Explicit Load Balancing Technique for NGEO Satellite IP Networks With On-Board Processing Capabilities

Abstract

Non-geostationary (NGEO) satellite communication systems offer an array of advantages over their terrestrial and geostationary counterparts. They are seen as an integral part of nextgeneration ubiquitous communication systems. Given the non-uniform distribution of users in satellite footprints, due to several geographical and/or climatic constraints, some Inter-Satellite Links (ISLs) are expected to be heavily loaded with data packets while others remain underutilized. Such scenario obviously leads to congestion of the heavily loaded links. It ultimately results in buffer overflows, higher queuing delays, and significant packet drops.To guarantee a better distribution of traffic among satellites, this paper proposes an explicit exchange of information on congestion status among neighboring satellites. Indeed, a satellite notifies its congestion status to its neighboring satellites. When it is about to get congested, it requests its neighboring satellites to decrease their data forwarding rates by sending them a self status notification signaling message. In response, the neighboring satellites search for less congested paths that do not include the satellite in question and communicate a portion of data, primarily destined to the satellite, via the retrieved paths. This operation avoids both congestion and packet drops at the satellite. It also ensures a better distribution of traffic over the entire satellite constellation. The proposed scheme is dubbed "Explicit Load Balancing" (ELB) scheme.While the multi-path routing concept of ELB has many advantages, it may lead to persistent packet reordering. In case of connection-oriented protocols, this phenomenon results in unnecessary shrinkage of the data transmission rate. A solution to this issue is also incorporated in the design of ELB. The interactions of ELB with mechanisms that provide different QoS by differentiating traffic (e.g., Differentiated Services) are also discussed. The good performance of ELB, in terms of better traffic distribution, higher throughput, and lower packet drops, is verified via a set of simulations using the Network Simulator (NS).

QoS based Admission Control using Multipath Scheduler for IP over Satellite Networks

“…Furthermore, the studies did not take into consideration the specific QoS requirements of each traffic type for the routing selection. Another previous related study on multipath routing over satellites by Taleb et al [5] has proposed a novel method called "Explicit Load Balancing" (ELB) which is a cooperative routing strategy for LEO satellites constellation that enables neighboring satellites to explicitly exchange information on their current congestion status for better distribution of packet traffics over the entire satellite constellation. The method also optimally prevents both congestion and packet drops at the satellites.…”

A Novel Routing Strategy Based on Fuzzy Theory for NGEO Satellite Networks

“…The Fuzzy Route Strategy is revealed in Algorithm 1, the signaling setting is similar with ELB scheme [6].…”

“…In above distributed load balancing techniques, satellites independently decide on the best next hop to which packets should be forwarded. Taleb et al [6] state a Explicit Load Balancing (ELB) metric taking the state of next hops into account when it selects the best next hop. Song et al [7] introduce a traffic-light-based intelligent routing strategy considering both the current and next hop congestion.…”

Challenges, opportunities, and solutions for converged satellite and terrestrial networks

“…With this regard, the number of levels of this hierarchy, the size of each level, the amount of control traffic that should be exchanged and the length of the monitoring interval time should be decided in a way that enhances the accuracy in the assessment of network dynamics while minimizing the overhead in terms of signaling messages. Such a context-aware routing scheme will yield a better load balancing over the entire network and will enhance the end-to-end (E2E) QoS [4].…”