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

Abstract

Non-geostationary (NGEO) satellite networks have a series of advantages over terrestrial networks. However, traditional routing algorithms such as the Dijkstra's Shortest Path (DSP) algorithm always lead to some Inter-Satellite Links (ISLs) heavily loaded. To guarantee a better distribution of traffic among satellites, this paper proposes a Fuzzy Satellite Congestion Indicator (FSCI) to estimate congestion status among neighboring satellites. Indeed, a satellite notifies its neighboring satellites of its FSCI. 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 according to Fuzzy Route Determination. The routing strategy discussed above is Fuzzy Satellite Routing(FSR). This routing algorithm avoids both congestion and packet drops at the satellite. It also ensures a better traffic distribution over the entire satellite constellation. The mechanism of multiple traffic classes is also discussed in FSR. The good performance of FSR, in terms of short end-to-end delay, higher throughput, and lower packet drops, is verified via a set of simulations using the Network Simulator 2 (NS2).

ASER: Scalable Distributed Routing Protocol for LEO Satellite Networks

“…Song et al [8] proposed to combine preliminarily planned routing and real-time adjustment based on "traffic lights" that indicate the congestion status, so as to forward each packet on a near-optimal path and avoid congestion. A similar approach proposed by Li et al [9] estimates congestion status by a fuzzy satellite congestion indicator. Tang [10] proposes a hierarchical control architecture for satellite-ground integrated networks, and solves an optimization problem to maximize the average throughput over a sequence of timeslots.…”

A resilient multi-path routing for the SDN based space-based network

“…And the path set between node 1 and node 6 is empty (2) we compute the path which weight is smallest:{1,2,4,6},{1,2,5,6} and {1,3,5,6}(the smallest weight is 3:{1,2,4,6}), (3) judge the path {1,2,4,6} is not in the path set. (4) add a Δw=1 to the weight of the link (1,2), (2,4) and (4,6), update the weight w(1,2)=w (2,4)=w (4,6)=2. (5) calculate the second path w{1,2,5,6}=2+2+2=6, w{1,3,5,6}=2+3+2=7, the w{1,2,5,6} is smaller and joins in a path set, then update the weight.…”

“…Lu et al [3] propose a novel inter-satellite routing based on link recognizing to improve the network routing problem and reduce the packet loss and delay. Li et al [4] propose a novel routing strategy based on fuzzy theory for satellite network to evaluate the satellite congestion and then decrease the network congestion and packet loss. Liu et al[5] analyze the efficiency of routing algorithms for satellite network under a single satellite node fault and random node fault.…”

Routing Strategy for LEO Satellite Networks Based on Membership Degree Functions

“…Zhang et al [27] transformed multiattribute parameters of satellites into a comprehensive parameter through the Choquet fuzzy integral. Li et al [28] estimated the congestion status between adjacent satellites through fuzzy congestion indicators and then proposed a fuzzy routing strategy to avoid congestion. Jiang et al [29] established a fuzzy rule set and proposed a fuzzy routing strategy that satisfies multiservice QoS for satellite networks.…”