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Disruption Tolerant Networking Flight Validation Experiment on NASA's EPOXI Mission

Disruption Tolerant Networking Flight Validation Experiment on NASA's EPOXI Mission
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  Disruption Tolerant Networking Flight Validation Experiment on NASA’s EPOXI Mission Jay Wyatt, Scott Burleigh, Ross Jones, Leigh Torgerson, Steve Wissler Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive Pasadena, California, 91109 {E.Jay.Wyatt, Scott.C.Burleigh, Ross.M.Jones, Jordan.L.Torgerson, Steven.S.Wissler}  Abstract— In October and November of 2008, the Jet  Propulsion Laboratory installed and tested essential elements of Delay/Disruption Tolerant Networking (DTN) technology on the Deep Impact spacecraft. This experiment, called Deep Impact Network Experiment (DINET), was  performed in close cooperation with the EPOXI project which has responsibility for the spacecraft. During DINET  some 300 images were transmitted from the JPL nodes to the spacecraft. Then they were automatically forwarded  from the spacecraft back to the JPL nodes, exercising DTN's bundle srcination, transmission, acquisition, dynamic route computation, congestion control, prioritization, custody transfer, and automatic retransmission procedures, both on the spacecraft and on the ground, over a period of 27 days.  All transmitted bundles were successfully received, without corruption. The DINET experiment demonstrated DTN readiness for operational use in space missions. This activity was part of a larger NASA space DTN development  program to mature DTN to flight readiness for a wide variety of mission types by the end of 2011. This paper describes the DTN protocols, the flight demo implementation, validation metrics which were created for the experiment, and validation results. Keywords- DTN, EPOXI, networking, protocols I.   I  NTRODUCTION  Disruption-Tolerant Networking (DTN; a.k.a. Delay-Tolerant Networking) is a communication architecture that is designed to provide automated data communication services in networks characterized by frequent and lengthy episodes of partitioning, lengthy signal propagation delays, and/or heterogeneity in protocol support below the application layer. Research into DTN has culminated in the publication of Internet experimental RFCs (Requests For Comments) describing the overall architecture of DTN technology (RFC 4838), the core DTN Bundle Protocol (RFC 5050), and the Licklider Transmission Protocol for automatic retransmission of data lost in transit (RFC 5326), with others in progress. Although this research has been substantially motivated by its applicability to such problem domains as sensor-based networks with scheduled intermittent connectivity, terrestrial wireless networks that cannot ordinarily maintain end-to-end connectivity, and underwater acoustic networks, the srcinal driver for the research was the emerging need to provide capable network services in support of space flight operations. Historically, communications in spacecraft mission operations have been managed by the spacecraft team. Transmission and reception episodes are individually configured, started, and ended by command. Reliability over deep space links is achieved by management: on loss of data, we command retransmission. Even the relaying of data from Mars rovers through Mars orbiters is managed: we send transmission commands to the rovers, and later we send transmission commands to the orbiters that received the data from the rovers. An alternative approach would be to implement an automatic space data communications network, similar in capability to the Internet. The Internet protocols themselves, however, are generally unsuitable for this  purpose because they rely on timely and continuous end-to-end delivery of data and acknowledgments: communication links to and from spacecraft are often subject to interruption and, for deep-space missions, signal propagation delays may  be very large. DTN is an alternative network architecture that is designed to address these problems. DTN runs as an “overlay” above the Internet where possible, but it runs directly over link-layer protocols, taking the place of the IP network protocol where necessary. That is, a TCP connection within an IP- based network may be one “link” of a DTN end-to-end data  path; a deep-space R/F transmission may be another. Reliability is achieved by retransmission between relay  points within the network, not end-to-end retransmission. There is no reliance on end-to-end acknowledgment. Route computation has temporal as well as topological elements, e.g., a schedule of planned contacts. Lengthy signal  propagation delays don’t compromise the accuracy of route computation. Forwarding at each router is automatic but not necessarily immediate: store-and-forward rather than “bent   pipe”, so link interruption doesn’t prevent the eventual delivery of data. Our discussion of flight validation results will rest on an understanding of the following features of the DTN architecture: •   Priority. The forwarding of DTN network protocol data units, termed bundles , is informed by user-assigned  priority markings: bundles may be assigned High, Medium, or Low priority, with higher-priority bundles forwarded in preference to lower-priority bundles wherever forwarding opportunities are constrained. •   Dynamic Routing. Traffic flow within a delay-tolerant network, as in the Internet, is more efficient if routers can automatically select different forwarding paths at different times, depending on nodes’ anticipated ability to forward data on a timely basis. Note, though, that Internet techniques for route computation are not well suited for operating a network over interplanetary distances where changes in topology may occur more rapidly than they can be reported. •   Automated Forwarding. Automatic initiation and termination of data transmission as transmission opportunities arise is a core capability of DTN. •   Custody Transfer. Performing retransmission of lost data at relay points rather than end-to-end enables each relay point along a bundle’s end-to-end path that receives the bundle to take custody  of it, i.e. to relieve the prior retransmission point (source or relay) of any further responsibility for transmitting the bundle. •   Delay Tolerant Retransmission. The need to retransmit lost data is normally signaled by the receiver, upon detection of a gap in the received data. But in the event that insufficient data is received to enable gap detection  – or in the event that the signal itself is lost in transmission – the only way to initiate retransmission is to detect the lapse of a timer prior to arrival of a  positive acknowledgment. Computing accurate intervals for retransmission timers is especially challenging in a delay-tolerant network, as link interruption may defer transmission of acknowledgments. Human operators readily compute these intervals based on their knowledge of contact schedules; DTN must do the same in order to automate retransmission. •   Flow and Congestion Control. Automated forwarding and retransmission rely on the availability of data storage resources, so rates of data transmission and reception must be controlled in order to prevent exhaustion of those resources and failure of network operations. A fully automated network must accomplish this resource conservation automatically. Interplanetary Overlay Network (ION) is an implementation of the DTN architecture that is specifically intended to be usable for interplanetary communications. As such, a key milestone in its development has been validation in operation on-board a functioning spacecraft. The Deep Impact Network experiment provided an opportunity not only to validate the software in flight but also to apply metrics by which the operational suitability of the software could be objectively assessed. II.   DINET   O VERVIEW  The Deep Impact Network Experiment (DINET) was a technology validation experiment of JPL’s implementation of Delay-Tolerant Networking (DTN) protocols. The DINET development produced a version of JPL’s implementation of Delay-Tolerant Networking protocols in flight and ground software that is now at technology readiness level (TRL) 8. The DINET software (SW) is of sufficient quality that future flight projects can easily use it at low risk. DINET was implemented on the Deep Impact spacecraft and was closely coordinated with the EPOXI  project. DINET operations were performed during the EPOXI spacecraft team “stand down” after Extrasolar Planet Observation and Characterization (EPOCH) operations and before the start of development for DIXI operations (i.e., during October and November 2008). DINET developments and operations were on a non-interference basis with EPOXI to the maximum extent  possible. DINET was sponsored by NASA Office of Space Operations / Space Communications and Navigation (OSO/SCAN) via JPL DSN office Space Networking and Mission Automation. The total cost of DINET was $1.4M, which included support for the EPOXI spacecraft team and their contractor Ball Aerospace and Technology Corporation. III.   DTN   I MPLEMENTATION  A DTN implementation intended to function in an interplanetary network environment – specifically, aboard interplanetary research spacecraft separated from Earth and one another by vast distances – must operate successfully within two general classes of design constraints: link constraints and processor constraints. Link constraints All communications among interplanetary spacecraft are, obviously, wireless. Less obviously, those wireless links are generally slow and are usually asymmetric. The electrical power provided to on-board radios is limited and antennae are relatively small, so signals are weak. This limits the speed at which data can be transmitted intelligibly  from an interplanetary spacecraft to Earth, usually to some rate on the order of 256 Kbps to 6 Mbps. The electrical power provided to transmitters on Earth is certainly much greater, but the sensitivity of receivers on spacecraft is again constrained by limited power and antenna mass allowances. Because historically the volume of command traffic that had to be sent to spacecraft was far less than the volume of telemetry the spacecraft were expected to return, spacecraft receivers have historically  been engineered for even lower data rates from Earth to the spacecraft, on the order of 1 to 2 Kbps. As a result, the cost per octet of data transmission or reception is high and the links are heavily subscribed. Economical use of transmission and reception opportunities is therefore important, and transmission is designed to enable useful information to be obtained from brief communication opportunities: units of transmission are typically small, and the immediate delivery of even a small  part (carefully delimited) of a large data object may be  preferable to deferring delivery of the entire object until all  parts have been acquired. Processor constraints The computing capability aboard a robotic interplanetary spacecraft is typically quite different from that provided by an engineering workstation on Earth. In part this is due, again, to the limited available electrical power and limited mass allowance within which a flight computer must operate. But these factors are exacerbated by the often intense radiation environment of deep space. In order to minimize errors in computation and storage, flight  processors must be radiation-hardened and both dynamic memory and non-volatile storage (typically flash memory) must be radiation-tolerant. The additional engineering required for these adaptations takes time and is not inexpensive, and the market for radiation-hardened spacecraft computers is relatively small; for these reasons, the latest advances in processing technology are typically not available for use on interplanetary spacecraft, so flight computers are invariably slower than their Earth-bound counterparts. As a result, the cost per processing cycle is high and processors are heavily subscribed; economical use of processing resources is very important. The nature of interplanetary spacecraft operations imposes a further constraint. These spacecraft are wholly robotic and are far beyond the reach of mission technicians; hands-on repairs are out of the question. Therefore the processing  performed by the flight computer must be highly reliable, which in turn generally means that it must be highly  predictable. Flight software is typically required to meet “hard” real-time processing deadlines, for which purpose it must be run within a hard real-time operating system (RTOS). One other implication of the requirement for high reliability in flight software is that the dynamic allocation of system memory may be prohibited except in certain well-understood states, such as at system start-up. Unrestrained dynamic allocation of system memory introduces a degree of unpredictability into the overall flight system that can threaten the reliability of the computing environment and  jeopardize the health of the vehicle. 1)    ION Design Principles The design of the ION implementation of DTN reflects several core principles that are intended to address these constraints. Shared memory Since ION must run on flight processors, it had to be designed to function successfully within an RTOS. Many real-time operating systems improve processing determinism by omitting the support for protected-memory models that is provided by Unix-like operating systems: all tasks have direct access to all regions of system memory. (In effect, all tasks operate in kernel mode rather than in user mode.) ION therefore had to be designed with no expectation of memory protection. But universally shared access to all memory can be viewed not only as a hazard but also as an opportunity. Placing a data object in shared memory is an extremely efficient means of passing data from one software task to another. Zero-copy procedures Given ION’s orientation toward the shared memory model, a further strategy for processing efficiency offers itself: if the data item appended to a linked list is merely a pointer to a large data object, rather than a copy, then we can further reduce processing overhead by eliminating the cost of byte-for-byte copying of large objects. Moreover, in the event that multiple software elements need to access the same large object at the same time, we can provide each such software element with a pointer to the object rather than its own copy (maintaining a count of references to assure that the object is not destroyed until all elements have relinquished their pointers). This serves to reduce somewhat the amount of memory needed for ION operations. Highly distributed processing The efficiency of inter-task communications based on shared memory makes it practical to distribute ION  processing among multiple relatively simple pipelined tasks rather than localize it in a single, somewhat more complex daemon. This strategy has a number of advantages: •   The simplicity of each task reduces the sizes of the software modules, making them easier to understand  and maintain, and thus it can somewhat reduce the incidence of errors. •   The scope of the ION operating stack can be adjusted incrementally at run time, by spawning or terminating instances of configurable software elements, without increasing the size or complexity of any single task and without requiring that the stack as a whole be halted and restarted in a new configuration. In theory, a module could even be upgraded with new functionality and integrated into the stack without interrupting operations. •   The clear interfaces between tasks simplify the implementation of flow control measures to prevent uncontrolled resource consumption. Portability Designs based on these kinds of principles are foreign to many software developers, who may be far more comfortable in development environments supported by  protected memory. It is typically much easier, for example, to develop software in a Linux environment than in VxWorks 5.4. However, the Linux environment is not the only one in which ION software must ultimately run. Consequently, ION has been designed for easy portability. POSIX™ API functions are widely used, and differences in operating system support that are not concealed by the POSIX abstractions are encapsulated in two small modules of platform-sensitive ION code. The bulk of the ION software runs, without any source code modification whatsoever, equally well in Linux™ (Red Hat®, Fedora™, and Ubuntu™, so far), Solaris® 9, OS/X®, VxWorks® 5.4, and RTEMS™, on both 32-bit and 64-bit processors. Developers may compile and test ION modules in whatever environment they find most convenient. Moreover, there is no need to maintain separate versions of the implementation for flight and ground. This reduces cost and the risk of error in software maintenance. 2)    ION Software Elements The following elements of ION software, conforming to these principles, implement the DTN architecture in a manner that we believe will be suitable for interplanetary network applications. Interplanetary Communication Infrastructure (ICI) The ICI package in ION provides a number of core services that, from ION’s point of view, implement what amounts to an extended POSIX-accessible operating system. ICI services include the following:  Platform The platform system contains operating-system-sensitive code that enables ICI to present a single, consistent  programming interface to those common operating system services that multiple ION modules utilize. For example, the platform system implements a standard semaphore abstraction that may invisibly be mapped to underlying POSIX semaphores, SVR4 IPC semaphores, or VxWorks semaphores, depending on which operating system the  package is compiled for. The platform system also implements a standard shared-memory abstraction, enabling software running on operating systems both with and without memory protection to participate readily in ION’s shared-memory-based computing environment.  Personal Space Management (PSM) Although sound flight software design may prohibit the uncontrolled dynamic management of system memory,  private management of assigned, fixed blocks of system memory is standard practice. Often that private management amounts to merely controlling the reuse of fixed-size rows in static tables, but such techniques can be awkward and may not make the most efficient use of available memory. The ICI package provides an alternative, called PSM, which performs high-speed dynamic allocation and recovery of variable-size memory objects within  an assigned memory block of fixed size.  Memmgr The static allocation of privately-managed blocks of system memory for different purposes implies the need for multiple memory management regimes, and in some cases a program that interacts with multiple software elements may need to  participate in the private shared-memory management regimes of all. ICI’s memmgr system enables multiple memory managers – for multiple privately-managed blocks of system memory – to coexist within ION and be concurrently available to ION software elements.  Lyst The lyst system is a comprehensive, powerful, and efficient system for managing doubly-linked lists in private memory. It is the model for a number of other list management systems supported by ICI; as noted earlier, linked lists are heavily used in ION inter-task communication. Smlist Smlist is another doubly-linked list management service. It differs from lyst in that the lists it manages reside in shared (rather than private) DRAM, so operations on them must be semaphore-protected to prevent race conditions. Simple Data Recorder (SDR) SDR is a system for managing non-volatile storage, built on exactly the same model as PSM. Put another way, SDR is a small and simple “persistent object” system or “object database”. It enables straightforward management of linked lists (and other data structures of arbitrary complexity) in non-volatile storage, nominally within a single file whose  size is pre-defined and fixed. SDR includes a transaction mechanism that protects database integrity by ensuring that the failure of any database operation will cause all other operations undertaken within the same transaction to be  backed out. The intent of the system is to assure retention of coherent protocol engine state even in the event of an unplanned flight computer reboot in the midst of communication activity.  Zero-Copy Objects (ZCO) ION’s zero-copy objects system leverages the SDR system’s storage flexibility to let user application data be encapsulated in any number of layers of protocol without copying the successively augmented protocol data unit from one layer to the next. It also implements a reference counting system that enables protocol data to be processed  by multiple software elements concurrently – e.g., a bundle may be both delivered to a local endpoint and, at the same time, queued for forwarding to another node – without requiring that distinct copies of the data be provided to each element. Licklider Transmission Protocol (LTP) The ION implementation of LTP conforms fully to RFC 5326, but it also provides two additional features that enhance functionality without affecting interoperability with other implementations: •   The service data units – nominally bundles – passed to LTP for transmission may be aggregated into larger  blocks before segmentation. By controlling block size we can control the volume of acknowledgment traffic generated as blocks are received, for improved accommodation of highly asynchronous data rates. •   The maximum number of transmission sessions that may  be concurrently managed by LTP (a protocol control  parameter), multiplied by the maximum block size, constitutes a transmission “window” – the basis for a delay-tolerant, non-conversational flow control service over interplanetary links In the ION stack, LTP serves effectively the same role that is performed by TCP in the Internet architecture, providing flow control and retransmission-based reliability. All LTP session state is safely retained in an SDR database for rapid recovery from a spacecraft or software fault. Bundle Protocol (BP) The ION implementation of BP conforms fully to RFC 5050, including support for the following standard capabilities: •   Prioritization of data flows •   Bundle reassembly from fragments •   Flexible status reporting •   Custody transfer, including re-forwarding of custodial  bundles upon failure of nominally reliable convergence-layer transmission The system also provides two additional features that enhance functionality without affecting interoperability with other implementations: •   Rate control provides support for congestion forecasting and avoidance. •   Bundle headers are encoded into compressed form  before issuance, to reduce protocol overhead and improve link utilization. In addition, ION BP includes an implementation of Contact Graph Routing (CGR), a system for computing dynamic routes through time-varying network topology assembled from scheduled, bounded communication opportunities. However, the details of CGR are beyond the scope of this  paper. To summarize, BP serves effectively the same role that is  performed by IP in the Internet architecture, providing route computation, forwarding, congestion avoidance, and control over quality of service. Together, the BP/LTP combination offers capabilities comparable to TCP/IP in the Internet. All bundle transmission state is safely retained in an SDR database for rapid recovery from a spacecraft or software fault. 3)    ION implementation architecture The ION implementation of BP/LTP is designed to work well within the constraints of the spacecraft flight software environment, emphasizing safety and efficiency. Figure 1  provides an overview of ION’s architecture. A few notes on this main line data flow:    For simplicity, the data flow depicted here is a “loopback” flow in which a single BP “node” is shown sending data to itself (a useful configuration for test purposes). In order to depict typical operations over a network we would need two instances of this node diagram, such that the <LSO> task of one node is shown sending data to the <LSI> task of the other and vice versa.    A BP application or application service (such as Remote AMS) that has access to the local BP node – for our  purposes, the “sender” – invokes the bp_send function to send a unit of application data to a remote counterpart. The destination of the application data unit is expressed as a BP endpoint ID (EID). The application data unit is encapsulated in a bundle and is queued for forwarding.    The forwarder task identified by the “scheme” portion of the bundle’s destination EID removes the bundle from the
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