Patent Application
20050131995
1. Statement of the Technical Field
The present invention relates to memory allocation for caching content in a web caching systems, including a content delivery network and more particularly to the autonomic evaluation of Web workload characteristics to facilitate the configuration of cache size for web caches.
2. Description of the Related Art
In the prototypical content delivery system, content can be delivered from an origin server to a community of content consuming clients. Content typically can be delivered according to a request-response paradigm in which the content consuming clients initiate a request for content to which one or more origin servers can respond with the requested content. Generally, one or more content caches can be disposed in the intermediate communications path between the content consuming clients and content servers in order to enhance the responsiveness of the servers to any single client request and to reduce the processing burden placed upon the origin server.
Observations of content request patterns drive the design choices and policies for all of these components of a content delivery architecture. In particular, a number of studies indicate that requests to retrieve static Web objects follow a Zipf-like popularity distribution. Specifically, in accordance with Zipf, the probability pi of a request for the ith most popular document is proportional to 1/iα for some parameter α where α is a number greater than zero and generally less than unity. In this Zipf-like distribution, a large number of object requests typically target the most popular object sources and the most popular objects within those sources. The Zipf-like distribution, however, also includes a long, heavy tail of less popular objects with poor reference locality.
Notably, higher a values increase the concentration of requests on the most popular objects. One implication of the Zipf-like behavior of the Web is that caching is highly effective for the most popular static, and thus cacheable objects, assuming that popularity dominates rate of change. Unfortunately, caching is less effective in respect to the heavy tail of the distribution, which comprises a significant fraction of requests. Hence, Web cache effectiveness typically improves only logarithmically with the size of the cache, measured either by capacity or by user population. Of course, establishing an optimal memory allocation for a cache can vary with the value of the α parameter and the footprint of processed Web traces.
Predicting an optimal memory allocation for a cache at design time, however, can be difficult for most. Moreover, whereas optimally selecting a suitable cache size can be problematic generally, in an autonomic system, the problem can be particularly acute. For the uninitiated, autonomic computing systems self-regulate, self-repair and respond to changing conditions, without requiring any conscious effort on the part of the computing system operator. To that end, the computing system itself can bear the responsibility of coping with its own complexity. The crux of autonomic computing relates to eight principal characteristics:
I. The system must “know itself” and include those system components which also possess a system identify.
II. The system must be able to configure and reconfigure itself under varying and unpredictable conditions.
III. The system must never settle for the status quo and the system must always look for ways to optimize its workings.
IV. The system must be self-healing and capable of recovering from routine and extraordinary events that might cause some of its parts to malfunction.
V. The system must be an expert in self-protection.
VI. The system must know its environment and the context surrounding its activity, and act accordingly.
VII. The system must adhere to open standards.
VIII. The system must anticipate the optimized resources needed while keeping its complexity hidden from the user.
Thus, in keeping with the principles of autonomic computing, memory allocations for cache size ought to change with the changing footprint of Web traces and with changing α parameter values.
The present invention addresses the deficiencies of the art in respect to the configuration of cache memory in content delivery systems, including Web caches, and provides a novel and non-obvious method, system and apparatus for selecting a cache memory allocation to provide an optimized target cache hit rate in a content delivery system. In a preferred aspect of the invention, a method for selecting a cache memory allocation to provide an optimized target cache hit rate can include identifying a current cache size and a contemporaneously experienced trace footprint. A hit rate produced in response to the current cache size and the contemporaneously experienced trace footprint can be determined and a Zipf alpha coefficient can be computed for the current cache size, trace footprint and hit rate. An optimal hit rate can be selected and an optimal cache size for the Zipf alpha coefficient, trace footprint and optimal hit rate can be computed in consequence. Once the optimal cache size has been computed, the cache memory allocation can be modified based upon the optimal cache size.
A system for selecting a cache memory allocation to provide an optimized target cache hit rate can include a Zipf alpha coefficient parameter computation processor coupled to an optimal cache size computation processor communicatively linked to a caching component in a content delivery system. A communicative linkage between the Zipf alpha parameter computation processor and a server log storing statistics related to a hit rate for the cache can further be provided. Notably, the hit rate can be communicated to the Zipf alpha parameter computation processor over the communicative linkage.
Importantly, the Zipf alpha parameter computation processor can include programming for computing a Zipf alpha coefficient for a supplied hit rate, cache size and trace footprint according to the equation
where α is the Zipf alpha coefficient, m is the cache size, T is the trace footprint and HitRate is the hit rate. Similarly, the optimal cache size computation processor can include programming for computing an optimal cache size for a supplied Zipf alpha coefficient, a preferred hit rate, and a known trace footprint according to the same equation
where α is the Zipf alpha coefficient, m is the optimal cache size, T is the known trace footprint and HitRate is the preferred hit rate.
Additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The aspects of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
The accompanying drawings, which are incorporated in and constitute part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention. The embodiments illustrated herein are presently preferred, it being understood, however, that the invention is not limited to the precise arrangements and instrumentalities shown, wherein:
The present invention is a method, system and apparatus for dynamically establishing an optimal cache size in a caching component of a content delivery network based upon computed workload characteristics. In accordance with the present invention, historically collected hit rate statistics can be retrieved in the content delivery network to determine a contemporarily experienced hit rate in the cache. The hit rate can include the rate at which requested content in the content delivery network can be served from the cache rather than from fixed storage. In addition to the hit rate, the contemporarily experienced request trace footprint can be determined as can a contemporary setting for the memory allocation in the cache.
A Zipf-alpha coefficient can be computed for the hit rate, footprint and memory allocation. Once the Zipf-alpha coefficient has been computed, a desired hit rate can be selected. Based upon the computed Zipf-alpha coefficient, the desired hit rate and the footprint, an optimal memory allocation for the cache can be computed. Once computed, the optimal memory allocation can be applied to the cache and the process can be performed again. In this way, the cache can self-configure repeatedly through the course of operation to ensure that the memory allocated for caching remains at an optimal level for a desired hit rate for the trace footprint experienced in the content delivery network
The content delivery server 120 can be coupled to a cache 150. The cache 150 can be allocated a fixed amount of memory in which the cache 150 can store frequently accessed content. The content delivery server 120 further can be coupled to a content delivery server log 160. The content delivery server log 160 can store therein statistics relating to the requests 140A processed in the content delivery server 120 and the responses 140B provided by the content delivery server 120 to the requests 140A.
Importantly, the content delivery server log 160 can include data suitable for computing a hit-rate associated with the cache 150. Specifically, through an inspection of the content delivery server log 160, a ratio can be determined for the number of requests 140A processed in the content delivery server 120 by serving content found in the cache 150 to requesting ones of the content consuming clients 110A, 110B, 110n, as compared to all content served by the content delivery server 120 to the content consuming clients 110A, 110B, 110n, regardless of whether the content is served from the cache, or from fixed storage.
Notably, although only a single content delivery server 120 is shown in the illustration of
In accordance with the present invention, a Zipf alpha parameter computation processor 180 can be coupled to the content delivery server 120. The Zipf alpha parameter computation process 180 can be configured to solve the equation
The Zipf alpha computation processor 180 can be coupled to an optimal cache size computation processor 190. The optimal cache size computation processor 190 can be configured to solve the same Zipf equation above, this time solving for an unknown, optimal cache size based upon a preferred hit rate, the contemporaneously experienced trace footprint, and the Zipf alpha coefficient produced in the Zipf alpha computation processor 180. Using the optimal cache size produced by the optimal cache size computation processor 190, the memory allocated for the cache 150 can be adjusted to reflect the optimal cache size.
In more particular illustration of the foregoing methodology,
In block 250, the Zipf equation can be solved based upon the retrieved elements to produce a computed value for the Zipf alpha coefficient. It is well known in the art to solve equations of the nature of the Zipf equation using Newton's iteration methodology, though any suitable method for solving for the Zipf alpha coefficient can suffice. In any case, in block 260 a preferred hit rate for the cache can be selected and in block 270 the Zipf equation once again can be solved for the optimal cache size using the known values: Zipf alpha coefficient; trace footprint and preferred hit rate. The resultant optimal cache size value can be applied to the cache in block 280.
Notably, the foregoing process can be repeatedly applied in blocks 230 through 290 (the cache size presumably will be known based upon the step performed in block 280) so as to maintain the self-configuring and self-healing aspects of an autonomically operated content delivery cache. As the Zipf alpha coefficient changes with the changing footprint of traces experienced in the content delivery server, so too can the optimal cache size. Accordingly, the content delivery server can behave autonomically in its constant configuration of the memory allocated for caching content in the content delivery system of
It is to be understood that solving for the Zipf alpha coefficient to compute an optimal cache size to produce a desired hit rate within a single cache further can be applied to the partitioning of a cache to service multiple servers. Specifically, while the foregoing specification is directed to the circumstance of providing a single cache for a corresponding content server or content server farm, the system and methodology of the present invention can be equally applicable to the circumstance where a single cache supports multiple unrelated content servers. In this case, portions of the cache can be allocated to service different ones of the multiple unrelated content servers. Consequently, the hit rate characteristics for each of the different ones of the multiple unrelated content servers can be considered in computing the proper allocation of the cache memory for use in the single cache by the individual content servers.
The present invention can be realized in hardware, software, or a combination of hardware and software. An implementation of the method and system of the present invention can be realized in a centralized fashion in one computer system, or in a distributed fashion where different elements are spread across several interconnected computer systems. Any kind of computer system, or other apparatus adapted for carrying out the methods described herein, is suited to perform the functions described herein.
A typical combination of hardware and software could be a general purpose computer system with a computer program that, when being loaded and executed, controls the computer system such that it carries out the methods described herein. The present invention can also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein, and which, when loaded in a computer system is able to carry out these methods.
Computer program or application in the present context means any expression, in any language, code or notation, of a set of instructions intended to cause a system having an information processing capability to perform a particular function either directly or after either or both of the following a) conversion to another language, code or notation; b) reproduction in a different material form. Significantly, this invention can be embodied in other specific forms without departing from the spirit or essential attributes thereof, and accordingly, reference should be had to the following claims, rather than to the foregoing specification, as indicating the scope of the invention.
