Fair and Distributed Resource Allocation in Wireless Networks Using Frogs’ Calling Behavior Algorithm

Abstract

Bio-inspired algorithms provide some notable characteristics, such as stability, scalability, convergence, and adaptability, which explains the reason why many researchers have attempted to apply bio-inspired algorithms to various kinds of engineering problems. In this paper, we propose a fair resource allocation method in wireless networks, which is inspired by the frogs' calling behavior algorithm. Because the frogs' calling behavior algorithm shows strict de-synchronization of the calling phase and adaptivity in the dynamically changing environment, it is suitable for nodes to achieve fair resource allocation in time-division multiple access (TDMA)-based wireless networks. The analysis of the proposed algorithm verifies the convergence criteria. The simulation results show that the proposed algorithm achieves strict de-synchronization for their phase-coupled oscillators and balanced distribution over all nodes, and thus enables the fair and distributed resource allocation over all nodes in a TDMA-based wireless network even with dynamically changing network topology. INDEX TERMS Bio-inspired, fair resource allocation, de-synchronization, frogs' calling behavior.

Adaptive Strategy to Change Firing Phases of Collided Nodes in Extended-Desync TDMA-Based MANETs

“…Desync-TDMA does not require global slot synchronization schemes as in ordinary TDMA-based methods [23,24]. Some extensions of Desync-TDMA [12][13][14][15][16][18][19][20][21][22] propose algorithm to cope with packet loss in lossy networks [12], to reduce desynchronization errors and convergence time [13,14,16,20,22], to provide weighted slot scheduling according to traffic demand of each node [15,17], or to reduce energy consumption [21]. The authors in [18] proposed the firing offset adjustment scheme to overcome the message split due to the firing message within a slot.…”

“…Desync-TDMA does not require any central agent; instead, each node in a Desync-TDMA network sends firing messages periodically and allocates its slot in a distributed manner considering its and other nodes' firing times. Desync-TDMA has been widely adopted and modified in many studies to enhance decentralized reservation-based scheduling and resource management schemes [12][13][14][15][16][17][18][19][20][21][22][23][24]. Since the studies related to Desync-TDMA have focused on single-hop wireless network environments with static nodes, they are not suitable to apply directly to multi-hop network environments.…”

Performance Demonstration of Decentralized TDMA Based on Desynchronization of Nonlinear Oscillators with Different Coupling Schemes

“…Previous research to realize distributed TDMA [4][5][6][7][8] includes Desync-TDMA [4], PCO-D [5], and Kuramoto-Desync [6]. In DESYNC, the phase is determined by taking the phase information of the two phases before and after in the phase space and taking the midpoint of the two phases.…”