Abstract. Our understanding of IPv6 deployment is surprisingly limited. In fact, it is not even clear how we should quantify IPv6 deployment. In this paper, we collect and analyze a variety of data to characterize the penetration of IPv6. We show that each analysis leads to somewhat different conclusions. For example: registry data shows IPv6 address allocations are growing rapidly, yet BGP table dumps indicate many addresses are either never announced or announced long after allocation; Netflow records from a tier-1 ISP show growth in native IPv6 traffic, but deeper analysis reveals most of the traffic is DNS queries and ICMP packets; a more detailed inspection of tunneled IPv6 traffic uncovers many packets exchanged between IPv4-speaking hosts (e.g., to traverse NAT boxes). Overall, our study suggests that from our vantage points, current IPv6 deployment appears somewhat experimental, and that the growth of IPv6 allocations, routing announcements, and traffic volume probably indicate more operators and users preparing themselves for the transition to IPv6.
Observations of the OH column abundance have been made by the Fourier Transform Ultraviolet Spectrometer at the JPL Table Mountain Facility (TMF) near Los Angeles since July 1997. In the January 1998–December 2003 data set we used five OH lines to derive the OH column abundance in the atmosphere. This data set was used to quantify the OH morning/afternoon asymmetry (AMPMDA). An analysis of summer and winter data showed that the daily OH maximum occurred 26–36 minutes after solar transit. This phase lag appears to be the primary reason why OH in the afternoon is larger than at corresponding solar zenith angles in the morning throughout the year. A simple heuristic model suggests that the asymmetry is a direct consequence of the finite lifetime of OH. Comparison of the TMF data with earlier results from Fritz Peak Observatory, Colorado, by Burnett et al. reveals significant differences in the behavior of the AMPMDA between the two sites.
The memory Internet routers use to store paths to destinations is expensive, and must be continually upgraded in the face of steadily increasing routing table size. Unfortunately, routing protocols are not designed to gracefully handle cases where memory becomes full, which arises increasingly often due to misconfigurations and routing table growth. Hence router memory must typically be heavily overprovisioned by network operators, inflating operating costs and administrative effort. The research community has primarily focused on clean-slate solutions that cannot interoperate with the deployed base of protocols.This paper presents an incrementally-deployable Memory Management System (MMS) that reduces associated router state by up to 70%. The MMS coalesces prefixes to reduce memory consumption and can be deployed locally on each router or centrally on a route server. The system can operate transparently, without requiring changes in other ASes. Our memory manager can extend router lifetimes up to seven years, given current prefix growth trends.
Running the Border Gateway Protocol (BGP), the Internet's interdomain routing protocol, consumes a large amount of memory. A BGP-speaking router typically stores one or more routes, each with multiple attributes, for more than 170,000 address blocks, and growing. When the router does not have enough memory to store a new route, it may crash or enter into other unspecified behavior, causing serious disruptions for the data traffic. In this paper, we propose a new mechanism for routers to handle memory limitations without modifying the underlying routing protocol and without negatively affecting convergence delay. Upon running out of memory, the router simply discards information about some alternate routes, and requests a "refresh" from its neighbors later if necessary. We present an optimal offline algorithm for deciding which alternate routes to evict, and explore the trade-off between memory size and refresh overhead using a large BGP message trace. Based on these promising results, we design and evaluate efficient online algorithms that achieve most of the performance benefits. We believe that our scheme can significantly improve the scalability and robustness of IP routers in the future.
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