Routing In Internet Of Things Research Articles

Secure routing for internet of things: A survey

The Internet of Things (IoT) could be described as the pervasive and global network which aids and provides a system for the monitoring and control of the physical world through the collection, processing and analysis of generated data by IoT sensor devices. It is projected that by 2020 the number of connected devices is estimated to grow exponentially to 50 billion. The main drivers for this growth are our everyday devices such as cars, refrigerators, fans, lights, mobile phones and other operational technologies including the manufacturing infrastructures which are now becoming connected systems across the world. It is apparent that security will pose a fundamental enabling factor for the successful deployment and use of most IoT applications and in particular secure routing among IoT sensor nodes thus, mechanisms need to be designed to provide secure routing communications for devices enabled by the IoT technology. This survey analyzes existing routing protocols and mechanisms to secure routing communications in IoT, as well as the open research issues. We further analyze how existing approaches ensure secure routing in IoT, their weaknesses, threats to secure routing in IoT and the open challenges and strategies for future research work for a better secure IoT routing.

Multipath Load Balancing Routing for Internet of Things

In the next-generation technology, Internet of Things (IoT), billions of smart objects will communicate with one another to make human lives more convenient. IoT is based on wireless sensor network (WSN), and Zigbee is one of the most popular WSN protocols. A mature IoT environment involves heavy WSN data transmission causing bottleneck problems. However, Zigbee’s AODV routing stack does not have load balance mechanism to handle bursty traffic. Therefore, we develop Multipath Load Balancing (MLB) Routing to substitute Zigbee’s AODV routing. Our proposed MLB consists of two main designs: LAYER_DESIGN and LOAD_BALANCE. LAYER_DESIGN assigns nodes into different layers based on node distance to IoT gateway. Nodes can have multiple next-hops delivering IoT data. All neighboring layer nodes exchange flow information containing current load, used by LOAD_BALANCE to estimate future load of next-hops. With MLB, nodes can choose the neighbors with the least load as the next-hops and thus can achieve load balance and avoid bottlenecks. Compared with Zigbee’s AODV and multipath version AODV (AOMDV), experiment results demonstrate that MLB achieves better load balance, lower packet loss rate, and better routing connectivity ratio in both grid and random uniform topologies. MLB provides a more convincing routing solution for IoT applications.

QOS by Priority Routing in Internet of Things

The aim of this study is to present a system which uses a new layered network architecture approach for IOT. Sudden and unpredictable large-scale changes are commonly prevalent in Internet of Things (IoT). The images or video data captured from the remote places have to be routed without delay. This is a tumultuous task in large scale. By using an Agents in various wireless networks and the packets are routed depends on the priority. The scope of this study is to avoid delay, interference during transfer of data from various wireless networks. This study deals with (i) congestion free data transfer under many cramped networks (ii) low processing overhead (iii) handling realistic failure scenarios, prioritized traffic in a flexible manner (iv) robust to both topology failures and traffic variations. This study presents a QoS routing method, by setting a priority to the networks to differentiate eclectic sensing vicinities in the smart space between sender and receiver.

Quantization Strategies of RFID Routing in Internet of Things

This paper researches wireless RFID routings in Internet of Things based on the idea of quantization. The researches include the obtaining of routing contexts, the measurement of contexts in evaluating the performance of routing, methods for controlling the quantification of contexts, the realization of a perceptive computational model, the mergence of the security policies. Its goal is to construct a precise lightweight and perceptive model of wireless RFID routing protocols in Internet of Things, and to lay a foundation for accelerating the developments in Internet of Things.