Effective TDMA scheduling for tree-based data collection using genetic algorithm in wireless sensor networks

Osamy, Walid; El‐Sawy, A. A.; Khedr, Ahmed M.

doi:10.1007/s12083-019-00818-z

Cited by 45 publications

(22 citation statements)

References 34 publications

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“…The tree TDMA supports full-duplex communication of voice and data. Osamy et al 27 proposed Effective TDMA scheduling for tree-based data collection using a genetic algorithm (ETDMA-GA). The genetic algorithm (GA) has been utilized to solve the generation of TDMA scheduling in ETDMA-GA.…”

Section: Related Workmentioning

confidence: 99%

Resource scheduling based on routing tree and detection matrix for Internet of things

Bai

Zhang

Liu

et al. 2021

International Journal of Distributed Sensor Networks

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Effective scheduling of limited communication resources is one of the critical methods for data transmission in the Internet of things. However, the time slot utilization rate of many existing resource scheduling methods of Internet of things is not high. This article proposes a new efficient resource scheduling based on routing tree and detection matrix for Internet of things. In heterogeneous Internet of things, according to the different working modes and functions, the nodes are divided into Internet of things devices, routing nodes, and base station. We use time slot multiplexing to improve the time slot utilization of continuous transmission in Internet of things. First, the time slot allocation table in a round is obtained by the time slot scheduling based on the routing tree. Then, the collision matrix and the transmission matrix are established based on the time slot allocation table in a round. Finally, the minimum time slot scheduling in continuous rounds is determined based on the routing tree and the detection matrix. The experimental results show that the resource scheduling based on routing tree and detection matrix effectively improves the utilization of time slots and improves the throughput of the Internet of things.

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Section: Related Workmentioning

confidence: 99%

Resource scheduling based on routing tree and detection matrix for Internet of things

Bai

Zhang

Liu

et al. 2021

International Journal of Distributed Sensor Networks

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“…Reference [10] considered the interference degree of sensor nodes in the proposed scheduling methods, IDeg-LO and IDeg-ReLO, and improved the network's latency. [9] Proposed an ETDMA-GA algorithm based on a genetic algorithm and cross-layer approach to obtain optimum TDMA scheduling for minimum latency. They compared the obtained results with [10], [36] and proved that the ETDMA-GA algorithm outperforms Rand-LO, Depth-LO, Depth-ReLO, IDeg-LO, and IDeg-ReLO in terms of average latency and average schedule length.…”

Section: A Tdma Scheduling Optimizationmentioning

confidence: 99%

“…For each node's traversal list, based on the connectivity and interference matrices, a TDMA scheduling can be deduced as presented in the following slot allocation algorithm [9], [10]:…”

Section: A Network Model and Scheduling Modelmentioning

confidence: 99%

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A Modified Particle Swarm Optimization Approach for Latency of Wireless Sensor Networks

Elrefaei¹,

Yahya²,

Shaat³

et al. 2021

IJACSA

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In time-sensitive applications, such as detecting environmental and individual nuclear radiation exposure, wireless sensor networks are employed.. Such application requires timely detection of radiation levels so that appropriate emergency measures are applied to protect people and the environment from radiation hazards. In these networks, collision and interference in communication between sensor nodes cause more end-to-end delay and reduce the network's performance. A time-division multiple-access (TDMA) media access control protocol guarantees minimum latency and low power consumption. It also overcomes the problem of interference. TDMA scheduling problem determines the minimum length conflict-free assignment of slots in a TDMA frame where each node or link is activated at least once. This paper proposes a meta-heuristic centralized contention-free approach based on TDMA, a modified particle swarm optimization. This approach realizes the TDMA scheduling more efficiently compared with other existing algorithms. Extensive simulations were performed to evaluate the modified approach. The simulation results prove that the proposed scheduling algorithm has a better performance in wireless sensor networks than the interference degree leaves order algorithm and interference degree remaining leaves order algorithm. The results demonstrate also that integrating the proposed algorithm in TDMA protocols significantly optimizes the communication latency reduction and increases the network reliability.

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“…There have been several different approaches, which can mainly be categorized into centralized and distributed scheduling. The early works were mostly centralized scheduling and focused on looking for an optimal solution for the scheduling problem [26]- [29]. However, as these algorithms require full knowledge on network topology, they are not suitable for large scale multi-hop networks, even though their expected complexity is just O(n), where n is the number of nodes in the network.…”

Section: Related Workmentioning

confidence: 99%

A Distributed TDMA Scheduling Algorithm Using Topological Ordering for Wireless Sensor Networks

Nguyen

Kim

2020

IEEE Access

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In distributed wireless sensor networks (WSNs), TDMA protocols are a widely applied solution when a reliable data-transferring mechanism is in demand. However, to produce a TDMA schedule is not an easy task. During the scheduling, there can be a large number of conflicts due to the nature of radio access, which leads to a waste of operating time and energy. In this paper, we first present and discuss the concept of Topological Ordering, which is based mainly on the local neighborhood size. It is aimed to create an order of scheduling that helps reduce the competition and conflicts. Next, we propose a fast and effective distributed scheduling algorithm using Topological Ordering, called DSTO, to create a collision-free TDMA schedule. This algorithm is promising in terms of reducing running time and message collisions during the scheduling phase, which in turn reduces overall message overhead. At the same time, efficient time slot allocation, which translates to a shorter frame, is guaranteed. We implement DSTO together with two other distributed scheduling algorithms on OPNET Network Modeler and thoroughly analyze the comparative results to prove its validity and effectiveness.INDEX TERMS Distributed, DSTO, scheduling algorithm, TDMA, topological ordering, wireless sensor networks.

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Effective TDMA scheduling for tree-based data collection using genetic algorithm in wireless sensor networks

Cited by 45 publications

References 34 publications

Resource scheduling based on routing tree and detection matrix for Internet of things

Resource scheduling based on routing tree and detection matrix for Internet of things

A Modified Particle Swarm Optimization Approach for Latency of Wireless Sensor Networks

A Distributed TDMA Scheduling Algorithm Using Topological Ordering for Wireless Sensor Networks

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