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Secure MQTT Protocol based on Attribute-Based Encryption Scheme
http://doi.org/10.5626/JOK.2018.45.3.195
Recently, with increasing scale of internet of Things (IoT), a large amount of data are generated and various services using such data are emerging. Therefore, a protocol suitable for IoT environment that can efficiently process / transmit big data is needed. MQTT is a lightweight messaging protocol for IoT environment. Although MQTT protocol can use TLS to provide security, it has a problem in that handshake and packet overhead will increase when TLS is used. Therefore, this paper proposed as Secure_MQTT protocol. It can provide stronger security by using lightweight encryption algorithm for MQTT protocol.
Rate Control Scheme for Improving Quality of Experience in the CoAP-based Streaming Environment
Hyunsoo Kang, Jiwoo Park, Kwangsue Chung
http://doi.org/10.5626/JOK.2017.44.12.1296
Recently, as the number of Internet of Things users has increased, IETF (Internet Engineering Task Force) has released the CoAP (Constrained Application Protocol). So Internet of Things have been researched actively. However, existing studies are difficult to adapt to streaming service due to low transmission rate that result from buffer underflow. In other words, one block is transmitted one block to client’s one request according to the internet environment of limited resources. The proposed scheme adaptively adjusts the rate of CON(Confirmable) message among all messages for predicting the exact network condition. Based on this, the number of blocks is determined by using buffer occupancy rate and content download rate. Therefore it improves the quality of user experience by mitigating playback interruption. Experimental results show that the proposed scheme solves the buffer underflow problem in Internet of Things streaming environment by controlling transmission rate according to the network condition.
Cluster Property based Data Transfer for Efficient Energy Consumption in IoT
Chungsan Lee, Soobin Jeon, Inbum Jung
http://doi.org/10.5626/JOK.2017.44.9.966
In Internet of Things (IoT), the aim of the nodes (called ‘Things’) is to exchange information with each other, whereby they gather and share information with each other through self decision-making. Therefore, we cannot apply existing aggregation algorithms of Wireless sensor networks that aim to transmit information to only a sink node or a central server, directly to the IoT environment. In addition, since existing algorithms aggregate information from all sensor nodes, problems can arise including an increasing number of transmissions and increasing transmission delay and energy consumption. In this paper, we propose the clustering and property based data exchange method for energy efficient information sharing. First, the proposed method assigns the properties of each node, including the sensing data and unique resource. The property determines whether the node can respond to the query requested from the other node. Second, a cluster network is constructed considering the location and energy consumption. Finally, the nodes communicate with each other efficiently using the properties. For the performance evaluation, TOSSIM was used to measure the network lifetime and average energy consumption.
Dynamic Discovery of Geographically Cohesive Services in Internet of Things Environments
KyeongDeok Baek, MinHyeop Kim, InYoung Ko
In Internet of Things (IoT) environments, users are required to search for IoT devices necessary to access services for accomplishing their tasks. As IoT technologies advance, a user task will utilize various types of IoT-based services that are deployed in an IoT environment. Therefore, to accomplish a user task effectively, the services that utilize IoT devices need to be found in a certain geographical region. In addition, the service discovery needs to be accomplished in a stable manner while considering dynamically changing IoT environments. To deal with these issues, we propose two service discovery methods that consider geographic cohesiveness of services in IoT environments. We compare the effectiveness of the proposed methods against a traditional service discovery algorithm that does not consider geographic cohesiveness.
A Conceptual Framework for Aging Diagnosis Using IoT Devices
Jae Yoo Lee, Jin Cheul Park, Soo Dong Kim
With the emergence of Internet-of-Things (IoT) computing, it has become possible to acquire users’ health-related contexts from various IoT devices and to diagnose their biological aging through analysis of the IoT health contexts. However, previous work on methods of aging diagnosis used a fixed list of aging diagnosis factors, making it difficult to handle the variability of users’ IoT health contexts and to dynamically adapt the addition and deletion of aging diagnosis factors. This paper proposes a design and methods for a dynamically adaptable aging diagnosis framework that acquires a set of IoT health contexts from various IoT devices based on a set of aging diagnosis factors of the user. By using the proposed aging diagnosis framework, aging diagnosis methods can be applied without considering the variability of IoT health contexts and aging diagnosis factors can be dynamically added and deleted.
Design and Implementation of DNS Name Autoconfiguration for Internet of Things Devices
As one of the most spotlighted research areas, these days, the Internet of Things (IoT) aims to provide users with various services through many devices. Since there exist so many devices in IoT environments, it is inefficient to manually configure the domain name system (DNS) names of such devices. Thus, for IPv6-based IoT environments, this paper proposes a scheme called the DNS Name Autoconfiguration (DNSNA) that autoconfigures an IoT device’s DNS name and manages it. In the procedure for generating and registering an IoT device’s DNS name, the standard protocols of the Internet Engineering Task Force (IETF) are used. Since the proposed scheme resolves an IoT device’s DNS name into an IPv6 address in unicast through a DNS server, it generates less traffic than multicast-based mDNS (Multicast DNS) which is a legacy DNS application for the DNS name service in the smart home. Thus, the proposed scheme is more appropriate in multi-hop IoT networks than mDNS. This paper explains the design of the proposed scheme and its service scenarios, such as smart home and smart road. It also explains the implementation and testing of the proposed scheme in the smart grid.
A Markov Game based QoS Control Scheme for the Next Generation Internet of Things
The Internet of Things (IoT) is a new concept associated with the future Internet, and it has recently become a popular concept to build a dynamic, global network infrastructure. However, the deployment of IoT creates difficulties in satisfying different Quality of Service (QoS) requirements and achieving rapid service composition and deployment. In this paper, we propose a new QoS control scheme for IoT systems. The Markov game model is applied in our proposed scheme to effectively allocate IoT resources while maximizing system performance. The results of our study are validated by running a simulation to prove that the proposed scheme can promptly evaluate current IoT situations and select the best action. Thus, our scheme approximates the optimum system performance.
A Routing Scheme Considering Bottleneck and Route Link Quality in RPL-based IoT Wireless Networks
Ik-Joo Jung, Sang-Hwa Chung, Sung-Jun Lee
In order to manage a large number of devices connected to the Internet of Things (IoT), the Internet Engineering Task Force (IETF) proposed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). The route of the RPL network is generated through the use of an Objective Function (OF) that is suitable for the service that is required for the IoT network. Since the route of the RPL network is conventionally simply chosen only by considering the link quality between the nodes, it is sensible to seek an OF that can also provide better Quality of Service (QoS). In previous studies, the end-to-end delay might possibly be sub-optimal because they only deal with problems related to the reduction of energy consumption and not to the link quality on the path to the sink node. In this study, we propose a scheme that reduces the end-to-end delay but also gives full consideration to both the quality on the entire route to the destination and to the expected lifetime of nodes with bottlenecks from heaped traffic. Weighting factors for the proposed scheme are chosen by experiments and the proposed scheme can reduce the end-to-end delay and the energy consumption of previous studies by 20.8% and 10.5%, respectively.
Efficient Packet Transmission Utilizing Vertical Handover in IoT Environment
The Internet of Things (IoT) has recently been showered with much attention worldwide. Various kinds of devices, communicating with each other in the IoT, demand multiple communication technologies to coexist. In this environment, mobile devices may utilize the vertical handover between different wireless radio interfaces such as Wi-Fi and Bluetooth, for efficient data transfer. In this paper, an IoT broker is implemented to support the vertical handover, which can also support and manage heterogeneous devices and communication interfaces. The handover is activated based on RSSI, Link Quality values, and real time traffic. The experimental results show that the proposed handover system substantially improves QoS in Bluetooth and reduces power consumption in mobile devices as compared with a system using only Wi-Fi.
Real-time and Parallel Semantic Translation Technique for Large-Scale Streaming Sensor Data in an IoT Environment
SoonHyun Kwon, Dongwan Park, Hyochan Bang, Youngtack Park
Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.
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