基于QoS的无线传感器网络感知调度协议

针对大规模随机部署传感器网络的节点密度不均匀性和不同应用对事件监测时延的不同需求,为提供全网可调的监测时延保障,设计了面向事件监测应用的全网能耗均衡的自适应分布式感知调度协议(ADSSP),仿真结果表明:相对于随机感知调度协议,ADSSP能获得更低的平均监测时延,在满足相同的平均监测延迟的前提下延长了30%的网络生存时间.     

无线传感器网络S-MAC协议研究

传感器节点能量受限,节能是传感器网络中媒体访问控制（MAC）协议设计的首要问题。采用周期性睡眠机制、自适应侦听机制、串音避免机制和消息传递机制可使得传感器媒体访问控制（S-MAC）协议在网络能耗和时延方面得到改进。对S-MAC协议的改进主要有两种方式：动态调整、区别控制包与数据包的发送条件进行发送。对无线传感器网络,要想设计出一种满足各方面要求的MAC协议是不现实的,可针对不同应用的要求,灵活采用不同的方式,设计出相应的协议。     

一种用于水声传感网的MAC层协议

针对分簇的水声传感网,提出了一种基于时分多址（TDMA）的MAC层协议——Cluster-TDMA。该协议主要由规划阶段和传输阶段组成。规划阶段,首先由网关节点规划能造成簇间干扰的子节点的传输,其次由各簇头节点分别规划本簇内其他子节点的传输;传输阶段,子节点根据规划表周期性地向簇头节点发送数据,这些数据最终汇聚到网关节点。该协议简单有效地解决了引起簇间干扰子结点的传输规划问题。C++仿真实验表明,该协议具有良好的吞吐率和能量效率性能。     

A cluster-based power-efficient MAC scheme for event-driven sensing applications

In developing an architecture for wireless sensor networks (WSNs) that is extensible to hundreds of thousands of heterogeneous nodes, fundamental advances in energy efficient communication protocols must occur. In this paper, we first propose an energy-efficient and robust intra-cluster communication bit-map assisted (BMA) MAC protocol for large-scale cluster-based WSNs and then derive energy models for BMA, conventional TDMA, and energy efficient TDMA (E-TDMA) using two different approaches. We use simulation to validate these analytical models. BMA is intended for event-driven sensing applications, that is, sensor nodes forward data to the cluster head only if significant events are observed. It has low complexity and utilizes a dynamic scheduling scheme. Clustering is a promising distributing technique used in large-scale WSNs, and when combined with an appropriate MAC scheme, high energy efficiency can be achieved. The results indicate that BMA can improve the performance of wireless sensor networks by reducing energy expenditure and packet latency. The performance of BMA as an intra-cluster MAC scheme relative to E-TDMA depends on the sensor node traffic offer load and several other key system parameters. For most sensor-based applications, the values of these parameters can be constrained such that BMA provides enhanced performance.     

Low-Energy Adaptive Unequal Clustering Protocol Using Fuzzy c-Means in Wireless Sensor Networks

Clustering technique in wireless sensor networks incorporate proper utilization of the limited energy resources of the deployed sensor nodes with the highest residual energy that can be used to gather data and send the information. However, the problem of unbalanced energy consumption exists in a particular cluster node in the network. Some more powerful nodes act as cluster head to control sensor network operation when the network is organized into heterogeneous clusters. It is important to assume that energy consumption of these cluster head nodes is balanced. Often the network is organized into clusters of equal size where cluster head nodes bear unequal loads. Instead in this paper, we proposed a new protocol low-energy adaptive unequal clustering protocol using Fuzzy c-means in wireless sensor networks (LAUCF), an unequal clustering size model for the organization of network based on Fuzzy c-means (FCM) clustering algorithm, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime. A heuristic comparison between our proposed protocol LAUCF and other different energy-aware protocol including low energy adaptive clustering hierarchy (LEACH) has been carried out. Simulation result shows that our proposed heterogeneous clustering approach using FCM protocol is more effective in prolonging the network lifetime compared with LEACH and other protocol for long run.     

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.     

Energy efficient clustering algorithm for the mobility support in an IEEE 802.15.4 based wireless sensor network

The traditional clustering algorithm is an advanced routing protocol for enhancing an energy efficiency, which selects a cluster head and transmits the aggregated data arriving from the sensor nodes in the cluster to a gateway. However, the existing literature works were not suitable for an IEEE 802.15.4 beacon enabled mode and did not provide the combined solution for an energy efficient scheduling and handover of the sensor nodes. To address these problems, in this paper, we propose an energy efficient clustering algorithm for the mobility support in IEEE 802.15.4 networks. The simulation results show that the proposed scheme reduces the energy consumption and the packet loss, thus enhancing the performance.

     

链路可靠的无线传感器网络组播路由协议

在无线传感器网络实际应用中,组播正在发挥着越来越重要的作用.但由于能量等多方面的因素,使得为无线传感器网络设计一个有效的组播路由是非常困难的.针对无线传感器网络中节点的能量限制,通过寻求节点间最短路径,提出一种能量有效的链路可靠组播路由协议(RLMR).该协议充分考虑到网络中节点的能耗因素和两节点间的链路可靠性等,通过对这两个因素的综合考虑,让能量较多并且以发送节点更靠近的节点承担更多传输任务的方式,为数据流优化路由选择,均衡无线传感器网络节点的能量消耗,以延长网络的生存时间.仿真结果证明了RLMR的有效性和可靠性.     

A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization

Energy consumption of sensor nodes is one of the crucial issues in prolonging the lifetime of wireless sensor networks. One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. The performance of the proposed protocol is compared with well-known clustering protocols developed for wireless sensor networks such as LEACH (low-energy adaptive clustering hierarchy) and protocols designed for sensor networks with mobile nodes called CM-IR (clustering mobility-invalid round). In addition, we also modify the improved version of LEACH called MLEACH-C, so that it is applicable to the mobile sensor nodes environment. Simulation results demonstrate that the proposed protocol using PSO algorithm can improve the energy consumption of the network, achieve better network lifetime, and increase the data delivered at the base station.     

无线传感器网络的分区异构分簇协议研究

针对无线传感器网络能量受限和路由协议中节点能量消耗不均衡的问题,提出一种新的无线传感器网络的分区异构分簇协议(PHC协议).该协议的核心是将3种不同能量等级的节点根据能量的不同分别部署在不同区域,能量较高的高级节点和中间节点使用聚类技术通过簇头直接传输数据到汇聚点,能量较低的普通节点则直接传输数据到汇聚点.仿真结果表明,该协议通过对节点合理的分配部署,使簇头分布均匀,更好地均衡了节点的能量消耗,延长了网络的稳定期,提高了网络的吞吐量,增强了网络的整体性能.     

RETT-gen: A globally efficient routing protocol for wireless sensor networks by equalising sensor energy and avoiding energy holes

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. Once deployed, the sensor nodes are usually inaccessible to the user, and thus replacement of the energy resource is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the entire network. Several routing protocols have been proposed to improve the effective lifetime of the network with limited energy supply. In this paper, we propose routing based on energy–temperature transformation, RETT-gen, a scalable energy-efficient clustering and routing protocol designed for wireless sensor networks. The main goal of RETT-gen is to evenly distribute the energy load among all the sensor nodes in the network so that there are no overly-utilized sensor nodes that will run out of energy before the others. To achieve this goal, RETT-gen uses heat conductivity as a metaphor and uses the heat dissipation difference equations. In RETT-gen, we transform the expected lifetime of each sensor node to an equivalent temperature, and then by using the heat dissipation equations, we find the hottest path for sending data to the base station, which will not always be the shortest path. We evaluate the performance of the RETT-gen protocol via simulations, and compare it to the performance of well-known routing protocols (i.e. LEACH [W. Heinzelman, A. Chandrakasan, H. Balakrishnan, Energy-efficient communication protocol for wireless microsensor networks, in: Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS’00), 2000.] and EEUC [C. Li, M. Ye, G. Chen, J. Wu, An energy-efficient unequal clustering mechanism for wireless sensor networks, in: Proceedings of the International IEEE Conference on Mobile Adhoc and Sensor Systems (MASS), 2005.]). Simulation results show that by equalizing the sensor nodes energy, RETT-gen insures that the lifetime of the entire sensor network is maximized, the connectivity in a sensor network is maintained for as long as possible, and that the residual energy of the entire network is of the same order.     

Energy-Aware Link Scheduling Protocol for Wireless Sensor Networks

By reducing interferences drastically, time division multiple access (TDMA) based approaches are considered one of the most efficient solutions to optimize resources’ use. The existing protocols, however, address only the latency minimization without considering the waste of energy, which typically results from idle listening or frequent transitions of the radio module between sleep and active modes. Besides, only saturated systems are considered in these protocols, which may imply resources’ underutilization in some practical use cases. In this paper, we present an energy-aware TDMA-based link scheduling protocol, named deterministic link scheduling protocol (DLSP), designed with the aim of achieving both low energy consumption and low latency in wireless sensor networks. DLSP takes advantage of the spatial reuse of interference-free time slots using conflict graphs. Unlike earlier studies that often considered saturated traffic, we propose to relax the saturation assumption in order to maintain good performance when some of the nodes have no data to send. Thus, we propose to define the following transmission periods: a period to send the own data of the nodes and a period to relay packets. The simulation results clearly show the effectiveness of the proposed protocol, in terms of latency and energy consumption, compared to existing approaches.     

System lifetime optimization for heterogeneous sensor networks with a hub-spoke technology

As a specific area of sensor networks, wireless in-home sensor networks differ from general sensor networks in that the network has nodes with heterogeneous resources and dissimilar mobility attributes. For example, sensor with different radio coverage, energy capacity, and processing capabilities are deployed, and some of the sensors are mobile and others are fixed in position. The architecture and routing protocol for this type of heterogeneous sensor networks must be based on the resources and characteristics of their member nodes. In addition, the sole stress on energy efficiency for performance measurement is not sufficient. System lifetime is more important in this case. We propose a hub-spoke network topology that is adaptively formed according to the resources of its members. A protocol named resource oriented protocol (ROP) was developed to build the network topology. This protocol principally divides the network operation into two phases. In the topology formation phase, nodes report their available resource characteristics, based on which network architecture is optimally built. We stress that due to the existence of nodes with limitless resources, a top-down appointment process can build the architecture with minimum resource consumption of ordinary nodes. In the topology update phase, mobile sensors and isolated sensors are accepted into the network with an optimal balance of resources. To avoid overhead of periodic route updates, we use a reactive strategy to maintain route cache. Simulation results show that the hub-spoke topology built by ROP can achieve much longer system lifetime.     

An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks

Wireless sensor and actuator networks are composed of sensor and actuator nodes interconnected via wireless links. The actuators are responsible for taking prompt decisions and react accordingly to the data gathered by sensor nodes. In order to ensure efficient actions in such networks, we propose a new routing protocol that provides QoS in terms of delay and energy consumption. The network is organized in clusters supervised by CHs (Cluster-Heads), elected according to important metrics, namely the energy capability, the riches of connectivity, which is used to select the CH with high node density, and the accessibility degree regarding all the actuators. The latter metric is the distance in number of hops of sensor nodes relative to the actuator nodes. This metric enhances more the network reliability by reducing the communication delay when alerting the actuator nodes, and hence, reducing the energy consumption. To reach efficiently the actuator nodes, we design a delay and energy sensitive routing protocol based on-demand routing approach. Our protocol incurs less delay and is energy efficient. We perform an evaluation of our approach through simulations. The obtained results show out performance of our approach while providing effective gain in terms of communication delay and energy consumption.     

TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.     

SW-MAC: A Low-Latency MAC Protocol with Adaptive Sleeping for Wireless Sensor Networks

A low duty-cycle operation medium access control (MAC) protocol is very important to conserve energy for resource-constrained wireless sensor networks. Traditional sleep-wake scheduling mechanisms of MAC protocols either require periodic synchronization beacons or bring high end-to-end delivery latency due to the lack of any synchronization. In this paper, we propose a low latency MAC protocol by adjusting the sleep window (SW-MAC) considering traffic patterns. Nodes in SW-MAC transmit a sequence of scout packets to wake up the next hop and estimate the traffic arrival time from upstream nodes to sleep adaptively. For the large variance traffic, we adjust the sleep window using additive increase/multiplicative decrease mechanism. And then we design a scout-based scheduling mechanism with the above algorithms to shorten the delivery latency. Simulation results indicate that SW-MAC could significantly reduce the end-to-end packet delivery latency without sacrificing energy efficiency.     

Traffic-Aware Density-Based Sleep Scheduling and Energy Modeling for Two Dimensional Gaussian Distributed Wireless Sensor Network

Sleep scheduling of sensors in network domain is considered to be the most fundamental way of achieving higher life expectancy of wireless sensor networks. In this paper we have proposed density-based sleep scheduling strategy with traffic awareness in Gaussian distributed sensor network for minimizing energy consumption. In uniform distributed sensor network, it has been found that nodes in the nearest belt around the sink consume more energy. The reason behind is that the nodes near the sink involve more packet relaying load than the distant nodes. Consequently, the energy of these sensors get exhausted rapidly, thereby creating connectivity breaks known as energy hole. For this purpose, Gaussian distribution is used by densely deploying nodes around the sink which well-balances the relaying load. In addition, we have developed the analytical model for computing the energy consumption and coverage analysis in the sensor network. The performance of our sleep scheduling method is evaluated with respect to the Randomized Scheduling and Linear Distance-based Scheduling protocols. The simulation results of our proposed work show commendable improvement in network lifetime.     

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.     

Distributed self-learning scheduling approach for wireless sensor network

Energy constraints pose great challenges to wireless sensor network (WSN) with battery-powered nodes. But the reduction of energy consumption often introduces additional latency of data delivery. In this paper, a new distributed scheduling approach, self-learning scheduling approach (SSA), is presented in order to reduce energy consumption and to achieve low latency for WSN. This approach, extending the Q-learning method, enables nodes to learn continuous transmission parameter and sleep parameter through interacting with the WSN. We compare SSA with S-MAC protocol and DW-MAC protocol using simulations. The results show that the SSA can make nodes to learn the optimal scheduling policy gradually. The results under different work loads also exhibit that SSA performs much better than S-MAC protocol and DW-MAC protocol in terms of energy consumption and throughput. With regard to latency and maximum queue length, SSA also outperforms the other two MAC protocols in the scenarios, where the collision is serious and the work load is heavy.     

A new load balancing and data collection algorithm for energy saving in wireless sensor networks

Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy consumption among sensor nodes and can prolong the lifetime of sensor networks.