DRL-ER: An Intelligent Energy-Aware Routing Protocol With Guaranteed Delay Bounds in Satellite Mega-Constellations
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Major space companies are developing satellite mega-constellations to provide global Internet coverage and services. Limited battery capacity is one of the biggest obstacles on mega-constellations due to the restricted weight and volume of satellites. Massive Internet packet routing tasks pose a big challenge to the energy system in such mega constellations. Incorrect use of satellite batteries during routing phases may significantly increase the energy consumption and cause node failure quickly. Existing state-of-the-art works on energy-saving routing for satellite networks paid much attention on traffic distribution and end-to-end delay issues. However, these methodologies were using many real-time network information for optimization which is not practical in mega-constellations. Note also that these works did not consider energy efficiency and guaranteed end-to-end delay simultaneously. In this paper, we propose a novel deep reinforcement learning based energy-efficient routing protocol called DRL-ER, which avoids the battery energy imbalance of constellations and can also guarantee a required bounded end-to-end delay. In DRL-ER, satellites can learn a routing policy that will balance energy usage among satellites. Extensive simulation results show that our proposed DRL-ER protocol reduces the energy consumption of satellites in average by more than 55% compared to the current state-of-the-art work, and prolongs the lifetime of constellations significantly.Keywords:
Satellite constellation
Geographic routing
End-to-end delay
Geographic routing uses the physical locations of devices for routing purposes instead of the conventional routing protocols which make use of logical addressing schemes representing an abstract hierarchy. Greedy geographic routing is a popular method favoured for its efficiency and its simplicity that considers only one hop neighbours. Greedy routing needs only minimal network information and as such is resilient to change and dynamic behaviour. Recent advances have seen the development of location prediction algorithms that use a variety of methods to determine a node’s future location based on their previous movements. Such prediction schemes can potentially benefit greedy geographic routing by allowing nodes to make routing decisions based on where a node will go rather than where it was according to the last update. The use of location prediction algorithms therefore allows geographic routing protocols to make decisions that are more intelligent, thus not only improving routing performance but providing a crucial step towards fully autonomous computer communications. The main contribution of this paper is the implementation and analysis of two existing location prediction schemes on top of the existing Greedy Perimeter Stateless Routing (GPSR) protocol ran in greedy mode.
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MANETs are collections of wireless nodes that can dynamically establish a network at any time at any place without using any fixed infrastructure. Due to dynamically changing topology routing in such network is very difficult. Traditional routing algorithms like distance vector and link state consumes more energy and less scalable. So we go for location based routing algorithms. Geographic routing is one of the most promising routing schemes in wireless sensor networks (WSNs), due to its simplicity, scalability, and efficiency. Unlike topological routing algorithms, they do not need to exchange and maintain routing information and work nearly stateless. This makes geographic routing attractive for wireless ad hoc and sensor networks. Most geographic routing algorithms use a greedy strategy that tries to approach the destination in each step. Even though they are scalable and simple energy consumption is very high. Here we introduce one new algorithm called GDBN sleep scheduling algorithm to reduce energy consumption. And compare the energy consumption with the normal geographic routing.
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The stateless, low overhead and distributed nature of the Geographic routing protocols attract a lot of research attentions recently. Since the geographic routing would face void problems, leading to complementary routing such as perimeter routing which degrades the performance of geographic routing, most research works are focus on optimizing this complementary part of geographic routing to improve it. The greedy forwarding part of geographic routing provides an optimal routing performance in terms of path stretch. If the geographic routing could adapt the greedy forwarding more, its performance would be enhanced much more than to optimize the complementary routing such as perimeter routings. Our work is the first time to do so. The aligned physical coordinate is used to do the greedy forwarding routing decision which would lead more greedy forwarding. We evaluate our design to most geographic routing protocols, showing it helps much and maintain the stateless nature of geographic routing.
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Conventional Routing Protocols proposed for Wireless Sensor Networks cannot fully accommodate the characteristics of WSNs. In particular, although it is possible to in the solution of energy consumption and global ID problems through applying position information, there are few protocols that actively apply such position information. In the case of the GEAR(Geographical and Energy Aware Routing),a typical algorithm, which uses positioning information, it does not fully represent the characteristics of WSNs. It is because it is limited to forward query messages and assumed as fixed network environments. The routing protocols proposed in this paper defines the direction of data, which is routed based on the position information of individual and sink nodes, in which each node configures its paths based on this direction and routes signals. Because it performs data-centric routing position information, it does not require certain global IDs in order to verify individual nodes and is able to avoid unnecessary energy consumption due to the forwarding of packets by defining its direction.
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Routing protocols are a critical aspect to performance in mobile wireless networks. The development of new protocols requires testing against well-known protocols in various sim- ulation environments. In this paper we present an overview of several well-known MANET routing protocols and the imp
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Location based routing protocols are used in Wireless Sensor Network (WSN) in which the information about the location of nodes is used for communication. It is also known as geographic routing protocol or position based routing protocols. These protocols reduce the energy consumption and increase the lifetime of the network. This paper gives an explanation about location based routing and also analysis some important location based routing protocols Geographical and Energy Aware Routing (GEAR), Geographic Adaptive Fidelity (GAF) and Minimum Energy Communication Network (MECN) in detail. For better understanding, the comparison between these protocols is shown.
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Vehicular Delay-Tolerant Networks (VDTNs) are networks where there are no permanent end-to-end connections. VDTNs have a variable topology, with frequent partitions in the connections. Given the dynamic characteristics of these networks, routing protocols can take advantage of dynamic information, such as the node's location, to route messages. Geolocation-based routing protocols choose the node that moves closer to the location of the message destination as the message carrier.In this article, the Spray and Locate geographical routing protocol was proposed. First, the protocol replicates a limited number of messages in the network, and then it uses the direction of movement of the nodes to route messages in the known destination's direction. In order to obtain the locations of nodes in the network, a VDTN localization system, known as VDTN-Locate, in which each node in the network maintains a dictionary with the last location information known, including position, movement direction, speed and age, was also proposed.The performance of Spray and Locate was compared with geographic and non-geographic routing protocols. The results show that the Spray and Locate protocol has a higher delivery rate and lower latency than the other evaluated protocols.
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Geographic routing algorithms are attractive for wireless ad hoc networks because they have been shown to scale better than other alternatives they require per-node state independent of network size, dependent only on network density. More recently, geographic routing algorithms have been proposed for use as a routing primitive for static sensor networks, as building blocks for data storage and flexible query processing in sensor networks, and even as a fallback routing mechanism for reduced state routing in the Internet.
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The aim of this work is to optimize existing routing protocols in self-organizing decentralized MANET networks by adding new metrics, creating control nodes that automate the process of selecting a routing protocol. Implementation of algorithms for use in routing based on given metrics and parameters are proposed. Analyzing the results obtained, the optimized protocol outperforms others in terms of network lifetime, in the case of a low mobility scenario, the gain reaches about 27% compared to the OLSRv2 routing protocol.
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To analyses the impact of high mobility, dynamic topologies, scalability and routing due to the more dynamic changes in network. To enhance mobile Ad-hoc network (MANET) self-organization capabilities by geographical routing algorithm during mobility. In this paper, a survey has been carried out on geographic routing protocols, such as hybrid routing, Greedy Routing, face-2 Algorithm, Perimeter Routing, quasi random deployment (QRD) techniques and time of arrival (TOA). An optimized multipath routing in wireless sensor network (WSN), energy utilization, detection of anonymous routing, node mobility prediction, data packet distribution strategies in WSN is analyzed. Geographic routing offers previous data packet information such as physical locations, packet elimination dependencies, storage capacity of topology, Associate costs and also identifies the dynamic behavior of nodes with respect to packets frequencies.
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