An adaptive in-network aggregation operator for query processing in wireless sensor networks

A wireless sensor network (WSN) is composed of tens or hundreds of spatially distributed autonomous nodes, called sensors. Sensors are devices used to collect data from the environment related to the detection or measurement of physical phenomena. In fact, a WSN consists of groups of sensors where each group is responsible for providing information about one or more physical phenomena (e.g., group for collecting temperature data). Sensors are limited in power, computational capacity, and memory. Therefore, a query engine and query operators for processing queries in WSNs should be able to handle resource limitations such as memory and battery life. Adaptability has been explored as an alternative approach when dealing with these conditions. Adaptive query operators (algorithms) can adjust their behavior in response to specific events that take place during data processing. In this paper, we propose an adaptive in-network aggregation operator for query processing in sensor nodes of a WSN, called ADAGA (ADaptive AGgregation Algorithm for sensor networks). The ADAGA adapts its behavior according to memory and energy usage by dynamically adjusting data-collection and data-sending time intervals. ADAGA can correctly aggregate data in WSNs with packet replication. Moreover, ADAGA is able to predict non-performed detection values by analyzing collected values. Thus, ADAGA is able to produce results as close as possible to real results (obtained when no resource constraint is faced). The results obtained through experiments prove the efficiency of ADAGA.     

Optimizing in-network aggregate queries in wireless sensor networks for energy saving

This study proposes a method of in-network aggregate query processing to reduce the number of messages incurred in a wireless sensor network. When aggregate queries are issued to the resource-constrained wireless sensor network, it is important to efficiently perform these queries. Given a set of multiple aggregate queries, the proposed approach shares intermediate results among queries to reduce the number of messages. When the sink receives multiple queries, it should be propagated these queries to a wireless sensor network via existing routing protocols. The sink could obtain the corresponding topology of queries and views each query as a query tree. With a set of query trees collected at the sink, it is necessary to determine a set of backbones that share intermediate results with other query trees (called non-backbones). First, it is necessary to formulate the objective cost function for backbones and non-backbones. Using this objective cost function, it is possible to derive a reduction graph that reveals possible cases of sharing intermediate results among query trees. Using the reduction graph, this study first proposes a heuristic algorithm BM (standing for Backbone Mapping). This study also develops algorithm OOB (standing for Obtaining Optimal Backbones) that exploits a branch-and-bound strategy to obtain the optimal solution efficiently. This study tests the performance of these algorithms on both synthesis and real datasets. Experimental results show that by sharing the intermediate results, the BM and OOB algorithms significantly reduce the total number of messages incurred by multiple aggregate queries, thereby extending the lifetime of sensor networks.     

Efficient distributed data scheduling algorithm for data aggregation in wireless sensor networks

With the rapid development of applications for wireless sensor networks, efficient data aggregation methods are becoming increasingly emphasized. Many researchers have studied the problem of reporting data with minimum energy cost when data is allowed to be aggregated many times. However, some aggregation functions used to aggregate multiple data into one packet are unrepeatable; that is, every data is aggregated only at most once. This problem motivated us to study reporting data with minimum energy cost subject to that a fixed number of data are allowed to be aggregated into one packet and every data is aggregated at most once. In this paper, we propose novel data aggregation and routing structures for reporting generated data. With the structures, we study the problem of scheduling data to nodes in the networks for data aggregation such that the energy cost of reporting data is minimized, termed MINIMUM ENERGY-COST DATA-AGGREGATION SCHEDULING. In addition, we show that MINIMUM ENERGY-COST DATA-AGGREGATION SCHEDULING is NP-complete. Furthermore, a distributed data scheduling algorithm is proposed accordingly. Simulations show that the proposed algorithm provides a good solution for MINIMUM ENERGY-COST DATA-AGGREGATION SCHEDULING.     

Performance modeling of the LEACH protocol for mobile wireless sensor networks

In many wireless sensor network applications, nodes are mobile, while many protocols proposed for these networks assume a static network. Thus, it is important to evaluate if a traditional protocol designed for a static network can tolerate different levels of mobility. This paper provides an analytic model to investigate the effect of mobility on a well-known cluster-based protocol, LEACH. The model evaluates data loss after construction of the clusters due to node mobility, which can be used to estimate a proper update interval to balance the energy and data loss ratio. Thus, the results can help the network designer to adjust the topology update interval given a value of acceptable data loss threshold. A practical approach to increase the mobility tolerance of the protocol is applying a buffer zone to the transmission ranges of the nodes. The model is extended in order to consider the effect of buffer zone. To validate the analytic evaluations, extensive simulations are conducted and correctness of the evaluations is tightly verified.     

An application adaptation layer for wireless sensor networks

In wireless sensor networks, poor performance or unexpected behavior may be experienced for several reasons, such as trivial deterioration of sensing hardware, unsatisfactory implementation of application logic, or mutated network conditions. This leads to the necessity of changing the application behavior after the network has been deployed. Such flexibility is still an open issue as it can be achieved either at the expense of significant energy consumption or through software complexity. This paper describes an approach to adapt the behavior of running applications by intercepting the calls made to the operating system services and changing their effects at run-time. Customization is obtained through small fragments of interpreted bytecode, called adaptlets, injected into the network by the base station. Differently from other approaches, where the entire application is interpreted, adaptlets are tied only to specific services, while the bulk of the application is still written in native code. This makes our system able to preserve the compactness and efficiency of native code and to have little impact on the overall application performance. Also, applications must not be rewritten because the operating system interfaces are unaffected. The adaptation layer has been implemented in the context of TinyOS using an instruction set inspired to the Java bytecode. Examples that illustrate the programming of the adaptation layer are presented together with their experimental validation.     

An agent-assisted QoS-based routing algorithm for wireless sensor networks

Existing routing algorithms are not effective in supporting the dynamic characteristics of wireless sensor networks (WSNs) and cannot ensure sufficient quality of service in WSN applications. This paper proposes a novel agent-assisted QoS-based routing algorithm for wireless sensor networks. In the proposed algorithm, the synthetic QoS of WSNs is chosen as the adaptive value of a Particle Swarm Optimization algorithm to improve the overall performance of network. Intelligent software agents are used to monitor changes in network topology, network communication flow, and each node's routing state. These agents can then participate in network routing and network maintenance. Experiment results show that the proposed algorithm can ensure better quality of service in wireless sensor networks compared with traditional algorithms.     

无线传感器网络中数据查询处理算法研究

提出一种改进的定向扩散路由,将传感器网络分簇,查询兴趣由sink节点发,只在各簇头节点扩散,簇头以广播的方式在簇内发散兴趣消息,簇成员将感知数据传送到簇头节点,簇头负责将收到的数据进行融合后传到sink节点。仿真结果表明,改进后的查询路由比典型的查询路由定向扩散具有更高的能量有效性和更低的时延,能较好地延长网络的生命周期,提高了传感器网络数据查询处理效率。     

无线传感器网络中一种能量有效的分簇算法

传感器网络中簇头与基站的通信方式可分为两种:多跳和单跳.如果采用多跳方式,靠近基站的簇头因传送数据较多而导致较早死亡;而在单跳方式中,远离基站的簇头因传送数据能耗太高而很快死亡.针对上述问题,提出一种基于非均衡分簇的数据收集算法,使靠近基站的簇的大小小于远离基站的簇.仿真实验表明,非均衡分簇的数据收集算法能有效地延长网络的生命周期.     

An energy-efficient protocol for data gathering and aggregation in wireless sensor networks

Data gathering is a major function of many applications in wireless sensor networks (WSNs). The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirement of applications/users such as sensing area coverage. In this paper, we propose a novel hierarchical clustering protocol (DEEG) for long-lived sensor network. DEEG achieves a good performance in terms of lifetime by minimizing energy consumption for in-network communications and balancing the energy load among all the nodes, the proposed protocol achieves a good performance in terms of network lifetime. DEEG can also handle the energy hetergenous capacities and guarantee that out-network communications always occur in the subregion with high energy reserved. Furthermore, it introduces a simple but efficient approach to cope with the area coverage problem. We evaluate the performance of the proposed protocol using a simple temperature sensing application. Simulation results show that our protocol significantly outperforms LEACH and PEGASIS in terms of network lifetime and the amount of data gathered.

Optimal wake-up scheduling of data gathering trees for wireless sensor networks

In order to gather sensor data, a data gathering tree is commonly created as a subnetwork of a wireless sensor network. Power conservation is of paramount importance in such networks, and using periodic sleep–wake cycles for sensor nodes is one of the most effective methods for power conservation. This paper addresses the problem of scheduling the sleep–wake cycles of nodes in a data gathering tree under deadline constraints. After formally modeling the problem being addressed, an optimal wake-up frequency assignment (OWFA) algorithm, which takes into account the data rate at each node and the total permitted delay, is proposed. The results of simulations under various conditions showed that OWFA consumed about 8.6%∼24.3% less average power, and thus resulted in a 7.4%∼26.0% longer network lifetime, than a previously proposed method that did not consider individual data rates.     

An energy-driven unequal clustering protocol for heterogeneous wireless sensor networks

Due to the limitation of energy resources, energy efficiency is a key issue in wireless sensor networks (WSNs). Clustering is proved to be an important way to realize hierarchical topology control, which can improve the scalability and prolong the lifetime of wireless sensor networks. In this paper, an energy-driven unequal clustering protocol (EDUC) for heterogeneous wireless sensor networks is proposed. EDUC includes an unequal clustering algorithm and an energy-driven adaptive cluster head rotation method. The unequal size of clusters can balance the energy consumption among clusters, and the energy-driven cluster head rotation method can achieve the balance of energy consumption among nodes within a cluster, which reduces the waste of energy. Simulation experiments show that EDUC balances the energy consumption well among the cluster heads and prolongs the network lifetime.     

基于模式码比较的数据融合和认证协议

致力于如何实现无线传感器网络的安全数据融合,提出了一种基于模式码的安全数据融合协议——SPDAA(Secure pattern-based data aggregation and authentication).该方案在节点的感应阶段采用差值比较法确定参与会话的节点,并采用基于两跳的认证技术在数据融合阶段进行数据(模式码)的认证,保证数据的完整性,避免了由于盲目拒绝虚假节点而造成的数据丢失.同时该方案考虑增加能量因子,有效地均衡了整个网络的能耗.仿真结果表明:SPDAA能够有效避免重要数据的丢失,保证网络数据高效安全性,均衡网络能耗,延长网络生存时间.     

Fault-tolerant and efficient data propagation in wireless sensor networks using local,additional network information

We propose a new data dissemination protocol for wireless sensor networks, that basically pulls some additional knowledge about the network in order to subsequently improve data forwarding towards the sink. This extra information is still local, limited and obtained in a distributed manner. This extra knowledge is acquired by only a small fraction of sensors thus the extra energy cost only marginally affects the overall protocol efficiency. The new protocol has low latency and manages to propagate data successfully even in the case of low densities. Furthermore, we study in detail the effect of failures and show that our protocol is very robust. In particular, we implement and evaluate the protocol using large scale simulation, showing that it significantly outperforms well known relevant solutions in the state of the art.     

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.     

An improved transport layer protocol for wireless sensor networks

Wireless sensor networks (WSNs) are a kind of communication networks having independent sensor nodes that form multi-hop ad hoc network to transfer data. In the past few years, various transport control protocols in wireless sensor networks (WSNs) have been developed and proposed in the literature. In this paper, we have analyzed pump slowly, fetch quickly (PSFQ) protocol and presented an improved transport layer protocol for wireless sensor networks. The improved protocol has been analyzed based on various factors such as average latency and average error tolerance and it is found that the proposed protocol is better than PSFQ in terms of these factors.     

Adaptive holistic scheduling for query processing in sensor networks

We observe two deficiencies of current query processing and scheduling techniques for sensor networks: (1) A query execution plan does not adapt to the hardware characteristics of sensing devices; and (2) the data communication schedule of each node is not adapted to the query runtime workload. Both cause time and energy waste in query processing in sensor networks. To address this problem, we propose an adaptive holistic scheduler, AHS, to run on each node in a wireless sensor network. AHS schedules both the query evaluation and the wireless communication operations, and is able to adapt the schedule to the runtime dynamics of these operations on each node. We have implemented AHS and tested it on real motes as well as in simulation. Our results show that AHS improves the performance of query processing in various dynamic settings.     

Novel sensor scheduling and energy-efficient quantization for tracking target in wireless sensor networks

This paper focuses on sensor scheduling and information quantization issues for target tracking in wireless sensor networks (WSNs). To reduce the energy consumption of WSNs, it is essential and effective to select the next tasking sensor and quantize the WSNs data. In existing works, sensor scheduling’ goals include maximizing tracking accuracy and minimizing energy cost. In this paper, the integration of sensor scheduling and quantization technology is used to balance the tradeoff between tracking accuracy and energy consumption. The main characteristic of the proposed schemes includes a novel filtering process of scheduling scheme, and a compressed quantized algorithm for extended Kalman filter (EKF). To make the algorithms more efficient, the proposed platform employs a method of decreasing the threshold of sampling intervals to reduce the execution time of all operations. A real tracking system platform for testing the novel sensor scheduling and the quantization scheme is developed. Energy consumption and tracking accuracy of the platform under different schemes are compared finally.     

传感器网络中自顶向下的轮廓监控算法

根据无线传感器网络的特殊性质,提出了自顶向下的轮廓监控算法.利用为节点分配的超立方,可以有效地对轮廓监控过程中的数据进行过滤,从而高效地完成轮廓的维护工作.仿真实验结果表明,该算法能有效地避免无用的数据传输.减少节点的能量消耗,从而延长传感器网络的使用寿命.     

A smart node architecture for adding mobility to wireless sensor networks

Adding a few mobile nodes into the conventional wireless sensor networks can greatly improve the sensing and control capabilities of the networks and can help researchers solve many challenges such as network deployment and repair. This paper presents an enhanced node architecture for adding controlled mobility to wireless sensor networks. The structural model, the power model and the networking model of the proposed mobile node have been built respectively for better node control. And it provides a novel robotic platform for experimental research in hybrid sensor networks or other distributed measurement and control systems. A testbed has finally been created for validating the basic functions of the proposed mobile sensor node. The results of a coverage experiment show that the mobile node can provide additional support for network coverage and can ensure that the sensor network will work properly in undesirable environments.