RESEARCH 》 A study on Deep Space Networks (DSN)

When you are dealing Deep Space Networks (DSN) one among the most challenging parts is the Interplanetary distances and communicating data across such vast distances. This is where we are not dealing with common Internet type traffic such as HTTP/FTP/VoIP/etc but it is completely different when it comes to DSN so far. So optimizing data in DSN becomes mandatory. For example if you think one of the Mars Rovers, they have used LZO lossless compression. Although they do to an extent lossy compression on images shot by these space-probes at times they we may also need high-resolution detailed high-quality images. And sometimes it is not just photos sent back to the earth, at times the space probes may also report their health status, keep alive messages as well transmit the scientific research data such as data recorded in various sensors situated on-board.

Although we got space probes across the space and ISS (International Space Station) orbiting over Earth, we do not have a scenario yet something like human colonies/bases on Moon or Mars and other planets. Eventually when such things happen in around 2020-2030 or so as the way NASA and scientists predict, DSN is going to be a case where more private companies may offer their solutions. But before that we need to still solve some of the fundamental data communication challenges involved in DSN. This is on of the fields which I am actively involved since a decade.

Unlike here on Earth upgrading a piece of hardware or communication technology is just impossible to do on a space probe which may exist millions of miles away from Earth. This also makes this technology evolve quite slowly unlike Earth bound communication technologies such as Mobile communications, Satellite networks and so on. For further complete coverage of this topic kindly refer my below detailed video titled Deep Space Communication - Episode1.

Understanding Communication Speeds: Most DSN networks are radio-wave signal based and not light (photonic) based communication. Radio waves do not travel at the speed of light. It is also one of the reason for the slow-down of the DSN unlike ground or earth bound fibre optic links since in this case data travels almost (since the medium is not vacuum and speed of light depends on the medium) at the speed of light. Before we imagine network speeds in DSN, let us understand an ideal situation of speed of light between two points in space:

Distance Speed of Light
Earth <> Moon1.5 seconds
Earth <> Mars4 minutes (240 seconds)
Earth <> Sun8 minutes (480 seconds)
Earth <> Jupiter30 minutes (1800 seconds)
Earth <> Saturn1 hour (3600 seconds)
Earth <> Neptune4 hours (14400 seconds)
Earth <> Pluto4.6 hours (16560 seconds)

NOTE: Since we compute network speeds often in bits/sec (and latency in nano-seconds and milli-seconds), in the above chart I am converting everything in seconds to understand the scale.

So based on the above chart now we can understand the scale of complexity in DSN. This underscores a fundamental limitation of physics !

Communication Protocols for DSN: For DSN a complete new set of protocols are defined which is SCP (stands for Space Communications Protocol). There are various RFCs which are defined which is called as SCPS (where S stands for Specifications). There are various variants under SCPS are defined such as SCPS-FP, SCPS-TP, SCPS-SP and SCPS-NP. The biggest difference you may find in DSN is that the delay involved due to inter-planetary distances. So based on the distance you may experience communication delays, loss of packets, etc. Say for example if you think a successful connection is established (for example a TCP session/connection), you may have to-and-fro keep alive acknowledgement packets exchanged every few milliseconds. But whereas in a case of DSN you may experience this happening every few minutes or every few hours. So that is how bizarre it is. Although there is no packet exchanges happening in few minutes or hours you should understand this is due to vast distances involved.

These SCPS specifications are defined by a committee called as CCSDS (stands for Consultative Committee for Space Data Systems). This is a body which is formed as per collaborative effort of various space agencies across the world. An Internet spanning across multiple planets is termed as IPN (stands for Interplanetary Network or in short InterPlanet). For further complete coverage of this topic kindly refer my below detailed video titled Deep Space Communication - Episode2.

Lossless Compression Algorithms for DSN: A specific set of tailor made algorithms are required for space communications unlike the ones which are used in communications here on Earth. They have to be light-weight and at the same time super-efficient and should have least processing latencies. The communication data could be just anything such as scientific research data collected via space probe sensors or it could be hi-resolution photos sent back to earth or it could be commands sent to these probes via ground control crew. I have done extensive research on this for almost more than a decade on various lossless compression algorithms. This is a case where we are dealing optimizing real-time data. This is not a passive file compression something like creating a tar-ball or some zipfile. This is a case you are sending and receiving packets continuously and you are processing them in real-time.

NASA have their own lossless compression variants and often they are customized. One of the well known algorithms which NASA uses is the LOCO-I (stands for Low Complexity Lossless Compression) which is mainly meant for compressing images. LOCO-I is a kind of lossless compression variant of JPEG. Which is why it is also can be sometimes called as JPEG-LS (stands for JPEG-Lossless). Based on LOCO-I NASA did hardware based solution which is FPGA-LOCO. Since it is hardware based, it is good in performance, reliability and extremely energy efficient.

Apart from this CCSDS have their own variant of RICE lossless compression algorithm. For further complete coverage of this topic kindly refer my below detailed video titled Space Lossless Compression.





Suggested Topics:

WAN Optimization and Network Optimization

💎 TOFFEE-MOCHA new bootable ISO: Download
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TOFFEE-DataCenter - First Live Demo and software development - Update: 26-Aug-2016 ↗
Saturday' 13-Mar-2021
Today I have done a test setup so that I can able to connect my Android Samsung Tab via TOFFEE DataCenter. Below is my complete test topology of my setup. For demo (and research/development) context I configured TOFFEE DataCenter in engineering debug mode. So I do not need two devices for this purpose.

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TOFFEE deployment topology guide ↗
Saturday' 13-Mar-2021
Assume you have two sites (such as Site-A and Site-B) connected via slow/critical WAN link as shown below. You can optimize this link by saving the bandwidth as well possibly improve the speed. However, the WAN speed can be optimized only if the WAN link speeds are below that of the processing latency of your TOFFEE installed hardware. Assume your WAN link is 12Mbps, and assume the maximum WAN optimization speed/capacity of Raspberry Pi is 20Mbps, then your link will get speed optimization too. And in another case, assume your WAN link is 50Mbps, then using the Raspberry Pi as WAN Optimization device will actually increase the latency (i.e slows the WAN link). But in all the cases the bandwidth savings should be the same irrespective of the WAN link speed. In other words, if you want to cut down the WAN link costs via this WAN Optimization set up, you can always get it since it reduces the overall bandwidth in almost all the cases (including encrypted and pre-compressed data).

INDEX :: Content Delivery Networks or Content Distribution Networks (CDN) ↗
Saturday' 13-Mar-2021

Demo TOFFEE-DataCenter WAN Optimization VM Test Setup ↗
Saturday' 13-Mar-2021

TOFFEE Benchmarks :: TOFFEE-1.1.28 ↗
Saturday' 13-Mar-2021
Here is the TOFFEE WAN Optimization benchmarks of the TOFFEE version: TOFFEE-1.1.28. This is the current TOFFEE development version till date (2-Jul-2016). This is a HPC TOFFEE variant meant for high-end custom build servers and high-end desktops (i.e High Performance Computing a.k.a HPC). TOFFEE built this way often needs customized kernel compilation and build such as processor specific and hardware specific tune-ups since it is highly CPU intensive (if not offloaded via Hardware Accelerator Cards).

Youtubeで見る - [976//1] 293 - iPerf Network Optimization - WAN Optimization Demo ↗

TOFFEE-Butterscotch Bandwidth saver software development - Update: 17-Nov-2016 ↗
Saturday' 13-Mar-2021
Here is my second software development update of TOFFEE-Butterscotch. In the previous update (28-Oct-2016) I discussed about the Alerts, etc. Whereas in my first TOFFEE-Butterscotch news update I have introduced about TOFFEE-Butterscotch research, project specifications, use-cases, etc.

Introducing TOFFEE-Fudge - Network Packet Generator ↗
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Building my own CDN - Finally Completed - Update: 17-Dec-2017 ↗
Saturday' 13-Mar-2021
Today I finally completed building my own private CDN. As I discussed so far in my earlier topics (Building my own CDN), I want to custom build the same step-by-step from scratch. And I don't want to for now use/buy third-party CDN subscriptions from Akamai, CloudFlare, Limelight, etc as I discussed earlier.

Optimization of network data (WAN Optimization) at various levels ↗
Saturday' 13-Mar-2021
WAN Network data can be optimized at various levels depending upon the network applications, protocols, topology and use-cases. So the amount of data you can optimize will depend on the strategy you choose to optimize. Such as: Network Packet level optimization, Session level optimization, File level optimization, etc.

Featured Educational Video:
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TOFFEE-DataCenter WAN Optimization software development - Update: 13-Aug-2016 ↗
Saturday' 13-Mar-2021
Earlier the TOFFEE is intended to work on IoT devices, Satellite Networks, branch office/SOHO deployments. In most cases the users may deploy just one or couple of TOFFEE devices per site. But in the case of TOFFEE-DataCenter, users can scale-up deploying the same in multiple servers in a sort of distributed cluster computing scenario. Besides the core TOFFEE-DataCenter components (such as packet processing engine/framework), I need to do lot of changes in its Graphical User Interface (GUI) too to address these new requirements.

TOFFEE-DataCenter Download :: TOFFEE-DATACENTER-1.2.2-1-portable ↗
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Detect and Monitor Failing Harddrive in Linux - My Seagate 500GB HDD Died ↗
Saturday' 13-Mar-2021
My 500GB Seagate Barracuda 7200RPM hard-drive suddenly started making mild clicking noise. I found this happening since morning. I was suspicious that something wrong in this drive and when I opened the Linux Disks app, I can find the cause of this issue. The disk is increasingly getting read errors. Besides I can see various other parameters such as Power-On Hours, Temperature, Head flying hours, etc.

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DIY TOFFEE WAN Optimization Device with Intel Celeron Mini PC ↗
Saturday' 13-Mar-2021
Here is a step-by-step DIY to build your own Intel based Mini PC WAN Optimization Device with TOFFEE. I chose this below Intel Celeron Mini PC since it is fan-less aluminium case and as well it has 2 dedicated inbuilt Gigabit Ethernet ports. You can use one for LAN Network and one for WAN Network.

Research :: Optimization of network data (WAN Optimization) at various levels:
Network File level network data WAN Optimization

Learn Linux Systems Software and Kernel Programming:
Linux, Kernel, Networking and Systems-Software online classes [CDN]

Hardware Compression and Decompression Accelerator Cards:
TOFFEE Architecture with Compression and Decompression Accelerator Card

TOFFEE-DataCenter on a Dell Server - Intel Xeon E5645 CPU:
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