Intelligent multimedia big data computing for internet of things

Multimedia Tools and Applications -     

Signature-based three-factor authenticated key exchange for internet of things applications

Multimedia Tools and Applications - Internet of Things (IoT) is one of several technology trends, and IoT applications are found in a wide range of industry sectors such as healthcare and critical...     

Interoperable access framework for internet of things backhauled heterogeneous applications

Internet of Things (IoT) provides large-scale interoperable service delegations for heterogeneous users through pervasive access. The interconnection of different devices and services in an on-demand and pervasive manner provides seamless responses for different applications. However, a few interconnected devices are stuck into a resource-constraint problem due to limited access and unavailability. This article proposes an interoperable access framework (IAF) for pervasive application services (PAS) for providing robust end-user solutions. The proposed framework balances the accessibility and semantics and its responses for providing seamless interoperability support. In this framework, transfer learning for different limited and free-flow service accessibility is used. The teaching is recurrent for identifying the unavailability of the resources. The process of serving the requests is achieved through interoperable replacement services. It reduces the impact of resource-constraint in the IoT platform, wherein the semantics between unavailability and accessibility is analyzed flawlessly. The proposed framework's performance is verified using the metrics service delay, responses, unavailability, resource utilization, and successful access.     

Topic-centric and semantic-aware retrieval system for internet of things

The Internet of things (IoT) has been considered as one of the promising paradigms that can allow people and objects to seamlessly interact. So far, numerous applications and services have been proposed, such as retrieval service. The retrieval, however, faces a big challenge in IoT because the data belongs to different domains and user interaction with the surrounding environment is constrained. This paper proposes Acrost, a retrieval system based on topic discovery and semantic awareness in IoT environment. The initial contents with interesting information is obtained through the combination of two topic centric collectors. The metadata is extracted by aggregating regular expression-based and conditional random fields-based approaches. Moreover, the semantic-aware retrieval is achieved by parsing the query and ranking the relevance of contents. In addition, we present a case study on academic conference retrieval to validate the proposed approaches. Experimental results show that the proposed system can significantly improve the response time and efficiency of topic self-adaptive retrieval manner.     

Bidirectional self-adaptive resampling in internet of things big data learning

Multimedia Tools and Applications - This paper focuses on the problem of low learning algorithm accuracy caused by serious imbalance of big data in Internet of Things, and proposes a bidirectional...     

面向海量数据应用的物联网信息服务系统研究综述*

物联网信息服务系统整合了基础设施层获取的海量数据,是面向各类物联网应用提供跟踪、监测和控制等信息服务的关键平台。阐述了物联网海量数据处理技术,包括存储、预处理和数据挖掘;总结了物联网信息服务系统在系统安全、隐私保护和可信性方面的安全保障机制;从系统架构、实现技术和系统实践三个方面,探讨了物联网信息服务系统的设计。最后,展望了这一领域面临的挑战和有待进一步研究的方向。     

CSF: Crowdsourcing semantic fusion for heterogeneous media big data in the internet of things

With the rising popularity of social media in the context of environments based on the Internet of things (IoT), semantic information has emerged as an important bridge to connect human intelligence with heterogeneous media big data. As a critical tool to improve media big data retrieval, semantic fusion encounters a number of challenges: the manual method is inefficient, and the automatic approach is inaccurate. To address these challenges, this paper proposes a solution called CSF (Crowdsourcing Semantic Fusion) that makes full use of the collective wisdom of social users and introduces crowdsourcing computing to semantic fusion. First, the correlation of cross-modal semantics is mined and the semantic objects are normalized for fusion. Second, we employ the dimension reduction and relevance feedback approaches to reduce non-principal components and noise. Finally, we research the storage and distribution mechanism. Experiment results highlight the efficiency and accuracy of the proposed approach. The proposed method is an effective and practical cross-modal semantic fusion and distribution mechanism for heterogeneous social media, provides a novel idea for social media semantic processing, and uses an interactive visualization framework for social media knowledge mining and retrieval to improve semantic knowledge and the effect of representation.     

A group key agreement protocol for intelligent internet of things system

The application of intelligent computing in Internet of Things (IoTs) makes IoTs systems such as telemedicine, in-vehicle IoT, and smart home more intelligent and efficient. Secure communication and secure resource sharing among intelligent terminals are essential. A secure communication channel for intelligent terminals can be established through group key agreement (GKA), thereby ensuring the security communication and resource sharing for intelligent terminals. Taking into account the confidentiality level of the shared resources of each terminal, and the different permissions of the resource sharing of each terminal, a GKA protocol for intelligent IoTs is proposed. Compared with previous work, this protocol mainly has the following advantages: (1) The hidden attribute identity authentication technology can achieve the security of identity authentication and protect personal privacy from being leaked; (2) Only intelligent terminals satisfying the threshold required of the GKA can participate in the GKA, which increases the security of group communication; (3) Low-level group terminals can obtain new permissions to participate in high-level group communication if they meet certain conditions. High-level group terminals can participate in low-level group communication through permission authentication, which increases the flexibility and security of group communication; (4) The intelligent terminals in the group can use their own attribute permission parameters to calculate the group key. They can verify the correctness of the calculated group key through a functional relationship, and does not need to exchange information with other members in the same group. Under the hardness assumption of inverse computational Diffie-Hellman problem and discrete logarithm problem, it is proven that the protocol has high security, and compared with the cited literatures, it has good advantages in terms of computational complexity, time cost and communication energy cost.     

基于量子密码的物联网RFID系统安全的研究

RFID系统的普及应用和计算机处理能力不断提高使得传统公钥密码体制的不足日益凸显。为了替代传统公钥密码体制,解决标签的安全问题,本文基于遍历矩阵构造多元二次多项式（Bisectional Multivariate Quadratic Equation,BMQE）的方法,建立一种新的基于量子计算机构造的公钥密码方案,并且给出物联网移动RFID安全协议模型。接着从密钥尺寸、加/解密速度等对该方案进行性能评估,表明该方案在RFID系统中应用的可行性。最后从各项攻击方法等进行分析,表明该方案的安全性。该研究成果对量子密码时代推进RFID的安全研究具有重要参考价值。     

A real-time distributed cluster storage optimization for massive data in internet of multimedia things

With the rapid growth of massive data in the Internet of Multimedia Things, there are some problems of insufficient storage space and unbalanced load in the current methods. For the problem of massive real-time data storage, a distributed cluster storage optimization method is proposed. Considering the impact of replica cost and the generation of intermediate data on the replica layout, a replica generation and storage strategy is given with consideration of cost and storage space. In the data center, the data sensitivity and data access frequency is used as migration factors to achieve massive data migration. The improved collaborative evolution method is used to code the task scheduling particle swarm in massive data storage to obtain the optimal solution, and achieve massive real-time data distributed cluster storage for the Internet of things. The experimental results showed that the cost of data management by this method was only between 10 and 15, which showed that this method can effectively improve data access speed, reduce storage space, lower cost and better load balancing.

     

An efficient networking protocol for internet of things to handle multimedia big data

In recent years, the emergence of multimedia big data (MBD) due to the excessive use of mobile Internet of Things (ioT) is imposing various challenges to develop efficient communication with the digital world. In this aspect, Mobile Adhoc Network based IoT (MANET-IoT) system is becoming popular due to its greater mobility support and cost-effective nature. A mobile ad hoc network (MANET) consists of randomly placed, battery-powered, moving nodes without an infrastructure that can administer and control traffic in the IoT network. In the MANET-IoT network, the major problems include energy consumption and congestion control to handle MBD data. In this paper, we present two proposals for solving these problems. In the first proposal, a new clustering approach that depends on a well-known protocol called the Low Energy Adaptive Clustering Hierarchy (LEACH) been used in a wireless sensor network (WSN) with modification to adapt to the MANET-IoT’s mobility. Our proposal for applying LEACH to a MANET-IoT consists of rounds, each containing three ordered phases as follows: (1) the announcement phase, in which all nodes announce their remaining energy and the node with the original message also announces itself; (2) the setup phase, in which all cluster heads are selected based on the probability factor with a cycling method; and (3) the steady state phase, in which message delivery to all nodes occurs using several types of links. The second proposal is to provide congestion control for all mobile nodes by link utilization that can support different data rates depending on the link status. Simulation results comparing our modified LEACH protocol to state-of-the-art protocols with utilized links show a great enhancement in energy consumption, received data, throughput, and delay.

     

Visualization for internet of things: power system and financial network cases

Multimedia Tools and Applications - National critical infrastructure networks, such as banks and industrial control systems (ICSs), can be serious damaged in the event of a security incident....     

基于物联网技术的电梯安全管理系统

介绍了基于物联网技术的电梯安全管理系统。该系统采集电梯运行过程中的各种参数进行分析处理,并及时将各种信息通过无线或短信发送到后台。这将极大地提高电梯的安全系数,对于电梯的制造者与使用者都有很大的现实意义。     

An internet of old things as an augmented memory system

The interdisciplinary Tales of Things and electronic Memory (TOTeM) project investigates new contexts for augmenting things with stories in the emerging culture of the Internet of Things (IoT). Tales of Things is a tagging system which, based on two-dimensional barcodes (also called Quick Response or QR codes) and Radio Frequency Identification (RFID) technology, enables the capturing and sharing of object stories and the physical linking to objects via read and writable tags. Within the context of our study, it has functioned as a technology probe which we employed with the aim to stimulate discussion and identify desire lines that point to novel design opportunities for the engagement with personal and social memories linked to everyday objects. In this paper, we discuss results from fieldwork with different community groups in the course of which seemingly any object could form the basis of a meaningful story and act as entry point into rich inherent ‘networks of meaning’. Such networks of meaning are often solely accessible for the owner of an object and are at risk of getting lost as time goes by. We discuss the different discourses that are inherent in these object stories and provide avenues for making these memories and meaning networks accessible and shareable. This paper critically reflects on Tales of Things as an example of an augmented memory system and discusses possible wider implications for the design of related systems.     

基于属性约简的物联网不完全数据填充算法

传统的数据填充算法采用统一方法对不完全数据进行填充,效率低下,不适合对物联网中大规模不完全数据进行填充,因此提出了一种基于属性约简不完全数据填充算法.利用属性约简区分数据的重要属性与非重要属性,分别采用不同的填充技术对两类属性进行填充,其中重要属性个数由用户根据实际需要设定.实验结果表明,该算法能够有效、快速地对物联网中大规模不完全数据进行填充.     

An adaptive meta-heuristic search for the internet of things

The number of sensors deployed around the world is growing at a rapid pace when we are moving towards the Internet of Things (IoT). The widespread deployment of these sensors represents significant financial investment and technical achievement. These sensors continuously generate enormous amounts of data which is capable of supporting an almost unlimited set of high value proposition applications for users. Given that, effectively and efficiently searching and selecting the most related sensors of a user’s interest has recently become a crucial challenge. In this paper, inspired by ant clustering algorithm, we propose an effective context-aware method to cluster sensors in the form of Sensor Semantic Overlay Networks (SSONs) in which sensors with similar context information are gathered into one cluster. Firstly, sensors are grouped based on their types to create SSONs. Then, our meta-heuristic algorithm called AntClust has been performed to cluster sensors using their context information. Furthermore, useful adjustments have been applied to reduce the cost of sensor search process and an adaptive strategy is proposed to maintain the performance against dynamicity in the IoT environment. Experiments show the scalability and adaptability of AntClust in clustering sensors. It is significantly faster on sensor search when compared with other approaches.