High-Speed Policy-Based Packet Forwarding Using Efficient Multi-dimensional Range Matching Lakshman and Stiliadis ACM SIGCOMM 98

Abstract Internet Service Providers (ISP) would like to provide differentiated services using the same shared, connectionless network infrastructure. The key mechanism is the packet classification function that  parses the headers of the packets,  and after determining their context, classifies them based on administrative policies or real- time reservation decisions.

Packet classification is  Complex, and thus the bottleneck in the gigabit links  Currently implemented at lower-speed edge routers  Not based on multiple fields This paper presents new packet classification schemes that can classify packets  at rates of a million packets per second  using range matches on more than 4 packet header fields  with a worst-case and traffic-independent performance metric  by checking amongst a few thousand filtering rules

Introduction Packet Filtering/Packet Classification  Forwarding engines must be able to  identify the context of packets,  apply the necessary actions so as to satisfy the user requirements.  Such actions may be  the dropping of unauthorized packets,  redirection of packets to proxy servers,  special queuing and scheduling actions,  routing decisions based on a criteria other than the destination address

The specification of the packet classification policies must allow aggregations in their definitions. Classification algorithms must be be able to process rules that define combinations of ranges of values. If the algorithms can only handle exact values and do not support aggregation, preprocessing is required to translate the ranges to exact values.

A trend worth noting is that  even though packet filtering was thought of as a tool necessary only at the network access points and mainly for firewall or security applications,  it is now becoming apparent that it is a valuable tool for performing traffic engineering and meeting the new service requirements of the commercial Internet. The main consequence of these new uses is that  all packet classification actions must be performed at wire-speed, i.e., the forwarding engines must have enough processing power to be able to process every arriving packet without queuing.

Design Goals The Requirement for Real-Time Operation  Traditional router architectures are based on flow-cache architectures to classify packets.  The complete header of the first packet of a flow is processed through a slow path.  The header is then inserted into a cache or hash table together with the action that must be applied all packets of the same flow.  When subsequent packets of that flow arrive, the corresponding action can be determined from the cache or hash table.

Three problems with the cache-based architectures: 1.The number of simultaneous flows is extremely high. ∴ The use of hardware caches is extremely difficult. Caches of such size will most likely be implemented as hash tables since hash tables can be scaled to these sizes. However, the O(1) look-up time of a hash table is an average case result and the worst-case performance of a hash table can be poor. 2.The performance of cache-based schemes is heavily traffic dependent. 3.A commercial Internet infrastructure should be robust and should provide predictable performance at all times.

Criteria for efficient packet classification and system constraints: 1.The algorithm must be fast enough for Gigabit routers. 2.The algorithm must process every packet at wire-speed. 3.Classification rules must be based on several fields of the packet header, including source and destination IP addresses, source and destination port numbers, protocol type, and Type-of-Service. The rules must be able to specify ranges and not just exact values. 4.Two-dimensional requirement for multicast lookup and RSVP reservations that use either wild-card filters or CIDR aggregations.

5.Priorities are imposed on the rules for multiple match. 6.Updates of rules are rare compare to searches in the data structures. 7.Memory accesses are expensive and are the dominant factor in determining the worst-case execution time. 8.Memory is organized in words of size w and the cost of accessing a word is the same as the cost of accessing any subset of bits in a word. 9.Memory cost can be relatively low if technologies such as Synchronous Dynamic RAMS (SDRAMs) are used. 10.For operation at very high speed the algorithm must be amenable to hardware implementation.

Previous Work Most previous papers were targeted mainly for an end-point and their main goal was to isolate packets that are destined to specific protocols or to specific connections.  Linear parsing but do not scale to high speed The first hardware implementation of packet filters  fast enough to support an OC-12 link  restricted to only a small number of rules (< 12)  The pipeline implementation results in O(1) performance using O(N) processing elements for O(N) rules.  cannot scale to a large number of filter rules ( ∵ a linear number of processing elements).  for rules with exact matching and not with ranges.

Point Location Problem The general packet classification problem can be viewed as a point location problem in multidimensional space. This is a classic problem in Computational Geometry and numerous results have been reported in literatures.

Definition of the point location problem Given a point in a d-dimensional space, and a set of n d-dimensional objects, find the object that the point belongs to. Most algorithms reported in the literature deal with the case of non-overlapping objects or specific arrangements of hyper-planes or hyper-surfaces of bounded degree. For d > 3 dimensions, the best algorithms have  either an O(log d-1 n) complexity with O(n) space,  or an O(log n) time-complexity with O(n d ) space.  not directly useful for high speed packet filtering

“No-queuing before processing”  Any packet queuing delays are only acceptable after the classification step is performed, because it is the header processing (including packet filtering) operation that enables the router to determine the quality-of-service (QOS) level to be accorded to a particular packet.

Figure 5: Operation of the 2-dimensional algorithm when one dimension includes only intervals created by prefixes and the propagation technique is used.