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Measurement and Evaluation of ENUM Server Performance

Shen, Charles; Schulzrinne, Henning G.

ENUM is a protocol standard developed by the Internet Engineering Task Force (IETF) for translating the E.164 phone numbers into Internet Universal Resource Identifiers (URIs). It plays an increasingly important role as the bridge between Internet and traditional telecommunications services. ENUM is based on the Domain Name System (DNS), but places unique performance requirements on DNS server. In particular, ENUM server needs to host a huge number of records, provide high query throughput for both existing and non-existing records in the server, maintain high query performance under update load, and answer queries within a tight latency budget. In this report, we evaluate and compare performance of serving ENUM queries by three servers, namely BIND, PDNS and Navitas. Our objective is to answer whether and how these servers can meet the unique performance requirements of ENUM. Test results show that the ENUM query response time on our platform has always been on the order of a few milliseconds or less, so this is likely not a concern. Throughput then becomes the key. The throughput of BIND degrades linearly as the record set size grows, so BIND is not suitable for ENUM. PDNS delivers higher performance than BIND in most cases, while the commercial Navitas server presents even better ENUM performance than PDNS. Under our 5M-record set test, Navitas server with its default configuration consumes one tenth to one sixth the memory of PDNS, achieves six times higher throughput for existing records and an order of two magnitudes higher throughput for non-existing records than the bottom line PDNS server without caching. The throughput of Navitas is also the highest among the tested servers when the database is being updated in the background. We investigated ways to improve PDNS performance. For example, doubling CPU processing power by putting PDNS and its backend database in two separate machines can increase PDNS throughput for existing records by 45% and that for nonexisting records by 40%. Since PDNS is open source, we also instrumented the source code to obtain a detailed profile of contributions of various systems components to the overall latency. We found that when the server is within its normal load range, the main component of server processing latency is caused by backend database lookup operations. Excessive number of backend database lookups is the reason that makes PDNS throughput for non-existing records its key weakness. We studied using PDNS caching to reduce the number of database lookups. With a full packet cache and a modified cache maintenance mechanism, the PDNS throughput for existing records can be improved by 100%. This brings the value to one third of its Navitas counterpart. After enabling the PDNS negative query cache, we improved PDNS throughput for non-existing records to the level comparable to its throughput for existing records, but this result is still an order of magnitude lower than the corresponding value in Navitas. Further improvements of PDNS throughput for non-existing records will require optimization of related processing mechanism in its implementation.

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Academic Units
Computer Science
Publisher
Department of Computer Science, Columbia University
Series
Columbia University Computer Science Technical Reports, CUCS-029-06
Published Here
April 27, 2011
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