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Thing-to-Thing Research Group                                 M. Burgess
Internet-Draft                                    Independent Researcher
Intended status: Informational                              H. Wildfeuer
Expires: April 21, 2016                                    Cisco Systems
                                                        October 19, 2015

 Federated Multi-Tenant Service Architecture for an Internet of Things


   This draft describes architectural recommendations for an Internet of
   Things scenario, based on tried and tested principles from
   infrastructure science.  We describe a functional service
   architecture that may be applied in the manner of a platform, from
   the smallest scale to the largest scale, using vendor agnostic
   principles.  The current draft is rooted in the principles of Promise
   Theory[Bergstra1] and voluntary cooperation.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
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   Internet-Drafts are draft documents valid for a maximum of six months
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   This Internet-Draft will expire on April 21, 2016.

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   Copyright (c) 2015 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Requirements and Promises Language  . . . . . . . . . . . . .   3
   3.  Definitions and concepts  . . . . . . . . . . . . . . . . . .   3
   4.  Device interconnection  . . . . . . . . . . . . . . . . . . .   4
   5.  Federation of agency  . . . . . . . . . . . . . . . . . . . .   6
     5.1.  Ownership . . . . . . . . . . . . . . . . . . . . . . . .   6
     5.2.  Tenancy and separation of concerns  . . . . . . . . . . .   6
     5.3.  Proximity of services to Things . . . . . . . . . . . . .   7
   6.  Workspaces  . . . . . . . . . . . . . . . . . . . . . . . . .   7
   7.  Generic Promise-Oriented Architecture . . . . . . . . . . . .   8
     7.1.  Control . . . . . . . . . . . . . . . . . . . . . . . . .   8
     7.2.  Services  . . . . . . . . . . . . . . . . . . . . . . . .   8
     7.3.  Promises  . . . . . . . . . . . . . . . . . . . . . . . .   9
     7.4.  Agents and their promises . . . . . . . . . . . . . . . .   9
     7.5.  Standard promises . . . . . . . . . . . . . . . . . . . .  10
     7.6.  Contextual policy-based adaptation  . . . . . . . . . . .  10
     7.7.  Workspace maintenance . . . . . . . . . . . . . . . . . .  11
     7.8.  Change of policy (system intent)  . . . . . . . . . . . .  11
     7.9.  Separation of concerns versus timescales  . . . . . . . .  12
     7.10. Device roles per workspace or region  . . . . . . . . . .  12
     7.11. Connectivity and Network Policy . . . . . . . . . . . . .  14
   8.  Characteristics . . . . . . . . . . . . . . . . . . . . . . .  15
   9.  Summary and Outlook . . . . . . . . . . . . . . . . . . . . .  16
   10. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . .  16
   11. Security Considerations . . . . . . . . . . . . . . . . . . .  16
   12. Normative References  . . . . . . . . . . . . . . . . . . . .  16
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  17

1.  Introduction

   The scenario we call the Internet of Things (IoT) is an inflection
   point in the development of information local and global
   infrastructure.  The facilitation of a platform for the next
   generation of global commerce presents a challenge of both
   technological and human dimensions.  This is a challenge that spans
   every layer of the software and networking stacks, but can be
   described in general terms without the need to specific
   implementations.  That is our goal in this draft.  Only a few new
   ideas are needed to synthesize this infrastructure, however several
   old technology practices must be deprecated for scaling and security

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   A platform for society must be vendor agnostic at its root, and must
   leave ample space for vendor specific creativity on top.  What
   distinguishes IoT from past scenarios is the prolific contact surface
   it will expose to the physical world, embedding devices pervasively
   in our close environments, and touching every part of human life.  At
   the time of writing, IoT has barely begun to emerge in domestic and
   industrial settings; however, choices we make now could help or
   hinder the development of an adequate platform over the coming
   decades.  The proposed architecture not only scales up to large
   numbers, it also scales down to small devices of low capability; from
   the largest installations to the smallest, and from the tiniest
   amounts of data, to vast data-stores collected by scientific
   computing at the limits of possibility.

2.  Requirements and Promises Language

   The term "PROMISE", "PROMISES" in this document are to be interpreted
   as described in Promise Theory [Bergstra1]

   When used, the key words "MUST", "MUST NOT", "REQUIRED", "SHALL",
   "OPTIONAL" in this document are to be interpreted as described in RFC
   2119 [RFC2119].

3.  Definitions and concepts

   IP endpoint  A hardware or software agent that is IP addressable, via
             a TCP/IP capable interface.

   Static endpoint  A hardware or software agent with an IP address
             (prefix and subnet) that is fixed over the timescale of
             application service interactions.

   Mobile endpoint  A hardware or software agent whose IP address
             location can change on the timescale of application service

   Application server/service  Any agent that promises to respond to
             requests, from external parties, and perform services of
             any kind, on a timescale that we may call the application
             service timescale.

   Multi-tenant application service  A collection of agents housed as
             tenants within a single host device, each offering
             different services, with potentially different timescales.

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   Client application  An agent that consumes data from an application
             service, requested either by imposed query or by promised

   Standalone Thing (FFD)  A full function device (FFD)[OneM2M], with an
             IP address, that can present its own service gateway or
             interface to the IP network.

   Peripheral Thing (RFD)  A reduced function device (RFD)[OneM2M], with
             no IP address, that attaches to a host gateway device as a
             peripheral, over an arbitrary network (USB, PCIe, CANbus,
             Profibus, ModBus, wireless sensor network, etc).  Devices
             are addressable, only through the gateway service.  This
             includes portmapped devices.

   Embedded network  Any network (IP or non-IP) that is non-IP routed,
             i.e. contained within a host endpoint as part of a black
             box, e.g. isolated NAT, device bus, serial channels.

   Transducer  An agent that consumes a service from another agent, and
             provides a new service based on the consumed service, e.g.
             a router, encrypter, compressor, etc.

   Trust     A unilateral policy assessment of one agent by another,
             concerning its reliability in honouring promises.  Trust is
             not necessarily a transitive property.

   Partial connectivity  A device is said to have partial connectivity
             if it is unavailable for intervals of time, e.g. due to
             loss of connectivity, mobility, or power napping.

4.  Device interconnection

   All devices are assumed to live in a partially connected environment.
   They MUST be fault tolerant to loss of communications, both with
   other agents in the course of providing application services, and
   with trusted sources of information.  A minimum interdependency
   design may be recommended to facilitate this.

   For a nascent Internet of Things, the focus is naturally drawn to the
   specialized leaf devices, where data may be produced or consumed.
   However, these are only half the picture. `Thing' devices, by design,
   also communicate with online services deployed `higher up', or
   `Northbound' in the system, to offload analysis and decision-making.
   Their physical capabilites thus place them into two broad categories:

   Standalone devices  These are assumed to connect by an IP addressable
             underlay network.  Connectivity is assumed end-to-end,

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             without reference to tunnels or software defined overlays.
             Routing is assumed to be provided end-to-end, and fully
             decoupled from the registration of devices.  Segregation
             and firewalling of certain network regions may be included
             in network design, but will not be considered here.

   Peripherals  These include bare sensors and actuators, which do not
             possess sufficient onboard resources or software
             interfaces, may attach to hosting standalone devices that
             act as a gateway and IP endpoint on their behalf.

   Transducers  These pass-through devices transformers, converters,
             encapsulation services, etc

     | FFD / Standalone |--> IP Endpoint

     | RFD / Peripheral |--+
     +------------------+  |      +------------------+
                           +------| FFD / Standalone |--> IP Endpoint
     +------------------+  |      +------------------+
     | RFD / Peripheral |--+

    Devices may be standalone (FFD), with service interfaces, or hosted
   peripherals (RFD), where data are exposed through service interfaces
        from other buses, e.g.  USB, CANbus, MODbus, Profibus, etc.

                                 Figure 1

   Standalone devices are full stack devices that provide data oriented
   services to data clients

   Stand-alone devices and transducers can vary considerably in their
   processing, memory and connectivity resources and constraints.  This
   architecture assumes a minimum resource level at the stand-alone
   device, but the device must support `full stack' implementations.  In
   practice, this implies that they contain an embedded OS (e.g.
   Linux), and are capable of running an agent providing secure service
   and connectivity interfaces.

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5.  Federation of agency

   Centralization of intent or control is not practical in environments
   with the density of devices and overlapping concerns exhibited by a
   pervasive Internet of Things.

5.1.  Ownership

   Device ownership is an important issue in a multi-tenant consumer
   environment.  While some devices will be centrally managed by
   providers, many devices in an Internet of Things will be personally
   owned, and would not be managed completely by centralized services.
   Devices may thus be managed by:

   Their owners  This applies in particular to personal consumer
             electronics, phones, cars, domestic appliances, etc, where
             users need to retain trusted ownership of their personal

   A service provider  This applies to managed services, factory
             machinery, fleet vehicles, set-top boxes placed in the
             home, power controllers, etc, where users do not need to
             interact with the devices on a management level, but there
             is an advantage to placing a device as a local presence in
             a smart environment.

5.2.  Tenancy and separation of concerns

   Federation of intent, aka multi-tenancy or diversity, all point to
   the need for Special Interest Groups (SIG) or work groups.
   Workspaces are places that are set aside for a particular purpose,
   that act as umbrellas for special interest groups.  For this, we
   introduce the notion of workspaces.

   Federation can be along a number of lines:

   o  Geographic partitioning (location)

   o  Separation of timescales (fast and slow)

   o  By special interest group (functional)

   See sections below for further information.

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5.3.  Proximity of services to Things

   Although devices will be separate from the agencies processing their
   sensory data, and feeding their guidance systems (policies and
   renderers), it is impractical to transport data over long distances
   between leaf devices and `cloud' services.  The logical outcome is
   therefore a decentralization of the cloud itself to insert converged
   resources close to the data sources themselves.  To scale such a
   distribution, the data services will naturally associate with private
   workspaces, which bound the scope of data generated by Things.

6.  Workspaces

   Workspaces may be thought of as a modernization of the domain
   concept.  Domains are typically linked to directory services (DNS,
   Active Directory, LDAP etc).  The demands of multi-tenant
   environments, where shared resources and separate business-processes
   mix and compete, make these older services less than optimal, though
   not inherently flawed.

   Workspaces are related to the more familiar notion of namespaces in
   information technology; however, namespaces refer only to a priority
   in name-referencing of objects, without underlying resource
   segmentation.  Workspaces MUST support multi-tenant separation of
   concerns within a hosted space.  Today, workspace facilities are
   commonly offered by user logins on computing devices, and quasi-
   workspace-like facilities are offered by virtual private networks,
   and VLANs, etc, in networking.

   For a collaborative Internet of Things, where interests span many
   issues from manufacturer interests, to personal ownership, functional
   responsibility, and security, the technologies for inter-group
   collaboration must be modernized to support logical, authenticated
   segmentation, shared directory information, as well as private
   naming, across converged resources: compute, network, and storage.

   1.  Workspaces may or may not be private, but they must be self-
       contained and separable, in the manner of namespaces.

   2.  Workspaces may or may not be associated with multiple tenants;
       but they are associated with multiple issues.

   3.  They represent a context for human activity, or separation of
       concerns, e.g.  some human activities might be modelled as
       workspaces include: the home, a children's playground, a squash
       court, an office, a shop, a factory floor, building, district,
       city, emergency channel frequency, hot and cold water pipes,
       dining room, drinks cabinet, etc.

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   Ubiquitous computing (the Internet of Things) is all about how
   networked devices support a wider variety of workspaces.  As the
   density of device resources (compute, storage, sensors, actuators) in
   a workplace or home environment increases, isolation of regions, and
   mapping of resources to responsible or interested parties become more
   difficult problems, both to implement and to understand.

   A detailed description of workspaces will be given separately

7.  Generic Promise-Oriented Architecture

   A promise-oriented architecture is described implicitly in [DSOM2005]
   and [Bergstra1].  It lays out a generic `bottom up' management
   concept, in which devices each have the responsibility for their own
   state and roles.  It resembles Service Oriented Architecture (SOA)
   superficially, without reference to specific technologies,
   implementations or protocols, and relates to the modern notion of
   microservices [MicroS]

   By formulating architecture from the bottom up, one can easily
   account for multi-contextual concerns, from developer concerns about
   realtime software updates (Continuous Delivery and DevOps etc), to
   operational service scaling, governance, and security, in a way that
   top-down schemes cannot easily achieve.

7.1.  Control

   A promise-oriented architecture communicates (e.g. intent and data)
   by authenticated publish-subscribe (aka "pull") methods, for security
   and predictability.  Thing devices MUST not accept control commands
   imposed upon them by "push" methods, as this exposes a security risk
   and may lead to inconclusive results if there are uncoordinated
   pushes.  In the vernacular usage of "control plane" and "data plane",
   control is asserted through agreed service level policies, and data
   are exchanged within services to carry out functions.

   Every standalone device operates autonomously, with direct policy
   input from its owner, without being managed from an external
   collective.  Similarly, any standalone device can give up that
   autonomy to a trusted manager, offering policy updates as a service.

7.2.  Services

   All devices provide services in varying degrees of sophistication.
   Peripheral devices serve data or actuators to host devices, and
   standalone devices expose functions to one another as software

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   services.  Each server plays a role to be composed into the wider

   Services may be used both for basic infrastructure support, and for
   driving user applications.  No limitations need be stated about
   applications.  Each fully functional, standalone device is free to
   host any application services.  The result is superficially similar
   to the Service Oriented Architecture [SOA], but without reference to
   a specific technology or methodology.  In modern parlance, the model
   is an example of microservices [MicroS].

   Data services are also best implemented as with pull methods, for
   resource-light scalability and security, but extremely limited
   application devices might initially struggle to support this mode.

7.3.  Promises

   The basic atom of bottom-up policy is a promise.  Each promise
   consists of three things:

   A `promiser'  i.e. a resource that will affect a change by keeping
             its promise to the system, e.g. a file, a process, a
             transaction, a measurement, device settings, etc.

   A description body  i.e. the desired-outcome that is achieved when
             the promise is kept.  This SHOULD be implemented in a
             convergent, idempotent manner [CFENGINE], [CONVERGE].

   A context in which the promise applies, based on time, location, type
             and group membership of the devices referred to in the

7.4.  Agents and their promises

   In a promise architecture, every device is contextually evaluated and
   integrated from the bottom up, according to the promises is keeps,
   e.g. the services it provides, its behaviours and properties, etc.
   Thus every device is modelled by its individual degree of agency to
   act as a proxy for human intent (policy).

   Standalone devices are assumed to be equipped with policy-keeping
   software agents.  Peripheral devices, such as sensors or actuators,
   are assumed to be integral parts of the standalone devices, and hence
   maintainable by the their software agents.

   No system must push changes or data to such agents ad hoc, without a
   documented promise to accept; thereafter, `fault tolerance' demands
   that we reject the word `must' from most descriptions, and replace it

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   with `promise of best effort', as to reply on perfect behaviour leads
   to brittle systems with unrealistic expectations.  For human safety
   in a rapidly expanding sphere of human involvement, the only `must'
   is for each agent to be stable and self-correcting, subject to the
   guidance of policy.

7.5.  Standard promises

   The following characteristics describe the cooperation between

   1.  Standalone devices promise to bootstrap to some trusted
       bootservice, i.e. register to one or more workspaces.

   2.  Standalone devices promise to refuse direct commands imposed from
       network peers (as mentioned above).

   3.  Policy consists of a collection of promises that apply in
       labelled contexts, each of which describes a unique desired end-

   4.  Promises are kept in a convergent manner, so that all promise-
       keeping actions lead to the desired end-state, no matter what the
       initial state of the device.

   5.  Agents that live on every device have drivers/renderers and make
       all changes without remote communication.

7.6.  Contextual policy-based adaptation

   Each policy agent promises to maintain a context evaluator that
   computes a set of classifying `tags' or `labels' that characterize
   the state of the agent.  This is updated every time the agent
   verifies policy, as its state may change as a result of repairs.
   These may be used as conditionals for distributed policy-based

   Contextual labels characterize the device, its environment, and its
   location and time.  The labels can then be used in policy to make
   certain promises apply only in specific contexts.

   When promises, within a policy, are tagged by issue or context,
   agents can select those that apply to its condition, within a larger
   trust relationship implied by policy sourcing.  This simplifies logic
   and promotes stability, as evidenced by experience with software
   agents [CFENGINE].

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7.7.  Workspace maintenance

   The following characteristics describe compatible policy update

   1.  Devices subscribe to policy from a trusted source, download
       changes to the policy model when they can, and cache it locally
       so that it is always available.

   2.  Local agents implement cached policy, without any dependence on
       remote communication, and in a fault tolerant fashion.  The
       failure to keep one promise should have minimal impact on the
       ability to keep others.

   3.  By verifying promises continuously, the agent that runs on each
       standalone device will know (or be able to calculate) its
       operational context, and can decide which promises are needed
       from the policy model, and whether or not to keep the promises.
       This scales O(1), i.e. without bottleneck.

   4.  Each promise that documents and intended outcome of the system is
       verified and measured in the process, providing immediate and
       statistical feedback to policy designers about the success of the
       policy in describing a stable desired outcome.

7.8.  Change of policy (system intent)

   Policy change can be initiated from within a workspace, subject to a
   defined quality assurance, or fit-for-purpose review.  Thus change of
   infrastructure may be instigated from the bottom-up also, as a self-
   service request.

   1.  Human operators (owners or managers) decide on a policy model for
       all devices in an organization or policy group.  This may be
       informed by the feedback about the success rate of previously
       kept promises.

   2.  The changes are edited into a model, which consists of a
       collection of promises that should be kept by all resources on
       all devices.

   3.  Changes are checked and tested before publishing.

   4.  Once changes are approved, they are published by a policy service
       for download at the convenience of the standalone device.

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7.9.  Separation of concerns versus timescales

   infrastructure stability is supported by a separation of systems into
   agencies that act in alignment with specific, separable timescales.
   Separation of fast and slow timescales avoids tight coupling and
   associated complex behaviours and should be considered a priority for
   maintaining safe, stable systems for human dependence.

   Systems scale along two broad lines, which a promise-oriented
   architecture helps to resolve:

   Dynamical scaling  Workload timescales concern the quantitative
             activity of the system: how fast requests are handled, how
             quickly service is delivered, and promises are kept.

   Semantic (functional) scaling  Semantics are normally the concern of
             software engineers and system designers.  This facilitates
             functional understanding.  It is a form of human interface
             or knowledge management.  It is sometimes at odds with the
             needs of dynamical scaling.

   Changes to semantics should generally be slow compared to the
   workload related dynamical activity, in order to maintain functional
   stability.  Cooperative design of workspaces may observe this
   principle to foster functional stability and workload efficiency.

7.10.  Device roles per workspace or region

   A number of functional roles are required to maintain a service
   lifecycle in a distributed environment.  Making these roles self-
   managed within each workspace is how one scales the diversity of
   human intent and concerns.  Roles are defined by the kinds of
   promises kept by devices:

   Bootstrap server  To provide trusted need-to-know data and local
             contacts so that clients can begin working within a policy

   Bootstrap client  To accept essential directory information on trust
             in order to join a local policy domain.

   Policy server  To deliver current policy from an authorized source,
             appropriate for each client (tenancy terms) from its global

   Policy client  To subscribe to the policy, selectively, depending on
             context from its local perspective.

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   Data server  data server (aka ``Thing'') To offer a catalogue of data
             streams to different tenants This includes sensors,

   Data Client  To subscribe to the policy, selectively, depending on
             context from its local perspective.

   Identity server  Manufacturer User Description service is promised by
             all Things providing a URI that points to a description of
             the device, its serial number characteristics, service
             details etc.

   Identity client  Identity clients promise to make use of data schemas
             and encodings involved in the interpretation of data
             pertaining to the device.

                         "Control data"                            "Application data"
 |+------------------+ +------------------+ +----------------- +| +-----------------+
 || Bootstrap server | | Policy server    | | Directory server || |  Data client(s) |
 |+------------------+ +------------------+ +----------------- +| +-----------------+
 +--------|---------------------|----------------------|--------+          |
          |                     |                      |                   |
          +----------------+    |                      |                   |
                           |    |                      |                   |
     +------------------+  |    |                      |                   |
     | FFD / Standalone |  |    |                      |                   |
     |  Bootstrap client|--+    |                      |                   |
     |  Policy client   |-------+                      |                   |
     |  Directory server|------------------------------+                   |
     |  Data client     |--------------------------------------------------+


   The roles in each collaborative workspace.  Devices at the bottom of
   the figure typically coordinate through workspace services hosted in
     the "cloud" or any nearby compute resource.  Efficiency suggests
     avoiding long data paths, instead moving computational resources
                     closer to data collection points.

                                 Figure 2

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   Bootstrapping new devices into a workspace represents the beginning
   of a device lifecycle.  Devices must begin with the location of a
   known bootstrap server.  Devices must also promise to advertise their
   nature and capabilities, called `identification'.  This may include
   Manufacturer Usage Description (MUD) identifiers [MUD].

7.11.  Connectivity and Network Policy

   So far, much as been said on how the application devices provide
   services via promises, and how system intent can be described and
   orchestrated via policy.  There is also a connectivity (transport)
   fabric for these devices that operates on a set of promises that
   underly the described service framework, i.e. the network.  Each
   network endpoint can be seen as providing its own set of promises
   that are used by other network elements to deliver routing and
   switching capabilities [PromiseNet].

   Intent driven networking is becoming more relevant as Software
   Defined Networking (SDN) deployments proliferate.  In the described
   IoT architecture, service policies that describe the IoT system
   intent can be used as an input to derive partial network policies
   (e.g.  Group Based Policy or some other model-based approach), with
   modulation by other data discovered from bootstrapping, etc.  The
   figure below illustrates the relationship between the service and
   network layer policies for IoT.

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                   | IoT Service Policy |
     +---------------------+ | +--------------------+
     | Topology / Location | | |   Orchestration    |
     |                     +-+-+
     |   Bootstrap data    | | | Organization policy|
     +---------------------+ | +--------------------+
                 |   IoT SDN policy   |

     Service policy could be partially rendered as an SDN baseline for
                    simplifying dependency management.

                                 Figure 3

8.  Characteristics

   The architecture, described in this draft, enables densely clustered
   IT resources to form arbitrary self-service communities that span
   local or wide area networks.  This is decouples a logical patchwork
   of segments on top of a plain end-to-end IP network.  By basing on
   principles of fault-tolerance, including publish-subscribe
   dissemination semantics, this may be scaled, without bottleneck, by
   only the well-known methods currently employed by the World Wide Web.

   IPv6 and successors will play a key role in recapturing network
   simplicity from the many workarounds that have been stacked on top of
   IPv4 and its limitations.  However, currently missing are adequate
   directory services to support a transparent workgroup concept.  The
   present Internet architecture is still geared principally towards a
   crudely shared single-tenant, top-down management model, with
   authority at the top.  Top down methods require the leaf domains to
   be exposed to attack from high up in the network.  However, shrink-
   wrapping workspace boundaries closer around their private resources,
   their management could be simplified, speeded up, and become less

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9.  Summary and Outlook

   The issues discussed and laid out in this draft address key issues of
   scalability, fault tolerance, separation of concerns, and federation
   of intent within networked information systems.  The platform is a
   synthesis of well-known techniques, and is deliberately aligned with
   the needs of agile commercial spaces, as well as large industrial
   distributions, and small domestic needs.  We purposely leave open
   vendor specific concerns, which can easily fit into the described
   architecture, on top of this common set of principles.

10.  Acknowledgments

   We are grateful for helpful conversations with K.  Burns, M.
   Dvorkin, D.  Maluf, and E.  Lear.

11.  Security Considerations

   With a pervasive contact surface onto both the Internet and the real
   world, security is obvious a major concern.  Experience with
   pervasive frameworks like [CFENGINE], as well as theoretical studies
   of pull-based architectures, suggest that the promise-oriented pull-
   only architecture can reduce the exposure to denial of service
   attacks and data-based overflow attacks, by rejecting all external
   data sent without invitation.  Moreover, the tie-in between service
   and network policy reduces the likelihood of errors in policy across
   the layers.

   Workspaces can play a role too here, as a shrink-wrapping of service
   scope around minimal set of endpoints, thus reducing the logical
   contact surface for data communications, and publishing information
   purely on a need-to-know basis.  We take is for granted that
   workspace data are encrypted with workspace authorized credentials.

12.  Normative References

              Bergstra, J. and M. Burgess, "Promise Theory: Principles
              and Applications", 2013.

              Burgess, M., "A site configuration engine, Computing
              Systems", 1995.

              Burgess, M., "Configurable immunity model of evolving
              configuration management, Science of Computer
              Programming", 2004.

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              Burgess, M., "An Approach to Understanding Policy Based on
              Autonomy and Voluntary Cooperation, Lecture Notes in
              Computer Science", 2005.

   [MicroS]   Richardson, C., "Pattern: Microservices Architecture",

   [MUD]      Lear, E., "Manufacturer Usage Description", 2015.

   [OneM2M]   OneM2M, , "Standards for M2M and the Internet of Things",

              Borrill, P., Burgess, M., Craw, T., and M. Dvorkin, "A
              Promise Theory of Networking", 2014.

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/
              RFC2119, March 1997,

   [SOA]      Open Group, , "SOA Reference Architecture Technical
              Standard : Basic Concepts", 2016.

   [WORKSPC]  Burgess, M., Dvorkin, M., and K. Burns, "Self-Service
              Workspaces for Federated IT Infrastructure", 2016.

Authors' Addresses

   Mark Burgess
   Independent Researcher

   Herb Wildfeuer
   Cisco Systems
   San Jose

   Email: hwildfeu@cisco.com

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