Data processing: measuring – calibrating – or testing – Measurement system – Performance or efficiency evaluation
Reexamination Certificate
2002-01-17
2004-02-03
Barlow, John (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system
Performance or efficiency evaluation
C702S186000, C709S226000, C370S468000, C370S230000, C370S235000
Reexamination Certificate
active
06687655
ABSTRACT:
BACKGROUND OF THE INVENTION
The invention disclosed and claimed herein generally pertains to a method for dynamically reserving, maintaining and releasing resources in a network using quality of service (QoS) management architecture. More particularly, the invention pertains to a method of the above type wherein either a part or the whole aggregated reservation state is established, maintained and released using a combination of the soft state principle and the explicit release principle.
The increasing diversity of internet applications, from the most simple ones such as e-mail and web browsing to multimedia screening applications like IP Telephony and Videoconferencing, has raised the demand for Quality of Service in the Internet. On the other hand, in the highly competitive environment of Internet Service Providers (ISPs), satisfying customer needs regardless of whether they are other ISPs or end users is key to their survival. Therefore, the desire of ISPs to provide value-added services to their customers is growing immensely. These demands have led to the evolvement of QoS on the Internet as a necessity. Enabling QoS on the best effort Internet model introduces complexity in several areas, from applications, different networking layers and network architectures to network management and business models. All these aspects have been major research topics over the past few years. Finding an efficient solution for end-to-end QoS over an Internet that will satisfy both ISPs and their customers is very difficult.
Quality of service can be provided by dynamically reserving resources for a flow of data. When dynamic QoS is required, reservation states have to be created in the nodes between the source and destination of the flow. The reservation states can be kept either per flow or per aggregate, i.e., a bundle of flows or flows belonging to a certain category of traffic (also known as class of service, CoS). Currently, two types of QoS management are standardized in the Internet, which are referred to respectively as RSVP, for Resource Reservation Protocol, and Diffserv, for Differentiated Services. In RSVP QoS is maintained on a per flow basis. However, due to the non-trivial amount of storage and processing required in each intermediate node, RSVP does not scale well when going deeper into the core of the network where all flows come together. Thus, in real systems, RSVP is not scalable to very large internet networks.
Diffserv is a per aggregate QoS management system. Accordingly, Diffserv scales very well, because states are kept per class of service in each intermediate node and are subject to a fixed limit. However, Diffserv is generally unable to dynamically adjust to changing resource requirements between the various CoSs. More particularly, Diffserv is not flexible enough to accommodate requirements for changes in the amount of reservations per CoS.
Currently, a protocol and method known as Load Control is used to make Diffserv more flexible. This method is described, for example, in an Internet document entitled “Load Control of Real Time Traffic” Westberg et al., draft-westberg-loadcntr-03.txt, April 2000 (Work in progress). Load Control uses reservation and refresh requests to establish and maintain an aggregated reservation state in the interior network nodes. The ingress nodes to the interior network accept reservations for microflows, and then translate them into a resource request for the aggregated reservations in the interior nodes. The egress nodes deaggregate these flows and continue the QoS for a particular microflow to its destination. The algorithm in the interior nodes uses soft state principles and a global, optionally synchronized refresh period. In order to maintain a reservation, a refresh request must be sent at the end of each refresh period in a sequence of refresh periods. When a refresh request is not received for more than a refresh period, an associated part of the aggregated state is released back to the unused resources, ready to be reserved again. This arrangement is referred to as “soft-state” because there is an automatic change of state, that is, certain resources go from being reserved to not being reserved, if a refresh request is not timely received.
The load control method enables the internal aggregated reservation state to be reserved and maintained per external reservation request, without the interior nodes being required to keep state on a per flow basis. However, a significant disadvantage of Load Control is that resources cannot be explicitly released. Thus, it can take as much as an entire refresh period to be able to re-use resources which have been reserved. This means that the reservation soft state is maintained longer than necessary, preventing utilization of resources in the interior nodes during this time. A trade-off must be made between the refresh period length and the overhead cost of sending refresh packets. With a shorter period, the interior nodes can react faster to reservations that are no longer used, but this requires more signaling overhead due to the higher frequency at which refresh request packets are sent.
At present, to improve use of RSVP in QoS management, RSVP microflow reservations can be aggregated in the interior network. One example of such solution is known as RSVP aggregation, described in the Request for Comments (RFC) 3175, entitled, “Aggregation of RSVP for IPv4 and IPv6 Reservations”, Baker et al., RFC 3175, Standards Track, September 2001. RSVP aggregation uses a combination of reservation softstate and explicit release principles. The edge nodes are either aggregators or deaggregators for RSVP microflows. The aggregators combine the microflows into aggregated flows for each destination (always a deaggregator), and the interior nodes are required to keep state per aggregate flow. The number of flow-states in the interior nodes can be as much as the number of aggregators multiplied by the number of deaggregators. The interior states can be updated (for each new or terminating microflow), and can be explicitly released by the edge nodes. Since the aggregated reservation state can be explicitly released, the time during which unused resources cannot be reserved for other microflows tends to be reduced. However, the aggregated reservation state can be updated at any time after receiving an explicit release request. If this updating time is near the end of the refresh period, the resources will be unavailable for longer than necessary, thus wasting resources in the interior nodes of the network. Moreover, due to the fact that the complete aggregated reservation state must be established, maintained and released at once, it is necessary for the interior nodes to store the ID or identifier of the aggregated reservation request.
SUMMARY OF THE INVENTION
The invention provides an efficient way of establishing, maintaining and releasing either a part of or the entire aggregated reservation state, using a combination of reservation soft state and explicit release principles. Thus, while the method maintains an aggregated reservation state, it still allows per microflow changes to the reservation without keeping explicit state per microflow. Since parts of the aggregated reservation state can be established, maintained and released, it is not necessary to store any identity of the resource request. Moreover, since part of the aggregated reservation state can be explicitly released, the time during which resources cannot be reserved by other requesting services tends to be reduced.
One embodiment of the invention uses a sliding time window algorithm that is split into a number of sub-windows or cells. The sliding window algorithm makes possible fast reaction times, without diminishing the period for refresh requests. Thus, the sliding window algorithm reduces the time during which unused resources are kept reserved. Overhead may be at most one refresh period plus one cell length. When release requests are also used, overhead may be reduced to at most one cell length. While the invention usefully app
Jacobsson Martin Edvard
Karagiannis Georgios
Oosthoek Simon
Barlow John
Telefonaktiebolaget LM Ericsson (publ)
Walling Meagan S.
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