BioStaR: A Bio-inspired Stable Routing for Cognitive Radio Networks (original) (raw)
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Bio-inspired route estimation in cognitive radio networks
International Journal of Electrical and Computer Engineering (IJECE), 2020
Cognitive radio is a technique that was originally created for the proper use of the radio electric spectrum due its underuse. A few methods were used to predict the network traffic to determine the occupancy of the spectrum and then use the 'holes' between the transmissions of primary users. The goal is to guarantee a complete transmission for the second user while not interrupting the transmission of primary users. This study seeks the multifractal generation of traffic for a specific radio electric spectrum as well as a bio-inspired route estimation for secondary users. It uses the MFHW algorithm to generate multifractal traces and two bio-inspired algorithms: Ant Colony Optimization and Max Feeding to calculate the secondary user's path. Multifractal characteristics offer a prediction , which is 10% lower in comparison with the original traffic values and a complete transmission for secondary users. In fact, a hybrid strategy combining both bio-inspired algorithms promise a reduction in handoff. The purpose of this research consists on deriving future investigation in the generation of multifractal traffic and a mobility spectrum using bio-inspired algorithms. 1. INTRODUCTION The implementation of new technologies in Cognitive Radio Networks (CRN) should require little computational complexity since the estimation of detection, decision, division, and mobility should not take more than fractions of a second. A spectrum handoff occurs when a Primary User (PU) requests service in a channel that is already occupied by a Secondary User (SU). Moreover, the SU must leave this channel and look for an available one. This process goes on until the SU finishes his transmission. A spectrum handoff has a negative impact on the performance of secondary users in terms of delay and link maintenance. Hence, the priority is to reduce handovers in the system [1]. A CRN is a system that allows the evaluation of the transmission medium, analyze the transmission parameters and make decisions in a dynamic time-frequency space. Based on the allocation and management of resources, it aims to improve the use of the electromagnetic radio spectrum [2]. Therefore, a CRN should be smart and be able to learn from its interaction experience with the RF environment. According to this statement, the learning process is a crucial component that can be tackled from various areas of knowledge such as artificial intelligence, machine learning, evolutionary algorithms or robust control methods [2]. The management of the spectrum under a CRN involves four stages that explain the interaction between PU and SU, in terms of occupying and sharing the spectrum [3]. Spectrum detection is the process in which the SUs look for available bands, capture their information and detect gaps in the spectrum. The spectrum decision-making process is encouraged to assign a channel by considering the spectrum availability and allocation policies. The spectrum division coordinates the allocation of spectral spaces and
Wireless sensor network is the need of today's and next generation requirement to provide the optimal solution for routing techniques in telecommunication. The many different challenges and issues are workout by various authors. We consider the fault-tolerance issues with multi-sink and multi-channel probabilistic approach. The sensor nodes are deployed in the region in an unattended fashion for data gathering from different places. The swarm optimization techniques as artificial intelligence are used to find out the optimal solution. In the communication network, there is a need for designing a fault-tolerance routing protocol. The node energy depletion as the nodes is in active mode. The node gets exhausted as it is used continuously for routing the packets. We extend our work in designing the fault-tolerance issues using the multi-sink approach as probabilistic techniques inspired from ant colony optimization for cognitive radio wireless sensor network (CR-WSN) using spectrum sensing, sharing techniques applying on AODV and DSR routing protocol. In this paper we try to analyze the adaptive routing protocol with existing bio-inspired AntHocNet routing protocol.
Bio Inspired Cross Layer Aware Network protocol for Cognitive Radio Networks
Global journal of computer science and technology, 2010
The reconfigurability and flexibility of cognitive radio heralds an opportunity for investigators and researcher community to reexamine how network layers protocols enhance quality of services(QoS) by interacting with lower layers of network services. Paper investigates enhancements of cognitive radio based computer networks. The enhancements are in form of better and agile network layer protocols ,which reconfigure itself as per need and change in physical network structure. Top operation like addressing, framing and error control are not modified . Super frame structure , flow control are reconfigured as per physical and data link parameter. Appropriate techniques are employed for better QoS for broad range of services over CRCN. The proposed Bio inspired Cross Layer Aware Network(BCLAN) Protocol is presented . The beauty of the protocol is that it uses ANT Colonization optimization which thought to be one of the best algorithm design strategy The protocol (BCLAN) is also tested f...
IJERT-A Survey on Routing Protocols for Cognitive Radio Networks
International Journal of Engineering Research and Technology (IJERT), 2015
https://www.ijert.org/a-survey-on-routing-protocols-for-cognitive-radio-networks https://www.ijert.org/research/a-survey-on-routing-protocols-for-cognitive-radio-networks-IJERTV4IS041166.pdf In today's world of communication, cognitive radio (CR) has emerged as one of the most promising technology to overcome the inefficient spectrum utilization problem. The basic intention behind CR is to opportunistically allow unlicensed users to utilize the vacant licensed spectrum without causing much interference to licensed users, thereby providing a solution to limited available spectrum. CR nodes are adapted to the dynamics of spectrum availability. Although, routing is a fundamental concept in ad hoc wireless communication, but in CR network, spectrum scarcity makes routing a challenging issue to carry out end-to-end data transmission.
ROUTING SCHEMES IN COGNITIVE RADIO NETWORK KANCHAN HADAWALE & SUNITA BARVE
TJPRC, 2013
Cognitive Radio (CR) is a promising technology which deals with using vacant spectrum of licensed frequency band opportunistically. Cognitive Radio Network (CRN) is introduced to solve spectrum usage inefficiency problem. Thus inefficient usage of the existing spectrum can be improved through opportunistic access to the licensed bands without interfering with the existing users. In CRN, route construction must not affect the transmission of Primary User activity. Thus, in CR technology challenge of maintaining optimal routes in Ad-Hoc CR network arises due to PU activity & mobility of spectrum resources i.e. CR users. The novel functionalities and current routing challenges in CRN are explained in detailed. This work focuses on designing effective routing solutions for multi-hop CRNs. Routing solutions are classifieds into two categories: Full spectrum knowledge based approaches and local spectrum knowledge based approaches. In each category we describe methodologies, routing metrics. Finally open research issues of routing in CRN are outlined.
Spectrum Aware On-Demand Routing in Cognitive Radio Networks
When a cognitive radio (CR) device changes its operation frequency, it experiences a hardware switching delay to tune to its new frequency before it can fully utilize it. This delay in general depends on the wideness between the two frequency bands. When the range of frequencies that the cognitive radio network (CRN) operates in is narrow, this delay difference might be negligible. But the CRNs of the future are envisioned to operate in a wide range of frequency bands. So the spectrum allocation and scheduling algorithms designed for CRNs have to take into account different delays that occur while switching to different frequency bands. The dependence of the switching delay on the wideness between the old and new central frequencies is unique to the dynamic spectrum access paradigm since other wireless technologies typically operate in a narrower bandwidth. In the proposed work a model is presented for spectrum aware on-demand routing in cognitive radio networks.