Given that satellite networks cannot assume continuous connectivity among nodes, an architecture known as Delay Tolerant Networking (DTN) has been proposed as an appealing communication paradigm. However, as space networks continue to grow in both number and size, the process of routing and forwarding tra c is rapidly becoming computationally expensive and challenging. Since these networks usually exhibit predictable trajectories and communication opportunities, the research community has proposed to provide nodes with scheduled contact plans in advance in order to make distributed routing decisions as they generate or receive tra c. On the other hand, a more attractive solution for the conservative space industry seems to be a centralized scheme. Based on a Software-De ned Network (SDN) approach, a route table can be computed on ground and then provisioned to nodes in space, which would no longer run any routing intelligence on board, only forwarding. In this work we analyze the dichotomy between distributed and centralized routing schemes in the context of DTN and provide insights regarding important aspects to take into account when designing and managing satellite networks.
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In: Proceedings of the IV School of Systems and Networks (SSN 2018), Valdivia, Chile, October 29-31, 2018. Published at http://ceur-ws.org 1
Large-scale satellite networks are becoming increasingly popular as a means to provide high quality imagery, video and communication services around the globe [1]. E cient space-terrestrial communication technologies, capable of successfully moving large volumes of data between space and ground networks, are a key element in these networks. In this context, Delay Tolerant Networking (DTN) has been identi ed as a novel approach which can meet this goal in a coste ective way by relaxing communication requirements and network infrastructure usually assumed in traditional protocols. The DTN architecture, originated from deep-space and interplanetary networking, embraces the concept of occasionally-connected networks that may su er from frequent partitions, high delay, and that may be comprised of more than one divergent set of protocols [2]. To this end, a bundle layer that exists at a layer above the transport (or other) layers of the network, employs a persistent storage on each DTN node to store-carry-and-forward data packets called bundles as transmission opportunities become available.
In the case of space-based networks, the
forthcoming episodes of communications and their properties
can be determined in advance based on orbital
dynamics. These types of deterministic DTNs are known as
scheduled DTNs, and can take advantage of a contact
plan comprising the future network connectivity in
order to optimize data forwarding. Indeed, as showed
in previous works [
On the other hand, a more attractive and
controllable solution for the conservative space industry
seems to be a centralized Software De ned
Networking (SDN) approach [
In this context, the present work aims to provide an analysis on the trade-o between a distributed and a centralized utilization of CGR algorithms. In Section 2 we provide some background on how routing is carried out in space DTNs. Then, in Section 3 we describe the speci c routing schemes which will be analyzed by means of simulations. Afterwards, in Section 4 we evaluate the schemes through simulations of two realistic satellite constellations. Finally, we discuss the relevance of the results and summarize them in Section 5. 2 2.1
In DTN, Bundle Protocol data units (called bundles) are forwarded in a store-carry-and-forward fashion without assuming the next-hop node will instantly be available to respond. Figure 1 illustrates a typical delayed and disrupted space-terrestrial network where a rover in another planet (node 1) needs to send bundles to a ground station (node 3). Since there is no direct communication between the source and destination nodes, data needs to go through an intermediate satellite (node 2). However, because of signal propagation, the transmission opportunity window (a.k.a. contact ) between node 1 and 2 is highly delayed, forbidding node 1 to assume node 2 can instantaneously con rm reception of bundles. Also, the communication between nodes 2 and 3 is temporarily disrupted and will not be available until a time speci ed in the future. Thus, once bundles are received in node 2, it decides to retain and carry in-transit data in its local storage until reaching the ground station communication range, allowing the nal data transmission to start. In this type of scenarios, the lack of a stable end-to-end path restricts the utilization of end-to-end feedback messages and encourage error detection and correction, security, and other network features to be implemented on a hop-by-hop basis. 2.2
It should be noted that, in this kind of networks, routing involves not only determining the next-hop node, but also considering time variables such as when the next-hop will be available or when is the latest time a bundle can be transmitted. Therefore each temporal route is conformed by a sequence of contacts, which, as we describe in the next section, result predictable in space DTNs and can be exploited with di erent schemes in order to achieve a good network performance. As shown in Figure 2, the work ow in space DTNs goes through four stages: (i ) planning, (ii ) routing, (iii ) enqueuing and (iv ) forwarding.
In the planning stage (i ), contact plans are
determined by a central entity (a ground station or a
Mission Operation Center (MOC)) based on the
estimation of future episodes of communication. This task
involves taking into account the physical disposition
and orientation of nodes through time as well as their
communication system con guration (antenna,
modulation, transmission power, etc.). As a result, orbital
propagators and communication models are combined
to determine the contact plan which can be further
tuned to reduce energy consumption or remove
conicting contacts [
Traffic
i Planning
ii Routing
iii Enqueuing
iv Forwarding
Predictable but there can be uncertainties
Compute Contact
Plans Compute
Route
Table Enqueue Traffic Send
Traffic
ternet, network tra c can be predicted in some types
of satellite networks such as Earth observation
missions where data acquisitions are generated by
operator commands. In general, although there can be
uncertainties regarding the topology or the tra c in
the future, both have a predictable nature and can be
used as a valuable input in the planning stage.
Afterwards, a routing procedure (ii ) takes the contact plan
as input to compute a route table, which can then be
used by satellites to send bundles to destination.
Currently, the most investigated routing scheme for
predictable DTNs is Contact Graph Routing (CGR) [
A conceptual comparison of the distributed and centralized use of CGR routing is summarized in Table 1. The main advantage of the centralized scheme is given by the reduction of the computation e ort that will be performed on constrained on-board satellite computers. However, this advantage comes at the expense of having to provide additional routes to cover the uncertainties with respect to the topology and/or the tra c generated. On the other hand, the distributed approach provides a greater routing intelligence and computation e ort to satellites, which allows to tolerate faults and uncertainties without incurring in the routes information overhead. In this work we will analize this trade-o by means of satellite constellation simulations. Particularly, we will put the focus on the schemes described in the next section. 3
Regarding the distributed CGR strategy, we will
consider two di erent possibilities. On the one hand,
we will call Distributed CGR Full Route Table to the
state-of-the-art algorithm as it is implemented in the
ION 3.5.0 ight software. In this case, each node
computes a complete route table to a given destination
whenever it receives a bundle for that destination. In
other words, the route table has as many entries as
routes is able to discover the CGR algorithm. The
interested reader is refereed to [
With respect to the centralized strategy, we will call Centralized CGR Full Route Table to the scheme in which a central MOC node, analogous to a SDN controller, is in charge of computing and providing the complete route table for each other node in the net
Each node has the intelligence to calculate route tables in orbit and by-demand based on a previously distributed contact plan.
Will calculate those routes that are strictly necessary to forward tra c (scales better).
Better adapt and react to unexpected events (unexpected tra c sources, contact failures, etc).
Di cult to optimize and control what each node calculates in the end, thus how the tra c will ow.
In-orbit nodes need to use its local processor to calculate route tables (high in-orbit processing overhead).
A central node (i.e., mission control on ground) calculates and distributes route tables in advance.
Will calculate several routes that probably will not be nally used (high provisioning
and memory overhead).
Reaction to unexpected events will require alternatives routes distributed in the route table (high provisioning and memory overhead).
Allow for more controlled calculation and
optimization of the whole network.
Free in-orbit nodes resource-constrained processors from calculating complex paths.
Ground stations (EID 1 to 6)
Ground targets (EID 7 to 31) 2 Walker formation: 11
ISLs on intersection of orbital planes 9 1 7 8 12 10 17 47 a) 3 18 16 14
15 13 4 work. To this end, the same CGR used in distributed approaches was executed on the topology on a centralized node and resulting paths were recorded and provisioned to nodes in advance. Once nodes receive their respective route tables, they only need to make enqueuing and forwarding decisions. Unlike the distributed case, if the full route table were limited in this case, nodes would not be able to compute new routes on demand in the case of uncertainties or unexpected events. Given that this would provoke a considerable performance reduction in terms of bundles delivered, we will not consider a Centralized CGR Limited Route Table strategy in the present analysis. 4
In order to analyze the proposed schemes, we have
adapted and extended a discrete event-driven
simulator publicly available called DtnSim [
The chosen constellations are suitable for Earth observation missions, data-collection or high-latency communication systems. If used for Earth observation, the ground target locations would represent points of interest from which on-board instrumentation can acquire optical or radar images, or other remote sensing data. If used for data-collection or high-latency communication systems, ground targets would stand for ground-based equipment relaying either science or local user data. In both cases, data sent from ground targets are addressed via orbiting satellites to the centralized MOC. We consider a bi-directional publish/subscribe tra c pattern from all ground targets to the MOC and reversal. In particular, each ground target generates an increasing number of bundles of 125 KBytes to be delivered to the MOC. In turn, the MOC sends an increasing number of bundles to each ground target. Besides, the transmission data-rates for both inter-satellite and Earth-to-satellite links are set to 100 Kbps.
We quantify the routes information overhead of the schemes proposed in Section 3 through the number of route table entries created in each case. Figures 4 a) and 4 b) show the results for the walker-formation and along-track scenarios respectively. The Centralized CGR, Full Route Table strategy provides the same quantity of route table entries independently of the increasing tra c, given that this scheme is proactive in terms of routes computation and does not take into account the tra c generation. As we previously discussed, this overhead information is necessary in order to face uncertainties both in the predicted topolCentralized CGR, Full Route Table Distributed CGR, Full Route Table Distributed CGR, Limited Route Table computed but not used by the centralized scheme as compared to distributed schemes. Although this study suggests that distributed approaches are appealing regarding the use of computed information, other relevant aspects like the cost of processing in space nodes and the required controllability of the network need to be taken into account when deciding the most appropriate scheme. Future work will explore other comparison metrics between distributed and centralized routing in order to derive a complete evaluation framework that facilitates future space DTN designers to make an informed decision on the optimal routing strategy. 0 200 400 600 1200 1400 30000 s ire25000 t n E20000 e l b Ta15000 e t u10000 o R 5000 30000
800 1000 Bundles Sent
a) 0 200 400 600 1200
1400 800 1000 Bundles Sent b) ogy or the tra c generated. On the other hand, the distributed approaches compute route tables as tra c is generated and routed through intermediate nodes. Therefore, these schemes compute a much smaller number of routes. Besides, as expected, the Distributed CGR, Limited Route Table scheme generates fewer route table entries than Distributed CGR, Full Route Table. 5
In this work, we have described and analyzed aspects concerning distributed and centralized routing solutions for satellite-based Delay Tolerant Networks (DTNs). The centralized approach was evaluated as a means to implement a Software De ned Networking (SDN) paradigm into DTN space networking.
We have evaluated the route table entries metric in two realistic satellite constellations and the results provided evidences on the quantity of routes which were [1] J. Alvarez and B. Walls, \Constellations, clusters, and communication technology: Expanding small satellite access to space," in 2016 IEEE Aerospace Conference, March 2016, pp. 1{11. [2] V. Cerf, S. Burleigh, A. Hooke, L. Torgerson, R. Durst, K. Scott, K. Fall, and H. Weiss, \Delay-tolerant networking architecture," Internet Requests for Comments, RFC Editor, RFC 4838, April 2007. [Online]. Available: http://www.rfc-editor.org/rfc/rfc4838.txt [3] P. Muri et al., \Topology design and performance analysis for networked earth observing small satellites," in MILCOM Proceedings, Baltimore, Maryland, Nov 2011, pp. 1940{1945. [4] M. Huang, S. Chen, Y. Zhu, and Y. Wang, \Coste cient topology design problem in time-evolving delay-tolerant networks," in IEEE GLOBECOM, Dec 2010, pp. 1{5. [5] J. A. Fraire and J. M. Finochietto, \Design challenges in contact plans for disruption-tolerant satellite networks," Communications Magazine, IEEE, vol. 53, no. 5, pp. 163{169, May 2015. [6] J. A. Fraire, P. G. Madoery, and J. M. Finochietto, \On the design and analysis of fair contact plans in predictable delay-tolerant networks," IEEE Sensors Journal, vol. 14, no. 11, pp. 3874{ 3882, Nov 2014. [7] J. Fraire and J. Finochietto, \Routing-aware fair contact plan design for predictable delay tolerant networks," Ad Hoc Networks, vol. 25, pp. 303 { 313, 2015, new Research Challenges in Mobile, Opportunistic and Delay-Tolerant Networks Energy-Aware Data Centers: Architecture, Infrastructure, and Communication. [Online]. Available: http://www.sciencedirect. com/science/article/pii/S1570870514001371