Self-adaptive Routing Algorithm Research Articles

A Self-Adaptive Routing Algorithm for Real-Time Video Transmission in VANETs

A Self-Adaptive Routing Algorithm for Real-Time Video Transmission in VANETs

AI-driven adaptive reliable and sustainable approach for internet of things enabled healthcare system.

Artificial Intelligence (AI) driven adaptive techniques are viable to optimize the resources in the Internet of Things (IoT) enabled wearable healthcare devices. Due to the miniature size and ability of wireless data transfer, Body Sensor Networks (BSNs) have become the center of attention in current medical media technologies. For a long-term and reliable healthcare system, high energy efficiency, transmission reliability, and longer battery lifetime of wearable sensors devices are required. There is a dire need for empowering sensor-based wearable techniques in BSNs from every aspect i.e., data collection, healthcare monitoring, and diagnosis. The consideration of protocol layers, data routing, and energy optimization strategies improves the efficiency of healthcare delivery. Hence, this work presents some key contributions. Firstly, it proposes a novel avant-garde framework to simultaneously optimize the energy efficiency, battery lifetime, and reliability for smart and connected healthcare. Secondly, in this study, an Adaptive Transmission Data Rate (ATDR) mechanism is proposed, which works on the average constant energy consumption by varying the active time of the sensor node to optimize the energy over the dynamic wireless channel. Moreover, a Self-Adaptive Routing Algorithm (SARA) is developed to adopt a dynamic source routing mechanism with an energy-efficient and shortest possible path, unlike the conventional routing methods. Lastly, real-time datasets are adopted for intensive experimental setup for revealing pervasive and cost-effective healthcare through wearable devices. It is observed and analysed that proposed algorithms outperform in terms of high energy efficiency, better reliability, and longer battery lifetime of portable devices.

Novel self-adaptive routing service algorithm for application in VANET

As a special MANET (mobile ad hoc network), VANET (vehicular ad-hoc network) has two important properties: the network topology changes frequently, and communication links are unreliable. Both properties are caused by vehicle mobility. To predict the reliability of links between vehicles effectively and design a reliable routing service protocol to meet various QoS application requirements, in this paper, details of the motion characteristics of vehicles and the reasons that cause links to go down are analyzed. Then a link duration model based on time duration is proposed. Link reliability is evaluated and used as a key parameter to design a new routing protocol. Quick changes in topology make it a huge challenge to find and maintain the end-to-end optimal path, but the heuristic Q-Learning algorithm can dynamically adjust the routing path through interaction with the surrounding environment. This paper proposes a reliable self-adaptive routing algorithm (RSAR) based on this heuristic service algorithm. By combining the reliability parameter and adjusting the heuristic function, RSAR achieves good performance with VANET. With the NS-2 simulator, RSAR performance is proved. The results show that RSAR is very useful for many VANET applications.

Energy-efficient and self-adaptive routing algorithm based on event-driven in wireless sensor network

In wireless sensor networks, the energy consumption is one of the major issues. This paper proposes an event driven based adaptive routing algorithm that avoids the node energy consumption used for emergency monitoring. A cluster tree based on connected dominating set is constructed. When a new event takes place, the algorithm constructs a local topology in that region to quickly transfer the message through a cluster tree, so as to avoid a wide range of flood routing in the network. In addition, it proposes a periodical replacement strategy of the cluster head, which avoids too fast consumption of cluster head node energy. Only the cluster member nodes in a restricted vicinity will change their status. Simulation results show that the proposed approach avoids the node energy consumption used for emergency monitoring and the cluster head can evenly distribute loads, which effectively balances the energy consumption of network nodes, and thus efficiently extends the lifetime of network.

Location-Based Self-Adaptive Routing Algorithm for Wireless Sensor Networks in Home Automation

The use of wireless sensor networks in home automation (WSNHA) is attractive due to their characteristics of self-organization, high sensing fidelity, low cost, and potential for rapid deployment. Although the AODVjr routing algorithm in IEEE 802.15.4/ZigBee and other routing algorithms have been designed for wireless sensor networks, not all are suitable for WSNHA. In this paper, we propose a location-based self-adaptive routing algorithm for WSNHA called WSNHA-LBAR. It confines route discovery flooding to a cylindrical request zone, which reduces the routing overhead and decreases broadcast storm problems in the MAC layer. It also automatically adjusts the size of the request zone using a self-adaptive algorithm based on Bayes' theorem. This makes WSNHA-LBAR more adaptable to the changes of the network state and easier to implement. Simulation results show improved network reliability as well as reduced routing overhead.