Lecture 6 - Other Distributed Systems.ppt
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1、Lecture 6 - Other Distributed Systems,CSE 490h Introduction to Distributed Computing, Spring 2007,Except as otherwise noted, the content of this presentation is licensed under the Creative Commons Attribution 2.5 License.,Outline,DNS BOINC PlanetLab OLPC & Ad-hoc Mesh Networks Lecture content wrap-u
2、p,DNS: The Distributed System in the Distributed System,Domain Name System,Mnemonic identifiers work considerably better for humans than IP addresses“? Surely you mean 66.102.7.99!”Who maintains the mappings from nameIP?,A Manageable Problem, 2006 Computer History Museum. All rights reserved. puterh
3、istory.org,In the beginning,Every machine had a file named hosts.txt Each line contained a name/IP mapping New hosts files were updated and distributed via email This clearly wasnt going to scale,DNS Implementations,Modern DNS system first proposed in 1983 First implementation in 1984 (Paul Mockapet
4、ris) BIND (Berkeley Internet Name Domain) written by four Berkeley students in 1985. Many other implementations today,Hierarchical Naming,DNS names are arranged in a hierarchy:www.cs.washington.eduEntries are either subdomains or hostnames subdomains contain more subdomains, or hosts (up to 127 leve
5、ls deep!) Hosts have individual IP addresses,Mechanics: Theory,DNS Recurser (client) parses address from right to left Asks root server (with known, static IP address) for name of first subdomain DNS server Contacts successive DNS servers until it finds the host,Mechanics: In Practice,ISPs provide a
6、 DNS recurser for clients DNS recursers cache lookups for period of time after a requestGreatly speeds up retrieval of entries and reduces system load,BOINC,What is BOINC?,“Berkeley Open Infrastructure for Network Computing” Platform for Internet-wide distributed applications Volunteer computing inf
7、rastructure Relies on many far-flung users volunteering spare CPU power,Some Facts,1,000,000+ active nodes 521 TFLOPS of computing power 20 active projects (SETIHome, FoldingHome, Malaria Control) and several more in development(Current as of March 2007),Comparison to MapReduce,Both are frameworks o
8、n which “useful” systems can be built Does not prescribe particular programming style Much more heterogeneous architecture Does not have a formal aggregation step Designed for much longer-running systems (months/years vs. minutes/hours),Architecture,Central server runs LAMP architecture for web + da
9、tabase End-users run client application with modules for actual computation BitTorrent used to distribute data elements efficiently,System Features,Homogenous redundancy Work unit “trickling” Locality scheduling Distribution based on host parameters,Client software,Available as regular application,
10、background “service”, or screensaver Can be administered locally or LAN-administered via RPC Can be configured to use only “low priority” cycles,Client/Task Interaction,Client software runs on variety of operating systems, each with different IPC Uses shared memory message passing to transmit inform
11、ation from “manager” to actual tasks and vice versa,Why Participate?,Sense of accomplishment, community involvement, or scientific duty Stress testing machines/networks Potential for fame (if your computer “finds” an alien planet, you can name it!) “Bragging rights” for computing more units “BOINC C
12、redits”,Credit & Cobblestones,Work done is rewarded with “cobblestones” 100 cobblestones = 1 day of CPU time for a computer with performance equaling 1,000 double-precision floating-point MIPS (Whetstone) & 1,000 integer VAX MIPS (Dhrystone) Computers are benchmarked by the BOINC system and receive
13、credit appropriate to their machine,Anti-Cheating Measures,Work units are computed redundantly by several different machines, and results are compared by the central server for consistency Credit is awarded after the internal server validates the returned work units Work units must be returned befor
14、e a deadline,Conclusions,Versatile infrastructure SETI tasks take a few hours Climate simulation tasks take months Network monitoring tasks are not CPU-bound at all! Scales extremely well to internet-wide applications Provides another flexible middleware layer to base distributed applications on Vol
15、unteer computing comes with addl considerations (rewards, cheating),PlanetLab,What if you wanted to:,Test a new version of Bittorrent that might generate GBs and GBs of data? Design a new distributed hashtable algorithm for thousands of nodes? Create a gigantic caching structure that mirrored web pa
16、ges in several sites across the USA?,Problem Similarities,Each of these problems requires: Hundreds or thousands of servers Geographic distribution An isolated network for testing and controlled experiments Developing one-off systems to support these would be Costly Redundant,PlanetLab,A multi-unive
17、rsity effort to build a network for large-scale simulation, testing, and research “Simulate the Internet”,Usage Stats,Servers: 722+ Slices: 600+ Users: 2500+ Bytes-per-day: 3 - 4 TB IP-flows-per-day: 190M Unique IP-addrs-per-day: 1M,As of Fall, 2006,Project Goals,Supports short- and long-term resear
18、ch goals System put up “as fast as possible” PlanetLab design evolves over time to meet changing needs PlanetLab is a process, not a result,Simultaneous Research,Projects must be isolated from one another Code from several researchers: Untrustworthy? Possibly buggy? Intellectual property issues? Tim
19、e-sensitive experiments must not interfere with one another Must provide realistic workload simulations,Architecture,Built on Linux, ssh, other standard tools Provides “normal” environment for application development Hosted at multiple universities w/ separate admins Requires trust relationships wit
20、h respect to previous goals,Architecture (cont.),Network is divided into “slices” server pools created out of virtual machines Trusted intermediary “PLC” system grants access to network resources Allows universities to specify who can use slices at each site Distributed trust relationships Central s
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