GPF: A Green Power Forwarding Technique for Energy-Efficient Network Operations

The energy consumption of network infrastructures is increasing; therefore, research efforts designed to diminish this growing carbon footprint are necessary. Building on prior work, which determined a difference in the energy consumption of network hardware based on their forwarding configurations and developed a real-time network energy monitoring tool, this research proposes a novel technique to incorporate individual device energy efficiency into network routing decisions. A new routing metric and algorithm are presented to select the lowest-power, least-congested paths between destinations, known as Green Power Forwarding (GPF). In addition, a network dial is developed to enhance GPF by allowing network administrators to tune the network to optimally operate between energy savings and network performance. To ensure the scope of this research for industry adoption, implementation details for different generations of networking infrastructure (past, present, and future) are also discussed. The experiment results indicate that significant energy and, in turn, cost savings can be achieved by employing the proposed GPF technique without a reduction in network performance. The future directions for this research include developing dynamically-tuning network dial modes and extending the principles to inter-domain routing.

Cross-Layer Routing for Outage Minimization in Multihop Ad-Hoc Networks

In this study, cross-layer approach for joint routing and power allocation problem is formulated in an optimization framework for end-to-end outage minimization under the constraint of total permissible transmission power. A closed form solution for optimal transmission power is obtained following the extraction of routing metric. The scheme is referred as minimum end-to-end outage probability (MEO) strategy. A distributed implementation of the proposed strategy is also presented. Simulation results prove that our proposed MEO routing and power allocation strategy succeeds in achieving significant improvement of end-to-end outage probability over MEO routing and equal power allocation scheme.

A hybrid objective function with empirical stability aware to improve RPL for IoT applications

The diverse applications of the internet of things (IoT) require adaptable routing protocol able to cope with several constraints. Thus, RPL protocol was designed to meet the needs for IoT networks categorized as low power and lossy networks (LLN). RPL uses an objective function based on specific metrics for preferred parents selection through these packets are sent to root. The single routing metric issue generally doesn’t satisfy all routing performance requirements, whereas some are improved others are degraded. In that purpose, we propose a hybrid objective function with empirical stability aware (HOFESA), implemented in the network layer of the embedded operating system CONTIKI, which combines linearly three weighty metrics namely hop count, RSSI and node energy consumption. Also, To remedy to frequent preferred parents changes problems caused by taking into account more than one metric, our proposal relies on static and empirical thresholds. The designed HOFESA, evaluated under COOJA emulator against Standard-RPL and EC-OF, showed a packet delivery ratio improvement, a decrease in the power consumption, the convergence time and DIO control messages as well as it gives network stability through an adequate churn.

Reliability-based routing metric for UAVs networks

<span>As a result of technological advances in robotic systems, electronic sensors, and communication techniques, the production of unmanned aerial vehicle (UAV) systems has become possible. Their easy installation and flexibility led these UAV systems to be used widely in both military and civilian applications. Note that the capability of one UAV is however limited. Nowadays, a multi-UAV system is of special interest due to the ability of its associate UAV members either to coordinate simultaneous coverage of large areas or to cooperate to achieve common goals/targets. This kind of cooperation/coordination requires a reliable communication network with a proper network model to ensure the exchange of both control and data packets among UAVs. Such network models should provide all-time connectivity to avoid dangerous failures or unintended consequences. Thus, the multi-UAV system relies on communication to operate. Flying ad hoc network (FANET) is moreover considered as a sophisticated type of wireless ad hoc network among UAVs which solved the communication problems into other network models. Along with the FANET’s unique features, challenges and open issues are also discussed especially in the routing protocols approach. We will try to present the expected transmission account metric with a new algorithm for reliability. In addition to this new algorithm mechanism, the metric takes into account the relative speed between UAVs, and thus the increase of the fluctuations in links between UAVs has been detected. Accordingly, the results show that the function of the AODV routing protocol with this metric becomes effective in high mobility environments.</span>

Link Availability Prediction Based on Capacity Optimization in MANET

Mobile Ad hoc Network (MANET) is a wireless network composed of multiple wireless nodes without fixed infrastructure support, which is expected to play an important role in future commerce and military, especially in marine and aerospace communications systems. In this paper, for link failure caused by node mobility in MANET, the prediction of link availability is given according to the dynamic characteristics of the link, and transmission modes and relay nodes are selected to optimize the link capacity and reduce the interference. Simulation results show that the proposed routing metric method can select stable routing paths with less interference, and reduce routing overhead caused by node movement based on link availability analysis.

FTC-OF: Forwarding Traffic Consciousness Objective Function for RPL Routing Protocol

The diversity of Internet of Things applications require a flexible routing protocol to cope with several constraints. In this context, the RPL protocol was designed to meet the needs of IoT. RPL relies on an objective function based on specific metrics to fulfill its routing strategy. The single routing metric problem leads generally to non-optimized routes selection. As a consequence, two major issues emerge, mainly the node’s congestion due to the high number of forwarded packets, also the greedy energy consumption by those nodes that conduct to fast batteries draining. In that purpose, Forwarding Traffic Consciousness Objective Function has been proposed, which combines three routing metrics, namely hop count, RSSI and a newly designed Forwarded Traffic Metric (FTM). The proposed method, evaluated using COOJA against ETX and Energy based RPL, showed a packet delivery ratio increase respectively with 2% and 11% in low and high traffics, considerably reduces the power consumption with approximately 47% as well as it achieves a good balance of traffic managed by the relay nodes.