MEQA-RPL: A Mobility Energy and Queue Aware Routing Protocol for Mobile Nodes in Internet of Things

Increase in mobile nodes has brought new challenges to IoT’s routing protocol-RPL. Mobile nodes (MN) bring new possibilities as well as challenges to the network. MN creates frequent route disruption, energy loss and increases end-to-end delay in the network. This could be solved by improving RPL to react faster to route failures through route prediction, while keeping energy expenditure for this process in reasonable limits. In this context a new Mobility Energy and Queue Aware-RPL (MEQA-RPL) is proposed that have the capability to sense route failure and to identify proactively the next possible route before the current route fails. While identifying the next route, MEQA-RPL employs constraint check on energy and queue availability to guarantee QoS for MN and better lifetime for the network. When compared to RPL with mobility support our model reduce average signaling cost by 31%, handover delay by 32% and improve packet delivery ratio by 17%. We run simulations with multiple mobile nodes which have also shown promising results on aforementioned parameters.

An Efficient Route Failure Detection Mechanism with Energy Efficient Routing (EER) Protocol in MANET

Mobile ad-hoc network (MANET) is a network with two or more number of nodes with restricted energy constraint. The high dynamic nature in MANET attracts needs to consider the energy efficient features in their construct. The routing protocol is an important criterion to be considered for evaluating the performance of the MANET. Energy consumption plays vital role in MANET. Hence designing the scheme that supports energy efficient is much needed for the high dynamic MANET environment concerned. This paper proposes the Energy Efficient Routing (EER) protocol based on efficient route failure detection. The Scope of this paper is to suggest a fresh routing procedure for Mobile Adhoc Network minimizes unsuccessful communication. The projected procedure practices three important criterions to locate the path that assure authentic communication. The channel caliber, connection caliber and node’s residual energy is important reason for the failure of the node in MANET. Hence, the suggested routing mechanism believes these three different parameters to choose the finest node in the route. The reliable transmission and reception are attained by transferring information through route nominated by the suggested system verified by means of NS-2 simulator.

FarpScusn: Fully Anonymous Routing Protocol with Self-Healing Capability in Unstable Sensor Networks

Anonymous technology is an effective way for protecting users’ privacy. Anonymity in sensor networks is to prevent the unauthorized third party from revealing the identities of the communication parties. While, in unstable wireless sensor networks, frequent topology changes often lead to route-failure in anonymous communication. To deal with the problems of anonymous route-failure in unstable sensor networks, in this paper we propose a fully anonymous routing protocol with self-healing capability in unstable sensor networks by constructing a new key agreement scheme and proposing an anonymous identity scheme. The proposed protocol maintains full anonymity of sensor nodes with the self-healing capability of anonymous routes. The results from the performance analysis show that the proposed self-healing anonymity-focused protocol achieves full anonymity of source nodes, destination nodes, and communication association.

A Predictive-Reactive Approach with Genetic Programming and Cooperative Coevolution for the Uncertain Capacitated Arc Routing Problem

The uncertain capacitated arc routing problem is of great significance for its wide applications in the real world. In the uncertain capacitated arc routing problem, variables such as task demands and travel costs are realised in real time. This may cause the predefined solution to become ineffective and/or infeasible. There are two main challenges in solving this problem. One is to obtain a high-quality and robust baseline task sequence, and the other is to design an effective recourse policy to adjust the baseline task sequence when it becomes infeasible and/or ineffective during the execution. Existing studies typically only tackle one challenge (the other being addressed using a naive strategy). No existing work optimises the baseline task sequence and recourse policy simultaneously. To fill this gap, we propose a novel proactive-reactive approach, which represents a solution as a baseline task sequence and a recourse policy. The two components are optimised under a cooperative coevolution framework, in which the baseline task sequence is evolved by an estimation of distribution algorithm, and the recourse policy is evolved by genetic programming. The experimental results show that the proposed algorithm, called Solution-Policy Coevolver, significantly outperforms the state-of-the-art algorithms to the uncertain capacitated arc routing problem for the ugdb and uval benchmark instances. Through further analysis, we discovered that route failure is not always detrimental. Instead, in certain cases (e.g., when the vehicle is on the way back to the depot) allowing route failure can lead to better solutions.

Performance analysis of wireless sensor networks assisted by on-demand-based cloud infrastructure

The wireless sensor networks composed of tiny sensor with the capability of mon- itoring the tangible changes for a wide range of applications are limited with the capabilities on processing and storage. Their limited capabilities make them seek the help of the cloud that provides the rented service of processing and storage. The dense deployment of the wireless sensor and their vulnerability to the unknown attacks, alterations make them incur difficulties in the process of the conveyance causing the modifications or the loss of the content. So, the paper proposes an optimized localization of the nodes along with the identification of the trusted nodes and minimum distance path to the cloud, allowing the target to have anytime and anywhere access of the content. The performance of the cloud infrastructure-supported wireless sensor network is analyzed using the network simulator 2 on the terms of the forwarding latency, packet loss rate, route failure, storage, reliability, and the network longevity to ensure the capacities of the cloud infrastructure-supported wireless sensor networks.

Energy and Congestion Aware Multipath Routing in MANET

An interconnection of wireless nodes in motion is called as Mobile AdHoc Network (MANET). One of the problems facing MANET is the route failure due to dynamic movement of nodes. Route failure leads to frequent path search and extra effort for maintaining existing path. An effective routing protocol should choose an elite path for dispatching data and consume less resources. Ad-hoc On-demand Multipath Distance Vector (AOMDV) protocol can sustain more than one path between the communicating nodes and switches between them, whenever communication fails over selected path. This way, it reduces the effort of discovering new path, whenever an existing path fails. However, while choosing alternative paths the protocol only considers the hop count as a deciding factor and it does not take into consideration the energy associated with node nor the congestion along the chosen path. In this paper, we consider both residual energy and active load while selecting path for communication. Performance of both protocols are tested on NS2 simulator. It was found that, the enhancement does provide an improvement in performance than the existing protocol

Improving AODV route recovery mechanism using PSO in WSN

Objective: The conventional Ad Hoc On-Demand Distance Vector (AODV) routing algorithm, route discovery methods pose route failure resulting in data loss and routing overhead. In the proposed method, needs significant low energy consumption while routing from one node to another node by considering the status of node forwards the packet. So that while routing it avoids unnecessary control overhead and improves the network performance. Methods: Particle Swarm Optimization (PSO) algorithm is a nature- inspired, population-based algorithm. Particle Swarm Optimization (PSO) is a Computational Intelligence technique which optimizes the objective function. It works by considering that every member of the swarm contributes in finding the ideal solution by keeping a track of their own best known location and the best-known location of the group and keeps updating them whenever there is a change and hence minimizes the objective fitness function. The fitness function which we considered here is the Node lifetime, Link Lifetime and available Bandwidth. If these parameters are with good then status of node will be strong and hence routing of packet over those nodes will reduce delay and improves network performance. Result: To verify the feasibility and effectiveness of our proposal, the routing performance of AODV and PSO-AODV is compared with respect to various network metrics like Network Lifetime, packet delivery ratio and routing overhead and validated the result by comparing both routing algorithm using Network Simulator 2. The results of the PSO-AODV has outperformed the AODV in terms of low energy, less end to end delay and high packet delivery ratio and less control overhead. Conclusion: Here we proposed to use Particle Swarm Optimization in order to obtain the more suitable parameters for the decision making. The existing AODV protocol was modified to make a decision to recover from route failure; at the link failure predecessor node implementing PSO based energy prediction concept and using weights for each argument considered in the decision function. The fitness values for each weight were found through PSO basic form. We observed that the PSO showed satisfactory behaviour improvement than the performance of AODV for all metrics on the investigated scenarios.

Flexible Particle Swarm Optimization based Routing Protocol to Reduce Energy Consumption in Mobile Ad-Hoc Network

MANET is a self-configuring, autonomous and infrastructure less network. MANET has received its popularity by its easy installation and usage at any environment. Sudden change in the network topology may lead to enormous challenges in finding and maintaining the optimal route between source and destination. The nodes in MANET can leave the network at any time which causes route failure leading to consume more energy in finding the alternate route. Routing is one of the top issues in network research domain and it prefers to find and maintain the routes among the nodes. In this paper flexible particle swarm optimization-based routing protocol is proposed to avoid route failure and energy consumption. The proposed protocol is designed to have increased communication between the particles in the swarm and this results in finding the best route towards the destination. This research work utilizes the benchmark performance metrics to measure the performance of proposed protocols against the existing routing protocols. The result shows that the proposed protocol outperforms than the existing routing protocols.