SBIR Final MeetingCollaboration Sensor Grid

and Grids of Grids Information Management

Anabas

July 8, 2008

Introduction I• Grids and Cyberinfrastructure have emerged as key

technologies to support distributed activities that span scientific data gathering networks with commercial RFID or (GPS enabled) cell phone nets. This SBIR extends the Grid implementation of SaaS (Software as a Service) to SensaaS (Sensor as a service) with a scalable architecture consistent with commercial protocol standards and capabilities. The prototype demonstration supports layered sensor nets and an Earthquake science GPS analysis system with a Grid of Grids management environment that supports the inevitable system of systems that will be used in DoD’s GiG.

Introduction II• The final delivered software both demonstrates the concept

and provides a framework with which to extend both the supported sensors and core technology

• The SBIR team was led by Anabas which provided collaboration Grid and the expertise that developed SensaaS. Indiana University provided core technology and the Earthquake science application. Ball Aerospace integrated NetOps into the SensaaS framework and provided DoD relevant sensor application.

• Extensions to support the growing sophistication of layered sensor nets and evolving core technologies are proposed

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Close-out Charts

• Background

• Status

• Result of the SBIR

• Future research

• Commercialization

• Appendices

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BackgroundProblem Statement

• Unable to perform advanced research for multi-layered sensor Net-Centric infrastructure without an advanced, scalable grid framework that allows existing systems and new systems to interact and cooperate.

• Information and communication have played increasingly critical roles in our nation’s security

• Increase use of low cost sensors generate tremendous amount of valuable data that needs to be managed and harnessed

• Need rapid situation awareness to provide better intelligence to enable high quality decision support

• The GiG is not one global seamless construct– Different pieces have different stakeholders with different missions– Each has own name and unique vision of network-centric operations– Many operations have been done independently

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Background (cont’d)

Commercial Backdrop

• XaaS or X as a Service is dominant trend

• X = S: Software (applications) as a Service

• X = I: Infrastructure (data centers) as a Service

• X = P: Platform (distributed O/S) as a Service

• Grids are any collection of Services and manage distributed services or distributed collections of Services i.e. Grids to give Grids of Grids

• We added• X = C: Collections (Grids) as a Service and

• X = Sens: Sensors as a Service

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Background (cont’d)

Objectives

• Integrate Global Grid Technology with multi-layered sensor technology to provide a Collaboration Sensor Grid for Network-Centric Operations research to examine and derive warfighter requirements on the GIG.

• Build Net Centric Core Enterprise Services compatible with GGF/OGF and Industry.

• Add key additional services including advance collaboration services and those for sensors and GIS.

• Support Systems of Systems by federating Grids of Grids supporting a heterogeneous software production model allowing greater sustainability and choice of vendors.

• Build tool to allow easy construction of Grids of Grids.

• Demonstrate the capabilities through sensor-centric applications with situational awareness.

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Background (cont’d)

Approach

• Investigate and leverage global and open grid technologies.

• Design and implement a grid middleware based on a general Grids of Grids architecture with particular support for sensor-centric grid to produce a prototype collaboration sensor grid that could interoperate with other grids.

• Integrate and demonstrate with Ball NetOps to provide collaboration sensor grid situational awareness.

• Demonstrate for Earthquake Science applications.

• Use sensor grid for warfighter GIG research.

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Background (cont’d)

Challenges

• Adapt the technologies so that valid experiments and demonstrations of fundamental GIG infrastructure requirements can be realized.

• Follow the rapidly evolving best practice in commercial and academic Grid technologies and standards

• Discover derived requirements for intelligence exploitation, decision support and advanced collaboration on the GIG.

• Perforate multi-layered sensor stovepipes to enable GIG operations without re-factoring existing software.

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Background (cont’d)

Technologies

• Anabas Impromptu Collaboration Framework

• Indiana University NaradaBrokering Messaging System

• Ball Aerospace & Technology’s NetOps (Network Operations) Situational Awareness technology

• Sun Microsystems Java platform

• Haskell Programming Language (Ball)

• Low cost sensors (e.g. Wii Remote sensor, RFID reader and tags, GPS sensors, accelerometer, gyroscope, compass, ultrasonic, temperature, audio/video recorders, etc.)

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StatusSchedule

• The spiral development methodology of design, development, testing and re-factoring led to the completion of a demonstrable Grids of Grids architecture with a distributed Grid Builder management tool prototype that supports Collaborative Sensor-Centric Grid and User-defined Operation Pictures and Common Operating Pictures in June 2008.

Funding

• The SBIR Phase 2 project is completed within budget.

Publication

• Paper on this SBIR presented at CTS2008 and published in proceedingsGeoffrey Fox, Alex Ho, Rui Wang, Edward Chu and Isaac Kwan A Collaborative Sensor Grids Framework 2008 International Symposium on Collaborative Technologies and Systems (CTS 2008) at The Hyatt Regency Irvine , California, USA May 19-23, 2008

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Results of the SBIR

Key Software Systems and ModulesReady For Use

• An Enabling and Extensible Collaborative Sensor-Centric Grid Framework that supports UDOP/COP using SensaaS (Sensor as a Service).

• An API for third-party legacy or new applications to easily acquire grid situational awareness.

• An API for sensor developers to easily integrate sensors with collaboration sensor grid to enhancement situational awareness.

• A Grid Builder Management System to build, deployment, management, monitor sensor and general grids.

• Examples of integrating filter (compute) and collaboration grids with Sensor Grids in Grid of Grids scenario

• A NetOps Situational Awareness Sensor-Grid Demo Client. • An Impromptu Sensor-Grid Demo Client with support for UDOP and

Earthquake Science.

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Typical Sensor Grid Interface

Different UDOPs

Participants

Presentation Area

Sensors Available

Component Grids Integrated

• Sensor display and control– A sensor is a time-dependent stream of information with a

geo-spatial location.

– A static electronic entity is a broken sensor with a broken GPS! i.e. a sensor architecture applies to everything

• Filters for GPS and video analysis (Compute or Simulation Grids)

• Earthquake forecasting

• Collaboration Services

• NetOps Situational Awareness Service

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Sensor Layer

Meta Data Layer

Information Management Layer

Application Layer

Images RSS RFID Tags GPS

LocationLogicalGroups

SensorType

UserDefined

Properties

MessagingServices

SensorManagement

MilitaryApplications

LogisticsApplications

FinancialApplications

UDOP ArchitectureUser Defined Operation Picture

Edge Detection Filter on Video Sensors

QuakeSim Grid of Grids with RDAHMM Filter (Compute) Grid

Grid Builder Service Management Interface

Technology Evolution• During course of SBIR, there was substantial technology

evolution in especially mainstream commercial Grid applications• These evolved from (Globus) Grids to clouds allowing

enterprise data centers of 100x current scale• This would impact Grid components supporting background

data processing and simulation as these need not be distributed• However Sensors and their real time interpretation are naturally

distributed and need traditional Grid systems• Experience has simplified protocols and deprecated use of

some complex Web Service technologies

Results of the SBIR (cont’d)

Key Lessons Learned I

• Grid technology supports layered sensor networks with high performance using approximately MN/1000 brokers for M small (in terms of message size) sensors producing an average of N messages per second

• The Sensor Grid can be integrated with a collaborative decision support environment

• General filters can be defined as Grid services

• The Grid framework supports a broad definition of sensor that includes any device that receives and returns information; demonstrated devices include environmental sensors, GPS, RFID, Robot and Game controllers and audio/video devices

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Results of the SBIR (cont’d)

Key Lessons Learned II• The Sensor Grid can be integrated with the NetOps Network

Operations tool; this integration is possible through well defined service interfaces

• The SensaaS (Sensor as a Service) approach is successful allowing architectural integration of sensors in Grids with SaaS (Software as a Service) used for other capabilities

• We successfully followed the significant changes in commercial distributed middleware and correctly focused on key concepts (use of services and message oriented middleware) that are still central

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Results of the SBIR (cont’d)

Key Lessons Learned III

• We identified importance of hierarchical topics in the publish-subscribe infrastructure and implemented in core technology but not in Sensor Grid

• We were able to integrate portable VPN software to mitigate impact of firewalls and provide additional security; limitations in current open source VPN software prevented useful deployment in sensor Grid

• Sensor grids of similar architecture can support DoD layered sensors as well as non military applications such as Earthquake and Environmental sensor networks

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Results of the SBIR (cont’d)

Key Lessons Learned IV• Security model developed and tested in point to messaging with

modest overheads. However we did not tackle collective security for optimal support of layered sensors

• It is straightforward to integrate Geographical Information Systems including Google and Microsoft clients as well as OGC (Open Geospatial Consortium) services such as WFS Web Feature Service which we extended from batch to streaming mode

• Our current deployments do not have sufficient data traffic to stress our Grids, We have developed several performance enhancements for OGC services that could be important in future

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Results of the SBIR (cont’d)

Key Lessons Learned V• Two key enhancements developed for Impromptu

collaboration grid• 1) Collaborative groups supporting sub grids and communities

of interest• 2) Hybrid shared display allowing dynamic choice of codec to

be used when sharing applications• These technologies are described in Appendices

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Illustration of Hybrid Shared Display on the sharing of a browser window with a fast changing region.

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Screen capturing

Region finding

Video encoding SD screen data encoding

Network transmission (RTP) Network transmission (TCP)

Video Decoding (H.261) SD screen data decoding

Rendering Rendering

Screen display

HSD Flow

Presenter

Participants

Through NaradaBrokering

VSD CSD

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Future Research

• The Anabas Grid of Grids Net-centric framework prototype for building, deploying and managing general sub-grids has been developed with the successful delivery of an enabling collaborative sensor-centric grid middleware as a testbed to support the exploration and operational demonstration of the vision of Layered Sensing with robust collaboration and trust capabilities.

• The collaborative sensor-grid middleware enables easy integration with any systems or systems of systems on one end and extensibility of sensor and computational services on the other for flexible aggregation and collaboration of multi-dimensional global operational pictures and trustworthiness.

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Future Research (cont’d)Layered Sensor Grid (i.e. collections of sensors)

• Extend current point to point security model to support collections and layers of sensors

• Investigate collective trust algorithms and services that use cross validation to enhance trust and concatenate trust, reliability and other data from sensors. One important set of services involves a database of trust metrics (as a set of time series) linked to services to analyze them (say using Hidden Markov methods) to give an estimate of current trust and projected reliability i.e. future trust.

• Design and develop sensor management services that can be used to task coordinated groups of sensors. These would use Grid workflow for coordination.

• Exploit new hierarchical topics in secure messaging subsystem

• Integrate other related systems such as NetOps and XCAT with layered sensors as a particular Grid within the Grid of Grids.

• Investigate a Web 2.0 style interface for users to define layering and additional resources of interest for their UDOP

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Future Research (cont’d)

Trusted Sensing (at level of individual sensors)

• Work with AFRL on extending capabilities of existing sensors such as RFID, GPS, Lego Robot-based, Wii, Nokia N8xx, Web-cams. Explore addition of other generic (non military) types such as cell phones, RSS/Atom feeds, Blogs and Twitter.

• Work with AFRL on supporting new sensors and new trust mechanisms with associated services and metadata. Extend the Anabas sensor framework SensaaS as needed and support implementation of sensors in testbed. This work includes extension of capabilities of current sensors. We expect most work on individual sensors and their trust will be performed by others and our responsibility will be common collective services (number 2 in Layered Sensor Grid) and supporting the integration of this other work into Grid of Grids

• Identify new sensor related services of interest to AFRL; for example particular data fusion or analysis algorithms for sensor types of interest.

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Future Research (cont’d)Grid of Grids

• Investigate security architecture needed to support trusted sensor grid including cloud deployment. Deploy enhanced framework.

• Investigate fault tolerance architecture needed to support trusted sensor grid including cloud deployment. Deploy enhanced framework.

• Investigate systematic use of virtual machine technology (Xen, VMware) for Grid service deployment. This complements Grids that virtualize system by virtualizing hosting nodes and allow a more powerful Grid builder model. The performance implications would be initial research

• Research Cloud Implementations of Grid Components I: Extend Grid Builder to deploy Grid Components on Clouds – including Amazon EC2 and small NSF TeraGrid cloud available to us.

• Research Cloud Implementations of Grid Components II: Measure and evaluate performance impact of cloud – especially on messaging substrate. Look at impact of federated clouds with different components of a given Grid deployed on different clouds.

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Future Research (cont’d)

Grid of Grids

• Add high performance metadata service based on WS-Context to those supported by Grid Builder.

• Quantify with AFRL guidance the “timeliness” of systems i.e. the performance of system measured in a simulated environment with characteristics similar to that expected in DoD use. The initial task here is defining and implementing the simulated environment with realistic bandwidth and latency characteristics. Measuring impact of trust mechanisms on performance would be a focus.

• Develop an Intranet Web 2.0 annotation service allowing tagging of services and electronic resources developing a rich user customizable environment. This environment can be searched to retrieve services and documents of interest to user. Tags are stored as part of system metadata. The Grid Builder will deploy Grids based on discovered services and electronic resources. Provide a secure Facebook style user profile compatible with Open Social Interface.

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Future Research (cont’d)

Grid of Grids

• Deploy a small cloud attached to AFRL Testbed. This involves investigating various IaaS (Infrastructure as a Service) and PaaS (Platform as a Service) software environments and installing on a small 4-8 node cluster.

• Develop a report surveying sensor nets, webs and grids in other communities including commercial (e.g. Microsoft Ocean network, Nokia cell phone), government (e.g. Ubiquitous City project in Korea) and academic projects (as many NASA sensor web projects, personal health monitoring).

• Support AFRL with needed project reports and presentations.

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Commercialization

Three-prong strategy:

1. Work with Ball and AFRL to get input for DoD application requirements for an integrable Grid situational awareness product.

2. Harden SBIR result prototype to seek In-Q-Tel type of funding to commericalize and customize the prototype for Home Land Security applications.

3. Commercial mobile solution applications for social networks with large number of sensors like the iPhone or Google phone.

Appendix A:

Summary Description of Collaborative Senor-Centric Grid

Framework

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Collaborative Sensor-Centric Grid Framework is designed to enable easy

• development• deployment• management• real-time visualization• organization• presentation

of collaborative geo-coded sensor grid applications withUDOP/COP capabilities.

MotivationMaking accurate decisions in a stressful operationalenvironment involves many processes including butnot limited to

• collecting, decomposing, analyzing, • visualizing, organizing, sharing of information, and• deriving new information

UDOP - User-Defined Operational Pictures• Enables situational awareness and facilitates a user to easily choose, create, visualize and present decision-focused views of an operation or mission

COP – Common Operational Pictures• Enables sharing of situational awareness operational

pictures with relevant personnel

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Distributed Architecture for Data Access

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Sensor Layer

Meta Data Layer

Information Management Layer

Application Layer

Images RSS RFID Tags GPS

LocationLogicalGroups

SensorType

UserDefined

Properties

MessagingServices

SensorManagement

MilitaryApplications

LogisticsApplications

FinancialApplications

UDOP Architecture

Sensor-Centric Grid Middleware Management System (SCGMMS)

SCGMMS API allows application developers to retrieve sensor data and metadataabout sensors. The SCGMMS SSAL facilitates sensor developers to define sensormetadata for application-level filtering and expose sensor services to applications.

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• Defining the properties of sensors• Deploying sensors according to defined properties• Monitoring deployment status of sensors• Remote Management - Allow management irrespective of the location of the sensors• Distributed Management – Allow management irrespective of the location of the manager / user

Grid Builder (GB)

GB is a sensor management module which provides services for

ANABAS Grid Builder (GB)

• GB is originally designed for managing Grids of Grids.• GB is extended to support sensor-centric grid.• The Grid which GB manages is arranged hierarchically into multi-layer domains.• Each domain is typically a PC which manages local sensors.• Sensors can be deployed in any domain and accessible from any domains.

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Domains have some basic components

• Managers and Resources• Each resource is wrapped in a Service Adapter

• Bootstrapping Service• Ensures the current domains are up and running. • It periodically spawns a health check manager that checks the health of the system.

• Registry• All data about registered services and SA are stored in Registry. WS-Context is used for persistency. • Processes messages for managing SA and update SA status.