QoS Routing Research Articles

A Bio inspired optimization with Reliable QoS Routing through Efficient Packet Transmission in Mobile ad-hoc Network

A collection of mobile devices is defined as a Mobile Ad-hoc Network (MANET). Without any prior management these devices can communicate and synchronize with one another. The state of the concerned channel determines how much life energy can be increased. It also extends the node's lifetime while it waits for the control messages to be completed. The nodes' lifespan and packet flow quality are harmed in the current system due to unanticipated energy conservation strategies. It causes post-network collapse due to an energy throughput trade off. This failure causes an increase in overhead and a decrease in Time-to-Live (TTL). In addition to proposing a novel performance modeling in Volunteered Computing MANET and tactile internet, this paper discusses an effective buffer management mechanism. The best execution the nodes can achieve with fractional data is depicted for utilities in general. A switch state promoting Optimized mutual MAC (OMAC) process was presented in this study for node conserving energy and the optimal utilization of accessible nodes before their resource drain to link the space between network efficiency conservation based on minimal overhead. As proof of the proposed solution, simulation results are provided. Compared the simulation outcomes with the existing system using the parameters like latency, quantity, node availability & energy consumption.

Hybrid multi-objective-optimization algorithm for energy efficient priority-based QoS routing in IoT networks

Hybrid multi-objective-optimization algorithm for energy efficient priority-based QoS routing in IoT networks

QoS Routing Algorithm for OBS Networks Based on a Multi-Objective Genetic Algorithm

To optimize the QoS of optical burst switching networks, a QoS routing optimization algorithm based on a multi-objective genetic algorithm is proposed. A Bayesian network model is used to locate the fault of optical burst switching network and obtain the fault location of the transmission link of optical burst switching network; In this position, the routing optimization algorithm based on a multi-objective genetic algorithm transforms the multi constrained network quality of service routing optimization problem into a constrained multi-objective routing optimization problem. Under multiple constraints, the best path of optical burst switching network service is obtained to realize the optical burst switching network quality of service routing optimization. The results show that after applying the proposed algorithm, the average delay of video, text and picture transmission in an optical burst switching network is less than 400ms. The proposed algorithm can improve the packet delivery rate of information transmission in an optical burst switching network, reduce the transmission delay, blocking probability and use cost of an optical burst switching network, and optimize the service quality of an optical burst switching network.

PROPOSING NEW ROUTING PROTOCOL BASED ON CHAOS ALGORITHM

In MANET, the multicast routing is considered as a non-deterministic polynomial (NP) complexity, it contains assorted objectives and restrictions. In the multicast issue of MANET, the Quality of services (QoS) based upon cost, delay, jitter, bandwidth, these are constantly deemed as multi-objective for intending multiple cast routing protocols. Conversely, mobile node has finite battery energy and the lifetime of network depending on its mobile node battery energy. If the mobile node has high battery energy consumption, it automatically reduces the network’s life time because of their route breaks. Alternatively, node’s battery energy has to be consumed to ensure higher level quality of services in multicast routing for transmitting the accurate data anywhere and anytime. Therefore, the network lifespan is deemed as multi-objective in the multicast routing (MR) problem. To overcome these issues, QoS and Network Lifetime Aware Reliable Multicast Routing Protocol are proposed by applying Chaos integrated Cuckoo Search Rider Optimization Algorithm for effectual data transmission in MANET (QOS-MRP-CSROA-MANET). The proposed method is the joint execution of both the Cuckoo Search Algorithm with chaos theory (Chaotic-CSA) and Rider Optimization (ROA) algorithm and hence it is called as Chaotic-CSA-ROA, which is utilized to solve the MR problem of MANET. Here, the MR problem of MANET have five objectives, viz cost, delay, jitter, bandwidth, network lifetime are optimized with the help of Chaotic-CSA-ROA. Then the proposed method is simulated in NS2 simulator for validating the performance of the proposed QOS-MRP-CSROA-MANET system. Here, evaluation metrics, via delay, delivery ratio, drop, Network lifespan, overhead and throughput are analyzed with node, rate and speed. The proposed QOS-MRP-CSROA-MANET provide higher throughput in node as 32.9496% and 65.5839%, higher throughput in rate as 16.6049% and 30.4654%, higher through put in speed as 10.1298% and 7.0825%, low packet drop in node as 63.7313% and 52.2255%, low packet drop in rate as 51.5528% and 25.6220%, low packet drop in speed as 18.0857% and 24.5953% compared with existing methods, like QOS aware of multicast routing protocol using particle swarm optimization algorithm in MANET (QOS-MRP-PSOA-MANET) and QOS aware of multicast routing protocol using genetic algorithm in MANET (QOS-MRP-GA-MANET) respectively.

An adaptive scheduling routing for multimedia services based on software-defined networks

We address the routing optimization problem in Software-Defined Networks (SDN) while satisfying multiple QoS constraints of multimedia services. In this paper, we 1) formally define the problem of routing optimization in SDN under multiple QoS constraints, and 2) suggest a novel architecture based on SDN for providing QoS services in the network. We propose an adaptive scheduling routing optimization approach in SDN that improves the classical Dijkstra routing algorithm. We report the results of experiments using the Mininet simulation framework that confirm the advantages of our proposed QoS routing optimization approach as compared to the state-of-the-art solutions.

Lifespan-Balance-Based Energy-Efficient Routing for Rechargeable Wireless Sensor Networks

The rechargeable wireless sensor networks provide efficient data services for many applications in the Internet of Things (IoT), in which the sensors can be recharged continuously. Wireless recharging technology has been widely studied and applied. Reasonable energy allocation and identification of the nodes which need recharging in each round is key to the technology. According to dynamic recharging planning, it is crucial to improve energy efficiency in networks with excellent Quality of Service (QoS). Hence, a lifespan-balance-based energy-efficient routing is proposed. The optimization problem of maximizing recharging payoff is first designed and it is solved by our heuristic algorithm, which enables dynamic adjustment of the ratio of moving time to recharging time according to energy states of nodes. Then the QoS routing based on multi-hop strategy which integrates multiple related factors is designed. Finally, the indicator which contains energy supplement to quantify lifespan is designed. Combined with our QoS routing, the method of lifespan balance based on the global relay range regulation is proposed to maximize the minimum lifespan of all nodes intelligently. The simulation result shows that our algorithm can improve the energy efficiency with excellent QoS in the studied networks and prolong the network lifetime.

GENETIC ALGORITHM FOR WIRELESS SENSOR NETWORKS

Ad hoc networks are made up of a collection of wireless mobile nodes that form a temporary network with no pre-existing infrastructure or centralized management.Routing policies are crucial in determining how traffic is forwarded across a network. Adhoc networks necessitate a routing method that is very adaptable. Finding the shortest path (SP) between source and destination in a specific period of time to meet Quality of Service standards is one of the most common issues in these networks (QoS). QoS routing is difficult in an Ad hoc network because the topology changes frequently and it takes time since many QoS criteria such as distance, cost, and energy are all variable, and the state information supplied for routing is inherently faulty. The optimum path for Adhoc networks is found using a Genetic Algorithm (GA) in this paper.GA uses natural evolution-inspired methodologies to find answers to optimization problems. Crossover and mutation operations, as well as the proper chromosome structure, are all defined.

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

Abstract 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.

Application-aware QoS routing in SDNs using machine learning techniques

Application-aware QoS routing in SDNs using machine learning techniques

Impact of Intermediate Bottleneck Nodes on the QoS Provision in Wireless Infrastructure less Networks

Wireless Infrastructure less networks consist of wireless mobile nodes with heterogeneous and constrained resources, to establish internet connectivity regardless of the location. The applications the networks are disaster relief, health care and military. These applications are sensitive, and demands the reliable, and best quality of communication. Routing is one of the resources to enable the communication. Routing is acceptable in an infrastructure less networks if it satisfies the quality of service requirements. Thus the paper aims to investigate the existing QoS routing protocol performance in various conditions. The aim is to achieve a broad understanding of QoS routing protocol designed for Wireless Infrastructure less networks, and further pave the pathway for future research. The paper analyses the QoS routing protocol performance in presence of bottleneck intermediate node, and it is the novel aspect of the work.

An SDN-based framework for QoS routing in internet of underwater things

An SDN-based framework for QoS routing in internet of underwater things

EFFICIENT TRUST BASED SCHEMES FOR QUALITY OF SERVICE IN MANET

Security is another crucial aspect of providing QoS since the existence of malicious nodes present all kinds of threats to MANETs. Although a number of mechanisms have been proposed for protecting MANETs, most of the solutions are only effective for a particular kind of attacks or provide security at the cost of sacrificing QoS. In this paper, we propose a trust-based secure QoS routing scheme by combining social and QoS trust. The primary approach of the proposed scheme relies on mitigating nodes that exhibit various packet forwarding misbehavior and on discovering the path that ensures reliable communication through the trust mechanism. The scheme would select the best forwarding node based on packet forwarding behavior as well as capability in terms of QoS parameters, such as residual energy, channel quality, link quality, etc. Simulation experiment using Network Simulator-2 (NS2) and under various network conditions show that mixing social and QoS trust parameters can greatly improve security and quality of service routing in terms of overhead, packet delivery ratio and energy consumption.

QoS routing in cluster OLSR by using the artificial intelligence model MSSP in the big data environnment

<p><span id="docs-internal-guid-75ba661c-7fff-7cfb-9afe-b7c901c3fe82"><span>The most complex problems, in data science and more specifically in artificial intelligence, can be modeled as cases of the maximum stable set problem (MSSP). this article describes a new approach to solve the MSSP problem by proposing the continuous hopfield network (CHN) to build optimized link state protocol routing (OLSR) protocol cluster. our approach consists in proposing in two stages: the first acts at the level of the choice of the OLSR master cluster in order to quickly make a local minimum using the CHN, by modeling the MSSP problem. As for the second step, the objective is the improvement of the precision making a solution of efficient at the first rank of neighborhood as a linear constraint, and at the end, to find the resolution of the model using the CHN. We will show that this model determines a good solution of the MSSP problem. To test the theoretical results, we propose a comparison with a classic OLSR.</span></span></p>

Improving NSGA-II for Multi-Constrained QoS Routing

With the development of 5G technology, the traffics which need multiple quality of service (QoS) constraints greatly increase. The existing QoS routing algorithms either support a single QoS constraint or support multiple constraints are mixed with fixed weights. The latter is essentially a single-constrained QoS algorithm. Few studies can provide the quality of service guaranteed under the true sense of multiple constraints, by which only one solution can be provided. In this paper, we propose NSGAII-MCR: a multi-constrained QoS routing algorithm based on non-dominated sorting genetic algorithm II (NSGA-II). In NSGAII-MCR, three representative constraints are selected: delay, bandwidth, and packet loss rate. The validity of the routing is guaranteed by a designed encoding and decoding scheme and a novel individual generation method. Meantime, the original NSGA-II crossover and mutation operators are modified. We further enhance the selection strategy to improve the diversity of solutions and the robustness of NSGAII-MCR. At last, multiple optional routes in the Pareto-optimal front are obtained. The experiment demonstrates that the proposed NSGAII-MCR can achieve high success rate by up to 95%. Compared with the benchmarking methods, NSGAII-MCR can support more constraints and finds more multi-constrained routes.

QoS Improvement in MANET using Self Organized Balanced Optimization

The provision of quality of service (QoS) for routing in MANET (mobile ad hoc networks) is a major challenge due to the topology, bandwidth sharing and resource scarcity in wireless nodes. Another key aspect of distributing QoS is security, as malicious nodes pose all variety of threats to MANETs. Although a variety of MANET defense measures have been suggested, most solutions are only successful for a particular form of attack or provide security at the risk of sacrificing QoS. A trust-based, secure QoS routing scheme is proposed in this paper by incorporating trust between social and QoS. The key solution of the proposed scheme focuses on minimizing nodes that show different abuses of packet forwarding and finding the way that through the trust mechanism, safe communication is ensured. The performances are compared in in terms of QoS parameters, as channel quality, residual energy, link quality, etc.

Minimization of Energy Consumption for Routing in High-Density Wireless Sensor Networks Based on Adaptive Clone Elite Genetic Algorithm

High-density wireless sensor networks (HDWSNs) perceive environmental information through sensor nodes, connects data to the network, and is widely used in environmental detection, intelligent control, and military fields. Since sensor nodes are usually randomly distributed in the environment and have limited energy, ensuring the energy supply of these nodes is still a difficult problem to solve at present. Therefore, how to effectively reduce network energy consumption, improve algorithm efficiency, and extend network life time is the main problem to be solved by QoS routing in HDWSNs. This paper proposes an adaptive clone elite genetic algorithm (ACEGA) to reduce the energy consumption of HDWSNs routing. The algorithm uses clone operators and elite operators to speed up the convergence speed, and uses adaptive operators to enhance the global search capability of the algorithm. To verify the effectiveness of ACEGA, we compare ACEGA with particle swarm optimization (PSO) and simulated annealing (GA). Simulation results demonstrate that the execution performance of the ACEGA outperforms SA and PSO. In addition, the system energy consumption of HDWSNs using ACEGA is also lower than that of SA and PSO. Therefore, the algorithm we proposed effectively reduces the routing consumption of the entire HDWSNs system.

Multipath QoS routing algorithm based on Ad Hoc network in mine environment

Multipath QoS routing algorithm based on Ad Hoc network in mine environment

An Energy Efficient Qos Routing Protocol Based On Red Deer Algorithm In MANET

MANETs (Mobile ad hoc networks) are overloaded with their heavy usage choking traffic. Recent studies have been attempting to find feasibility of routes in these networks. Most proposed schemes have failed to consider the network traffic or MANET requirements. MANET routing done by RPs (Routing Protocols) would perform better when they adhere to QoS (Quality of Service) or application requirements. As a result, RPs must satisfy numerous QoS metrics at a time where soft computing algorithm based RPs are a solution to QoS routing problems. Evolutionary algorithm based routing do not achieve enough energy efficiency which is a major drawback. To overcome this drawback, this work, proposes Red Deer algorithm (RDA) based energy efficient QoS routing for MANETs called (RDA-EQRP). The proposed RDA based routing algorithm discovers the shortest path from a source to a destination which can consumes less energy while supporting the metrics such of reliability, bandwidth, SRC (Static Resource Capacity), Quality and delay. Simulation results show that proposed rotting scheme RDA-EQRP consumes lesser energy in MANET routing.

Quality-of-Service-Based Minimal Latency Routing for Wireless Networks

Minimized and nearly deterministic end-to-end latency facilitates real-time data acquisition and actuator control. In addition, defined latency is an integral part of quality-oriented service in order to get closer to the reliability of wired networks and at the same time takes advantage of wireless networking. This article introduces a QoS routing protocol capable of balancing power consumption between wireless sensor and actuator nodes while minimizing end-to-end latency. We introduce a time-division multiple access scheme in the routed wireless network to enable defined latency, and in addition, it improves the energy efficiency by avoiding collisions, which eliminates time and energy consuming retries. Our novel routing method allows latency and round-trip times to be calculated in advance. We implement a demonstrator and show experimental results of a wireless sensor network with our proposed routing scheme.

TRAQR: Trust aware End-to-End QoS routing in multi-domain SDN using Blockchain

Recent advances in today’s Internet introduced huge demand for End-to-End Quality of Service (E2E QoS) assurances for delivering different types of traffic (video, live streaming, and telemedicine), originating from a wide spectrum of applications. Such applications stretch across multiple administrative domains and require fair and robust coordination for E2E QoS provisioning. While the selection of trusted domains is of paramount importance for the successful realization of E2E QoS, the issue of domain’s trust while finding E2E QoS paths has not been actively explored in the existing works. Trust awareness reduces the risk of violating QoS and improves the confidence of operating QoS across multiple domains. However, identifying trusted domains, finding the source of trust, and quantifying trust are the major challenges for enabling trust aware E2E QoS routing. Auditability of QoS implementation results at each domain forms a vital source for verifying QoS compliance and subsequently evaluating the trust of the domain. However, securely obtaining logs from the domains and identifying the accountability of domains for E2E QoS, without relying on a third party introduces significant difficulty when evaluating domain trust with respect to QoS compliance. This work proposes Trust aware E2E QoS Routing (TRAQR) framework for provisioning E2E QoS with trust and verifying the QoS compliance in Multi-Domain Software Defined Networks (MD-SDN). TRAQR efficiently leverages the tamper-proof and decentralized properties of Blockchain to store and exchange different kinds of trust information required to provision and verify E2E QoS compliance of the domains. This work developed a proof of concept implementation of the TRAQR in an MD-SDN environment emulated using Mininet, RYU SDN controller, Ethereum Blockchain and Smart Contracts to demonstrate the performance and benefits of TRAQR. Further, the simulations showed that the domain trust parameter introduced significant improvement in QoS compliance, even in the presence of untrusted domains.