CDCA 2008 paper


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CDCA 2008 paper

  1. 1. Real-time Autonomic Asset Tracking Robert A. Mueller BNet Corporation, Inc. 206-932-1868 Jon R. Boyd Raytheon Missile Systems (520) 663-7827 The current use of RFID devices for asset and container tracking offers considerable benefits vice barcodes, but also have significant limitations in their ability to provide real-time information on asset location and environmental events and exceptions. Many of the active RFID protocols are also proprietary and burdened with intellectual property restrictions (and associated expensive licensing fees). We propose an intelligent and secure autonomic logistics information system that delivers contextual-based knowledge of high-value item location and environmental status. The Autonomic Tracking & Response System (“ATaRS”) is based on secure data feeds from distributed and disparate (and possibly legacy) information sources, intelligent data fusion and situational analysis and presentation, and advanced autonomic edge devices built on open standards that feature long battery life and low-maintenance, safety when operating close to ordnance, mesh network scalability to thousands of nodes, and reliable environmental monitoring and transmission from inside sealed metallic containers with no external antennas or container modification. ATaRS is a demonstrated technical integration of three (3) existing and proven systems: Phase IV Engineering’s AWAVE™ family of IEEE 802.15.4 based wireless mesh network sensing devices; and Raytheon’s intelligent distributed agent platform and Distributed Common Ground System (DCGS) Integration Backbone (DIB), an open-architecture designed to provide interoperability at the data services level for all the U.S. military and coalition services.
  2. 2. Problem A principal issue with military logistics asset tracking is reliance on dated technology. Barcodes can be quite effective but require short distance scanning with line-of-sight. And the core technology and operating principals of the basic, most commonly used active RFID for DOD strategic transport tracking is almost 20 years old. The consequences are significant:  Limited capabilities. The ability to read and write tags when a tag is within direct range of a reader and the limited ability for several specific sensing applications.  Proprietary solutions. While based on standards, they are encumbered with patent protections and require expensive licenses, and there are limited numbers of sources.  Dependence on expensive infrastructure. The most common deployment of active RFID tracking systems requires the installation of fixed interrogators with line power. There is “visibility” only where there are interrogators, and there is limited range between an interrogator and a tag, so expensive infrastructure is required for broad visibility.  Lack of data security. Data on tags and within interrogators is unprotected, and it is relatively easy to intercept over-the-air data transmissions between interrogator and tag.  Visibility limited to (stale) data. When depending on fixed interrogators, asset visibility is limited to the last time a tag was within range of the interrogator.  Technology improvement limited by legacy dependence. The extensive outlay of fixed interrogators limits new improvements to maintain backward compatibility. Key Attributes for a Viable Real-time Asset Tracking Solution Improvements to existing military logistics tracking systems necessarily involve technology (both hardware and software) and improved business processes. Addressing the key attributes of technology that contribute to meeting the demands of modern military logistics suggest the following: RF Hardware  Standards-based. Proprietary RF hardware should be avoided. The preference is for RF protocols that subscribe to documents available from major standards organizations (e.g., IEEE or ISO) that are not burdened with patent claims or expensive licensing requirements.  Open interfaces. All forms of communication should be through open interfaces. For RF, standard protocols (e.g., IEEE 802-15.4); for sensors, an industry-standard and documented bus interface (e.g., I2C); for data communication, open data formats (e.g., Web services, XML, SOAP).  Scalable. All aspects of the tracking system should scale: number of sensors/device; number of devices that concurrently communicate; number of (edge) devices per information system; scope of the information system components.  Flexible Support for sensing. Build in support for commonly requested sensors (e.g. temperature and relative humidity) but allow the hardware and software components to be easily adapted by third-party developers to support many different sensors.
  3. 3.  Flexible WLAN interoperability. Local area tracking devices can provide accurate data about asset location and status, but for real-time asset visibility, there must be interoperability with wider area communication devices. This spans from WiFi to cellular to global satellite communication.  Operates from inside containers. To autonomically monitor a containerized asset, the asset tracking device must monitor the asset from inside the container, and transit asset data (wirelessly) to a communication system outside the container, without requiring container modifications (which are often prohibited). Tracking systems without these capabilities cannot provide real-time asset visibility either in storage or in-transit situations.  Operational Safety. Military assets often include ordnance. Wireless devices that operate around ordnance must be tested for Hazardous Emitted Radiation in the presence of Ordnance (HERO) to establish a certified Safe Separation Distance (SSD). To have practical application, tracking devices must have small SSDs (inches, rather than feet).  Data Security. Military assets and their status are often sensitive. Asset data should be secured using government approved data security methods.  Long battery life. Military assets are often stored and/or moved without use for many years. Asset tracking devices that require manual operation or frequent maintenance have limited application. A battery life of at lest five years is generally requested. User-Interface and Sense and Respond Information System  Standards-based with Open interfaces. Asset tracking system solutions must co-exist and communicate in a disparate and distributed environment with other software components. Examples include Java Remote Method Invocation (Java RMI) which enables the programmer to create distributed Java technology-based to Java technology-based applications; Simple Object Access Protocol (SOAP), a simple XML-based protocol to let applications exchange information over HTTP; Object Query Language (OQL), a query language standard for object-oriented databases modeled after SQL; Java Message Service (JMS), a messaging standard that allows application components based on the Java 2 Platform to create, send, receive, and read messages; and Universal Description, Discovery and Integration (UDDI), a platform-independent, XML-based registry for businesses worldwide to list themselves on the Internet.  Interoperability with legacy systems. Asset tracking system solutions cannot stand alone and be independent. They must seamlessly and securely interoperate with existing systems.  Scalable. Asset tracking system solutions must not be limited in the number of data feeds; the type of data feeds; the volume of information to be processed; the complexity of business rules to adopt; or the number of legacy interfaces required.  Data Security. Information flow within or between software systems cannot be compromised. Typical data security represents include object level access control, encrypted communications, and PKI based authentication and non-repudiation.  Data Fusion. Data fusion is the use of techniques that aggregate data from multiple sources to achieve information and inferences. In the presence of potentially massive data streams, data fusion is required to avoid information overload and associated misinterpretation of data.  Situational Awareness & Reasoning. Situation awareness provides knowledge of the situation surrounding an asset. Situational reasoning entails understanding what those situational
  4. 4. factors mean in relation to requirements, expectations, limitations, and plans, and understanding what might happen in the near future.  Powerful location and visualization engine. Getting real-time assets location displays, including accurate geo-spatial location and accurately mapped facilities, with both 2D and 3D visualization.  Fully programmable. Adapting the asset visibility system should be through third-party adaptive programmable interface and tools, and not require modifying the asset visibility software. Wireless Sensing Mesh Networks Wireless mesh networks have emerged as a key technology for next-generation wireless networking. Because of their advantages over other wireless networks, wireless mesh networks have seen rapid technological progress, open standards, and numerous and broad applications. Military logistics represents a unique and challenging application area for wireless technology. The AWAVE wireless sensing mesh network products developed by Phase IV Engineering were designed for safe and reliable ordnance tracking and monitoring. AWAVE wireless sensing devices manage themselves into highly reliable and fault-tolerant mesh networks with long range, fast data rates, and automatic transaction processing. Built on industry standards, the platform’s extensible open architecture allows third parties to adapt its capability to their requirements. The mesh network delivers accurate manifest, environmental, and security events in near real-time using IEEE 802.15.4-compliant wireless sending nodes (WSNs) that operate at 2.4 GHz, the most widely accepted worldwide unlicensed ISM band. The low-power, long-life sensor nodes are remotely programmable and certified safe from Hazards of Electromagnetic Radiation to Ordnance (HERO) with 0” Safe Separation Distance. Direct-sequence 16-channel spread- spectrum modulation makes the nodes less susceptible to RF noise and jamming than fixed- frequency devices. The WSNs accommodate up to 32 sensors on an industry-standard I2C bus. The mesh network is controlled by a Wireless Data Controller available in many forms, including a USB device for personal-computer connection, a Handheld Reader integrated with a rugged Windows Mobile scanner/computer, and a Remote Data Controller with GPS receiver and SATCOM transceiver. The mesh network operates autonomously with self-managing nodal connectivity.
  5. 5. Information flow between WSNs and the mesh network employs the xTango web-server-based architecture for easy interfacing and application programming. All data on the xTango network is sent using industry-standard Extensible Markup Language and Service-Oriented Architecture Protocol. The xTango server can be local or remote from the mesh network while interoperating seamlessly with ATaRS. The battery is a 3.6V Lithium Thionyl Chloride (AA size). Battery life is dependent upon the utilization scenario (polling times, type of sensors, frequency of sensed events). A WSN meshed for 10 minutes every 6 hours, with temp / RH reading once per hour and shock observed continuously, is expected to have a battery life of 5.5 years. Figure 2. Top and Bottom View of Wireless Sensing Node (WSN) Range between nodes depends upon the scenario (type of container the WSN is placed in, surrounding metallic structures); however, the range in open air between two WSNs is typically 200-300 ft. The mesh network is designed to scale to many thousands of nodes using a multi- channel, “multi-layer” mesh protocol. The expected maximum mesh network range will exceed several miles. Figure 3. Actual Screen Shot of Multi-level Mesh
  6. 6. The AWAVE devices have been tested inside every Raytheon Missile System container, without container modification or external antenna, as well as ISO standard containers and specialized ammunition boxes, and have a transmission range of from twenty feet to over one hundred feet from the device inside the container to a wireless data controller outside the container. Figure 4. WSN inside a Missile Container Some additional current AWAVE wireless sensing mesh network capabilities include:  Data pipes (high speed data transfer). Data throughput rates of up to 38K bps for higher- speed data transfer.  Point to Multi-Point (command and control). Real-time delivery and acknowledgement for direct wireless control of electronic systems.  RF Quiet Mode. Ability to put an entire mesh network of up to 330 nodes into a receiver-only mode within five (5) seconds.  Over-the-air programmability (including firmware upgrade). All programmable sensor and timing controls, as well as mesh network node device firmware, can be wirelessly programmed remotely.  CTX (autonomic transformation of Mesh Node and Mesh Controller). Wireless sensing mesh network nodes can autonomically morph between being mesh network nodes (when there is a controller operating in an active network) and a controller (when there are network nodes that seek to join a network that does not currently have a controller). CTX is also used for load balancing in the multi-layer mesh network mode.  Bluetooth Handheld reader communication. The AWAVE wireless gateway has a Bluetooth interface for wireless communication for handheld devices.  GPS and Distributed Radio Location. The AWAVE system currently supports two-dimensional geo-location of wireless network nodes using RSSI-based ranging, statistical error processing (to compensate for multi-path signals), and trilateration. Some future wireless sensing mesh network capabilities currently on the roadmap include:  FIPS 197 Data Security: We will integrate an AES-128 hardware encryption engine that provides data security yet requires limited computation cycles and battery power.
  7. 7.  GSM Cellular: GSM is emerging as one of the most widely available and cost effective wide- area communication protocols. We will provide a GSM cellular interface for the WDC gateway.  Differential GPS: GPS offers reasonable geo-location accuracy when line-of-sight to the sky is available. By providing differential error-correction, it is possible to get CEP accuracy of less than 1 meter. This can be important when trying to provide geo-location of closely placed assets (e.g., a container in a 3D stack). We will integrate differential GPS into WSNs, and provide guidance on COTS differential reference stations. Autonomic Sense & Respond: ATaRS Asset visibility has been identified as a critical enabler to increase system effectiveness, improve availability and readiness, and decrease life asset cycle costs. To date, asset visibility systems have been labor intensive, error prone, and limited in scope and capability. There is an ever increasing need for reliable, real time information for monitoring assets (in transit and/or storage) that enables a cost efficient sense and respond capability (see GAO Report 05-15, Improvements Needed in DOD's Implementation of Its Long-Term Strategy for Total Asset Visibility of Its Inventory,, which projects DoD to slip yet again its target date for a consolidated approach). The problem of limited or no asset visibility is particularly acute for high-value, sensitive, and mission critical items, including aviation and vehicle repair parts, weapon systems, and ordnance. Raytheon Missile Systems (RMS) is developing the Autonomic Tracking and Response System (ATaRS) to address this need. ATaRS seeks to increase inventory accuracy, provide reliable monitoring of asset conditions, and reduce associated resource (manpower, equipment) requirements. Unlike most currently used asset tracking systems, which provide basic data with limited or no context for interpretation, ATaRS will deliver situational knowledge and situational views (see, for example, ActiveEdge® Situational Reasoning Framework Technical Overview at Situational knowledge is generally derived from multiple, distributed, and diverse data streams, and using knowledge-based tools such as data fusion, intelligent agents, and reasoning engines. Situational views present a logistics systems’ different communities and constituencies with information that is specific to their mission, security level, and viewing preferences. Figure 5. ATaRS will offer Situational Knowledge & Intelligent Action Some key attributes of ATaRS include:  Intelligent, Context-aware Asset Control  Dynamic Liability Management and Mitigation  Prognostics / condition-based maintenance  A wireless, sensing, communications, and response system  An open architecture information system using wireless sensing devices
  8. 8. ATaRS could be provided through a service or performance-based contract, to eliminate many of the acquisition, installation, and maintenance problems by moving the burden from the Government to the supplier. Capabilities Automated Environme Flexibility Intrusion Raytheon 0”DoD Wireless ATaRS Mobile Auto- HERO Conclusion ATaRS ATaR The 0” Infrastructu Certificatio Monitoring Movement Inventory ntal I/A  Eliminati Flexibilit Capabili S ties is a Manageme Condition Compliant Tracking re re n HERO Standards-based wireless sensing mesh networks offer considerable advantages over current Nod on/redu flexible y Monitoring nt Certifica ction of legacy active RFID systems. They can be built with openly available COTS radios and sensors; they offer open interfaces making it easy to adapt and interface them to virtually any sensors or es– no tion enterp manual wide area communication systems, and to exchange information with industry standard XML and SOAP; a single mesh network can scale to many thousands of nodes, cover a very wide area, and autonomically self-manage and self-heal; they can operate reliably from inside sealed metallic containers without container modification or external antenna mounts; they emit low transmitted energy making them (HERO) safe to operate in close proximity to ordnance; they can securely decrypt and encrypt data using internationally accepted cryptographic methods; and they can operate off COTS AA batteries for many years. Through the use of intelligent software systems, ATaRS can deliver situational and actionable knowledge in near real-time. These capabilities are enablers. They allow military logisticians to rethink business processes to address emerging imperatives such as distance support and sea basing, and process improvement methods such as the theory of constraints. Working in concert with existing tracking systems and technologies, they will improve asset visibility, reduce inventory footprint, speed up repair part delivery and maintenance, monitor and predict high-value asset life expectancy, and pro-actively detect defective items, References Akyildiz, I.F., and Xudong Wang, 2005. A survey on wireless mesh networks. IEEE Communications Magazine, Volume 43, Issue 9, Sept. 2005 Page(s): S23 - S30. Robert Mueller is currently CEO, BNet Corporation; Vice Chairman, Phase IV Engineering; Director, Hawkeye Tracking; and Director, AMARCOR. Dr. Mueller has been a technical contributor or principal investigator for the Advanced Technology for Ordnance Surveillance (ATOS); USN Wireless Aviation Pack-up Kit; USMC Expeditionary Pack-up Kit; OSD UID Missile Tracking Project; NAVSUP Collaborative Logistics Productivity program; Raytheon’s Autonomic Tracking & Response system (ATaRS); and numerous SBIR projects related to RFID, wireless sensing, and real-time asset visibility. Dr. Mueller was formerly tenured Associate Professor of Computer Science at Colorado State University. He received the Ph.D. in Computer Science from the University of Colorado. Jon Boyd is Mission Support Manager for Air Warfare Systems at Raytheon Missile Systems in Tucson, Arizona. He also served as Support and Aircraft Integration Manager for the AGM-65 Maverick missile program. Prior to joining Raytheon, he served on active duty in the US Air Force for 22 years, retiring with the rank of lieutenant colonel as the Deputy Operations Group Commander, 355th Operations Group, 355th Wing, Davis Monthan AFB, AZ. Jon is a graduate of the University of SW Louisiana with a degree in psychology. He holds a Masters degree in aeronautical science from Embry Riddle University, and is an adjunct faculty member of the anthropology/archaeology department of Pima Community College.