物联网搜索技术综述

随着物联网的普及和发展,物联网搜索是摆在学术界和工业界面前迫切需要解决的问题,物联网搜索因此成为当前的一个研究热点。面对越来越多的传感器以及它们所产生的数据,只有结合智能的物联网搜索,才能体现这些数据的生命力。与传统的Baidu、Google、Bing、Yahoo等搜索引擎不同,物联网搜索从搜索对象、物理网数据的特点（大规模的、实时变化的、高度动态的、异构的、复杂的安全环境等）到物联网搜索的架构均与传统互联网不同,这导致了物联网搜所面临的挑战将更大。由此,阐述了物联网搜索的概念、特点、相关技术,对现有的典型系统和算法进行了比较性总结,分析了目前研究中存在的问题和挑战,并展望了其未来的发展方向。     

An energy‐aware approach for resource managing in the fog‐based Internet of Things using a hybrid algorithm

Regarding the recent information technology improvement, the fog computing (FC) emergence increases the ability of computational equipment and supplies modern solutions for traditional industrial applications. In the fog environment, Internet of Things (IoT) applications are completed by computing nodes that are intermediate in the fog, and the physical servers in data centers of the cloud. From the other side, because of resource constraints, dynamic nature, resource heterogeneity, and volatility of fog environment, resource management problems must be considered as one of the challenging issues of fog. The resource managing problem is an NP‐hard issue, so, in the current article, a powerful hybrid algorithm for managing resources in FC‐based IoT is proposed using an ant colony optimization (ACO) and a genetic algorithm (GA). GAs are computationally costly because of some problems such as the lack of guarantee for obtaining optimal solutions. Then, the precision and speed of convergence can be optimized by the ACO algorithm. Therefore, the powerful affirmative feedback pros of ACO on the convergence rate is considered. The algorithm uses GA's universal investigation power, and then it is transformed into ACO primary pheromone. This algorithm outperforms ACO and GA under equal conditions, as the simulation experiments showed.     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

面向物联网的隐私数据安全问题研究

随着社会的发展,物联网已成为社会发展的重要新兴产业,在各个领域中广泛应用。物联网是基于互联网技术产生的,在物联网的运行过程中势必会产生大量数据,这些数据都是客户的隐私,切实保护好客户隐私是物联网进一步发展的首要条件。在面向物联网的隐私数据安全问题时,相关技术人员一定要清楚威胁物联网隐私数据安全的主要途径,加大安全防护力度,保护人们的隐私。文章从信息获取、信息传输以及信息处理3个途径,对隐私数据安全问题进行探讨,并提出一些加大隐私安全防护的举措。     

An optimal energy‐efficient clustering method in wireless sensor networks using multi‐objective genetic algorithm

In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi‐objective two‐nested genetic algorithm is presented. The top level algorithm is a multi‐objective genetic algorithm (GA) whose goal is to obtain clustering schemes in which the network lifetime is optimized for different delay values. The low level GA is used in each cluster in order to get the most efficient topology for data transmission from sensor nodes to the cluster head. The presented clustering method is not restrictive, whereas existing intelligent clustering methods impose certain conditions such as performing two‐tiered clustering. A random deployed model is used to demonstrate the efficiency of the proposed algorithm. In addition, a comparison is made between the presented algorithm other GA‐based clustering methods and the Low Energy Adaptive Clustering Hierarchy protocol. The results obtained indicate that using the proposed method, the network's lifetime would be extended much more than it would be when using the other methods. Copyright © 2011 John Wiley & Sons, Ltd.     

Joint consideration of energy‐efficiency and coverage‐preservation in microsensor networks

This paper presents an energy‐efficient and coverage‐preserving communication protocol which distributes a uniform energy load to the sensors in a wireless microsensor network. This protocol, called Distance‐based Segmentation (DBS), is a cluster‐based protocol that divides the entire network into equal‐area segments and applies different clustering policies to each segment to (1) reduce total energy dissipation and (2) balance the energy load among the sensors. Therefore, it prolongs the lifetime of the network and improves the sensing coverage. Moreover, the proposed routing protocol does not need any centralized support from a certain node which is at odds with aiming to establish a scalable communication protocol. Results from extensive simulations on two different network configurations show that by lowering the number of wasteful transmissions in the network, the DBS can achieve as much as a 20% reduction in total dissipated energy as compared with current cluster‐based protocols. In addition, this protocol is able to distribute energy load more evenly among the sensors in the network. Hence, it yields up to a 66% increase in the useful network lifetime. According to the simulation results, the sensing coverage degradation of the DBS is considerably slower than that of the other cluster‐based protocols. Copyright © 2009 John Wiley & Sons, Ltd.     

A novel energy‐aware routing mechanism for SDN‐enabled WSAN

Energy consumption is one of the most important design constraints when building a wireless sensor and actuator network since each device in the network has a limited battery capacity, and prolonging the lifetime of the network depends on saving energy. Overcoming this challenge requires a smart and reconfigurable network energy management strategy. The Software‐Defined Networking (SDN) paradigm aims at building a flexible and dynamic network structure, especially in wireless sensor networks. In this study, we propose an SDN‐enabled wireless sensor and actuator network architecture that has a new routing discovery mechanism. To build a flexible and energy‐efficient network structure, a new routing decision approach that uses a fuzzy‐based Dijkstra's algorithm is developed in the study. The proposed architecture can change the existing path during data transmission, which is the key property of our model and is achieved through the adoption of the SDN approach. All the components and algorithms of the proposed system are modeled and simulated using the Riverbed Modeler software for more realistic performance evaluation. The results indicate that the proposed SDN‐enabled structure with fuzzy‐based Dijkstra's algorithm outperforms the one using the regular Dijkstra's and the ZigBee‐based counterpart, in terms of the energy consumption ratio, and the proposed architecture can provide an effective cluster routing while prolonging the network lifetime.     

Distributed fuzzy logic based energy‐aware and coverage preserving unequal clustering algorithm for wireless sensor networks

In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency.     

物联网在我国的发展及遇到的几个问题

近几年内,物联网技术引起社会各界的关注,结合物联网的发展,首先介绍了物联网的概念和背景及在我国的发展及应用状况,最后着重论述了物联网在我国的发展所遇到的一些问题。     

Data gathering and aggregation with selective transmission technique to optimize the lifetime of Internet of Things networks

The periodic sensor networks (PSNs) represent the bigger provider of data to the Internet of Things (IoT) due to their use in a wide range of IoT applications. Examples of IoT applications using PSNs are disaster recovery, connected vehicles, smart healthcare, smart cities, smart grids, and networks of robots. In PSNs, the large volume of data gathering and aggregation represent significant challenges that must be handled in the IoT applications. Therefore, it is necessary to find a dynamic way to gather data and get rid of the redundancy in the gathered data prior to transferring it to the sink (base station) for the sake of extending the PSN lifetime and preserving its energy. This article proposes data gathering and aggregation with selective transmission (DGAST) technique for optimizing lifetime in PSNs of IoT applications. DGAST gathers periodically the sensor data to extend the sensor's battery lifetime. DGAST protocol divides the lifetime of PSN into rounds. There are four phases in each round: data gathering, data aggregation, selective transmission, and adjusting the frequency of samples taken for each node in the context of dynamic climate change of the sensed environment. OMNeT++ simulator and real sensory data gathered at Intel Lab are used in the simulation experiments. The results of the simulation demonstrate DGAST efficiency in comparison with prefix frequency filtering (PFF) and Harb protocols, that is, overhead reduction up to 67% in gathered data, 73% in transmitted data, and 78% in consumed energy while maintaining the accuracy of sent data as high as 94.6%.     

Clustering‐based resource discovery on Internet‐of‐Things

Resource discovery on Internet‐of‐Things paradigm is an eminent challenge due to data‐specific activities with respect to foraging and sense‐making loops. The prerequisite to deal with the challenge is to process and analyze the data that require resources to be indexed, ranked, and stored in an efficient manner. A novel clustering technique is proposed to resolve the specified challenge. The technique, namely, iterative k‐means clustering algorithm, targets concrete cluster formation using similarity coefficients of vector space model and performs efficient search against matching criteria with respect to complexity. It is simulated on MATLAB, and the obtained results are compared with fuzzy k‐means and fuzzy c‐means clustering algorithm with similarity coefficients of vector space model against exponential increase in the number of resources.     

基于区块链的物联网技术应用

随着区块链技术的不断发展,其应用变得越来越普及。文章主要针对区块链的数据结构及整体架构进行分析,并审视了区块链为物联网带来的挑战;最后从物联网数据交易系统方面、电网管理方面、车联网方面以及防伪安全管理方面,细化阐述了基于区块链的物联网技术应用,以期为基于区块链的物联网技术发展提供可靠支持。     

High energy‐efficient and privacy‐preserving secure data aggregation for wireless sensor networks

An efficient data process technology is needed for wireless sensor networks composed of many sensors with constrained communication, computational, and memory resources. Data aggregation is presented as an efficient and significant method to reduce transmitted data and prolong lifetime for wireless sensor networks. Meanwhile, many applications require preserving privacy for secure data aggregation. In this paper, we propose a high energy‐efficient and privacy‐preserving scheme for secure data aggregation. Because of the importance of communication overhead and accuracy, our scheme achieves less communication overhead and higher data accuracy besides providing for privacy preservation. For extensive simulations, we evaluate and conclude the performance of our high energy‐efficient and privacy‐preserving scheme. The conclusion shows that the high energy‐efficient and privacy‐preserving scheme provides better privacy preservation and is more efficient than existing schemes. Copyright © 2012 John Wiley & Sons, Ltd.     

e‐LiteSense: Self‐adaptive energy‐aware data sensing in WSN environments

Currently deployed in a wide variety of applicational scenarios, wireless sensor networks (WSNs) are typically a resource‐constrained infrastructure. Consequently, characteristics such as WSN adaptability, low‐overhead, and low‐energy consumption are particularly relevant in dynamic and autonomous sensing environments where the measuring requirements change and human intervention is not viable. To tackle this issue, this article proposes e‐LiteSense as an adaptive, energy‐aware sensing solution for WSNs, capable of auto‐regulate how data are sensed, adjusting it to each applicational scenario. The proposed adaptive scheme is able to maintain the sensing accuracy of the physical phenomena, while reducing the overall process overhead. In this way, the adaptive algorithm relies on low‐complexity rules to establish the sensing frequency weighting the recent drifts of the physical parameter and the levels of remaining energy in the sensor. Using datasets from WSN operational scenarios, we prove e‐LiteSense effectiveness in self‐regulating data sensing accurately through a low‐overhead process where the WSN energy levels are preserved. This constitutes a step‐forward for implementing self‐adaptive energy‐aware data sensing in dynamic WSN environments.     

认知网络管理在物联网中的应用

The wide variety of smart embedded computing devices and their increasing number of applications in our daily life have created new opportunities to acquire knowledge from the physical world anytime and anywhere, which is envisioned as the“Internet of Things” (IoT). Since a huge number of heterogeneous resources are brought into IoT, one of the main challenges is how to efficiently manage the increasing complexity of IoT in a scalable, flexible, and autonomic way. Furthermore, the emerging IoT applications will require collaborations among loosely coupled devices, which may reside in various locations of the Internet. In this paper, we propose a new IoT network management architecture based on cognitive network management technology and Service-Oriented Architecture to provide effective and efficient network management of IoT.     

构建可运营可管理的物联网

IBM提出的"智慧地球"被奥巴马政府认为是振兴经济、确定美国全球竞争优势的新战略。在中国,三大电信运营商相继成立了专门的物联网研究机构,推出一批成熟的物联网应用,但在物联网的组网和运营方面还没有成熟的提案。本文从运营和管理的角度,提出可运营可管理的物联网概念、架构和运营管理模式。     

Network‐layer security for the Internet of Things using TinyOS and BLIP

The design of standard communications and security mechanisms for resource‐constrained sensing applications and devices may provide an important contribution for its integration with the Internet and consequently towards the realization of what we nowadays identify as the Internet of Things. This vision will only be realizable if appropriate security mechanisms are available, and in this context we target the design and experimental evaluation of security mechanisms for communications at the network‐layer with sensing devices (smart objects) using the standard IPv6 protocol. Our work proposes and evaluates the usage of new compressed security headers for the network layer with smart objects. We implement and evaluate what is, as far as we know, the first proposal of security at the network layer experimentally evaluated using the TinyOS operating system and its networking stack. As we verify in the course of our evaluation study, various scenarios employing network‐layer secure communications involving smart objects are feasible, particularly when security mechanisms are designed to benefit from cross‐layer interactions that allow the optimization of expensive cryptographic operations. Copyright © 2012 John Wiley & Sons, Ltd.     

P-IoT自组网模式研究

为降低专网物联网(P-IoT)的建网成本,实现灵活部署和增强抗毁性以满足行业用户的应用要求,需对P-IoT自组网模式进行研究。首先,阐述了P-IoT自组网模式的重要性;在此基础上,从系统架构、支持的拓扑类型、协议栈设计以及技术优势对P-IoT自组网模式加以分析;最后,分析了P-IoT自组网模式在智能抄表与智能林防领域的创新应用。P-IoT自组网模式在多种应用环境下都能很好地满足行业用户的需求,在未来专网市场P-IoT自组网模式必将具备极强的竞争力。     

异构物联网的开放式架构研究

An open architecture for converged Internet of Things (IoT) is proposed in this paper. By  using  this model, the various and huge amount of data can be converted into converged data and then encapsulated as service packages. Moreover, a Representational State Transfer (REST) platform has been implemented in the lab environment. The merit of this architecture is the enhancement of data efficiency. Experimental results are provided to show the benefits of the proposed architecture.     

构建电信物联网开放数据服务体系的思考

物联网的一个特征是智能处理,面对海量的物联网数据,如何存储、分析和共享使用是一个值得关注和需要解决的问题。基于对电信运营商物联网经营现状和未来发展趋势的分析,本文提出了建设电信物联网开放数据服务体系的构想,并详细设计了物联网数据服务的服务内容和体系框架,针对数据服务体系建设中涉及的关键技术点进行了分析,最后对电信运营商构建物联网开放数据服务体系的策略给出了建议。