding region to decrease the overhead for route decision by utilizing local information. We conducted simulations to show that the proposed routing scheme outperforms the coordination-based data dissemination scheme (CODE) (Xuan, H. L., & Lee, S. Proceedings of the Sensor Networks and Information Processing Conference, pp. 13–18, 2004).     

Assimilation of fuzzy clustering approach and EHO‐Greedy algorithm for efficient routing in WSN

The problems related to energy consumption and improvement of the network lifetime of WSN (wireless sensor network) have been considered. The base station (BS) location is the main concern in WSN. BSs are fixed, yet, they have the ability to move in some situations to collect the information from sensor nodes (SNs). Recently, introducing mobile sinks to WSNs has been proved to be an efficient way to extend the lifespan of the network. This paper proposes the assimilation of the fuzzy clustering approach and the Elephant Herding Optimization (EHO)‐Greedy algorithm for efficient routing in WSN. This work considers the separate sink nodes of a fixed sink and movable sink to decrease the utilization of energy. A fixed node is deployed randomly across the network, and the movable sink node moves to different locations across the network for collecting the data. Initially, the number of nodes is formed into the multiple clusters using the enhanced expectation maximization algorithm. After that, the cluster head (CH) selection done through a fuzzy approach by taking the account of three factors of residual energy, node centrality, and neighborhood overlap. A suitable collection of CH can extremely reduce the utilization of energy and also enhancing the lifespan. Finally, the routing protocol of the hybrid EHO‐Greedy algorithm is used for efficient data transmission. Simulation results display that the proposed technique is better to other existing approaches in regard to energy utilization and the system lifetime.     

GCRP: Grid-cycle routing protocol for wireless sensor network with mobile sink

Energy conservation is a critical issue in resource constraint wireless sensor networks. Employing mobile sink to deliver the sensed data becomes pervasive approach to conserve sensors’ limited energy. However, mobile sink makes data delivery a hard nut to crack since nodes need to know its latest location. Providing sink’s latest location by traditional flooding, erode the energy conservation goal. In this paper, we propose a Grid-Cycle Routing Protocol (GCRP) with the aim of minimizing the overhead of updating the mobile sink’s latest location. In GCRP, sensor field is partitioned into grid of cells and for each cell a grid cell head (GCH) is elected. Cycles of four GCHs is formed. Cycle(s) involving border GCHs is called exterior cycle and said to belong to a region. Another cycle involving non-boundary GCHs is called interior cycle, connecting GCHs of different regions. When sink stays at one location, it updates the nearest GCH, which in turn updates the other GCHs through exterior and interior cycle. Moreover, we propose a set of sharing rules that govern GCHs when and with who share sink’s latest location information. The performance of GCRP is evaluated at different number of nodes and compared with existing work using NS-2.31.     

A reliable and energy‐efficient routing protocol for underwater wireless sensor networks

Recently, underwater wireless sensor networks (UWSNs) have attracted much research attention to support various applications for pollution monitoring, tsunami warnings, offshore exploration, tactical surveillance, etc. However, because of the peculiar characteristics of UWSNs, designing communication protocols for UWSNs is a challenging task. Particularly, designing a routing protocol is of the most importance for successful data transmissions between sensors and the sink. In this paper, we propose a reliable and energy‐efficient routing protocol, named R‐ERP²R (Reliable Energy‐efficient Routing Protocol based on physical distance and residual energy). The main idea behind R‐ERP²R is to utilize physical distance as a routing metric and to balance energy consumption among sensors. Furthermore, during the selection of forwarding nodes, link quality towards the forwarding nodes is also considered to provide reliability and the residual energy of the forwarding nodes to prolong network lifetime. Using the NS‐2 simulator, R‐ERP²R is compared against a well‐known routing protocol (i.e. depth‐based routing) in terms of network lifetime, energy consumption, end‐to‐end delay and delivery ratio. The simulation results proved that R‐ERP²R performs better in UWSNs.Copyright © 2012 John Wiley & Sons, Ltd.     

Sink selection and clustering using fuzzy‐based controller for wireless sensor networks

Applying multiple sink nodes in a large‐scale wireless sensor networks (WSN) can increase the scalability and lifetime of the network. The current sink selection mechanisms assume an unlimited amount of buffer and bandwidth for the sink nodes. This can be problematic in real‐world applications, especially when many cluster heads select a specific sink node and send their data to the sink at the same time. In this situation, the sink node may not have enough buffer to receive and process data; consequently, some packets are dropped. To mitigate these occasions, a fuzzy‐based controller with reduced rules is proposed for sink selection by considering the capacity of the sink nodes. The capacity of the sink nodes is estimated using the long short‐term memory (LSTM) technique. Then another fuzzy‐based controller with reduced rules is designed to select the cluster head. The fuzzy rules are reduced by employing R‐implications method. Reducing the number of fuzzy rules decreases the complexity of the fuzzy controllers. The results show the efficiency of the proposed sink selection and clustering techniques in terms of consumed energy, remaining energy, first node dead (FND), half nodes dead (HND), last node dead (LND), packet loss, and delay.     

Optimized mobile sink based grid coverage-aware sensor deployment and link quality based routing in wireless sensor networks

Mobile sink (MS) has been used in wireless sensor networks (WSN) to increase the network lifetime by changing the location over time. The major quality of service given by WSN is coverage energy consumption (EC) and network lifetime. There are many methods implemented for enhance the coverage hole restoration and reduce the EC. We propose a novel MSCOLER (MS based Coverage Optimization and Link-stability Estimation Routing) protocol for Optimal Coverage restoration and Link stability Estimation. An optimization algorithm is used to optimize the coverage hole and move the redundant node besides the hole. During the routing process, link quality based routing is used to discover the relay nodes with the estimation of link stability to enhance the entire network lifetime and practically make the perfect transmission distance for energy saving. Experimental results demonstrate that proposed protocol can solve the coverage restoration problem, decrease the EC and reduce the network lifetime. The performance is evaluated regarding Average of residual energy (ARE), Receiving packets ratio (RPR), Moving energy consumption (MEC), Network lifetime (NL), Percentage of coverage (%C) and Average Energy Consumption (AEC).     

基于移动Agent和WSN的突发事件场景数据收集算法研究

该文针对无线传感器网络应用于突发事件监测场景的能量消耗和网络延迟问题,提出了基于移动Agent的无线传感器网络簇式数据收集算法.动态成簇过程基于事件严重程度,并由其决定簇的生命周期和覆盖范围.Sink和簇头之间形成以Sink节点为簇头的虚拟簇.移动Agent迁移路径规划过程中下一跳节点的选取基于节点剩余能量、路径损耗及受刺激强度.移动Agent通过节点遍历的方式完成对所有簇内成员节点信息的收集.仿真结果表明,相对于C/S数据收集模型,基于移动Agent的模型具有更好的节能效果,并能一定程度地减少网络延迟,尤其适用于大规模无线传感器网络应用.     

Distributed trajectory design for data gathering using mobile sink in wireless sensor networks

Several studies have demonstrated the benefits of using a mobile sink (MS) to reduce energy consumption resulting from multi-hop data collection using a static sink in wireless sensor networks (WSNs). However, using MS may increase data delivery latency as it needs to visit each sensor node in the network to collect data. This is a critical issue in delay-sensitive applications where all sensed data must be gathered within a given time constraint. In this paper, we propose a distributed data gathering protocol utilizing MS for WSNs. The proposed protocol designs a trajectory for the MS, which minimizes energy consumption and delay. Our protocol operates in four main phases: data sensing, rendezvous point (RP) selection, trajectory design, and data gathering. In data sensing, a number of deployed sensor nodes keep sensing the target field for a specific period of time to capture events. Then, using a cluster-based RP selection algorithm, some sensor nodes are selected to become RPs based on local information. The selected RPs are then used to determine a trajectory for the MS. To do so, we propose three trajectory design algorithms that support different types of applications, namely reduced energy path (REP), reduced delay path (RDP), and delay bound path (DBP). The MS moves through the constructed path to accomplish its data gathering according to an effective scheduling technique that is introduced in this work. We validate the proposed protocol via extensive simulations over several metrics such as energy, delay, and time complexity.     

时延受限的移动sink数据收集算法

在实时性要求比较高的应用中,时延要求限制了sink的移动速率与移动轨迹,sink的移动速率限制了节点与sink的通信时间,因此很难兼顾时延要求与数据收集效率。提出一种时延受限的移动sink数据收集算法MSDC,在低能耗缓存区内找到一条sink的最优移动轨迹,在有限的时间限制内利用sink的移动性来提升传感器网络的数据收集性能。仿真结果表明,与已有算法比较,该方案能够提高网络数据采集量,降低能耗,延长网络生命周期。