Development of information collection scheme in internet of things environment for intelligent radiation monitoring systems

The new revolution in computing and wireless communications technologies led to Internet of Things (IoT). Information collection scheme performs an important role for energy efficient utilization and latency awareness in IoT environments. The enhancement of an effectual information collection scheme is crucial to improve the overall performance of the internet of things applications. In this paper, the proposed information collection scheme aimed to enhance the confidence regarding any captured measurements under IoT environment. The scheme can verify the selection of optimal information collection routes through using the Dijkstra algorithm. It depends on selecting the preferable IoT devices (collectors) with optimal paths in efficient energy utilization. The IoT devices (sources) have to elect whichever a preferable collector can deliver the captured information with an endeavour to sense the latest contextual information. They elect the optimal collectors through implicit and explicit solutions. Also, it considers different failure conditions to specify the optimal collection time for furtherance scalability of IoT environment. The simulation results show the ability of our scheme to improve the performance in terms of network lifetime, energy consumption, and reliability.

     

SALA: Smartphone-Assisted Localization Algorithm for Positioning Indoor IoT Devices

This paper proposes a Smartphone-Assisted Localization Algorithm (SALA) for the localization of Internet of Things (IoT) devices that are placed in indoor environments (e.g., smart home, smart office, smart mall, and smart factory). This SALA allows a smartphone to visually display the positions of IoT devices in indoor environments for the easy management of IoT devices, such as remote-control and monitoring. A smartphone plays a role of a mobile beacon that tracks its own position indoors by a sensor-fusion method with its motion sensors, such as accelerometer, gyroscope, and magnetometer. While moving around indoor, the smartphone periodically broadcasts short-distance beacon messages and collects the response messages from neighboring IoT devices. The response messages contains IoT device information. The smartphone stores the IoT device information in the response messages along with the message’s signal strength and its position into a dedicated server (e.g., home gateway) for the localization. These stored trace data are processed offline through our localization algorithm along with a given indoor layout, such as apartment layout. Through simulations, it is shown that our SALA can effectively localize IoT devices in an apartment with position errors less than 20 cm in a realistic apartment setting.     

Reliable and secure data transfer in IoT networks

With the rapid technological improvements in mobile devices and their inclusion in Internet of Things (IoT), secure key management becomes mandatory to ensure security of information exchange. For instance, IoT applications, such as smart health-care and smart homes, provide automated services to the users with less or no user intervention. As these application use user-sensitive data, ensuring their security and privacy should be paramount, especially during the key management process. However, traditional approaches for key management will not suit well in IoT environment because of the inherent resource constraint property of IoT devices. In this paper, we propose a novel distributed key management scheme for IoT ecosystem. The proposed scheme efficiently provides security to IoT devices by delegating most of the resource consuming cryptographic processing to a local entity. This entity coordinates with other peer entities to provide a distributed key as well as an authentication mechanism to network devices. In particular, the proposed scheme exploits the advantages of mobile agents by deploying them in different subnetworks as and when required: (1) to process the cryptography work for the IoT devices, and (2) to act as an local authenticated entity to perform fast authentication process. To verify the effectiveness and correctness of our proposed scheme, we have simulated it in a large IoT scenario and evaluated against relevant metrics that includes user mobility, certification generation time, and communication overhead.

     

Smart Cities via Data Aggregation

Cities have an ever increasing wealth of sensing capabilities, recently including also internet of things (IoT) systems. However, to fully exploit such sensing capabilities with the aim of offering effective city-sensing-driven applications still presents certain obstacles. Indeed, at present, the main limitation in this respect consists of the vast majority of data sources being served on a “best effort” basis. To overcome this limitation, we propose a “resilient and adaptive IoT and social sensing platform”. Resilience guarantees the accurate, timely and dependable delivery of the complete/related data required by smart-city applications, while adaptability is introduced to ensure optimal handling of the changing requirements during application provision. The associated middleware consists of two main sets of functionalities: (a) formulation of sensing requests: selection and discovery of the appropriate data sources; and (b) establishment and control of the necessary resources (e.g., smart objects, networks, computing/storage points) on the delivery path from sensing devices to the requesting applications. The middleware has the intrinsic feature of producing sensing information at a certain level of detail (geographical scope/timeliness/accuracy/completeness/dependability) as requested by the applications in a given domain. The middleware is assessed and validated at a proof-of-concept level through innovative, dependable and real-time applications expected to be highly reproducible across different cities.     

DDC-OMDC: Deadline-based data collection using optimal mobile data collectors in Internet of Things

Mobile data collectors (MDCs) are very efficient for data collection in internet of things (IoT) sensor networks. These data collectors collect data at rendezvous points to reduce data collection latency. It is paramount to determine these points in an IoT network to collect data in real time. It is important to consider IoT network characteristics to collect data on a specific deadline. First, the disconnected IoT sensor network is a real challenge in IoT applications. Second, it is essential to determine optimal data collection points (DCPs) and MDCs simultaneously to collect data in real time. In this study, Deadline-based Data Collection using Optimal Mobile Data Collectors (DDC-OMDC) scheme is proposed that aims to collect data in a disconnected network with the optimal number of mobile data collectors in a specific deadline for delay-intolerant applications. DDC-OMDC works in two phases. In the first phase, the optimal number of MDCs is determined to collect data at the optimal data collection points to guarantee one-hop data collection from each cluster. The optimal mobile data collectors are determined using optimal DCPs, data collection stopping time, and a specific deadline. In the second phase, the optimal data collection trajectory is determined for each MDC using the nearest neighbor heuristic algorithm to collect data in real time. The simulation results show that the proposed scheme outperforms in collecting data in real time and determines optimal mobile data collectors and optimal data collection trajectory to collect data in a specific deadline for delay-intolerant applications.     

A web service‐based internet of things framework for mobile resource augmentation

Mobile devices are the primary communication tool in day to day life of the people. Nowadays, the enhancement of the mobile applications namely IoTApps and their exploitation in various domains like healthcare monitoring, home automation, smart farming, smart grid, and smart city are crucial. Though mobile devices are providing seamless user experience anywhere, anytime, and anyplace, their restricted resources such as limited battery capacity, constrained processor speed, inadequate storage, and memory are hindering the development of resource‐intensive mobile applications and internet of things (IoT)‐based mobile applications. To solve this resource constraint problem, a web service‐based IoT framework is proposed by exploiting fuzzy logic methodologies. This framework augments the resources of mobile devices by offloading the resource‐intensive subtasks from mobile devices to the service providing entities like Arduino, Raspberry PI controller, edge cloud, and distant cloud. Based on the recommended framework, an online Repository of Instructional Talk (RIoTalk) is successfully implemented to store and analyze the classroom lectures given by faculty in our study site. Simulation results show that there is a significant reduction in energy consumption, execution time, bandwidth utilization, and latency. The proposed research work significantly increases the resources of mobile devices by offloading the resource‐intensive subtasks from the mobile device to the service provider computing entities thereby providing Quality of Service (QoS) and Quality of Experience (QoE) to mobile users.     

RAD‐EI: A routing attack detection scheme for edge‐based Internet of Things environment

Internet of Things (IoT) offers various types of application services in different domains, such as “smart infrastructure, health‐care, critical infrastructure, and intelligent transportation system.” The name edge computing signifies a corner or edge in a network at which traffic enters or exits from the network. In edge computing, the data analysis task happens very close to the IoT smart sensors and devices. Edge computing can also speed up the analysis process, which allows decision makers to take action within a short duration of time. However, edge‐based IoT environment has several security and privacy issues similar to those for the cloud‐based IoT environment. Various types of attacks, such as “replay, man‐in‐the middle, impersonation, password guessing, routing attack, and other denial of service attacks” may be possible in edge‐based IoT environment. The routing attacker nodes have the capability to deviate and disrupt the normal flow of traffic. These malicious nodes do not send packets (messages) to the edge node and only send packets to its neighbor collaborator attacker nodes. Therefore, in the presence of such kind of routing attack, edge node does not get the information or sometimes it gets the partial information. This further affects the overall performance of communication of edge‐based IoT environment. In the presence of such an attack, the “throughput of the network” decreases, “end‐to‐end delay” increases, “packet delivery ratio” decreases, and other parameters also get affected. Consequently, it is important to provide solution for such kind of attack. In this paper, we design an intrusion detection scheme for the detection of routing attack in edge‐based IoT environment called as RAD‐EI. We simulate RAD‐EI using the widely used “NS2 simulator” to measure different network parameters. Furthermore, we provide the security analysis of RAD‐EI to prove its resilience against routing attacks. RAD‐EI accomplishes around 95.0% “detection rate” and 1.23% “false positive rate” that are notably better than other related existing schemes. In addition, RAD‐EI is efficient in terms of computation and communication costs. As a result, RAD‐EI is a good match for some critical and sensitive applications, such as smart security and surveillance system.     

Security and Privacy in IoT: A Survey

The Internet of Things (IoT) is a network of globally connected physical objects, which are associated with each other via Internet. The IoT foresees the interconnection of few trillions of intelligent objects around us, uniquely and addressable every day, these objects have the ability to accumulate process and communicate data about themselves and their surrounding environment. The best examples of IoT systems are health care, building smart city with advance construction management system, public and defense surveillance and data acquisition. Recent advancement in the technology has developed smart and intelligent sensor nodes and RFIDs lead to a large number of wireless networks with smart and intelligent devices (object, or things) connected to the Internet continuously transmit the data. So to provide security and privacy to this data in IoT is a very challenging task, which is to be concerned at highest priority for several current and future applications of IoT. Devices such as smart phone, WSNs and RFIDs etc., are the major components of IoT network which are basically resource constrained devices. Design and development of security and privacy management schemes for these devices is guided by factors like good performance, low power consumption, robustness to attacks, tampering of the data and end to end security. Security schemes in IoT provide unauthorized access to information or other objects by protecting against alterations or destruction. Privacy schemes maintain the right to control about the collected information for its usage and purpose. In this paper, we have surveyed major challenges such as Confidentiality, Integrity, Authentication, and Availability for IoT in a brief manner.

     

Performance evaluation of a priority‐based resource allocation scheme for multiclass services in IoT

Recently, the deployment of novel smart network concepts, such as the Internet of things (IoT) or machine‐to‐machine communication, has gained more attention owing to its role in providing communication among various smart devices. The IoT involves a set of IoT devices (IoTDs) such as actuators and sensors that communicate with IoT applications via IoT gateways without human intervention. The IoTDs have different traffic types with various delay requirements, and we can classify them into two main groups: critical and massive IoTDs. The fundamental promising technology in the IoT is the advanced long‐term evolution (LTE‐A). In the future, the number of IoTDs attempting to access an LTE‐A network in a short period will increase rapidly and, thus, significantly reduce the performance of the LTE‐A network and affect the QoS required by variant IoT traffic. Therefore, efficient resource allocation is required. In this paper, we propose a priority‐based allocation scheme for multiclass service in IoT to efficiently share resources between critical and massive IoTD traffic based on their specific characteristics while protecting the critical IoTDs, which have a higher priority over the massive IoTDs. The performance of the proposed scheme is analyzed using the Geo/G/1 queuing system focusing on QoS guarantees and resource utilization of both critical and massive IoTDs. The distribution of service time of the proposed system is determined and, thus, the average waiting and service times are derived. The results indicate that the performance of the massive IoTDs depends on the data traffic characteristics of the critical IoTDs. Furthermore, the results emphasize the importance of the system delay analysis and demonstrate its effects on IoT configurations.     

Authentication-based Access Control and Data Exchanging Mechanism of IoT Devices in Fog Computing Environment

The emergence of fog computing has witnessed a big role in initiating secure communication amongst users. Fog computing poses the ability to perform analysis, processing, and storage for a set of Internet of Things (IoT) devices. Several IoT solutions are devised by utilizing the fog nodes to alleviate IoT devices from complex computation and heavy processing. This paper proposes an authentication scheme using fog nodes to manage IoT devices by providing security without considering a trusted third party. The proposed authentication scheme employed the benefits of fog node deployment. The authentication scheme using fog node offers reliable verification between the data owners and the requester without depending on the third party users. The proposed authentication scheme using fog nodes effectively solved the problems of a single point of failure in the storage system and offers many benefits by increasing the throughput and reducing the cost. The proposed scheme considers several entities, like end-users, IoT devices, fog nodes, and smart contracts, which help to administrate the authentication using access policies. The proposed authentication scheme using fog node provided superior results than other methods with minimal memory value of 4009.083 KB, minimal time of 76.915 s, and maximal Packet delivery ratio (PDR) of 76.

     

Data analytics in wireless systems and IoT issues and challenges

The emergence of data engineering along with the support of Online Social Networks is growing by millions every day due to the introduction of wireless systems and Internet of Things. The rapid growth of usage of smart devices helps to create new generation knowledge sharing platforms. Data Analytics has a major role to play in the growth and success of wireless and IoT applications. The growth of data has become exponential and is difficult to analyze. Many researchers depend on the data available on Wireless Systems and IoT for developing new generation services and applications. With the opportunity of information and communication technologies like heterogeneous networking, cloud computing, web services, crowd sensing and data mining, ubiquitous and asynchronous information sharing is feasible. But this also brings out a lot of provocations with respect to conflicting standards, data portability, data aggregation, data distribution, differential context and communication overhead. The smart information and communication technology has changed many features of human lifestyle: personal and work places.     

物联网智能终端技术研究

物联网智能终端从炒作阶段进入产品化阶段。微型化、集成化、智能化和多样化的传感器帮助物联网智能终端将现实世界数字化。而具备应用处理能力的处理器和先进的操作系统实现物联网终端的智能,通过云计算和大数据加强其智能化。和智能手机一样,物联网智能终端需要建立活跃的生态系统,激发开发者创新。旨在探讨、分析和展示上述几个关键技术的新进展和演进趋势。     

Design and Realization of an NFC-Driven Smart Home System to Support Intruder Detection and Social Network Integration

The Internet of thing (IoT) emerges as a possible solution to realize a smart life in the modern age. In this article, we design and realize a novel near field communication (NFC)-driven smart home system for IoT, which integrates the wireless sensor network (WSN), social networks, and the cloud computing. NFC technology provides a way for users to exchange information between them and the system by simply contacting. So, we propose to use NFC as the system drive in the architecture, such that users can intuitively interact with the system and deliver their intentions. Then, the corresponding service over the system will control or adjust the things at home to fit users' needs. Furthermore, the proposed system provides a platform for developers to easily and rapidly implement their smart home related services. In the system, WSN sensing and control, NFC communications and identification, user profile management and preference analysis, and social network integration are all provided as platform services. We will show how the system works for home automation, intruder detection, and social network sharing.     

A lightweight IoT‐based security framework for inventory automation using wireless sensor network

Internet of things (IoT) has evolved as an innovation of next generation in this world of smart devices. IoT tends to provide services for data collection, data management, and data and device security required for application development. Things or devices in IoT communicate and compute to make our lives comfortable and safe. In inventory automation, real‐time check on items, their information management, and status management, monitoring can be carried out using IoT. The huge amount of data that flows among the devices in the network demands for a security framework that ensures authentication, authorization, integrity, and confidentiality of data. The existing security solutions like SIMON or SPECK offer lightweight security solutions but are vulnerable to differential attack because of their simplicity. Moreover, existing solutions do not offer inbuilt authentication. Therefore, this research work contributes a secure and lightweight IoT‐based framework using wireless sensor network (WSN) as a technology. The existing security solutions SPECK and SIMON are compared with the proposed security approach using COOJA simulator. The results show that proposed approach outstands others by 2% reduction in number of CPU cycles, 10% less execution time, 4% less memory requirements of security approach, and with minimum 10% more security impact.     

Design and Performance Studies of an Adaptive Scheme for Serving Dynamic Web Content in a Mobile Computing Environment

Currently, people gain easy access to an increasingly diverse range of mobile devices such as personal digital assistants (PDAs), smart phones, and handheld computers. As dynamic content has become dominant on the fast-growing World Wide Web (C. Yuan et al., 2003), it is necessary to provide effective ways for the users to access such prevalent Web content in a mobile computing environment. During a course of browsing dynamic content on mobile devices, the requested content is first dynamically generated by remote Web server, then transmitted over a wireless network, and, finally, adapted for display' on small screens. This leads to considerable latency and processing load on mobile devices. By integrating a novel Web content adaptation algorithm and an enhanced caching strategy, we propose an adaptive scheme called MobiDNA for serving dynamic content in a mobile computing environment. To validate the feasibility and effectiveness of the proposed MobiDNA system, we construct an experimental testbed to investigate its performance. Experimental results demonstrate that this scheme can effectively improve mobile dynamic content browsing, by improving Web content readability on small displays, decreasing mobile browsing latency, and reducing wireless bandwidth consumption     

The Digital Fingerprinting Analysis of Generic Twitter Sessions from Internet of Things Security Aspect

Nowadays, the unparalleled growth of Internet of Things (IoT) is a new digital disruption which intelligent devices are connected and working together. IoT connects personal computers, tablets, and smart phones in our daily communications from leisure purposes to business tasks. However, the security concern of IoT can’t be overemphasized due to the connectivity among communication gadgets. Sustainably, Twitter is one of the most popular Instant Message (IM) toolkits today. When Twitter is being utilized, there will be some negligible and imperceptible digital remnants left in the computing devices, which could be probative digital evidences in a court of law when IoT application is involved. Hence, the digital forensics of IM has been a relatively rigorous, competitive, and novel research field by the law enforcement agency officers and the information security staffs with respect to some cybercrimes concerning IoT. Consequently, this research is targeting on the utilization of Twitter on the desktop PC under Windows 7 operating system via the acquisition of volatile digital bread crumbs inside physical memory of the computing device for the purpose of presenting supportive digital evidences for some information security concerns. The proposed various scenarios in the design of the experiment could be the paradigms for digital forensics specialists or law enforcement agencies to follow in order to reconstruct the previous operations in the Twitter sessions of a certain user under the IoT ecosystems.

     

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.     

A blockchain future for internet of things security: a position paper

Internet of Things (IoT) devices are increasingly being found in civilian and military contexts, ranging from smart cities and smart grids to Internet-of-Medical-Things, Internet-of-Vehicles, Internet-of-Military-Things, Internet-of-Battlefield-Things, etc. In this paper, we survey articles presenting IoT security solutions published in English since January 2016. We make a number of observations, including the lack of publicly available IoT datasets that can be used by the research and practitioner communities. Given the potentially sensitive nature of IoT datasets, there is a need to develop a standard for sharing IoT datasets among the research and practitioner communities and other relevant stakeholders. Thus, we posit the potential for blockchain technology in facilitating secure sharing of IoT datasets (e.g., using blockchain to ensure the integrity of shared datasets) and securing IoT systems, before presenting two conceptual blockchain-based approaches. We then conclude this paper with nine potential research questions.     

A survey on communication protocols and performance evaluations for Internet of Things

The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, IoT interacts with many application areas such as smart city, smart building, security, traffic, remote monitoring, health, energy, disaster, agriculture, industry. The IoT network in these scenarios comprises tiny devices, gateways, and cloud platforms. An IoT network is able to keep these fundamental components in transmission under many conditions with lightweight communication protocols taking into account the limited hardware features (memory, processor, energy, etc.) of tiny devices. These lightweight communication protocols affect the network traffic, reliability, bandwidth, and energy consumption of the IoT application. Therefore, determining the most proper communication protocol for application developers emerges as an important engineering problem. This paper presents a straightforward overview of the lightweight communication protocols, technological advancements in application layer for the IoT ecosystem. The survey then analyzes various recent lightweight communication protocols and reviews their strengths and limitations. In addition, the paper explains the experimental comparison of Constrained Applications Protocol (CoAP), Message Queuing Telemetry (MQTT), and WebSocket protocols, more convenient for tiny IoT devices. Finally, we discuss future research directions of communication protocols for IoT.