Energy efficient and low latency biased walk techniques for search in wireless sensor networks

Random walk is one of the widely used techniques for information discovery in unstructured networks like Ad hoc Wireless Networks (AWNs) and Wireless Sensor Networks (WSNs). In a random walk, instead of taking all steps uniform randomly, our idea is to modify the random walk to take some level biased steps to improve its energy efficiency and latency which are important design parameters of protocols for WSNs. The level of a node is defined as the minimum number of hops in which it can reach the sink node. We propose three protocols viz., Several Short Random Walks (SSRW) search, Random Walk with Level Biased Jumps (RWLBJ) search, and Level Biased Random Walk (LBRW) search. The proposed protocols use a combination of random and level biased steps to search for the target information. As we move from SSRW to LBRW, the percentage of biased steps increases and the percentage of random steps decreases i.e., SSRW uses fewer biased steps compared to the other proposals, LBRW uses only biased steps, and the usage of biased steps in RWLBJ is somewhere in between. We show by extensive simulations and testbed experiments that SSRW, RWLBJ, and LBRW are better choices compared to that of a pure Random walk in terms of the energy consumption and latency of search, and we also show that among the proposed protocols, LBRW and RWLBJ are the best.     

Energy-efficient forwarding in wireless sensor networks

For maximizing the energy efficiency in a wireless network, we propose two forwarding schemes termed single-link and multi-link energy-efficient forwarding that tradeoff delivery ratios against energy costs. Multi-link forwarding improves the network performance substantially by addressing multiple receivers at once during the packet forwarding process. If the first forwarding node does not receive a packet correctly, other nodes may act as backup nodes and perform the forwarding instead. By means of mathematical analyses, we derive how the energy efficiency of a forwarding path can be computed and how a forwarding tree is established. Routing cycles are explicitly taken into account and prevented by means of sequence numbers. Simulations and real-world experiments provide a comparison to other reference strategies, showing a superior performance of our forwarding scheme in terms of energy efficiency.     

Clustering of wireless sensor and actor networks based on sensor distribution and connectivity

Wireless Sensor and Actor Networks (WSANs) employ significantly more capable actor nodes that can collect data from sensors and perform application specific actions. To take these actions collaboratively at any spot in the monitored regions, maximal actor coverage along with inter-actor connectivity is desirable. In this paper, we propose a distributed actor positioning and clustering algorithm which employs actors as cluster-heads and places them in such a way that the coverage of actors is maximized and the data gathering and acting times are minimized. Such placement of actors is done by determining the k-hop Independent Dominating Set (IDS) of the underlying sensor network. Basically, before the actors are placed, the sensors pick the cluster-heads based on IDS. The actors are then placed at the locations of such cluster-heads. We further derive conditions to guarantee inter-actor connectivity after the clustering is performed. If inter-connectivity does not exist, the actors coordinate through the underlying sensors in their clusters to adjust their locations so that connectivity can be established. The performances of the proposed approaches are validated through simulations.     

A distributed energy-efficient clustering protocol for wireless sensor networks

Minimizing energy dissipation and maximizing network lifetime are among the central concerns when designing applications and protocols for sensor networks. Clustering has been proven to be energy-efficient in sensor networks since data routing and relaying are only operated by cluster heads. Besides, cluster heads can process, filter and aggregate data sent by cluster members, thus reducing network load and alleviating the bandwidth. In this paper, we propose a novel distributed clustering algorithm where cluster heads are elected following a three-way message exchange between each sensor and its neighbors. Sensor’s eligibility to be elected cluster head is based on its residual energy and its degree. Our protocol has a message exchange complexity of O(1) and a worst-case convergence time complexity of O(N). Simulations show that our algorithm outperforms EESH, one of the most recently published distributed clustering algorithms, in terms of network lifetime and ratio of elected cluster heads.     

Energy-efficient cooperative data aggregation for wireless sensor networks

Recently, cooperative communication mechanism is shown to be a promising technology to improve the transmit diversity only by a single transceiver antenna. Using this communication paradigm, multiple source nodes are able to coordinate their transmissions so as to obtain energy savings. As data aggregation is one of the most important operations in wireless sensor networks, this paper studies the energy-efficient data aggregation problem through cooperative communication. We first define the cooperative data aggregation (CDA) problem, and formally prove that this problem is NP-Hard. Due to the difficult nature of this problem, we propose a heuristic algorithm MCT for cooperative data aggregation. The theoretical analysis shows that this algorithm can reach the approximate performance ratio of 2. Moreover, the distributed implementation DMCT of the algorithm is also described. We prove that both centralized and distributed algorithms can construct the same topology for cooperative data aggregation. The experimental simulations show that the proposed algorithms will decrease the power consumption by about 12.5% and 66.3% compared with PEDAP and PEGASIS algorithms respectively.     

Distributed clustering algorithms for data-gathering in wireless mobile sensor networks

One critical issue in wireless sensor networks is how to gather sensed information in an energy-efficient way since the energy is a scarce resource in a sensor node. Cluster-based architecture is an effective architecture for data-gathering in wireless sensor networks. However, in a mobile environment, the dynamic topology poses the challenge to design an energy-efficient data-gathering protocol. In this paper, we consider the cluster-based architecture and provide distributed clustering algorithms for mobile sensor nodes which minimize the energy dissipation for data-gathering in a wireless mobile sensor network. There are two steps in the clustering algorithm: cluster-head election step and cluster formation step. We first propose two distributed algorithms for cluster-head election. Then, by considering the impact of node mobility, we provide a mechanism to have a sensor node select a proper cluster-head to join for cluster formation. Our clustering algorithms will achieve the following three objectives: (1) there is at least one cluster-head elected, (2) the number of cluster-heads generated is uniform, and (3) all the generated clusters have the same cluster size. Last, we validate our algorithms through an extensive experimental analysis with Random Walk Mobility (RWM) model, Random Direction Mobility (RDM) model, and a Simple Mobility (SM) model as well as present our findings.     

Auction-based adaptive sensor activation algorithm for target tracking in wireless sensor networks

Due to the severe resource constraints in wireless sensor networks (WSNs), designing an efficient target tracking algorithm for WSNs in terms of energy efficiency and high tracking quality becomes a challenging issue. WSNs usually provide centralized information, e.g., the locations and directions of a target, choosing sensors around the target, etc. However, some ready strategies may not be used directly because of high communication costs to get the responses for tracking tasks from a central server and low quality of tracking. In this paper, we propose a fully distributed algorithm, an auction-based adaptive sensor activation algorithm (AASA), for target tracking in WSNs. Clusters are formed ahead of the target movements in an interesting way where the process of cluster formation is due to a predicted region (PR) and cluster members are chosen from the PR via an auction mechanism. On the basis of PR calculation, only the nodes in the PR are activated and the rest of the nodes remain in the sleeping state. To make a trade-off between energy efficiency and tracking quality, the radius of PR and the number of nodes are adaptively adjusted according to current tracking quality. Instead of fixed interval (usually used in existing work), tracking interval is also dynamically adapted. Extensive simulation results, compared to existing work, show that AASA achieves high performance in terms of quality of tracking, energy efficiency, and network lifetime.     

无线传感器网络路由协议分析与改进

定向扩散(directed diffusion,DD)协议的兴趣扩散和发送探测分组数据阶段,采用的洪泛方式能量开销较大.先对定向扩散协议进行研究分析,提出利用节点的区域信息控制兴趣数据包的转发和通过最佳跳数值控制探测数据的扩散范围.最后通过仿真验证改进的定向扩散协议具有更好的节能性和适应性.     

Application-aware integration of data collection and power management in wireless sensor networks

Sensors are typically deployed to gather data about the physical world and its artifacts for a variety of purposes that range from environment monitoring, control, to data analysis. Since sensors are resource constrained, often sensor data is collected into sensor databases that reside at (more powerful) servers. A natural tradeoff exists between resources (bandwidth, energy) consumed and the quality of data collected at the server. Blindly transmitting sensor updates at a fixed periodicity to the server results in a suboptimal solution due to the differences in stability of sensor values and due to the varying application needs that impose different quality requirements across sensors. In order to adapt to these variations while at the same time optimizing the energy consumption of sensors, this paper proposes three different models and corresponding data collection protocols. We analyze all three models with a Markov state machine formulation, and either derive closed forms for the operation point of the data collection application or suggest algorithms for estimating this operating point to achieve a minimal energy consumption. We observe that the operating point depends on environmental characteristics and application quality requirements, which the proposed algorithms aim to accommodate. Our experimental results show significant energy savings compared to the naive approach to data collection.     

Energy efficient and QoS based routing protocol for wireless sensor networks

The increasing demand for real-time applications in Wireless Sensor Networks (WSNs) has made the Quality of Service (QoS) based communication protocols an interesting and hot research topic. Satisfying Quality of Service (QoS) requirements (e.g. bandwidth and delay constraints) for the different QoS based applications of WSNs raises significant challenges. More precisely, the networking protocols need to cope up with energy constraints, while providing precise QoS guarantee. Therefore, enabling QoS applications in sensor networks requires energy and QoS awareness in different layers of the protocol stack. In many of these applications (such as multimedia applications, or real-time and mission critical applications), the network traffic is mixed of delay sensitive and delay tolerant traffic. Hence, QoS routing becomes an important issue. In this paper, we propose an Energy Efficient and QoS aware multipath routing protocol (abbreviated shortly as EQSR) that maximizes the network lifetime through balancing energy consumption across multiple nodes, uses the concept of service differentiation to allow delay sensitive traffic to reach the sink node within an acceptable delay, reduces the end to end delay through spreading out the traffic across multiple paths, and increases the throughput through introducing data redundancy. EQSR uses the residual energy, node available buffer size, and Signal-to-Noise Ratio (SNR) to predict the best next hop through the paths construction phase. Based on the concept of service differentiation, EQSR protocol employs a queuing model to handle both real-time and non-real-time traffic.     

无线传感器网络LEACH协议的研究与改进

在分析了无线传感器网络中分层路由LEACH算法的基础上,提出了一种新型选择簇首节点的方法,并通过matlab对改进后的LEACH算法进行了仿真,仿真结果显示改进后的LEACH算法在网络生命周期和网络能量消耗两方面比LEACH算法有很大的提高。     

Satisfying the target network lifetime in wireless sensor networks

Generally, the lifetime of a wireless sensor network (WSN) is defined as the duration until any sensor node dies due to battery exhaustion. If the traffic load is not properly balanced, the batteries of some sensor nodes may be depleted quickly, and the lifetime of the WSN will be shortened. While many energy-efficient routing schemes have been proposed for WSNs, they focus on maximizing the WSN lifetime. In this paper, we propose a scheme that satisfies a given ‘target’ lifetime. Because energy consumption depends on traffic volume, the target lifetime cannot be guaranteed through energy-efficient routing alone. We take an approach that jointly optimizes the sensing rate (i.e., controlling the sensor-traffic generation or duty cycle) and route selection. Satisfying the target lifetime while maximizing the sensing rate is a NP-hard problem. Our scheme is based on a simple Linear Programming (LP) model and clever heuristics are applied to compute a near-optimal result from the LP solution. We prove that the proposed scheme guarantees a 1/2-approximation to the optimal solution in the worst case. The simulation results indicate that the proposed scheme achieves near-optimality in various network configurations.     

AWARE: Activity aware maintenance of communication structures for wireless sensor networks

Energy efficiency and high data relevancy are crucial for wireless sensor network applications; challenges usually tackled by network clustering or event-driven techniques focused only on the performance of clusterheads or too restricted to specific applications. In contrast, this paper formalizes the combined NP-Complete problem of event-driven network clustering. We hereby propose AWARE, an innovative distributed activity-aware and energy-efficient technique for the maintenance of network’s communication structure. AWARE groups active nodes together, thus making clusterheads report efficiently with only relevant data. On top of several theoretical proves, extensive performance studies validate AWARE’s effectiveness and efficiency.     

Adaptive compressive sensing based sample scheduling mechanism for wireless sensor networks

Sample scheduling is a crucial issue in wireless sensor networks (WSNs). The design objectives of efficient sample scheduling are in general two-folds: to achieve a low sample rate and also high sensing quality. Recently, compressive sensing (CS) has been regarded as an effective paradigm for achieving high sensing quality at a low sample rate. However, most existing work in the area of CS for WSNs use fixed sample rates, which may make sensor nodes in a WSN unable to capture significant changes of target phenomenon, unless the sample rate is sufficiently high, and thus degrades the sensing quality. In this paper, to pursue high sensing quality at low sample rate, we propose an adaptive CS based sample scheduling mechanism (ACS) for WSNs. ACS estimates the minimum required sample rate subject to given sensing quality on a per-sampling-window basis and accordingly adjusts sensors’ sample rates. ACS can be useful in many applications such as environment monitoring, and spectrum sensing in cognitive sensor networks. Extensive trace-driven experiments are conducted and the numerical results show that ACS can obtain high sensing quality at low sample rate.     

Topology control for delay-constraint data collection in wireless sensor networks

Data collection is one of the most important operations in wireless sensor networks. Many practical applications require the real-time data transmission, such as monitoring, tracking, etc. In this paper, we import and define the topology control problem for delay-constraint data collection (TDDC), and then formalize this problem into an integer programming problem. As NP-Hardness of this problem, we present a load-aware power-increased topology control algorithm (namely LPTC) to heuristically solve the problem. The theoretical analysis shows that this algorithm can reach O(1)-approximation ratio for the linear networks. And we also analyze the impact of the delay-constraint on the worst-case for the planar networks. Moreover, this paper designs two localized algorithms, called as SDEL and DDEL, based on the area division for TDDC problem. The experimental results show that LPTC algorithm can save at least 17% power consumptions compared with HBH algorithm in many situations.     

Design and analysis of a multi-candidate selection scheme for greedy routing in wireless sensor networks

Sleep and wake-up scheduling of sensor nodes is an efficient solution to prolong the network lifetime. However, existing scheduling algorithms may significantly decrease the number of active nodes so that the network may be intermittently connected. In such networks, traditional geographic routing protocols are inappropriate to obtain low latency routes due to route discovery and data forwarding latency. In this paper, we propose a novel multi-candidate selection (MCS) scheme for greedy routing that makes the best effort to find minimum latency routes in the sensor networks. In MCS, each source node sends an RREQ to a list of first wake-up forwarder candidates and selects a route with minimum estimated delivery latency based on their replies. The route found by MCS may be longer than that of distance-based greedy forwarding (DGF) (Finn, 1987). Hence, we introduce a latency-adaptive distance-based multi-candidate selection scheme for greedy forwarding to find routes with a small number of hops and acceptable delivery latency. Probabilistic analysis and simulation results demonstrate that MCS increases the routing performance significantly compared with DGF and ODML (Su et al., 2008) in terms of delivery latency.     

Energy-efficient adaptive sensor scheduling for target tracking in wireless sensor networks

Sensor scheduling is essential to collaborative target tracking in wireless sensor networks (WSNs). In the existing works for target tracking in WSNs, such as the information-driven sensor query (IDSQ), the tasking sensors are scheduled to maximize the information gain while minimizing the resource cost based on the uniform sampling intervals, ignoring the changing of the target dynamics and the specific desirable tracking goals. This paper proposes a novel energyefficient adaptive sensor scheduling approach that jointly selects tasking sensors and determines their associated sampling intervals according to the predicted tracking accuracy and tracking energy cost. At each time step, the sensors are scheduled in alternative tracking mode, namely, the fast tracking mode with smallest sampling interval or the tracking maintenance mode with larger sampling interval, according to a specified tracking error threshold. The approach employs an extended Kalman filter (EKF)-based estimation technique to predict the tracking accuracy and adopts an energy consumption model to predict the energy cost. Simulation results demonstrate that, compared to a non-adaptive sensor scheduling approach, the proposed approach can save energy cost significantly without degrading the tracking accuracy.     

An asynchronous MAC protocol for wireless sensor networks

The MAC protocol for wireless sensor network plays a very important role in the control of energy consumption. It is a very important issue to effectively utilize power under the condition of limited energy. The most energy-wasting part of the MAC protocol for wireless sensor network is at the idling condition. Therefore it is crucial for power saving to be able to turn off the signal transducer of the wireless network when the equipment is idling. Pattern-MAC (PMAC) allows sensors that did not transfer for a long period of time to quickly enter a dormant state, so that the problem of sensor overhearing can be greatly improved, and the whole network structure can fully respond to the actual transfer rate without too much energy consumption, but this type of design requires precise time synchronization mechanism. Achieving time synchronization is a very energy consuming and very expensive mechanism in the sensor network structure, achieving the goal is coupled with excess energy consumption and reduction of the lifespan of the sensor. Additionally, the exchange action with the neighboring pattern after each cycle, not only generates additional energy consumption for data transfer, but is also accompanied by factors such as competition, collision and pattern exchange failure. We propose an asynchronous MAC protocol (AMAC) in this paper and expect to improve the problem of energy wasting and time synchronization due to sleeping schedule exchange under the PMAC basic protocol.     

On the efficient and fast response for sensor deployment in sparse wireless sensor networks

Wireless sensor networks have recently become new techniques and popular research issues. A wireless sensor network consists of a large number of sensor nodes that have the capabilities of sensing, computing and wireless transmission. Wireless sensor networks (namely WSNs) assist people in working under dangerous environments, provide long-term target observations and track on moving objects. Consequently, WSNs decrease risk and increase efficiency. Although WSNs have been studied extensively, several problems should be addressed, such as sensor-deployment policy, data aggregation/fusion issue, and data transmission issue. An efficient sensor-deployment approach could decrease cost, minimize transmission delay and reduce time complexity. Most studies have proposed the probability-based sensor-deployment policies to monitor an overall area. However, not the entire network is interested to be sensed/monitored. Monitoring of an entire area brings several disadvantages: (1) high cost of placing large number of sensors, (2) long delay of data transmission, (3) slow response and (4) unnecessary data aggregation. Furthermore, previous works were lack of considering the difference between the sensing and the transmission radii, and then yield inaccurate analysis. This work thus proposes an efficient sensor placement approach (namely ESP) for a sparse interested area with considering of obstructers that block the data transmission and sensing signal. Additionally, the issue of different radii of sensing and transmission is analyzed in detail. Numerical results demonstrate that the proposed ESP approach requires the least number of sensor nodes under various network sizes and different number of obstacles. Simulation results indicate that the number of sensor nodes decreases when the sensing or transmission radius increases. The running time of ESP, O(K²), is also analyzed, which is better than that of the probability-based approaches, O(N²), where K is the number of interested grids and N is the number of grids.     

无线传感器网络动态重传算法

无线传感器网络路由协议通过点到点的重传来提高数据传输的可靠性,其重传机制没有考虑不同业务数据的可靠性需求差异,统一设定一个静态的最大重传次数。本文提出了一种动态重传算法,为每种业务分别根据其可靠性需求动态设定最大重传次数。对于较低可靠性需求的业务,相比于传统重传机制减少了重传次数。仿真表明动态重传算法能有效降低网络能耗。