The TOFFEE Project
HOMEDOCUMENTATIONUPDATESVIDEOSRESEARCHDOWNLOADSPONSORSCONTACT


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.

References:

NASA:

Wikipedia:

Other:



Suggested Topics:


WAN Optimization and Network Optimization

💎 TOFFEE-MOCHA new bootable ISO: Download
💎 TOFFEE Data-Center Big picture and Overview: Download PDF


Recommended Topics:

TOFFEE-Mocha WAN emulator Lab deployment and topology guide ↗
Saturday' 13-Mar-2021

Benchmark Raspberry Pi and other embedded SoC with TrueBench ↗
Saturday' 13-Mar-2021
TrueBench is an unique open-source benchmarking system in which the core system performance and efficiency parameters are measured at extreme high resolution in the order of several million/billion ยต-seconds for a given specific task. TrueBench is a part of The TOFFEE Project research. With TrueBench Raspberry Pi 3, Raspberry Pi 2B and Raspberry Pi 2 are benchmarked and you can do a comparative analysis with standard mainstream x86 devices.

TOFFEE DataCenter WAN Optimization - Google Hangouts demo and VOIP Optimization ↗
Saturday' 13-Mar-2021
TOFFEE DataCenter WAN Optimization - Google Hangouts demo and VOIP Optimization

TCP Tune-up and Performance Analysis Graphs - Congestion Control - Research - Dos and Don'ts ↗
Saturday' 13-Mar-2021

IP Header Compression in WAN Links and TOFFEE-DataCenter WAN Optimization ↗
Saturday' 13-Mar-2021

CDN Hosting ↗
Saturday' 13-Mar-2021
It is quite interesting that there are few web hosting firms are offering direct CDN based hosting services. Since it is a direct CDN based hosting, it is cheap, extremely easy or transparent CDN service. It is transparent, since each time you publish your content in the hosting web-server (origin server), it is immediately is in sync automatically in the user-serving CDN caching machines. Since the hosting vendor and the CDN vendor are all the same, it is also easy to use their services. There is no incompatibility issues, interoperability issues, and better integrated analytics, are all the benefits of CDN Hosting services.

Watch on Youtube - [466//1] 158 VLOG - TOFFEE WAN Optimization Software Development live update - 6-Nov-2016 ↗


A study on Deep Space Networks (DSN) ↗
Saturday' 13-Mar-2021
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.

Raspberry Pi as a Networking Device ↗
Saturday' 13-Mar-2021
Raspberry Pi is often used as a single board computer for applications such as IoT, hobby projects, DIY, education aid, research and prototyping device. But apart from these applications Raspberry Pi can be used for real-world applications such as in making a full-fledged networking devices. Raspberry Pi is a single board ARM based hardware which is why it is also classified as ARM based SoC. Since it is ARM based it is highly efficient, tiny form-factor and lower in power consumption with moderate computational power. This will allow it to work several hours on emergency battery backup power supply such as low-cost domestic UPS and or some renewable energy source, which is a prerequisite for a typical networking device.

IP Header Compression in WAN Links and TOFFEE-DataCenter WAN Optimization ↗
Saturday' 13-Mar-2021

Network Packet Queue or Buffer - Packet Flow Control, Fragmentation and MTU ↗
Saturday' 13-Mar-2021
Network Packet Queue or Buffer - Packet Flow Control, Fragmentation and MTU



Featured Educational Video:
Watch on Youtube - [435//1] 0x1d3 Who gets Laid off (or Fired) during a recession ? #TheLinuxChannel #KiranKankipati ↗

First TOFFEE Code Release ↗
Saturday' 13-Mar-2021
I started working on the new TOFFEE project (which is the fork of my earlier TrafficSqueezer open-source project) starting from 1st January 2016 onwards. Ever since I was busy in research and altering certain old features so that it is more minimal than TrafficSqueezer, a more focused agenda, deliver refined code and a broader vision. I have lined up more things to follow in the upcoming months. I want to focus about all aspects of WAN communication technologies not just on core WAN Optimization research and technology.

TOFFEE hardware selection guide ↗
Saturday' 13-Mar-2021
When you build a WAN Optimization device with TOFFEE the entire packet processing (data optimization) takes place in software layer or in other words more precisely Operating System kernel space. However if you have any compression or encryption hardware accelerator hardware card the parts of the TOFFEE packet processing modules can be offloaded to hardware layer and thus improving its efficiency.

Network Packet Queue or Buffer - Packet Flow Control, Fragmentation and MTU ↗
Saturday' 13-Mar-2021
Network Packet Queue or Buffer - Packet Flow Control, Fragmentation and MTU

Demo TOFFEE-DataCenter WAN Optimization packaging feature ↗
Saturday' 13-Mar-2021




TOFFEE (and TOFFEE-DataCenter) optimized Wireless Mesh-Networks - B.A.T.M.A.N [open-mesh.org (Open Mesh)] ↗
Saturday' 13-Mar-2021
TOFFEE/TOFFEE-DataCenter can be used to optimize Ad-Hoc Mobile Wireless Mesh-Networks. To learn more about the same here are some references: B.A.T.M.A.N. - https://en.wikipedia.org/wiki/B.A.T.M.A.N. Mobile ad hoc network (MANET) - https://en.wikipedia.org/wiki/Mobile_ad_hoc_network Wireless ad hoc network (WANET) - https://en.wikipedia.org/wiki/Wireless_ad_hoc_network open-mesh.org (Open Mesh) Wiki - https://www.open-mesh.org/projects/open-mesh/wiki



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


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


TOFFEE-DataCenter on a Dell Server - Intel Xeon E5645 CPU:
TOFFEE-DataCenter screenshots on a Dual CPU - Intel(R) Xeon(R) CPU E5645 @ 2.40GHz - Dell Server