A Bioinspired Fair Resource-Allocation Algorithm for TDMA-Based Distributed Sensor Networks for IoT

Abstract

Many studies on distributed resource-allocation algorithms have been conducted recently because of the increasing number of network nodes and the rapidly changing network environments in the Internet of Things (IoT). In this paper, we propose the multihop DESYNC algorithm, which is a bioinspired Time Division Multiple Access-(TDMA-) based distributed resourceallocation scheme for distributed sensor networks. We define a detailed frame structure for the proposed multihop DESYNC algorithm and a firing message, which acts as a reference for resource allocation. In addition, operating procedures for resource allocation and collision detection avoidance under multihop DESYNC are explained. Simulations show that multihop DESYNC effectively resolves the hidden-node problem and that it fairly shares resources among nearby nodes in multihop networks. Moreover, it achieves better performance than the CSMA/CA algorithm in terms of channel reuse gain and average throughput.

Blockchain Design for an Embedded System

“…Systems-There are several examples of decentralized robotic systems that incorporate peer-to-peer communication between the agents using limited local communication, such as line of sight schemes, 6 , 7 as well as simulations where the communication is virtually restricted to nearest neighbors. 8,9 Many examples, and simulations of distributed robotic systems also exist where communication is received by all nodes and they form a mesh network for routing information, 10 while other mesh applications are focused on covering distances too large for a single point of communication, such as wireless sensor networks (WSN), 11 forming point-to-point and multi-hop networks.…”

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

“…where N is the number of nodes in a fully-connected network, and ϕ ∈ [0, 1] is a parameter that scales how far node i moves from its current phase. All nodes observe their neighbors' firing-phases, then use this information to jump backwards in the phase using equation (4). As a result, all of the oscillators are spaced evenly around the phase ring, as shown in Fig.…”

“…Recently, biologically inspired (bio-inspired) algorithms have gained the attentions of many researches. Bio-inspired algorithms are modeled on the behavior of organisms on Earth such as flies flashing, cardiac pacemaker cells, bees' cooperative searching for food, flocking of birds, schooling of fish, routing of ants, and frogs' calling behavior [4]- [6]. Bio-inspired algorithms have evolved with the goal of achieving given purposes and ultimately obtaining optimal results by encapsulating simple, heuristic rules for operation in a distributed way.…”

Weighted-DESYNC and Its Application to End-to-End Throughput Fairness in Wireless Multihop Network

“…Because the DESYNC-TDMA method assumes a fully connected network topology, it causes a hidden-node problem and thus cannot be directly applied to multihop networks. Therefore, the MH-DESYNC method was proposed, with the purpose of facilitating collision-free and fair resource allocation among not only one-hop neighbors but also two-hop neighbors in wireless multihop networks [18].…”

“…Regarding data time-slot allocation, the methods for detecting and resolving firing-phase collision and allocating an actual data time slot to each node are provided. Frame t + 1: [18]. Specifically, in MH-DESYNC, the amount of resource allocated to node is 1/( 1( ) + 2( ) + 1), where 1( ) and 2( ) are the numbers of one-hop and two-hop neighbor nodes of node , respectively.…”