Temporal Routing Metrics for Networks with Advance Reservations

Author(s):  
Christoph Barz ◽  
Markus Pilz ◽  
Andr Wichmann
2022 ◽  
Vol 16 (1) ◽  
pp. 0-0

This paper presents a proposed Objective Function (OF) design using various routing metrics for improving the performance of IoT applications. The most important idea of the proposed design is the selection of the routing metrics with respect to the application requirements. The various metrics, such as Energy, Distance, Delay, Link quality, Trust (EDDLT) are used for improving the objective function design of the RPL in various IoT applications. Here, the Adaptive Deep rider LSTM is newly employed for the energy prediction where the Adaptive Deep Rider LSTM is devised by the combination of the adaptive theory with the Rider Adam Algorithm (RAA), and the Deep-Long Short Memory (Deep-LSTM). However, the evaluation of the proposed method is carried out energy dissipation, throughput, and delay by achieving a minimum energy dissipation of 0.549, maximum throughput of 1, and a minimum delay of 0.191, respectively.


Author(s):  
T. Nyandeni ◽  
C. Kyara ◽  
P. Mudali

Routing is an essential mechanism for proper functioning of large networks, and routing protocols make use of routing metrics to determine optimal paths. The design of routing metrics is critical for achieving high throughput and we begin this chapter by proposing the design principles for routing metrics. These design principles are for ensuring the proper functioning of the network and achieving high throughput. We continue by giving a detail analysis of the existing routing metrics. We also look at the pitfalls of the existing routing metrics. We conclude the chapter by outlining the future research directions.


2019 ◽  
Vol 95 ◽  
pp. 534-547 ◽  
Author(s):  
Joaquin Chung ◽  
Rajkumar Kettimuthu ◽  
Nam Pho ◽  
Russ Clark ◽  
Henry Owen
Keyword(s):  

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