Computing Status Awareness, Advertisement and Service Routing methods of SAN Based on Databases

Introduction With computing resource continuously migrating to edges, services residing distributedly turns to be delivered in a dynamic way. More fine-grained networking policies awaring of service SLA requirements are urgently required. As illustrated in , a typical SAN framework consists of service client, service server, SAN ingress, SAN relay and SAN egress. A fine-grained networking policy can be achieved through successive procedures:

The perception of the status of computing resources: Changes and variations in the current status of computing resources should be notified and reflected. Static configurations together with the dynamic changes comprise a thorough and overall view as a reference to select a proper resource pool.
The advertisement of the status of computing resources: A group of nodes in the network domain should further be aware of the current distributions and conditions among various resource pools so that the networking and routing policies can be adjusted or formulated. The advertisement of the running status is also a learning procedure for the network domain.
The formulation of a specific service routing policy: With the knowledge of the running status and network conditions, an appropriate resource pool can be selected to satisfy the service SLA requirements. A specific fine-grained service routing policy can further be formulated to forward the packets.

The mentioned procedures are shown in Figure 1:

Computing Resource Perception and Advertisement in SAN +-------+ |Service| +-----------+ +----------+ +----------+ |Service| | +----+SAN Ingress+---+SAN Relay+---+SAN egress+---+ | |Client | +-----------+ +----------+ +----------+ |Server | +-------+ | +-------+ | | | | | | | |<-----SAN Fowarding and Routing Domain---->| | | | | |<---------------Service Identification Domain------------>| ]]> Since the perception and advertisement procedures are the premises to achieve service routing, enabling the network to be aware of the running status timely is regarded to be a significant problem. Currently, the perception of computing resources can be commonly achieved by application protocols, FTP for instance. With the connection between clients and the server establishd, the cloud side is required to spontaneously upload the running status of computing resources. The process of advertising computing resource information is commonly fulfilled by extending IGP or BGP. Packets with a designated format carrying information of computing resources flood in the network to complete the learning process. In current schemes, service routing is strongly coupled with traditional IP routing which results in the following deficiencies:

The status of computing resources is updated with delay attributed to a relatively long authentication duration and the usage of multiple protocols.
Responses in the network to the highly dynamic computing resources is relatively slow by using IGP or BGP.
Compared to conventional IP routing, service routing is comprehensively designated by both network metrics and service SLA requirements in which the status of computing resources is highly dynamic. Thus, advertising the dynamic status emerge a large amount of extra packets and exert relatively severe impact on the traffic bearer in the current network. Furthermore, conventional network services are not concerned about the status of computing resource.

According to the analysis above, the following problems are required to be solved:

Reduce the overwhelmed utilization of L3 protocols and improve the compatibility of the network.
Simplify the perception and advertisement process and optimize the learning procedure of updated status.

This draft proposes computing resources perception and advertisement method by introducing a distributed database to fulfill service routing decoupled from conventional IP routing.

Requirements Language The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 when, and only when, they appear in all capitals, as shown here.

Terminology

LB: Load Balancer
FTP: File Transfer Protocol
IGP: Interior Gateway Protocol
BGP: Border Gateway Protocol
DB-Agent: Agent of a database
GW: Gateway
SLA: Service Level Agreements
SID: Segment ID
SAN: Service Awareness Network
SAN ID: Service Awareness Network Identification, an identification designed to indicate the fundamental and common service types

The Perception of the Status of Computing Resources The computing resources information of the cloud-side server is used to reflect the performance and a running status of resource pools. It is obtained to facilitate unified collaborative invocation of computing power resources. It is noted that identical services can be provided by multiple resource pools which connects to different gateways and status of resource pools varies from each other. Thus, the description of computing resource may include the following attributes as shown in Figure 2:

Status Table of Computing Resources Since the status of computing resources can be modeled as a collection of key-value pairs with keys as unique identifiers, this draft introduced a distributed database to store and update the running status. As shown in Figure 2, a service identification defined as a SAN ID(Service ID) in to represent a globally unique service semantic identification and its connected gateway should be configured as the key for the extracted data model. A distributed system has the advantages of advanced performance, high availability and simple extensibility. It is highly partitionable and allows horizontal scaling which satisfies the practical scenarios of large scale of service instances. Also, both keys and values can be anything from simple objects to complex compound objects, and thus heterogeneous computing resources can be described and stored. After the key-value pairs are extracted and further written into the database by the cloud side as multiple DB-Agents, the perception of the status of computing resources is fulfilled.

The Advertisement of the Status of Computing Resources

The status of computing resources learning procedures With the introduction of a distributed database, the data of the computing resources can be stored in hierarchically organized directories. A typical form is described as below:

/service instances/GW
/service instances/SAN ID
/service instances/SAN ID/CPU Load
/service instances/SAN ID/Memory Remains

As shown in Figure 3, a group of edge devices in the network domain observes the key value information through a publish-subscribe mechanism. Specific keys or directories can be watched for changes and multiple clients can react to changes in values. Since multiple edge devices simultaneously observe the variations, the running status is advertised to all edge devices. It is concluded that, by introducing a database, functions of perception and advertisement are unified. It can be understood that in the mentioned writing and reading process, there is no necessity to perform additional authentication on a management protocol and network layer protocols, thereby simplifying the overall procedure.

Service Routing Decoupled from IP Routing

Service Routing Decoupled from IP Routing + IP Routing Table | +-----------------------+ +------------------+ ]]> As shown in Figure 4, after the current computing status is obtained, a proper resource pool can be selected to satisfy the service SLA requirements, so as to quickly and accurately guide data forwarding. Together with path metrics in the network, a specific service routing table is formulated. Since the service routing table is generated additionally, it is completely decoupled from the conventional IP routing table. As shown in Figure 5, for services with requirements for computing resources, the service routing table maps to the IP routing table to complete a forwarding operation. With the service gateway determined, an Interface IP or an SRv6 policy can be indexed. For conventional services which are not sensitive to computing resources, a forwarding operation can be implemented simply in the original way.

Use Case As shown in Figure 6, suppose CPU load is a sample attribute and 70% is configured to be a threshold. If the CPU load beyonds 70%, the traffic needs to be steered to another satisfied resource pool . The procedure of learning and processing updated computing resource status is described as follows:

The CPU load of the container or VM where the service instance is located reaches the threshold 70% and the updated status is then written into the database in a key-value model.
Edge devices in the network domain subscribe the information by watching the prefix of the key-value pair.
Any variations in the subscribed information can be perceived and further learned by the edge devices.
Learning the CPU load reaches 70%, the service routing table is updated or regenerated.

An Example of Database-Based Computing Resource Perception Procedure | | | | | | | | | |<------------| | | | | notify | | | |notify | (/Service | | | |(/Service | Instances | | | |Instances/ | prefix/) | | | |SAN ID/ | | | | |CPU Load 70)| | | | |<-----------| | | | | | | | | ]]>

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