Demand Based State Aware Channel Reconfiguration Algorithm for Multi-Channel Multi-Radio Wireless Mesh Networks

Abstract

Efficient utilization of Multi Channel-Multi Radio (MC-MR) Wireless Mesh Networks (WMNs) can be achieved only by intelligent Channel Assignment (CA) and Link Scheduling (LS). Due to the dynamic nature of traffic demand in WMNs, the CA has to be reconfigured whenever traffic demand changes, in order to achieve maximum throughput in the network. The reconfiguration of CA requires channel switching which leads to disruption of ongoing traffic in the network. The existing CA algorithms for MC-MR WMNs in the literature do not consider the channel reconfiguration overhead that occurs due to this channel switching. In this paper, we propose a novel reconfiguration framework that considers both network throughput and reconfiguration overhead to quantitatively evaluate a reconfiguration algorithm. Based on the reconfiguration framework, we propose an online heuristic algorithm for CA called Demand based State Aware channel Reconfiguration Algorithm (DeSARA) that finds the CA for the current traffic demand by considering the existing CA of the network to minimize the reconfiguration overhead. We show through simulations that DeSARA outperforms both static CA and fully dynamic CA in terms of total achieved throughput.

An overview of topology control mechanisms in multi-radio multi-channel wireless mesh networks

“…Finally, it studies the spectral occupancy of steady state topologies, and shows that despite the non-cooperative behavior, the NE topologies achieve load balancing. To maximize network utilization and minimizing traffic disruption, a polynomially bound online heuristic algorithm, DeSARA, is proposed in [43], which finds the CA for the current traffic demand by considering the existing CA of the network to minimize the reconfiguration overhead. In [44], the authors define a utility-based framework for joint CA and TC in MR-MC WMNs, and present a greedy algorithm for solving the corresponding optimization problem.…”

“…Both CA and PC functions are employed in TICA (Chaudhry [41]), which use a novel approach of controlling the network topology based on PC before intelligently assigning the channels to the multi-radio mesh router. Moreover, some or all the functions of PC, CA, and routing are employed in the proposed mechanisms of Alicherry [9], TiMesh (Rad [10]),JTCR (Chen [21]), DeSARA (Franklin [43]), and Tang [46]. Such joint approach of TC mechanisms with joint optimization of some or all the functions of PC, CA, and routing often leads to NP-hard complexity.…”

“…Such joint approach of TC mechanisms with joint optimization of some or all the functions of PC, CA, and routing often leads to NP-hard complexity. To have a realistic solutions, suboptimal heuristic mechanisms with reduced complexity have been investigated in some mechanisms such as CLICA (Marina [37]), Alicherry [9], DeSARA (Franklin [43]), and Tang [46].…”

Αναδιάρθρωση Αναθέσεων Πόρων Σε Δίκτυα Γνωσιακής Ραδιοεπικοινωνίας

“…Η τελευταία αδυναμία, μάλιστα, είναι και αυτή η οποία τελικά καθιστά την εν λόγω προσέγγιση ακατάλληλη για εφαρμογή σε Δίκτυα Γνωσιακής Ραδιοεπικοινωνίας. Η εργασία[28] θεωρεί, επίσης, ως μοναδική αιτία αναδιάρθρωσης ισχυουσών αναθέσεων πόρων τη χρονικά μεταβαλλόμενη φύση των απαιτήσεων των χρηστών των εξεταζόμενων από πλευράς της δικτύων. πόρων σε περιπτώσεις όπου τροποποιείται η διαθεσιμότητα των καναλιών των ασύρματων συσκευών των εξεταζόμενων από πλευράς της δικτύων.…”