Patent Application
20120311614
This application is related to the Applicants and/or Assignees co-pending patent applications Attorney Docket Nos. 20080529.2, 20091113.2 and 2009117.1. The entire contents of each of these patent applications is incorporated herein by reference.
This disclosure relates to software platforms and architectures and in particular to platforms and architectures for use in a heterogeneous device environment.
There is an explosion of mobile and embedded devices throughout the consumer, commercial and government arenas. These devices have ever increasing processing power, data gathering power and data storage capacity. Additionally there is a growing need for advanced applications that are centered around the use case of a dynamic collection of people and devices, for some transient period of time, participated in a coordinate process, task, goal involving knowledge sharing. These types of application range from the DoD, DHS, and Commercial and Consumer worlds. The need for a software platform that enables a Distributed Knowledge Network is now very evident.
But there is currently no Distributed Knowledge Network platform to enable intelligent applications that span these heterogeneous networks and devices, underlying operating systems, software languages, and software protocols. This is not only true for simple client-server mobile environments, but also environments that involve peer-2-peer and peer-2-group communication.
There are no solutions that enable end-to-end Distributed Knowledge Networks and Intelligent Sensor Networks. There are platforms for client-server applications, and simple peer-2-peer networks, but there are no intelligent, unified pervasive platforms that allow for intelligent data gathering, synthesis, fusion and distribution over dynamic collections of heterogeneous devices.
Existing software platforms are either not pervasive enough or intelligent enough. By pervasive, it is meant that the platforms that do exist either are limited in the devices/operating systems they support, or the software languages they support, or the distributed protocols they support, or the messaging capabilities they support.
What is required is a system, method and/or architecture that meets these requirements.
In one aspect of the disclosure, there is provided a pervasive computing platform comprising a device API Abstraction layer configured to operate as an interface between one or more applications operating on a device and an operating platform of the device, the device API abstraction layer comprising a universal set of APIs.
In one aspect of the disclosure there is provided a method for providing a distributed knowledge network/intelligent sensor network. The method may comprise deploying a pervasive computer platform onto a plurality of devices, the pervasive computer platform comprising a device API abstraction layer comprising a universal set of APIs that enables agent software applications to execute on those devices irrespective of the parameters of the device. One or more agent software applications may be deployed to one or more of the plurality of devices which executes the deployed agent software application.
In one aspect of the disclosure, there is provided a device comprising at least one processor and at least one memory operatively associated with the at least one processor, the at least one memory storing a universal set of APIs that provides a hardware-independent agent software abstraction layer for one or more sensor capabilities of the device.
Reference will now be made, by way of example only, to specific embodiments and to the accompanying drawings in which:
The embodiments, modules and examples described below are intended to demonstrate the components and capabilities of a single pervasive platform, that is a one-stop-shopping for enterprise, mobile and embedded servers/devices support for capabilities needed to build advanced applications that span networks, devices and enterprises. These applications can be broadly categorized as Distributed Knowledge Networks and Intelligent Sensor Networks.
Normally a developer would have to go through the arduous task of integrating “n” software products and platforms to create such a platform, where “n” is a very significant number and is growing constantly. Currently, there is no single platform that through a set of Universal API's, brings them together in a platform that extends from the sensor to the cloud, and every major device type in-between.
This single pervasive platform enables plug-n-play technologies, be they geared for the enterprise, mobile or embedded space. An intelligent, distributed computing platform that can provide these capabilities, will be the superhighway for software engineers to leverage in creating the next generation of applications.
Software architects and engineers will have the flexibility to freely develop dynamic, intelligent, and decentralized applications in their language of choice, on the devices and servers they need to target, whether the device/node is a mainframe, desktop, PDA, Smartphone, RFID reader, camera, or embedded sensor.
By utilizing such a platform, developers will have at their disposal a choice of wireless networks, distributed protocols, and decentralized and centralized messaging capabilities to leverage in creating the ad-hoc and distributed social, knowledge, and problem-solving networks of tomorrow.
Utilizing rules engines such as RETE-based rules engine integrated within this next generation platform, engineers can create artificial intelligence and cognitive capabilities into Mobile 2.0 software agents residing on all targeted devices and servers. Engineers will be able to produce applications that provide real-time intelligence, situational awareness, and coordination at the edge not found today.
Enterprise software stacks, like software languages, continue to be born, but “old” ones never go away. J2EE and .NET architectures and related languages dominate, but CORBA and Mainframe systems and their associated languages, are still prevalent within many of these same organizations.
A distributed knowledge network (DKN) and Intelligent Sensor Network (ISN) offers new capabilities for more intelligent, more interoperable and more distributed processes for information gathering, data filter/analysis, information dissemination, and collaboration that ultimately results in faster and more efficient decision making in mobile, widely distributed, heterogeneous environments. These environments span many device types and wired and wireless networks.
These DKNs/ISNs may be developed on the proposed software platform, described below, that allows for decentralized, intelligent, mobile, high-performance, transaction-based applications. The proposed pervasive platform will seamlessly interoperate with the hardware and software technologies of today to pave the way for next-generation solutions for commercial, government, and consumer development. The resulting applications will provide quantum leaps in real-time intelligence capabilities and coordination among widely distributed groups, as well as offer greatly increased productivity and cost savings. In this paradigm, data may be gathered on edge devices, rapidly turned into actionable knowledge, and distributed efficiently to ad hoc, possibly dynamically assembled groups of interested participants, devices, and enterprise systems.
Mobile software components (agents) residing on these edge devices may continuously learn from the data they get and interpret. This can cause them to respond differently and possibly assemble and communicate with an ever-changing audience, forming a distributed knowledge-sharing network.
Software agent-based technologies allow for complex or large software processes to be broken down into smaller components that can be mobilized and reused to enable dynamic decision distribution and integration capabilities via an intelligent software abstraction layer. Data can be analyzed at the source or point of input to the network and prioritized and distributed in an automated process to appropriate consumers of the information on the network. The information consumers can potentially be sensors, smartphones, PDAs, MIDs, UMPCs, Laptops, and an extremely wide array of wireless and embedded devices and systems.
The agent-based distributed knowledge network (DKN) and Intelligent Sensor Network (ISN) will provide the key enabling technologies for translating recent advances in automated data acquisition, digital storage, computers and communications into fundamental advances supporting data Filter/Analysis, dynamic process management, dynamic integration and collaboration for advanced enterprise, consumer, and government applications.
Intelligent mobile agent technology, utilizing dynamically loadable and mobile rule-sets, provides the intelligence behind the framework in the design and implementation of a DKN/ISN. Agent-based peer-2-peer peer-2-group and peer-2-enterprise system architecture provides the framework for varied, no-single-point-of failure, interconnection of computer “nodes”. Using agent-based rule-sets to encapsulate logical processes or algorithms, programmable rules or processes can then be delivered to processing nodes that range from large computer servers to mobile phones and wireless sensors.
In order to implement these new applications, including a DKN/ISN, there is required a next-generation pervasive software platform that can operate seamlessly in the complex, widely distributed environment we find today. One aspect of such is software agent technology that will provide the mobility infrastructure for process mobility, code mobility, rule-set mobility and remote communications.
A true pervasive software platform that forms the foundation of a Distributed Knowledge Network will have extensive support for all devices, their operating systems and platforms, networks, distributed protocols, supported software languages and messaging capabilities. By devices and underlying operating systems, it is meant those that power everything from servers to mobile and embedded devices. By software languages it is meant that the pervasive platform will support prominent languages such as Java, .NET, C++ and other appropriate language as well as scripting languages such as JavaScript, ActionScript, PHP and Ruby. By distributed protocols, it is meant that the pervasive software platform can host Distributed Knowledge Networks via, e.g. Binary XML, SOAP, XML-RPC, IIOP and RMI. And by messaging, it is meant device-to-device (a.k.a peer-2-peer), device-to-device-group (a.k.a peer-2-group) or device-2-enterprise (peer-2-enterprise). Additionally this messaging will be via common and prominent standardized messaging protocols, be it IPv4/IPv6 based (TCP/IP, UDP, JMS, MSMQ, DDS) or not (Bluetooth, Zigbee, Near Field Communication).
The Distributed Knowledge Network (DKN) may be built using an intelligent agent platform that runs devices ranging from servers, to laptops, PDAs, smartphones, Mobile Internet Devices, UItra Mobile PCs, and sensors. Specifically, the DKN System provides:
A true pervasive, peer-to-peer application will be able to run, in some form, on all devices ranging from smartphones, routers, MIDs, UMPCs, Netbooks, VoIP phones, sensors, and those found in, or coming soon, to automobiles and remote controlled machines, to name a few. To do so, its software platform will run natively on these same devices. Software agents comprising these applications, also need to be able to run in the popular mobile/embedded software stacks, such as Java's Micro Edition, Android, Microsoft's Compact Framework, and OSGI Containers, on a wide range of mobile/embedded operating systems such as iPhone, Blackberry, Windows Mobile, Symbian, BREW, and Embedded Linux versions (Android, LIMO, Maemo, etc.) to name just a few. All of which will facilitate these pervasive services to function within smartphones, routers, MIDs, UMPCs, VoIP Phones, Telepresence, sensors, automobiles, bus stops, smart meters, and other ICT connected participatory nodes.
Depicted in
The architecture 10 includes a device API Abstraction layer 11 that provides an abstraction of at least the most common and prominent engines for each relevant capability. Specific APIs include a messaging API 12, security API 13, discovery API 14 (e.g. white pages and yellow pages), transaction API 15, universal user interface API 16, ontology API 17, database API 18, rules API 19 and PIM API 111. The API Abstraction layer operates between a network layer 112, representing the most common type of wired and wireless networks (a.k.a. Networks), and an operating platform layer 113 which represents the most common Operating Systems and software platforms (Operating Systems/Platforms).
A) Dynamic, Decentralized and Centralized Messaging Capability via Messaging API 12
The proposed pervasive platform 10 will enable communication and sharing of application data, between groups of devices/systems without the need of a centralized messaging server. It will support the creation of ad-hoc communities of devices or nodes, as well as the ability to support filtering of application messages across these communities. Support will exist for devices joining and leaving the network, which will result in changing “internet” addresses. Integration with a SIP/IMS Server is one way to provide dynamic IP support along with voice, data, and chat support over IP. The platform will also support passing messages over standard centralized messaging servers for integration with enterprise and legacy systems. More specifically, there needs to be seamless integration with Microsoft's Message Queue (MSMQ), Java's Message Server (JMS) and Object Management Group's (OMG) Data Description Service (DDS), etc.
The messaging capability may be achieved by a Pervasive Software Platform Universal Peer-2-Peer Messaging Sub-Module 12 which is described in further detail below.
B) Network Scalability, Survivability and Discovery Capability via Discovery API 14
The proposed pervasive platform 10 will enable filtering and analyzing of data processing at the source to minimize network traffic, handle unreliable and/or limited network connections, and adjust to hardware failures or CPU load. Therefore, these devices will be able to persist data via a micro relational or objects database. Additionally, the software components or agents running on edge devices need to support multiple wireless protocols (GSM, CDMA, Wi-Fi, UWB, Bluetooth, NFC, RFID, 4G/WiMax/LTE, etc.) and associated networks (Telco, Wide Area, Local, Personal, etc.). Ideally, they will dynamically reconfigure themselves to use a communication protocol that best matches the capabilities of their current network connection and the current node(s) they are in communication with. These capabilities may be provided by Universal Core Request Brokering Sub-Modules such as a Universal Transport Interface, universal Serialization interface and Universal Distributed Protocol/Remote Interface, each of which will be described in more detail below.
C) Mobile SOA Architecture Capability
The proposed pervasive platform will also provide an enhanced Service-Oriented Architecture (SOA) that supports services running on mobile and embedded devices. In other words, any device will be able to host and access services. These services will be accessible in a decentralized fashion directly to agents, exposed as services, that are running on edge and wireless devices. The distributed agents will act more as providers of services and facilitators of exchanges and transactions versus a traditional client/server central provisioning approach. The location of intelligent agents/services and the Mobile Web Services they expose will be irrelevant to the client or target device. Finally, all agents/services need to be accessible by a Service Description in adaptive directories, ideally ones with Universal Description, Discovery, and Integration (UDDI) compliance. Finally, these services will be discoverable over SIP/IMS registries as well, along with network based discovery techniques for advanced abilities to compose and provision services across the layers. These capabilities may be provided by a Universal White Pages and Yellow Pages sub-modules 14, an Intelligent Agent software platform and a Universal Agent sub-module
D) Configurable, Adaptable Security Framework via Security API 13
In a ubiquitously networked world, it will often be necessary to maintain data on edge devices. The security concerns facing enterprises today will need to incorporate solutions that extend to a collaborative environment. The proposed pervasive software platform will provide a high level of security to ensure privacy and protection from rogue/viral clients and software agents. This will involve security agents and agent managers that provide capabilities above and beyond the current encryption, authentication, and authorization that are currently employed in today's centralized client server applications.
As with every capability within the pervasive platform, the security capability 13 needs to be configurable and pluggable, to allow for adaptable and custom security features specific to the date and/or services being hosted on any particular node. For example, encryption, authentication, and authorization around peer-to-peer and peer-to-group application/event exchanges will all have pluggable security capabilities that tap into the various security services from networks, to clouds, to applications, and so forth.
E) Universal Platform/Services—.NET/Java/C++/JS from Clouds to Sensors
Advanced pervasive applications cannot be limited to a single development environment and programming language. Furthermore, the same API will be provided to .NET, Java, C/C++ and JavaScript developers. The platform will support a common set of collections and algorithms across these languages as well. This would greatly increase programmer productivity and allow developers from all camps to easily work together and share software. The platform will seamlessly integrate with .NET, JEE and legacy (MVS, CORBA, etc.) enterprise systems and services, and any combination thereof, in either a traditional Web Services architecture, or in a high performance manner using binary protocols. Pervasive applications may need to communicate with more than one enterprise/organization or governmental entity.
With the advent of Software-As-A-Service (SAAS) and Infrastructure-As-A-Service (IAAS) based cloud computing, there will be an evolving need for inter-cloud interoperability. This holds especially true since companies, organizations and governments are adopting cloud computing at every level. Protocol standards are being debated here, and likely will never be universally agreed upon. This all furthers leads to the need for pluggable protocol architecture since different nodes, systems, clouds and devices will need to communicate using different protocols, at different times, for different reasons.
The platform needs to extend from the fore-mentioned enterprise, desktop and mobile/embedded environments down to the very nodes, sensors, and devices. This paves the way of providing Distributed Knowledge Networks (DKN) that extend to and integrates with Intelligent Sensor Networks (ISN).
The ISN will provide sensor instrumentation architecture with rules-based software agents that will provide self-monitoring, self-healing, non-intrusive data transfer methods. The architecture will also describe data routing, multi level security and delivery rules for node collaboration on networks. These robust ISNs will have the capability to reconfigure; self-heal/organize, and adjust to changing data needs and network node availability dynamically as an event evolves. They will do so by leveraging peer-to-peer and peer-to-group communication with like sensors nodes as well as more robust mobile and embedded devices. Logic to filter and analyze data, and distribution of more refined information the data, will occur where/whenever sufficient processing power and energy sources allow.
F) Location and PIM Peer-to-Peer and Peer-to-Group Services Module via PIM API 111
To enable location-aware, community-based, collaborative applications, the proposed pervasive platform will provide location and PIM services that allows determination of any node's location from any other node, as well as sharing of such information as contacts, calendaring, tasks and files (audio, video, photo, etc.). These services will form the building blocks of many ad-hoc, community-based applications. These APIs will be compliant with standards, such as BONDI, and be consistent across all platforms, languages and devices, and will be accessible by both peer-to-peer based messaging, peer-to-group messaging across dynamic communities and of course peer-to-enterprise/cloud for integration with enterprise systems, SAAS and IIAS clouds. In one embodiment, these capabilities may be provided by a Universal Location and PIM Sub-Module 29.
G) Universal UI API Module 16
The proposed pervasive platform will also provide a Universal UI API 16, to compliment its Universal API's for discovering, accessing and hosting services and data across all devices. Considered nearly an impossible task, technology has been described in the Applicant's co-pending patent application Attorney Docket No. 20091117.1, referenced above, to make this feasible in a standards-compliant, truly ubiquitous manner. More specifically, WebKit (based on HTML 5 and JavaScript 1.5) is becoming very prevalent on desktops and mobile devices. Android/Chrome, Apple/iPhone/Safari, Symbian/QT all have WebKit support within their corresponding platform's SDK via their own APIs and RIM have a similar platform under development. So WebKit and Microsoft's Silverlight seem to be poised to be the two dominant “web engines” across all devices. A Universal UI Interface that can communicate with WebKit and Silverlight, would allow developers to have their application process layer communicate with a JS/HTML presentation layer, all utilizing a single set of APIs.
H) Transactional on Edge Devices and Ad-Hoc Communities Capability
The proposed pervasive platform will extend transactions from the enterprise to edge devices, allowing for distributed, but coordinated tasks and information sharing and collaborative communications among peers, peer groups, enterprise, cloud, and federated clouds. Support will be provided to allow for intelligent agents/services running on the edge to participate in guaranteed service, message, and communication delivery either via an enterprise pub-sub JMS/MSMQ-like capability described above, or with XA-compliant enterprise transaction managers such as those provided in .NET's Microsoft Transaction Service (MTS), Java's Transaction Service (JTS), and OMG's Object Transaction Service (OTS).
I) Embedded and Enterprise Database Integration and Synchronization Module 18
This advanced platform will provide a simple way to access databases, regardless of the type of database—whether it is a relational, object, XML or a multi-user enterprise database or single-user embedded. Developers need to be shielded from the intricacies that exist with these various flavors and have support for data synchronization between a mobile/embedded device, the communities of devices it belongs to, and enterprise systems such as Software and Infrastructure-As-A-Service (SAAS, IAAS) Clouds. By providing this level of abstraction, pervasive applications built using this platform will be able to leverage the high-performance, highly distributed databases being developed for advanced, high-speed full-text searches that are making their way into non-traditional environments such as smartphones and routers.
J) Artificially Intelligent, Cognitive Edge Processing Module
A next-generation application will need to utilize intelligent software agents/services that can gather data, respond quickly based on this data as it changes, produce and distribute knowledge, and even initiate other agent/service activities on another device or group thereof. The underlying rules engine will be easy to use, provide very high performance against potentially large rule sets, and will be available in multiple languages. These agents will also be able to understand different ontologies as a powerful abstraction to the modeling of knowledge about different domains. This is accomplished by utilizing the Agents 110, Rules 19 and Ontology 17 API modules depicted in
K) Support for Complex Event Processing (CEP)
The proposed pervasive platform with the capabilities described has the ability to filter and analyze data on any node and distribute resulting universal business/data to any other node, or interested groups of nodes regardless of their location and software platform.
The data will often originate from a wide range of sources often from sensory/mobile/embedded devices. The filtering, analyzing and distribution of information/events will first occur as close to the sensory/mobile/embedded device as possible (ideally on it). Such is the basis of the aforementioned ISN.
Additionally, the proposed pervasive platform will support dynamic groups that represent connected and/or hierarchical analysis/decision support/collaboration groups. Each level of groups analyzes micro events in determining relevant, increasingly coarsely grained, macro events leading to additional data/event filtering, analyzing, collaboration, response and also for determining the routing of that information to enterprise systems/clouds (governments, corporations, research institutions, trading floors, health organizations, etc.).
This results in the transformation of sensory data to knowledge (DKN) and ultimately to situational awareness and actionable knowledge in real-time or near real-time (CEP). The data traversing this ISN/DKN/CEP needs to be able to navigate firewalls, support (NAT), and be transportable to communities of disparate devices applications, systems and clouds that have expressed interest in receiving such data.
Every aspect of the platform's flexibility and support for heterogeneous the nodes, protocols, networks, messaging and discovery capabilities is fully leveraged in such a scenario.
Currently, the process of recording limitless sets of data from sensors, weapons, and communication and intelligence systems results in enormous unique data sets requiring extensive data Filter/Analysis to derive conclusions. The technology of this proposal will provide the logistics community with a network centric communications capability leading to the establishment of a Distributed Knowledge Network, which can operate with any combination of sensors/nodes/participants at various security and need to know levels of information exchange. The use of intelligent mobile agents can move the conduct of multi-service or joint network centric logistics planning into a new level of capability allowing the commander to have real-time knowledge of logistics information during the course of any operation. The two main areas of investigation proposed are providing Synthetic Instrumentation and Self-describing Smart Sensors via Intelligent Mobile Agent Architectures and Intelligent Software Agents and Distributed Knowledge Networks.
Using an agent-based architecture provides a solid solution capable of being deployed on any industry computing domains (including those with multi-level security and need-to-know domains). Typical uses for agent-based computing techniques are:
Recent advances in sensors and instrumentation systems with high throughput data, and digital information storage technologies, have made it possible to acquire, analyze and store large volumes of data in digital form. Advances in computers, communications, Internet, and mobile computing have made it possible to have large volumes of data, Filter/Analysis and decision support tools residing on multiple, geographically distributed, heterogeneous, hardware and software platforms around the globe. However, leveraging the advances in our ability to acquire, store, and analyze into gains in understanding and knowledge requires sophisticated tools for information retrieval, knowledge discovery, and distributed Filter/Analysis solving and decision-making in multi-level security and need-to-know environments.
Rapid and constant changes in hardware and software technologies related to tracking systems, monitoring devices, sensors, and other situational awareness tools requires a Data and Service Delivery Platform that provides a flexible, standards based data communication and integration system. Because of the increasing data entry points into the systems and the networks, this platform will require a capability to easily distribute analytical software code or task-based software objects to the data entry points of the systems or networks to effectively sort and analyze data at the source and then communicate more mature or specific knowledge across the systems or networks to lower network bandwidth utilization and route and deliver detailed data or actionable knowledge to enable more effective consumption of the data by appropriate systems, applications or users.
With the users entering data from various locations, this platform requires the ability to distribute the analytical or task-based software objects to the point of origin. By co-locating at the source, the software can perform initial sort and data Filter/Analysis required to refine the data set. The refining of the data before transmission results in lower network bandwidth utilization and more effective routing to the appropriate systems and/or users for action.
In order to lower life cycle management and technology upgrade costs, the data and service delivery platform will require the capability to distribute software updates dynamically (at different security levels) without disrupting the system. To efficiently distribute large volumes of data across a distributed network requires the capability to propagate messages across a connection of node “communities” or “spaces” that will increase speed and performance proportional to the number of nodes—in a sense creating a network of networks that scales dynamically.
Unique Capability Requirements:
A Distributed Knowledge Network (DKN) including Intelligent Software Agents (ISAs) is a technical architecture and distributed Filter/Analysis capability that will provide some of the key enabling technologies for translating recent advances in automated data acquisition, digital storage, computers and communications into fundamental advances supporting data Filter/Analysis, collaborative reviews and related applications
An ISA is a named object which contains software code, a persistent state, data and a set of attributes (requirements, history, authentication keys, etc.) and can move from one device or system as needed for accomplishing its tasks. Mobile agents provide an efficient framework for performing distributed computation at locations where the relevant data is available instead of expensive shipping of large volumes of data across the network. Most software agent designs consist of at least three components: agent servers, agent interfaces, and agent brokers (service directory). Agent servers support basic agent migration mechanisms, authentication, and sometimes provide other services. Agent brokers provide addresses of agent servers and support mechanisms for uniquely naming agents and agent servers. The agent interface is used by application programs to create and interact with agents.
ISA architecture is a valuable strategy due to the ability to:
The agent performs its task and saves any results until its connection to the user is re-established. Mobile agents provide a reliable transport between a client and server without necessitating a reliable underlying communications medium.
Intelligent Software Agents & Knowledge Network Concepts
An Agent is software that assists with tasks and acts on behalf of the initiator. Agents are typically: goal-driven, reactive, social, adaptive and mobile. Agents have one or more of these characteristics:
The many features of a robust, intelligent, self-managing agent platform and the various types of agents provide for a very powerful, non-obtrusive, monitoring, healing and problem-solving capability. Specifically, the more challenging and diverse an environment is, the more an intelligent, agent-based approach will be considered. Next-generation solutions for mobile applications will provide a high level of security to ensure privacy, and protection from rogue/viral processes. This is most effectively accomplished via security software agents and agent managers that provide capabilities above and beyond the current encryption, authentication and authorization that are currently employed in today's centralized client server applications.
Intelligent software agents can reside on any heterogeneous device or node such as sensors, readers, cameras, PDA's, smart phones, desktops, laptops, tablets, servers and mainframes. Additionally they can execute effectively within any software architecture from thick and thin client-server applications to widely decentralized applications or DKNs. More specifically, at any point in time a node will be acting as a client or server. Briefly multi-level, role-based security is often accomplished as follows:
The innovative capabilities of a DKN will enhance advances in scientific research and military operational test and training applications (e.g., intelligence data handling, situation assessment, command and control, network centric warfare). DKNs will significantly reduce the total ownership costs of new weapon systems while enhancing force readiness in a non-intrusive manner. There is also opportunity in many other areas for enhancement and improvement of information retrieval, knowledge discovery, and distributed Filter/Analysis for problem solving and decision-making. The proposed technology and design can improve crisis management and communications infrastructure, which offer numerous scenarios that require reactive as well as proactive decision-making, often under tight time, resource, and performance constraints to accomplish the desired objectives.
A software platform with the described pervasive features and inherit Distributed Knowledge Network and Intelligent Sensor network capabilities brings revolutionary capabilities and ease of use to today's application architects. It gives them maximum flexibility to develop dynamic, intelligent, and decentralized applications in .NET, Java and C++ on the devices and servers they need to target. Additionally, the extensive protocol support—in combination with its multi-language support and SOA—allows the intelligent mobile agents in these applications to access systems written in any language. They can also be accessed by systems written in any language in a variety of ways and messaging techniques, be they centralized or decentralized. By leveraging the AI rules integration and the pervasive mobile agents residing on any and all targeted devices and servers, organizations could create applications that provide real-time intelligence, coordination, and capabilities not found today.
There is great deal of momentum behind enterprises moving toward the .NET architecture, but there's a lot of Java, CORBA, and mainframe systems in many of these same organizations.
A very similar situation exists in the device world. Android is gaining speed and acceptance among device makers, but devices running iPhone, Symbian, embedded Linux (LiMo and Meego), Windows Mobile and PalmOS will likely always exist. This unifying platform will allow next-generation applications to exist seamlessly in this diverse software environment and the increasingly diverse wired and wireless networks they are running on.
This platform would provide the capability to create a new set of applications that are distributed knowledge and problem-solving networks with dynamic and ad hoc participants using different devices and enterprise software systems. It's not hard to see where this could be of great benefit in the domains of disaster recovery, terrorist response, and homeland security to name only a select few applicable areas in the government. In the commercial arena, the energy, transportation, insurance, education, telecom, healthcare, and finance industries are obvious verticals that could create vast new opportunities with such a platform. Indeed there's not a vertical in the commercial, government, or consumer arena that could not create revolutionary new capabilities with such a platform to leverage and use.
Further details of applications and code generation for the pervasive platform are described in the Applicant's co-pending patent application Attorney Docket No. 20080529.2, referenced above.
By universal, it is meant that the system caters for the world's common and prominent devices, networks, operating systems, software languages, software protocols etc. Being universal allows the platform to implement applications on the world's major servers, desktop/laptops, MID/UMPC/Netbook/Tablets, smart-phones, embedded and smart-sensor operating systems, etc.
Pervasive Software Platform Universal Core Request Brokering Sub-Modules
A) Pervasive Software Platform Universal Transport Interface
A Transport Interface 21 that allows for communicating via multiple transports both IP-based (TCP-IP, UDP, JMS, MSMQ) and non-IP based (Bluetooth, Zigbee, NFC). A specific implementation is determined via the Peer-2-Peer 23 and Peer-2-Group 24 messaging APIs. The Pervasive Platform determines which underlying network protocol to utilize based on rules that weigh performance, cpu utilization, network bandwidth, etc. Peer-2-Peer and Peer-2-Group messaging can occur over multiple transports within the same application.
B) Pervasive Software Platform Universal Serialization Interface
A Serialization Interface 24 that allows for communicating via multiple data serialization standards (Binary Objects, XML, JSON, XMPP) to be supported within various the payloads of various distributed protocols. A specific serialization is determined via the Peer-2-Peer and Peer-2-Group messaging APIs 22, 23. The Pervasive Platform decides on what serialization implementation to use, based on a similar ruleset which weighs performance, cpu utilization, network bandwidth, network connectivity support.
So within the same application, Peer-2-Peer and Peer-2-Group messaging can occur over multiple transports and multiple payload serialization protocols.
C) Pervasive Software Platform Universal Dist. Protocol/Remote Interface
A Distributed Protocol Interface 25 that allows for communicating via multiple distributed protocols standards (VRMP, SOAP, XMPP, etc), in a Peer-2-Peer and Peer-2-Group manner. A specific distributed protocol is determined via the Peer-2-Peer and Peer-2-Group APIs 22, 23. So within the same application, Peer-2-Peer and Peer-2-Group messaging can occur using multiple distributed protocols, those in turn use multiple payload serialization standards, while running over various transports.
Features and functions of the Pervasive Software Platform Universal Peer-2-Peer Messaging Sub-Module 22 include
Implicit:
Explicit:
The Peer-2-Peer Messaging sub-module 22 manages changing and multiple addresses on both the “client” node and the “server node”. The addresses may be based on IP, Zigbee, Near Field Communication or Bluetooth protocols/addressing/identification.
Features and functions of the Pervasive Software Platform Universal Peer-2-Group Messaging Sub-Module 23 include:
Multicast Messaging:
Publish and Subscribe:
The Universal Pub-Sub API may include the following interface.
1) An Interface which Allows You to Publish/Subscribe to data by Topic:
2) A Callback Interface which Allows You to Receive Messages:
There is Pub-Sub Messaging Factory, which loads an instance of the appropriate class that implements the above Pub-Sub interface; based on the platform the application is running on and configuration settings describing the type of publish and subscribe messaging capability desirable on such a platform.
The implementation class is exposed as a remotely accessible object via the first interface described above. The object is bound to the Universal Directory, with a well-known name. From that point on the local application simply communicates with the Universal Pub-Sub Messaging interface described above. Remote nodes can communicate with the remotely accessible interface, by discovering it via the Universal Directory, based on its well-known name.
Pervasive Software Platform Universal White Pages Sub-Module
The Universal White Pages API 26 is a White Pages Interface that allows for discovering services by name. A specific implementation is utilized via a configuration file and implementations can be centralized, decentralized, persistent or transient. Implementations can utilize “Naming Servers” from Enterprise Software stacks such as CORBA's Naming Service (CosNaming), JEE's Java Naming and Directory Interface (JNDI), Lightweight Directory Access Protocol (LDAP) or .NET's Windows Communication Foundation (WCF)
The white pages API 26 may be created by an abstraction of the API's that are out there for the different types of White Pages (Service discovery by name) implementations outlined. Implementations of that interface can then be created that can communicate with the most common commercial and open-source implementations of White Pages.
The Universal White Pages API consists of the following interface.
1) An Interface which Allows You to Access or Register a Service by Name:
There is White Pages Factory, which loads an instance of the appropriate class that implements the above interface; based on the platform the application is running on and configuration settings that describe the type of white pages desirable on such a platform. The implementation class is exposed as a remotely accessible object via the first interface described above. The object is bound to the Universal Directory, with a well-known name. From that point on the local application simply communicates with the Universal White Pages interface described above. Remote nodes can communicate with the remotely accessible interface, by discovering it via the Universal Directory, based on its well-known name.
Pervasive Software Platform Universal Yellow Pages Sub-Module
There is a Yellow Pages Interface 27 that allows for discovering services by description. Implementations can be centralized, decentralized, persistent or transient. Implementations can utilize “Yellow Pages Servers” such as UDDI, IMS, CORBA Trading Service, WS-Discovery etc.
The yellow pages API 27 may be created by creating an abstraction of the API's that are out there for at least the common and prominent types of Yellow Pages (Service discovery by description) implementations outlined. Implementation of that interface can then be created that can communicate with the most common commercial and open-source implementations of Yellow Pages.
The Universal Yellow Pages API may include the following interface.
1) An Interface which Allows You to Access or Register a Service by Name:
There is Yellow Pages Factory, which loads an instance of the appropriate class that implements the above interface; based on the platform the application is running on and configuration settings describing the type of yellow pages desirable on such a platform. The implementation class is exposed as a remotely accessible object via the first interface described above. The object is bound to the Universal Directory, with a well-known name. From that point on the local application simply communicates with the Universal Yellow Pages interface described above. Remote nodes can communicate with the remotely accessible interface, by discovering it via the Universal Directory, based on its well-known name.
Pervasive Software Platform Universal User Interface Sub-Module
A UI API that allows for communicating bi-directionally with the platforms underlying web-engine (WebKit, IE/Silverlight etc) via JavaScript and support HTML 5. The UI API 28 allows for Bi-directional communication between Application Process Layer and Presentation Layer utilizing Universal API's of the Pervasive Computing Platform 20.
A specific implementation is utilized via a configuration file and is typically dictated by the underlying Native Platform (e.g. Android, iPhone, Windows etc). The UI API 28 may be created from an abstraction of the Web-engine-based API's that are out there for the different types of device/platforms outlines. Implementations of that interface can then be created that can communicate with the most common commercial and open-source implementations of those web-engines.
This User Interface API may also be made to be remotely accessible to other devices on the network. The result is remote devices can access and/or update the presentation layer of the application running on a given device. This is accomplished by using the Pervasive Software Platform Universal Peer-2-Peer Messaging Sub-Module 22 and Pervasive Software Platform Universal Peer-2-Group Messaging Sub-Module 23.
The Universal UI Interface may include the following two interfaces.
1) A Remotely Accessible Interface, which Represents the Type of Actions that can be Done to Render or Access a User Interface's State
2) A Locally Accessible Interface, which Represents Additional Actions that are Needed to Interact with the Underlying User Interface Engine
There is Universal UI Factory, which loads an instance of the appropriate class that implements the above interfaces; based on the platform the application is running on. The implementation class is exposed as a remotely accessible object via the first interface described above. The object is bound to the Universal White Pages, with a well-known name. From that point on the local application simply communicates with the Universal UI interface described above. Remote nodes can communicate with the remotely accessible interface, by discovering it via the Universal White Pages, based on its well-known name.
Pervasive Software Platform Universal Database API
A Universal Database Interface that allows for persisting to a wide array of databases is shown in
A specific implementation is utilized via a configuration file. Implementations can be relational, object, object-relational, XML etc. These databases may exist in the enterprise, mobile and/or embedded environments.
The Universal Database API may be created from an abstraction of the API's that are out there for the different types of databases outlined. Implementations of that interface can then be created that can communicate with the most common commercial and open-source implementations of databases.
This Database API may also be made to be remotely accessible to other devices on the network. The result is remote devices can access and/or update data on a given device. This is accomplished by using the Pervasive Software Platform Universal Peer-2-Peer Messaging Sub-Module 22 and Pervasive Software Platform Universal Peer-2-Group Messaging Sub-Module 23.
The Universal UI Database may include:
1) An Interface, (UniversaIDBAction) which represents the type of actions that can be done on a database:
There is Database Factory, which loads an instance of the appropriate class that implements the above interfaces; based on the platform the application is running on and configuration settings describing the desired database type. The implementation class is exposed as a remotely accessible object via the first interface described above. The object is bound to the Universal White Pages, with a well-known name. From that point on the local application simply communicates with the Universal Database interface described above. Remote nodes can communicate with the remotely accessible interface, by discovering it via the Universal White Pages, based on its well-known name.
Pervasive Software Platform Universal Location and PIM Sub-Module
A universal Location and PIM Sub-Module 15 is depicted in
These API's may also be made to be remotely accessible to other devices on the network. This allows for remote devices to access location information and retrieve/update PIM data on other devices. This is accomplished by using the Pervasive Software Platform Universal Peer-2-Peer Messaging Sub-Module 22 and Pervasive Software Platform Universal Peer-2-Group Messaging Sub-Module 23.
The sub-module 15 may be created by first creating an abstraction of the API's that are out there for the different types of Location APIs available on the most popular platforms/devices. Implementations of that interface can then be created that can communicate with the most common commercial and open-source Location determination implementations.
The Universal PIM Interface may include:
1) A Contact Interface, which represents the type of actions that can be done on a Contact:
2) A Calendar Interface, which represents the type of actions that can be done on a Calendar Event:
3) A Task Interface, which represents the type of actions that can be done on a Task:
The Universal Location Interface consists of:
4) A Location Interface, which represents the type of actions that can be done on a Contact:
There is PIM and Location Factory, which load an instance of the appropriate class that implements the above interfaces; based on the platform the application is running on and configuration settings. For Location, the implementation class could be for a 3rd party location capability. The implementation class is exposed as a remotely accessible object via the first interface described above. The object is bound to the Universal White Pages, with a well-known name. From that point on the local application simply communicates with the Universal PIM and Location interfaces described above. Remote nodes can communicate with the remotely accessible interface, by discovering it via the Universal PIM and Location, based on its well-known name.
Pervasive Software Platform Universal Rules Sub-Module
A Rules Interface 17 that allows for execution of rule sets (bound to business objects) that are executed within a wide array of rules/inference engines base on abstraction of JSR is depicted in
The Universal Rules Engine API 17 may be created by first creating an abstraction of the API's that are out there for the different types of Rules APIs available on the most popular platforms/devices. Implementations of that interface can then be created that can communicate with the most common commercial and open-source Rule-engine implementations.
This Rules API may also be made to be remotely accessible to other devices on the network. This allows for remote devices to execute rule sets on other devices. This is accomplished by using the Pervasive Software Platform Universal Peer-2-Peer Messaging Sub-Module 22 and Pervasive Software Platform Universal Peer-2-Group Messaging Sub-Module 23.
The Universal Rule Interface may include:
1) An Rule Interface, which represents the type of actions that can be done on a Rule Engine:
There is a Rule Engine Factory, which load an instance of the appropriate class that implements the above interface; based on the platform the application is running on, as well as configuration information describing any particularly desired agent platform. The implementation class is exposed as a remotely accessible object via the first interface described above. The object is bound to the Universal White Pages, with a well-known name. From that point on the local application simply communicates with the Universal Rule interface described above.
Pervasive Software Platform Universal Agent Sub-Module
An Agent Interface 28 that allows for Agents to interoperate with multiple Agent Framework/Platforms is depicted in
There will be a default Agent Framework/Platform that comes with the Pervasive Software platform, which is described in greater detail below.
The Universal Agent Interface may include:
1) An Agent Interface, which represents the type of actions that can be done on a Software Agent:
There is an Agent Factory, which load an instance of the appropriate class that implements the above interface; based on the platform the application is running on, as well as configuration information describing any particularly desired agent platform. The implementation class is exposed as a remotely accessible object via the first interface described above. The object is bound to the Universal White Pages, with a well-known name. From that point on the local application simply communicates with the Universal Agent interface described above.
The following is a description of the proposed Agent Framework, which runs on the proposed Pervasive Software Platform described above.
In general Agents are used to integrate service tool sets and other capabilities with the DKN. As additional components continue to be integrated, Agent Frameworks help control and manage the maintenance required for that integration over time.
Agent Communications Description
Agents are used as a means of communication between components of a system oriented architecture (SOA). Agents translate instructions from an agent controller in context to the DKN component they integrate with as a proxy. This process is depicted in
(1) Agent Manifest 131 communicates to the server the agents (federates) to be loaded on nodes across the network.
(2) The Agent Controller 132 communicates to each agent (federate) the configuration to use in the conduct of its work.
(3) The Agent Configuration 133 communicates to the agent the work to be conducted in the form of an instanced software component (class and class path) and other configuration items.
(4) The Software Instance 134 for an agent is loaded or connected to the Agent Proxy 135.
(5) Ontologies and Rule-Sets that communicate the vocabulary, structure and type of data retrieval and collection (feedback) needed to conduct its work.
(6) The Knowledge Repository Database 136 communicates to the Agent data as input to the work to be conducted.
(7) The Agent client/instance 134 communicates inputs/results from network, GUI, Filter/Analysis to the Knowledge Repository Database 136 as a Data Gatherer.
Agent Functionality Description
Agent frameworks represent classes of agents. Each class of agent (framework) utilizes a specific configuration schema to perform a capability. The schema for agent configuration files ensures common APIs for a class or framework of agents. This common API provides a plug-in capability that enables each framework to scale without compounding integration efforts and other dependencies across the DKN team members.
Agent Controller—For every class of agents there is a server instance. The controller instructs and monitors agent activity. Agent Controllers can also include an instance of a Data Gatherer. Agent controllers include:
Agent Controller Manifest—This manifest represents a record of the agents employed by the Agent Controller. It is used both as a record of how agents were used as well as a plan for what agents will be used under any individual agent controller (see Data Collection Manifest).
Agent Proxy—The Agent Proxy provides a wrapper around each Agent Client forming a federation of agents that are centrally controlled by the Agent Controller.
Agent Configuration—The agent configuration is used to customize an agent instance to do the work it is intended to accomplish. The configuration is used in place of hard coded implementations where applicable. The agent configuration file is specified by the Agent Class.
Agent Instance (Client)
Ontologies and Rule-Sets—This is a repository of ontologies and rule-sets employed by the agents. The Ontologies are represented in OWL (Web Ontology Language) or RDF (Resource Description Framework) format, and the rule-sets are described in a canonical language that is independent of any RETE-based rule set.
Knowledge Repository Database—This can be one or more databases that either deliver data to the agent and/or receive generated/collected data from the agent. The connection to the databases is specified in the Agent Configuration file.
Agent frameworks include:
Data Gatherer Agent—This class of agent is integrated with the Data Collection Manager as a proxy interface over each DKN Data Gatherer.
Filter/Analysis Agent—This class of agent is integrated with the Data Gatherer Manager to automatically perform quantitative evaluations of collected data. These agents perform work such as detecting hostile interdictions over a defended asset. These agents represent a subclass of Data Gatherer Agents.
Interface Agent—This class of agent is used by Humans to observe, monitor and annotate DKN information. Interface Agents represent human-in-the-loop Data Gatherers for evaluative information specific to the goals of the application.
DKN Controller Component Agent—This class of agent is integrated with the Controller Workstation as a proxy interface over each DKN Component. These agents synchronize components for replay, report, and product generation. This synchronization includes:
Agent Operational Activity to Systems Function
Collaboration—Agent frameworks provide a common flexible means for establishing collaborative federations of individuals, teams, and software components.
Data Retrieval—Agent frameworks use a common flexible means for retrieving data from Knowledge Repository Databases.
Data Fusion—The results of collaboration are fused to/with the data queried by an agent.
Agent Data Exchange Matrix
The data exchange matrix shown in Table 1 summarizes the types of data exchanged between each class of agent and the Agent Controller which manages and instructs those agents. Specific details on this data can be found in Section.
The Agent Framework fulfills the needs of various federations that work toward a common purpose as defined across the Distributed Knowledge Network.
The Agent platform provides a number of capabilities, which apply to integration challenges faced today:
Agent Configuration Schema
Agent configurations are used to specify the implementation detail within the Agent Framework of the DKN. Each Agent Framework is focused on providing a particular class of functions to include:
The Agent Configuration Schema binds each framework API with the specific implementation (instance) detail for that class of agents. Each class of agent (framework) utilizes a specific schema. The Agent configuration scheme ensures APIs for a class or framework of agents is common. This common API provides a plug-in capability that enables each framework to scale without compounding integration efforts and other dependencies across the DKN team members
The platform will also be intelligent and adaptive, not just on servers, and powerful devices, but on mobile and embedded devices. It will support the notion of intelligent software components that can act autonomously on any device, written in any language, and communicate using the most effective protocol with any other device/system, or dynamically assembled groups of devices/systems.
By intelligent and adaptive, it is meant that these software components can learn and change behavior dynamically or an array of potential reason, based on what they learn, or based on changing goals or missions of the applications.
Although embodiments of the present invention have been illustrated in the accompanied drawings and described in the foregoing description, it will be understood that the invention is not limited to the embodiments disclosed, but is capable of numerous rearrangements, modifications, and substitutions without departing from the spirit of the invention as set forth and defined by the following claims. For example, the capabilities of the invention can be performed fully and/or partially by one or more of the blocks, modules, processors or memories. Also, these capabilities may be performed in the current manner or in a distributed manner and on, or via, any device able to provide and/or receive information. Further, although depicted in a particular manner, various modules or blocks may be repositioned without departing from the scope of the current invention. Still further, although depicted in a particular manner, a greater or lesser number of modules and connections can be utilized with the present invention in order to accomplish the present invention, to provide additional known features to the present invention, and/or to make the present invention more efficient. Also, the information sent between various modules can be sent between the modules via at least one of a data network, the Internet, an Internet Protocol network, a wireless source, and a wired source and via plurality of protocols.
