On energy‐efficient performance‐guaranteed channel assignment in cognitive radio‐based wireless mesh networks

Abstract

In recent years, in order to make efficient use of spectrum resources, much attention has been given to solving the problem of channel assignment in cognitive radio-based wireless mesh networks (CR-WMNs). Current approaches focus mainly on avoiding interference in order to enhance performance in terms of throughput. WMNs are intended to provide low-cost multimedia communication. Therefore, in order to provide lowcost real-time communication, channel assignment in CR-WMNs should take into consideration not only the issue of throughput, but also energy consumption and delays. In this paper, we first define an optimization problem to maximize the end-to-end throughput per unit of energy consumption while minimizing, as well as guaranteeing, the delay constraint specified for a data stream. Based on this, we then propose a novel distributive heuristic channel assignment approach to solve the optimization problem in a self-organized manner. Finally, we present the simulation results to evaluate the performance of the proposed solution in terms of end-to-end throughput per unit of energy consumption and delays.require that network performance should be optimized not only in terms of throughput, but also in terms of energy consumption (given the fact that the cost of energy continues to rise) and delay, because several broadband services such as video streaming, video conferencing and online gaming are delay sensitive. Moreover, in recent years, a dramatic growth has been witnessed in Internet of Things (IoT). Because it is anticipated that IoT will be carried over multi-hop mesh-type networks with a large number of energy-constrained devices and delay-sensitive applications [6], an energy and delay efficient WMN will be the most suitable choice for IoT applications. Hence, a channel assignment mechanism optimizing performance in terms of throughput and energy consumption while considering the delay constraints for CR-WMNs is highly desired.This paper focuses on the channel assignment problem in multi-hop CR-WMNs with the aim of maximizing the end-to-end throughput per unit of energy consumption while keeping the end-toend delay within the specified limit for each flow. Therefore, we first establish link/hop throughput, energy consumption and delay models based on PU activities. Then, an optimization problem is formulated for channel assignment in CR-WMN with the objective function of maximizing the end-to-end throughput per unit of energy consumption while satisfying the spectrum-sharing constraints among the nodes and the end-to-end constraints for each flow. To solve the problem, a novel distributive heuristic channel assignment (DHCA) is presented, which works in a distributive and self-organized manner, while keeping in view the scalability concerns of CR-WMNs and the simplicity of the solution to be implemented in real time. DHCA works in two steps. The first step is to introduce the concept of delay gradient. The delay gradient is defined as the difference in the accumulative delay incurred by the packets of a fl...

Distributed energy‐efficient channel assignment in cognitive mesh network for IoT systems

“…The delay performance of the network is characterized using queue theoretic analysis. In the work of Hasan and Tu, a heuristic approach is presented for throughput maximization in an end‐to‐end delay constraint CRMN. However, both of the aforementioned works are not applicable to IoTs due to heterogeneous nature of IoT devices.…”

“…In greedy approach, each node tries to select the best channels in terms of for its interfaces without violating constraints mentioned in (16). First, a node computes the energy efficiency by trying a combination of (i) set of all of its interfaces (which are not being used so far), (ii) set of possible number of nodes (with whom this node can communicate), and the set of channels (all channels which are being unused so far).…”

Sensing Device Management for History‐Based Spectrum Sharing in Cognitive Radio Networks

“…This greatly simplifies the design and implementation of the system [3,14]. Also, distributed systems have inherent scalability and robustness that cannot be matched in a centralized network [1,25].…”

A novel approach for energy‐efficient resource allocation in double threshold‐based cognitive radio network

“…14 Hasan et al proposed a novel distributive heuristic channel assignment (DHCA) approach to maximize the throughput under the constraint of minimum queuing delay in. 15 In, 16 EE in the centralized cognitive radio network (CRN) was maximized by using Particle Swarm Optimization (PSO) algorithm considering the spectrum switching delay and minimum rate requirement. In, 17 the optimal power allocation was obtained by using fractional programming approach in green CRN under the PU's interference constraint.…”

“…2017;30:e3198. https://doi.org/10.1002/ dac.3198APPENDIX Appendix ADerivation of(15).The outage of ith SU is O gi ¼ P r log 2…”