Routing Metrics For Networks Research Articles

Energy harvesting effect on prolonging low-power lossy networks lifespan

Low-power lossy networks performance relies heavily on the wireless node battery status. Furthermore, Routing Protocol for Low-Power and Lossy Network routing protocol was not optimally designed with sustainable energy consumption in mind to suit these networks. Prolonging the lifespan of these networks is of utmost priority. This article introduces a solar energy harvesting module to power energy-constrained network devices and quantifies the effect of using harvested energy on prolonging their network lifetime when Routing Protocol for Low-Power and Lossy Network routing protocol is used. Simulation of the new developed module is conducted in three different scenarios using Contiki Cooja simulator sporting Zolertia Z1 motes. Furthermore, the harvested energy used was fed from a Cooja-based Simulation model of actual PV supercapacitor circuit design. All battery levels were set to 1% of their total capacity for all nodes in the network to speed up observing the energy harvesting effect. The performance evaluation results showed that the network with no-energy harvesting operated for time duration of 4:08:04 time units (i.e. hour:minute:second) with a dramatic decrease in connection between nodes in the network. However, the same network, when using the harvested energy to back up the battery operation, lasted for 6:40:01 in time units with improved connectivity, a total extended network lifetime of 2:31:97-time units. Furthermore, for the Routing Protocol for Low-Power and Lossy Network routing metrics, OF0 outperformed ETX in term of throughput, packet delivery ratio, energy consumption, and network connectivity. Results indicate that the developed harvested energy module fits perfectly for any Cooja-based simulation and mimics actual photovoltaic-based supercapacitor battery. It should also help researchers introduce and quantify accurately new energy consumption-based routing metrics for Routing Protocol for Low-Power and Lossy Network.

Parallel data transmission for navigation satellite network with agility link

SummaryThe topology of the navigation satellite network with agility link evolves with chain‐building slots periodically. The navigation data are transmitted in a “store, carry and forward” manner without requiring end‐to‐end paths. Thus, the navigation satellite network with agility link can be considered as a deterministic delay tolerant network (DTN). The data transmission of navigation satellite network is limited by chain‐building slot and bandwidth. To utilize network transmission link and communication bandwidth fully, this paper proposed an algorithm called parallel data transmission for the navigation satellite network with agility link. Based on the network characteristics, the algorithm is designed with polling pattern of link establishment and formulated as parallel data transmission problem based on deterministic scheduling DTN. Then, we design the method based on Dynamic Game from the view of data, while the Dynamic Programming method is proposed referring to Linear Programming–based method for optimization. Finally, the results were compared with three methods using the standard network routing metrics and showed that the proposed algorithm is better than the existing methods.

On the Design and Analysis of Fair Contact Plans in Predictable Delay-Tolerant Networks

Delay-tolerant networks (DTNs) have become a promising architecture for wireless sensor systems in challenged communication environments where traditional solutions based on persistent connectivity either fail or show serious weaknesses. As a result, different routing schemes have been investigated that take into account the time-evolving nature of the network topology. Among them, contact graph routing has been proposed for space environments with predictable connectivity. In order to evaluate routing decisions, DTN nodes need to know the contact plan in advance, which comprises all communication links among nodes that will be available in the future. Since not all potential contacts can belong to the contact plan, its design requires analyzing conflicting contacts in order to select those that meet an overall goal. In this paper, we consider the design of contact plans that can maximize fairness requirements while still maximizing the overall capacity as well. To this end, we propose to formalize the problem by means of an optimization model and evaluate its performance in terms of different fairness metrics. Since this model can be computationally intractable for a large number of contacts, we also propose to tackle it as a matching problem, resulting in algorithms of polynomial complexity, and compare these results with those of the original model. We show that fairness can be properly modeled to design contact plans and that efficient algorithms do exist to compute these plans quite accurately while also improving overall network routing metrics for a proposed case study.