MR-MC无线传感器网络基于森林的数据收集研究

传感器网络的部署环境以及节点自身的限制,导致传感器节点很容易出现故障并且难以维护。在基于树的数据收集过程中,节点故障或者链路拥塞会造成较高的通信时延,甚至数据丢失。针对该问题提出以森林作为路由结构进行数据收集的策略。首先提出一个建立森林的算法,然后以多棵树作为路由结构进行数据收集。理论分析和实验结果表明,提出的方法可以有效减少数据收集过程中的数据丢失,在有25个故障节点的情况下,3棵树的森林路由结构收集的数据量与基于连通支配集的路由树收集的数据量相比多55%,并且能降低数据收集的延迟。     

Capacity of data collection in randomly-deployed wireless sensor networks

Data collection is one of the most important functions provided by wireless sensor networks. In this paper, we study theoretical limitations of data collection and data aggregation in terms of delay and capacity for a wireless sensor network where n sensors are randomly deployed. We consider different communication scenarios such as with single sink or multiple sinks, regularly-deployed or randomly-deployed sinks, with or without aggregation. For each scenario, we not only propose a data collection/aggregation method and analyze its performance in terms of delay and capacity, but also theoretically prove whether our method can achieve the optimal order (i.e., its performance is within a constant factor of the optimal). Particularly, with a single sink, the capacity of data collection is in order of \Uptheta(W)\Uptheta(W) where W is the fixed data-rate on individual links. With k regularly deployed sinks, the capacity of data collection is increased to \Uptheta(kW)\Uptheta(kW) when k=O(\fracnlogn)k=O\left({\frac{n}{\log n}}\right) or \Uptheta(\fracnlognW)\Uptheta\left({\frac{n}{\log n}}W\right) when k=\Upomega(\fracnlogn)k=\Upomega\left({\frac{n}{\log n}}\right). With k randomly deployed sinks, the capacity of data collection is between \Uptheta(\fracklogkW)\Uptheta\left({\frac{k}{\log k}}W\right) and \Uptheta(kW)\Uptheta(kW) when k=O(\fracnlogn)k=O\left({\frac{n}{\log n}}\right) or \Uptheta(\fracnlognW)\Uptheta\left({\frac{n}{\log n}}W\right) when k=w(\fracnlogn)k=\omega\left({\frac{n}{\log n}}\right). If each sensor can aggregate its receiving packets into a single packet to send, the capacity of data collection with a single sink is also increased to \Uptheta(\fracnlognW)\Uptheta\left({\frac{n}{\log n}}W\right).     

基于移动sink的无线传感器网络数据采集方案

对无线传感器网络的数据采集问题进行了研究,提出了一种基于可移动sink节点的数据采集方案DCSR。DCSR包括2个阶段,第1个阶段根据传感器节点的分布情况确定一批采集点,第2个阶段使用量子遗传算法求解出经过采集点的最短回路。计算完之后,sink沿着这条回路运动,周期性进行数据采集。理论分析和仿真实验表明,DCSR的性能较好,采集的数据量也更多。     

Towards trusted and energy-efficient data collection in unattended wireless sensor networks

Wireless Networks - The Internet of Things (IoT), including wireless sensors, is one of the highly anticipated contributors to big data; therefore, avoiding misleading or forged data gathering in...     

On reducing delay in mobile data collection based wireless sensor networks

In a wireless sensor network, battery power is a limited resource on the sensor nodes. Hence, the amount of power consumption by the nodes determines the node and network lifetime. This in turn has an impact on the connectivity and coverage of the network. One way to reduce power consumed is to use a special mobile data collector (MDC) for data gathering, instead of multi-hop data transmission to the sink. The MDC collects the data from the nodes and transfers it to the sink. Various kinds of MDC approaches have been explored for different assumptions and constraints. But in all the models proposed, the data latency is usually high, due to the slow speed of the mobile nodes. In this paper, we propose a new model of mobile data collection that reduces the data latency significantly. Using a combination of a new touring strategy based on clustering and a data collection mechanism based on wireless communication, we show that the delay can be reduced significantly without compromising on the advantages of MDC based approach. Using extensive simulation studies, we analyze the performance of the proposed approach and show that the packet delay reduces by more than half when compared to other existing approaches.     

Locally scheduled packet bursting for data collection in wireless sensor networks

In wireless sensor networks, the many-to-one data communication pattern induces high collision losses as multiple transmissions cause contention and interference along the paths from sources to the sink. This paper proposes a low-overhead MAC layer solution to address the high contention problem to improve system throughput and reduce energy consumption. Periods of burst transmissions with reduced contention from neighboring nodes are exploited to efficiently clear up backlogged queues and improve the performance of CSMA. Through analytical modeling we characterize the expected performance improvement. Using extensive simulations on ns-2 and experiments on the 49-node sensor network testbed (Kansei) running TinyOS, we show that the proposed scheme can increase the throughput by up to a factor of four.     

Distributed wake-up scheduling for data collection in tree-based wireless sensor networks

In a multi-hop wireless network, a conventional way of defining interference neighbors is to prohibit a node from using the same slot/code as those of its 1-hop and 2-hop neighbors. However, for data collection in a wireless sensor network, since the set of communication nodes is limited and the transmission directions are toward the sink, we show that a less strict set of interference neighbors can be defined. Based on this observation, we develop an efficient distributed wake-up scheduling scheme for data collection in a sensor network that achieves both energy conservation and low reporting latency.     

An efficient data collection and load balance algorithm in wireless sensor networks

The nature of multi-hop data transmission in wireless sensor network will cause serious load unbalance which will produce great restrains in related applications considering the limited energy resource. Relative load balance algorithms are usually performed inside the clusters without considering about the energy consumption of the whole network. A cluster-based balanced energy consumption algorithm (BECA) is proposed by introducing in multiple inter-cluster links to distribute the load, so as to achieve global load balance. Moreover, an efficient data collecting mechanism is proposed based on BECA to improve the traffic balance further. Simulating results based on NS2 show that BECA can obtain better balance properties and prolong the network lifetime effectively.

     

Opportunistic data collection for disconnected wireless sensor networks by mobile mules

This paper considers a field with a number of isolated wireless sensor networks served by some mobile mules and base stations (BSs). Sensing data needs to be carried by mobile mules to BSs via opportunistic contact between them. Also, such contact may not be frequent. Thus there are four types of communications in this environment: (i) inter-node communications within a WSN, (ii) opportunistic WSN-to-mule communications, (iii) opportunistic mule-to-mule communications, and (iv) opportunistic mule-to-BS communications. In such disconnected WSNs, since sensors’ memory spaces are limited and data collection from isolated WSNs to mules and then to BSs relies on opportunistic communications in the sense that contact between these entities is occasional, storing and collecting higher-priority data is necessary. Therefore, there are two critical issues to be addressed: the data storage management in each isolated WSN and opportunistic data collection between these entities. We address the storage management problem by modeling the limited memory spaces of a WSN’s sensor nodes as a distributed storage system. Assuming that there is a sink in the WSN that will be visited by mobile mules occasionally, we address three issues: (i) how to buffer sensory data to reduce data loss due to a shortage of storage spaces, (ii) if dropping of data is inevitable, how to avoid higher-priority data from being dropped, and (iii) how to manage the data nearby the sink to facilitate the downloading jobs of mules when the downloading time is unpredictable. We propose a Distributed Storage Management (DSM) strategy based on a novel shuffling mechanism similar to heap sort. It allows nodes to exchange sensory data with neighbors efficiently in a distributed manner. For the opportunistic data collection problem, based on a utility model, we then develop an Opportunistic Data Exchange (ODE) strategy to guide two mules to exchange data that would lead to a higher reward. To the best of our knowledge, this is the first work addressing distributed storage strategy for isolated WSNs with opportunistic communications using mobile mules. We conduct extensive simulations to investigate the merit of DSM and ODE. The simulation results indicate that the level of data importance collected by our DSM is very close to a global optimization and our ODE could facilitate delivery of important data to BSs through mules. We also implement these strategies in a real sensor platform, which demonstrates that the simple and lightweight protocols can achieve our goals.     

Energy-efficiency clustering protocol in wireless sensor networks

The conventional clustering method has the unique potential to be the framework for power-conserving ad hoc networks. In this environment, studies on energy-efficient strategies such as sleeping mode and redirection have been reported, and recently some have even been adopted by some standards like Bluetooth and IEEE 802.11. However, consider wireless sensor networks. The devices employed are power-limited in nature, introducing the conventional clustering approach to the sensor networks provides a unique challenge due to the fact that cluster-heads, which are communication centers by default, tend to be heavily utilized and thus drained of their battery power rapidly. In this paper, we introduce a re-clustering strategy and a redirection scheme for cluster-based wireless sensor networks in order to address the power-conserving issues in such networks, while maintaining the merits of a clustering approach. Based on a practical energy model, simulation results show that the improved clustering method can obtain a longer lifetime when compared with the conventional clustering method.     

Hybrid data dissemination protocol (HDDP) for wireless sensor networks

Wireless Networks - Wireless sensor networks (WSNs) are often used for monitoring environmental conditions. One of the most important tasks in a WSN is to gather sensed data for the users to...     

Double Q-learning-based adaptive trajectory selection for energy-efficient data collection in wireless sensor networks

This paper proposes a novel distributed stochastic routing strategy using mobile sink based on double Q-learning algorithm to improve the network performance in wireless sensor network with uncertain communication links. Furthermore, in order to extend network lifetime, a modified leach-based clustering technique is proposed. To balance the energy dissipation between nodes, the selected cluster head nodes are then rotated based on the newly suggested threshold energy value. The simulation results demonstrate that the proposed algorithms outperform the QWRP, QLMS, ESRP and HACDC in terms of network lifetime by 18.33%, 35.1%, 39.7% and 44.7%, respectively. Moreover, the proposed algorithms considerably enhances the learning rate and hence reduces the data collection latency.     

Distributed semi‐adaptive compressive sensing data collection in wireless sensor networks

Recently, many researches have been conducted to exploit the compressive sensing (CS) theory in wireless sensor networks (WSNs). One of the most important goals in CS is to prolong the lifetime of WSNs. But CS may suffer from some errors during the reconstruction phase. In addition, an adaptive version of CS named Bayesian compressive sensing has been studied to improve the reconstruction accuracy in WSNs. This paper investigates these adaptive methods and identifies their associated problems. Finally, a distributed and semi‐adaptive CS‐based data collection method is proposed. The proposed method tackles the aforementioned problems. Simulation results show that considering both lifetime and accuracy factors as a compound metric, the proposed method yields a 200% improvement compared with the Bayesian compressive sensing‐based method and outperforms other compared methods in the literature.     

Time-diffusion synchronization protocol for wireless sensor networks

In the near future, small intelligent devices will be deployed in homes, plantations, oceans, rivers, streets, and highways to monitor the environment. These devices require time synchronization, so voice and video data from different sensor nodes can be fused and displayed in a meaningful way at the sink. Instead of time synchronization between just the sender and receiver or within a local group of sensor nodes, some applications require the sensor nodes to maintain a similar time within a certain tolerance throughout the lifetime of the network. The Time-Diffusion Synchronization Protocol (TDP) is proposed as a network-wide time synchronization protocol. It allows the sensor network to reach an equilibrium time and maintains a small time deviation tolerance from the equilibrium time. In addition, it is analytically shown that the TDP enables time in the network to converge. Also, simulations are performed to validate the effectiveness of TDP in synchronizing the time throughout the network and balancing the energy consumed by the sensor nodes.     

H-SPREAD: a hybrid multipath scheme for secure and reliable data collection in wireless sensor networks

Communication security and reliability are two important issues in any network. A typical communication task in a wireless sensor network is for every sensor node to sense its local environment, and upon request, send data of interest back to a base station (BS). In this paper, a hybrid multipath scheme (H-SPREAD) to improve both the security and reliability of this task in a potentially hostile and unreliable wireless sensor network is proposed. The new scheme is based on a distributed N-to-1 multipath discovery protocol, which is able to find multiple node-disjoint paths from every sensor node to the BS simultaneously in one route discovery process. Then, a hybrid multipath data collection scheme is proposed. On the one hand, end-to-end multipath data dispersion, combined with secret sharing, enhances the security of the end-to-end data delivery in the sense that the compromise of a small number of paths will not result in the compromise of a data message in the face of adversarial nodes. On the other hand, in the face of unreliable wireless links and/or sensor nodes, alternate path routing available at each sensor node improves the reliability of each packet transmission significantly. The extensive simulation results show that the hybrid multipath scheme is very efficient in improving both the security and reliability of the data collection service seamlessly.     

Ratio-based time synchronization protocol in wireless sensor networks

Time synchronization plays a key role in the wireless sensor networks (WSNs). Time synchronization is realized by those messages that are time-stamped. But there are several delay times during transmission after time stamping. Most of them are uncertain and contribute directly to synchronization error. The uncertainties include send time, channel access time, transmission time, and receive time. In addition to the uncertainties, clock drift is also a main source of time synchronization error. In this paper, we present a time synchronization protocol that can be applied in the multi-hop WSNs. The proposed protocol estimates the clock drift between two nodes to keep them synchronized for duration after once synchronizing. It uses lower communication overhead and establishes more robust synchronization situations for all nodes in the network. By periodical re-synchronization, the un-synchronization conditions such as nodes failures or topology change can be easily overcome. We implement our protocol in the Berkeley MICAz platform. The experimenting scenarios are 5-node and 18-node multi-hop topologies, and the re-synchronization periods are 30-second and 300-second. The experiment results show that the average synchronization errors of all nodes run with our protocol are ranged within several micro-seconds which are better than the previous protocol.     

Evaluating revised MintRoute protocol in wireless sensor networks

A small device‐based, low‐rate, short‐range wireless radio communication often hampers high reliability in wireless sensor networks. However, more applications are increasingly demanding high reliability. For this requirement to be met, various approaches have been proposed in a layered manner. Among those, MintRoute is a well‐known network layer approach to develop a new metric based on link quality for path selection toward the sink. By choosing the link with the highest measured value, the proposed approach can afford a higher possibility to transmit a packet over the link without error. However, there are still several issues to be discussed during operations. In this paper, we propose how to improve the MintRoute protocol through several revised algorithms, including the development of a new metric, a parent selection considering distance and level from the sink node, and a fast recovery method against failures. Simulations and analysis are performed to validate the suitability of reduced end‐to‐end delay and fast recovery from failures.Copyright © 2013 John Wiley & Sons, Ltd.     

无线传感器网络中PECR协议的改进

PECR协议中对下游节点是否拥塞仅仅是一种预测,这种预测有时是不准确的,且在下游节点没有满足条件拥塞度和剩余能量的时候,传输层的问题要回到网络层去处理。为了解决PECR协议中存在的这些问题,文章引入了具有发送优先级的两个队列,优先发送优先级高的数据,在实际出现拥塞时会通知上游节点减少发送速率,并先抛弃掉优先级低的数据。在拥塞严重的时候也会抛弃掉优先级高的数据,但不会再回到网络层去处理问题。