Multi-objective Routing Protocol Research Articles

An Energy-Efficient Routing Protocol with Reinforcement Learning in Software-Defined Wireless Sensor Networks.

The enormous increase in heterogeneous wireless devices operating in real-time applications for Internet of Things (IoT) applications presents new challenges, including heterogeneity, reliability, and scalability. To address these issues effectively, a novel architecture has been introduced, combining Software-Defined Wireless Sensor Networks (SDWSN) with the IoT, known as the SDWSN-IoT. However, wireless IoT devices deployed in such systems face limitations in the energy supply, unpredicted network changes, and the quality of service requirements. Such challenges necessitate the careful design of the underlying routing protocol, as failure to address them often results in constantly disconnected networks with poor network performance. In this paper, we present an intelligent, energy-efficient multi-objective routing protocol based on the Reinforcement Learning (RL) algorithm with Dynamic Objective Selection (DOS-RL). The primary goal of applying the proposed DOS-RL routing scheme is to optimize energy consumption in IoT networks, a paramount concern given the limited energy reserves of wireless IoT devices and the adaptability to network changes to facilitate a seamless adaption to sudden network changes, mitigating disruptions and optimizing the overall network performance. The algorithm considers correlated objectives with informative-shaped rewards to accelerate the learning process. Through the diverse simulations, we demonstrated improved energy efficiency and fast adaptation to unexpected network changes by enhancing the packet delivery ratio and reducing data delivery latency when compared to traditional routing protocols such as the Open Shortest Path First (OSPF) and the multi-objective Q-routing for Software-Defined Networks (SDN-Q).

Secure trust aware multi-objective routing protocol based on battle competitive swarm optimization in IoT

Secure trust aware multi-objective routing protocol based on battle competitive swarm optimization in IoT

MO-CBACORP: A new energy-efficient secure routing protocol for underwater monitoring wireless sensor network

With the rapid progress of sensor technology, underwater monitoring wireless sensor network (UMWSN) equipped with water resource monitoring capabilities have surfaced. UMWSN is currently emerging as a popular research and application area, with a wide range of applications in various fields, including but not limited to disaster warning, pollutant monitoring and hydrological data monitoring. However, due to the limited size and computing power of wireless sensors, UMWSN are exceedingly susceptible to network security attacks by contaminating entities. In order to tackle the problems of inadequate security, elevated network energy consumption, and high system latency in existing QoS routing research, this paper puts forward an innovative multi-objective routing protocol named multi-objective chaotic Boltzmann ant colony optimization routing protocol (MO-CBACORP). MO-CBACORP can minimize the energy consumption of sensor nodes in UMWSN routing, thereby effectively diminishing system latency and significantly enhancing routing security. During the routing optimization process, MO-CBACORP proposed an innovative design of the chaos operator and Boltzmann selection strategy, which effectively avoids the issue of being stuck in local optimal solutions and greatly enhances the convergence speed of the algorithm. Additionally, a novel experiment for underwater monitoring environments is presented that precisely replicates underwater monitoring conditions and attack scenarios. According to the experimental results, MO-CBACORP exhibits superior performance compared to the latest state-of-the-art research including THOA-MHR, ACO-MCMC, and MAP-ACO, with a minimum improvement of 7.25%, 9.31%, and 7.68% in terms of route security, network energy consumption, and delay, respectively. All in all, MO-CBACORP exhibits superior performance compared to the three latest research algorithms.

Multiobjective routing protocol for wireless sensor network optimization using ant colony conveyance algorithm

SummaryThe widely deployed wireless sensor networks, incorporated with the capabilities of sensing, processing, and communicating, require more effective routing to maintain the balance between the performance parameters and to be prevented from the security attacks. The cryptographic methods used were effective but consumed more energy on the authentication, the encryption, and the decryption. So the routing addressing the security problems, with the reduced energy consumption, latency, and PDR losses, maximizing the network lifetime is proposed in the paper. This multiobjective routing problem of the sensor networks is handled using the ant colony routing techniques, taking into consideration the remaining energy of the nodes, the distance between the nodes, and the trust credentials of the nodes, to reduce the energy consumption and enhance the lifetime of the sensor networks. The further performance evaluation using the network simulator‐2 reveals the efficiency and the quality of the service of proposed routing technique over existing techniques on the grounds of energy utilization, PDR, lifetime of sensor networks, and the security enhancement rate.

A Multiobjective, Lion Mating Optimization Inspired Routing Protocol for Wireless Body Area Sensor Network Based Healthcare Applications.

The importance of body area sensor networks (BASNs) is increasing day by day because of their increasing use in Internet of things (IoT)-enabled healthcare application services. They help humans in improving their quality of life by continuously monitoring various vital signs through biosensors strategically placed on the human body. However, BASNs face serious challenges, in terms of the short life span of their batteries and unreliable data transmission, because of the highly unstable and unpredictable channel conditions of tiny biosensors located on the human body. These factors may result in poor data gathering quality in BASNs. Therefore, a more reliable data transmission mechanism is greatly needed in order to gather quality data in BASN-based healthcare applications. Therefore, this study proposes a novel, multiobjective, lion mating optimization inspired routing protocol, called self-organizing multiobjective routing protocol (SARP), for BASN-based IoT healthcare applications. The proposed routing scheme significantly reduces local search problems and finds the best dynamic cluster-based routing solutions between the source and destination in BASNs. Thus, it significantly improves the overall packet delivery rate, residual energy, and throughput with reduced latency and packet error rates in BASNs. Extensive simulation results validate the performance of our proposed SARP scheme against the existing routing protocols in terms of the packet delivery ratio, latency, packet error rate, throughput, and energy efficiency for BASN-based health monitoring applications.

Routing Optimization in Vehicular Networks: A New Approach Based on Multiobjective Metrics and Minimum Spanning Tree

Recently, distributed mobile wireless computing is becoming a very important communications paradigm, due to its flexibility to adapt to different mobile applications. As many other distributed networks, routing operations assume a crucial importance in system optimization, especially when considering dense urban areas, where interference effects cannot be neglected. In this paper a new routing protocol for VANETs and a new scheme of multichannel management are proposed. In particular, an interference-aware routing scheme, for multiradio vehicular networks, wherein each node is equipped with a multichannel radio interface is investigated. NS-2 has been used to validate the proposed Multiobjective routing protocol (MO-RP) protocol in terms of packet delivery ratio, throughput, end-to-end delay, and overhead.

Multipath Fault Tolerant Routing Protocol in MANET

Mobile ad hoc networks (MANETs) consist of a collection of wireless mobile nodes which dynamically exchange data among themselves without the reliance on a fixed base station or a wired backbone network and it the makes the routing a crucial issue to the design of the MANET.Multiple path routing protocols are shown to be performance -effective alternatives over single-path routing for ad hoc networks and it represents a promising routing methodfor wireless mobile ad hoc networks. Multi -path routing achieves load balancing and is more resilient to route failures. .In this paper we propose an energy efficient multipath fault tolerant routing protocol to improve the reliability of data routing in Mobile ad hoc networks. The proposed RFTA is a multi objective routing protocol that meets diverse application requirements by considering the changing conditions of the n etwork. The efficiency of the proposed protocol has been evaluated on different scenarios and there has been a noticeable improvement in the packet delivery ratio and also in the reduction of end -to-end delay comparing toSMR,SMS and MDSR.