Modeling and proving dynamic behaviors of a routing protocol: A tutorial

With the increasing adoption of Internet of Things technologies for controlling physical processes, their dependability becomes important. One of the fundamental functionalities on which such technologies rely for transferring information between devices is packet routing. However, while the performance of Internet of Things–oriented routing protocols has been widely studied experimentally, little work has been done on provable guarantees on their correctness in various scenarios. To stimulate this type of work, in this article, we give a tutorial on how such guarantees can be derived formally. Our focus is the dynamic behavior of distance-vector route maintenance in an evolving network. As a running example of a routing protocol, we employ routing protocol for low-power and lossy networks, and as the underlying formalism, a variant of linear temporal logic. By building a dedicated model of the protocol, we illustrate common problems, such as keeping complexity in control, modeling processing and communication, abstracting algorithms comprising the protocol, and dealing with open issues and external dependencies. Using the model to derive various safety and liveness guarantees for the protocol and conditions under which they hold, we demonstrate in turn a few proof techniques and the iterative nature of protocol verification, which facilitates obtaining results that are realistic and relevant in practice.

A Multi-Agent Reinforcement Learning-Based Optimized Routing for QoS in IoT

The Routing Protocol for Low power and lossy networks (RPL) is used as a routing protocol in IoT applications. In an endeavor to bring out an optimized approach for providing Quality of Service (QoS) routing for heavy volume IoT data transmissions this paper proposes a machine learning-based routing algorithm with a multi-agent environment. The overall routing process is divided into two phases: route discovery phase and route maintenance phase. The route discovery or path finding phase is performed using rank calculation and Q-routing. Q-routing is performed with Q-Learning reinforcement machine learning approach, for selecting the next hop node. The proposed routing protocol first creates a Destination Oriented Directed Acyclic Graph (DODAG) using Q-Learning. The second phase is route maintenance. In this paper, we also propose an approach for route maintenance that considerably reduces control overheads as shown by the simulation and has shown less delay in routing convergence.

Equal Area Partition-Based Energy Efficient Routing Algorithm for Circular WSN

Wireless sensor network (WSN) is communicating method with each other without the assistance of communication cable. The circular environment is an important application scenario in WSN. As a core technology, routing algorithm is the brain of WSN monitoring system. In this paper, we propose a new routing algorithm named Equal Area Partition Based Energy Efficient Multipath Algorithm (EAPEEM), which tries to exploit sector equal area model in node deployment, data transfer, and route maintenance. Existing algorithms, as compared to our existing models, do not fully match with routing and nodes. One attractive feature of our protocol is its balanced network transmission capacity and improved node energy utilization, which can reduce the possibility of system damage. Simulations show that EAPEEM can retain at least 28.6% of batteries and expand stability by more than 43%.

Adaptive-Sunflower Based Grey Wolf Algorithm For Multipath Routing In Iot Network

This paper devises a routing method for providing multipath routing inan IoT network. Here the Fractional Artificial Bee colony(FABC)algorithm is devised for initiating clustering process. Moreover the multipath routing is performed by the newly devised optimization technique, namely Adaptive-Sunflower based grey wolf(Adaptive-SFG)optimization technique which is designed by incorporating adaptive idea in Sunflower based grey wolf technique. In addition the fitness function is newly devised by considering certain factors that involves Context awareness, link lifetime Energy, Trust, and Delay.For the computation of the trust, additional trust factors like direct trust indirect trust recent trust and forwarding rate factor is considered. Thus, the proposed Adaptive SFG algorithm selects the multipath for routing based on the fitness function.Finally, route maintenance is performed to ensure routing without link breakage.The proposed Adaptive-SFG outperformed other methods with high energy of0.185Jminimal delay of 0.765sec maximum throughput of47.690%and maximum network lifetime of98.7%.

Hybrid Congestion Sharing and Route Repairing Protocol for Bluetooth Networks

Bluetooth is a widespread wireless technology standard for limited wireless networks that permits Bluetooth devices to create a one-hop (piconet) or multi-hop (scatternet) network. During data transmission, a large number of links passing through a single master or bridge device may create congestion problems in a Bluetooth network. Therefore, routing in a multi-hop dynamic Bluetooth network, where a number of routing masters and routing bridges exist, sometimes create technical problems in a scatternet. Mobility and failure of routing devices disconnects the routing links and link reconstruction process consumes more resources that eventually decrease the performance. In this paper, Hybrid Congestion Sharing and Route Repairing protocol for Bluetooth networks” (HCSRR) is proposed. The objective of this paper is to provide an efficient technique for scatternet congestion avoidance and route maintenance. The proposed protocol is implemented and compared with most relevant protocols. From simulation results, it is observed that the HCSRR outperforms the existing protocols.

Optimal Route Maintenance based on Adaptive Equilibrium Optimization and GTA based Route Discovery Model in MANET

Recently, routing is considered the main problem in MANET due to its dynamic nature. The route discovery and the optimal route selection from the multiple routes are established for the efficient routing in MANET. The major objective of this research is to select the optimal route for packet transmission in MANET. In this paper, four stages namely trust evaluation, route discovery, optmal route selection and route maintanance are elucidated. Initially, the trust evaluation is made by using ANFIS where the primary trust values are evaluated. The next stage is the route discovery scheme, in which the routes are established by Group teaching optimization algorithm (GTA). From the route discovery scheme, multiple routes are found. The optimal route for the transmission is selected with the help of the Adaptive equilibrium optimizer (AO) algorithm. Finally, the route maintenance process is established; if any of the routes fails for the broadcast it immediately selects the alternate optimal route from the multi-zone routing table for efficient packet transmission. The proposed approach is evaluated by various performance measures like throughput, energy consumption, packet delivery ratio, end-to-end delay, packet loss rate, detection rate, and routing overhead. This result describes that the proposed approach outperforms other state-of-art approaches.

ANFIS Based Optimal Routing using Group Teaching and Adaptive Equilibrium Optimization based Trust Aware Routing Protocol in MANET

Recently, routing is considered the main problem in MANET due to its dynamic nature. The route discovery and the optimal route selection from the multiple routes are established for the efficient routing in MANET. The major objective of this research is to select the optimal route for packet transmission in MANET. In this paper, four stages namely trust evaluation, route discovery, optmal route selection and route maintanance are elucidated. Initially, the trust evaluation is made by using ANFIS where the primary trust values are evaluated. The next stage is the route discovery scheme, in which the routes are established by Group teaching optimization algorithm (GTA). From the route discovery scheme, multiple routes are found. The optimal route for the transmission is selected with the help of the Adaptive equilibrium optimizer (AO) algorithm. Finally, the route maintenance process is established; if any of the routes fails for the broadcast it immediately selects the alternate optimal route from the multi-zone routing table for efficient packet transmission. The proposed approach is evaluated by various performance measures like throughput, energy consumption, packet delivery ratio, end-to-end delay, packet loss rate, detection rate, and routing overhead. This result describes that the proposed approach outperforms other state-of-art approaches.