A novel scheme for processing packets in a router is presented, which provides for load sharing among multiple network processors distributed within the router. It is complemented by a feedback control mechanism designed to prevent processor overload. Incoming traffic is scheduled to multiple processors based on a deterministic mapping. The mapping formula is derived from the robust hash routing (also known as the highest random weight - HRW) scheme, introduced in K.W. Ross, IEEE Network, 11(6), 1997, and D.G. Thaler et al., IEEE Trans. Networking, 6(1), 1998. No state information on individual flow mapping needs to be stored, but for each packet, a mapping function is computed over an identifier vector, a predefined set of fields in the packet. An adaptive extension to the HRW scheme is provided in order to cope with biased traffic patterns. We prove that our adaptation possesses the minimal disruption property with respect to the mapping and exploit that property in order to minimize the probability of flow reordering. Simulation results indicate that the scheme achieves significant improvements in processor utilization. A higher number of router interfaces can thus be supported with the same amount of processing power. I.

Sophisticated middlebox services–such as network monitoring and intrusion detection, DDoS mitigation, worm scanning, XML parsing and protocol transformation–are becoming increasingly popular in today’s Internet. To support highthroughput, these services are often deployed on Distributed Memory, Multi-processor (DM-MP) hardware platforms such as a cluster of network processors. Scaling the throughput of such platforms, however, is challenging because of the difficulties and overheads of accessing persistent, shared state maintained by the services. In this paper, we describe the design and implementation of Oboe, a run-time system for DM-MP platforms that addresses the above challenge through two foundations: (1) categoryspecific management of shared state, and (2) adaptive flowlevel load distribution for addressing persistent processor overload. Our simulations demonstrate that Oboe can achieve performance within 0-5 % of an ideal adaptive system. Our prototype implementation of Oboe on a cluster of IXP2400 network processors, demonstrates the scalability achieved with increasing number of processors, number of flows and state size. I.

Load balancing in packet-switched networks is a task of ever-growing importance. Network traffic properties, such as the Zipf-like flow length distribution and bursty transmission patterns, and requirements on packet ordering or stable flow mapping, make it a particularly difficult and complex task, needing adaptive heuristic solutions. In this paper, we present two main contributions: Firstly, we evaluate and compare two recently proposed algorithmic heuristics that attempt to adaptively balance load among the destination units. The evaluation on real life traces confirms the previously conjectured impact of the Zipf-like flow length distribution and traffic burstiness. Furthermore, we identify the distinction between the goals of preserving either the sequence order of packets, or the flowto-destination mapping, showing different strengths of each algorithm. Secondly, we demonstrate a novel hybrid scheme that combines best of the flow-based and burst-based load balancing techniques and excels in both of the key metrics of flow remapping and packet reordering.

Today’s large multi-core Internet servers support thousands of concurrent connections or flows. The computation ability of future server platforms will depend on increasing numbers of cores. The key to ensure that performance scales with cores is to ensure that systems software and hardware are designed to fully exploit the parallelism that is inherent in independent network flows. This paper identifies the major bottlenecks to scalability for a reference server workload on a commercial server platform. However, performance scaling on commercial web servers has proven elusive. We determined that on web server running a modified SPECweb2005 Support workload, throughput scales only 4.8 × on eight cores. Our results show that the operating system, TCP/IP stack, and application exploited flow-level parallelism well with few exceptions, and that load imbalance and shared cache affected performance little. Having eliminated these potential bottlenecks, we determined that performance scaling was limited by the capacity of the address bus, which became saturated on all eight cores. If this key obstacle is addressed, commercial web server and systems software are well-positioned to scale to a large number of cores.

The vast development of World Wide Web traffic has produced great interest in distributed web server systems. While considering architecture of distributed web servers, the DNSbased distributed system is an optimistic solution in context of scalability, performance, and availability. DNS(Domain Name Server) name caching, Random Early Detection Method and Load Buffer Range Method have considerable effects on the load balance of distributed web server systems. In this paper, we examine the various load balancing techniques for web servers and evaluate the performance of the distributed Webserver system. URL-name to the IP address of a Web-server, the DNS of a distributed Web-server system can collect information from Web-servers for various statistics[22]. The DNS can select the address of a Web-server based on the collected information. In order to select the address of the suitable Web-server, the DNS could use some scheduling policy to balance the load among several Web-servers to avoid becoming overloaded.