Location privacy and resilience in wireless sensor networks querying

Due to the wireless nature of communication in sensor networks, the communication patterns between sensors could be leaked regardless of the adoption of encryption mechanisms—those would just protect the message content. However, communication patterns could provide valuable information to an adversary. For instance, this is the case when sensors reply to a query broadcast by a Base Station (BS); an adversary eavesdropping the communication traffic could realize which sensors are the ones that possibly match the query (that is, the ones that replied). This issue is complicated by the severe resource constrained environment WSNs are subject to, that call for efficient and scalable solutions.In this paper, we have addressed the problem of preserving the location privacy of the sensors of a wireless sensor network when they send a reply to a query broadcast by the BS. In particular, we deal with one of the worst scenarios for privacy: When sensors are queried by a BS to provide the MAX of their stored readings. We provide a probabilistic and scalable protocol to compute the MAX that enjoys the following features: (i) it guarantees the location privacy of the sensors replying to the query; (ii) it is resilient to an active adversary willing to alter the readings sent by the sensors; and, (iii) it allows to trade-off the accuracy of the result with (a small) overhead increase. Finally, extensive simulations support our analysis, showing the quality of our proposal.     

Secure lightweight password authenticated key exchange for heterogeneous wireless sensor networks

Several three-party password authenticated key exchange (3-PAKE) protocols have recently been proposed for heterogeneous wireless sensor networks (HWSN). These are efficient and designed to address security concerns in ad-hoc sensor network applications for a global Internet of Things framework, where a user may request access to sensitive information collected by resource-constrained sensors in clusters managed by gateway nodes. In this paper we first analyze three recently proposed 3-PAKE protocols and discuss their vulnerabilities. Then, based on Radio Frequency Identification technologies we propose a novel 3-PAKE protocol for HWSN applications, with two extensions for additional security features, that is provably secure, efficient and flexible.     

一种无线传感器网络链式传输分簇路由协议

由于周围环境对无线传感器网络(WSNs)的影响,在布设到特殊环境下时会产生信号的衰减与损耗,导致通信不畅。针对此问题,提出一种以LEACH路由协议为基础适应特殊环境(长直空间)的新型路由算法。本算法采用链式传输,即从内部逐一将信号传输给距空间最外端且距基站位置较近的簇头,克服了内部节点死亡过快的问题。同时簇内采用链式传输并且改进簇头阈值与成簇半径,减小了能量消耗,提高了稳定性,克服了LEACH算法的不足。     

Model-based approximate querying in sensor networks

Declarative queries are proving to be an attractive paradigm for interacting with networks of wireless sensors. The metaphor that “the sensornet is a database” is problematic, however, because sensors do not exhaustively represent the data in the real world. In order to map the raw sensor readings onto physical reality, a model of that reality is required to complement the readings. In this article, we enrich interactive sensor querying with statistical modeling techniques. We demonstrate that such models can help provide answers that are both more meaningful, and, by introducing approximations with probabilistic confidences, significantly more efficient to compute in both time and energy. Utilizing the combination of a model and live data acquisition raises the challenging optimization problem of selecting the best sensor readings to acquire, balancing the increase in the confidence of our answer against the communication and data acquisition costs in the network. We describe an exponential time algorithm for finding the optimal solution to this optimization problem, and a polynomial-time heuristic for identifying solutions that perform well in practice. We evaluate our approach on several real-world sensor-network datasets, taking into account the real measured data and communication quality, demonstrating that our model-based approach provides a high-fidelity representation of the real phenomena and leads to significant performance gains versus traditional data acquisition techniques. This article includes and extends results that were previously published in VLDB 2004 [Desphande, A., Guestrin, C., Madden, S., Hellerstein, J.M., Hong, W.: Model-driven data acquisition in sensor networks. In {VLDB} (2004)], and combines these techniques with the conditional planning approach published in ICDE 2005 [Deshpande, A., Guestrin, C., Madden, S., Hong, W.: Exploiting correlated attributes in acquisitional query processing. In {ICDE} (2005)].     

Localization in time and space for wireless sensor networks: An efficient and lightweight algorithm

In many applications that use Wireless Sensor Networks (WSNs), detected events need to be localized in both time and space. As a result, sensor nodes need to have precisely synchronized clocks as well as to be localized in a common spatial reference system. While synchronization and localization algorithms have been proposed to solve these problems independently, in this work we propose to combine both synchronization and localization into a single problem that we refer to as the time–space localization problem. We then propose a novel and efficient time–space localization algorithm for wireless sensor networks which we refer to as the Lightness algorithm. Our proposed algorithm not only takes advantage of the additional hardware resources required by the positioning mechanism in order to improve the performance and scalability of synchronization, but also benefits from the additional communication needed by the synchronization mechanism in order to decrease positioning errors. We also present an extensive set of experiments to evaluate the performance of our algorithm. Our results indicate clearly that our proposed scheme is scalable while keeping a low synchronization error and a low communication overhead. Our results also indicate that the additional packets needed to compute clocks’ drift have the ability to decrease the positioning errors to almost one third of the initial positioning.     

W-Grid: A scalable and efficient self-organizing infrastructure for multi-dimensional data management,querying and routing in wireless data-centric sensor networks

Data-centric sensor networks are advanced ad hoc networks that act like a distributed database managing and indexing sensed data in order to efficiently perform advanced in-network tasks, such as routings, searches, data processing, fusion and analysis. The supplied distributed services, such as routing, content location and information sharing should be provided anywhere and at any time optimizing energy consumptions, computational resources, memory occupation and radio transmissions. Moreover, the network traffic should be equally balanced among participants in order to avoid premature discharge of some devices that may partition the network. This work describes a fully decentralized infrastructure able to self-organize nodes in ad hoc networks by exploiting local interactions and topology learning among devices. In this solution all nodes are peers and nothing prevent the approach to be used in wireless mesh networks as well. Differently from existing solutions, our proposal does not require global information or external help, such as the Global Positioning System, which works only outdoor with a precision and an efficacy both limited by weather conditions and obstacles. The infrastructure natively enables devices to perform routing and data management without using message broadcast/flooding operations. The work introduces also a feature, called full learning, that improves routing performances while balancing the traffic among devices. We report an extensive number of simulations comparing the new solution results with four existing proposals, two of which deriving from preceding versions of the infrastructure.     

A biologically-inspired clustering protocol for wireless sensor networks

Lately, wireless sensor networks are garnering a lot of interests, as it is feasible to deploy them in many ad hoc scenarios such as for earthquake monitoring, tsunami monitoring and battlefield surveillance. As sensor nodes may be deployed in hostile areas, these battery-powered nodes are mostly expected to operate for a relatively long period. Clustering is an approach actively pursued by many groups in realizing more scalable data gathering and routing. However, it is rather challenging to form an appropriate number of clusters with well balanced memberships. To this end, we propose a novel application of collective social agents to guide the formation of these clusters. In order to counter the usual problems of such meta-heuristics, we propose a novel atypical application that allows our protocol to converge fast with very limited overhead. An analysis is performed to determine the optimal number of clusters necessary to achieve the highest energy efficiency. In order to allow for a realistic evaluation, a comprehensive simulator involving critical components of the communication stack is used. Our protocol is found to ensure a good distribution of clusterheads through a totally distributed approach. To quantify certain clustering properties, we also introduced two fitness metrics that could be used to benchmark different clustering algorithms.     

一种新的无线传感器网络分簇模型

从工业现场应用的角度对无线传感器网络进行研究,提出了一种新的双簇头分级模型。该模型在单簇头模型的基础上增加了一个冗余簇头节点,在簇头节点电池耗尽或出现故障之时,冗余簇头节点能够实时切换成簇头节点以维持簇稳定工作。介绍了双簇头分级模型的工作原理、覆盖范围和能耗管理,并且对该模型的性能进行了实验仿真,实验结论证明双簇头分级模型比之单簇头分级模型有更好的稳定性和安全性,以及长的生存时间而更适合应用于工业现场。     

Machine learning algorithms for wireless sensor networks: A survey

Wireless sensor network (WSN) is one of the most promising technologies for some real-time applications because of its size, cost-effective and easily deployable nature. Due to some external or internal factors, WSN may change dynamically and therefore it requires depreciating dispensable redesign of the network. The traditional WSN approaches have been explicitly programmed which make the networks hard to respond dynamically. To overcome such scenarios, machine learning (ML) techniques can be applied to react accordingly. ML is the process of self-learning from the experiences and acts without human intervention or re-program. The survey of the ML techniques for WSNs is presented in [1], covering period of 2002–2013. In this survey, we present various ML-based algorithms for WSNs with their advantages, drawbacks, and parameters effecting the network lifetime, covering the period from 2014–March 2018. In addition, we also discuss ML algorithms for synchronization, congestion control, mobile sink scheduling and energy harvesting. Finally, we present a statistical analysis of the survey, the reasons for selection of a particular ML techniques to address an issue in WSNs followed by some discussion on the open issues.     

Time synchronization methods for wireless sensor networks: A survey

Wireless sensor networks consist of many nodes that collect real-world data, process them, and transmit the data by radio. Wireless sensor networks represent a new, rapidly developing direction in the field of organization of computer networks of free configuration. Sensor networks are used for monitoring a parameter field, where it is often required to fix time of an event with high accuracy. High accuracy of local clocks is also necessary for operation of network protocols (for energy-saving purposes, the nodes spend most of the time in the sleeping mode and communicate only occasionally). In the paper, base techniques used in the existing time synchronization schemes are analyzed; models of local clock behavior and models of interaction of the network devices are described; classification of the synchronization problems is presented; and a survey of the existing approaches to synchronization of time in sensor networks is given.     

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。     

A spatiotemporal communication protocol for wireless sensor networks

In this paper, we present a spatiotemporal communication protocol for sensor networks, called SPEED. SPEED is specifically tailored to be a localized algorithm with minimal control overhead. End-to-end soft real-time communication is achieved by maintaining a desired delivery speed across the sensor network through a novel combination of feedback control and nondeterministic geographic forwarding. SPEED is a highly efficient and scalable protocol for sensor networks where the resources of each node are scarce. Theoretical analysis, simulation experiments, and a real implementation on Berkeley motes are provided to validate the claims.     

一个无线传感器网络的网络分割模型

首先指出网络分割会影响网络连通性，并进而影响网络的通信效率；接着从物理层和MAC协议入手，讨论了导致无线传感器网络网络分割问题的通信因素。为了定量地刻画网络分割，定义了网络分割比，并分析了影响网络分割比的物理及几何因素。通过试验采集的大量数据及曲线族拟合法，建立了一个无线传感器网络的网络分割模型，定量地确定了网络节点数、面积比与网络分割比的数学关系。     

一种距离无关的无线传感器网络定位算法

通过分析和仿真,指出距离无关的无线传感器网络定位算法DV-Hop在节点分布密度不均匀的网络中的局限性.由此,提出一种新的定位算法.该算法中,各节点感知周边的节点密度,基于此对周边锚节点分区,利用相同区域的锚节点执行定位计算.通过仿真验证,在节点分布密度不均的网络中,该算法有效地降低了未知节点的定位误差,提高了定位精度.     

A case for centrally controlled wireless sensor networks

In this article we present the Intelligent, Manageable, Power-Efficient and Reliable Internetworking Architecture (IMPERIA), a centrally managed architecture for large-scale wireless sensor networks (WSNs). We discuss the advantages of a centralized management over distributed approaches and derive our design by rigorously minimizing the amount of state information on individual sensor nodes and all sources of message collision during network operations. The result is a clustered multi-hop TDMA protocol that globally synchronizes the network and collects data at ultra-low power consumption.We present the end-to-end architecture and detail the algorithms we developed for (a) efficient network topology discovery and link quality estimation, (b) combined routing and clustering for pre-defined basestations, and (c) the scheduling of the medium access for multi-cluster and multi-channel data collection.IMPERIA has been implemented on TinyOS and IBM’s Mote Runner and successfully deployed in applications for vibration sensing as well as datacenter energy management. This article summarizes the performance results from simulations, laboratory experiments, and deployment measurements that support our design decisions.     

A security policy language for wireless sensor networks

Authenticated computer system users are only authorized to access certain data within the system. In the future, wireless sensor networks (WSNs) will need to restrict access to data as well. To date, WSN security has largely been based on encryption and authentication schemes. The WSN Authorization Specification Language (WASL) is a mechanism-independent composable WSN policy language that can specify arbitrary and composable security policies that are able to span and integrate multiple WSN policies. Using WASL, a multi-level security policy for a 1000 node network requires only 60 bytes of memory per node.     

A proportional fairness scheduling for wireless sensor networks

This paper describes a packet scheduling algorithm for wireless sensor networks (WSNs) that meets the proportional fairness principle. Based on the weighted round-robin strategy, the proposed scheduling algorithm allocates a different service quota to different traffic according to the average packet arrival rate. This guarantees proportional fairness in terms of the average packet delivery delay and the average packet loss ratio. Since the scheduling algorithm does not perform high-load operations such as time stamping and sorting, it can be implemented easily and is suitable for resource-limited WSNs. The proposed scheduling algorithm is tested in a WSN and is found to guarantee the proportional fairness of the average packet delivery delay when this is used as the performance metric, and to realize proportional fairness in the average packet loss ratio when all the queues are overflowing and the average packet loss ratio is used as the performance metric.     

一种低延时的无线传感器网络MAC协议

针对典型无线传感器网络X-MAC协议在多跳环境下累积延迟问题,提出一种具有低时延的Ex-MAC协议。利用管理邻居节点工作周期和虚通道算法,使得虚通道中的所有节点近似于同步,从而减少数据传输延迟,而且不需要交换同步控制帧。仿真结果与X-MAC协议相比,减少了端到端的延迟和数据包冲突的几率,提高了网络的吞吐量。