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
21、ystem control Federated control,Resource allocation,PLC authenticates users and understands relationships between principals; issues tickets SHARP system at site validates ticket + returns lease,User Verification,Public-key cryptography used to sign modules entered into PlanetLab X.509 + SSL keys ar
22、e used by PLC + slices to verify user authenticity Keys distributed “out of band” ahead of time,Final Thoughts,Large system with complex relationships Currently upgrading to version 4.0 New systems (GENI) are being proposed Still provides lots of resources to researchers CoralCache, several other pr
23、ojects run on PlanetLab,OLPC,“They want to deliver vast amounts of information over the Internet. And again, the Internet is not something you just dump something on. Its not a big truck. Its a series of tubes.”,The Internet is a series of tubes,The internet is composed of a lot of infrastructure: C
24、lients and servers Routers and switches Fiber optic trunk lines, telephone lines, tubes and trucks And if we map the density of this infrastructure, it probably looks something like this,Photo: cmu.edu,How do we distribute knowledge when there are no tubes?,What if we wanted to share a book? Pass it
25、 along, door-to-door. What if we wanted to share 10,000 books? Build community library. How about 10 million books? Or 300 copies of one book? A very large library?,Solutions,We need to build infrastructure to make large-scale distribution easy (i.e., computers and networking equipment) We need to b
26、e cheap Most of those dark spots dont have much money We need reliability where reliable power is costly Again, did you notice that there werent so many lights? Its because theres no electricity!,The traditional solution: a shared computer with Internet,India 75% of people in rural villages 90% of p
27、hones in urban areas Many villagers share a single phone, usually located in the town post office Likewise, villages typically share a few computers, located at the school (or somewhere with reliable power) Whats the downside to this model? It might provide shared access to a lot of information, but
28、 it doesnt solve the “300 copies of a book” case,The distributed solution: the XO,AKA: Childrens Machine, OLPC, $100 laptop A cheap ($150) laptop designed for children in developing countries,OLPC = One Laptop Per Child.,Photo: laptop.org,XO design,Low power consumption No moving parts (flash memory
29、, passive cooling) Dual-mode display In color, the XO consumes 2-3 watts In high-contrast monochrome, less than 1 watt Can be human powered by a foot-pedal Rugged, child-friendly design Low material costs Open-source software,XO networking,The XO utilizes far-reaching, low-power wireless networking
30、to create ad-hoc mesh networks If any single XO is connected to the Internet, other nearby computers can share the connection in a peer-to-peer scheme Networks can theoretically sprawl as far as ten miles, even connecting nearby villages,XO storage and sharing,XO relies on network for content and co
31、llaboration Content is stored on a central servers Textbooks Cached websites (Wikipedia) User content Software makes it easy to see other users on the network and share content,XO distribution,XO must be purchased in orders of 1 million units by governments in developing nations (economies of scale
32、help to lower costs) Governments are responsible for distribution of laptops Laptops are only for children, designed solely as a tool for learning,XO downfalls,Distribution downfalls What about children in developed nations? Sell to developed markets at a higher price to subsidize costs for developi
33、ng nations. Can governments effectively distribute? What about black markets? OLPC could perhaps partner with local schools and other NGOs to aid in distribution, training and maintenance Too expensive? Some nations can only afford as much $20 per child per year. How can we cater to them?,What can t
34、he XO achieve?,Today, only 16 percent of the worlds population is estimated to have access to the Internet Develop new markets Microcredit Make small loans to the impoverished without requiring collateral Muhammad Yunus and the Grameen Bank won the 2006 Nobel Peace Prize for their work here The powe
35、r of the village economy As millions of users come online in developing nations, there will be many new opportunities for commerce. Helps those in developing nations to advance their economies and develop stronger economic models,Why give the XO to children?,UN Millennium Development Goal #2: “achie
36、ve universal primary education” Empower children to think and compete in a global space Children are a nations greatest resource Backed by a bolstered economy, they will grow to solve other issues (infrastructure, poverty, famine),The Course Again (in 5 minutes),So what did we see in this class? Moo
37、res law is starting to fail More computing power means more machines This means breaking problems into sub problems Sub-problems cannot interfere with or depend on one another Have to “play nice” with shared memory,MapReduce,MapReduce is one paradigm for breaking problems up Makes the “playing nice”
38、 easy by enforcing a decoupled programming model Handles lots of the behind-the-scenes work,Distributed Systems & Networks,The network is a fundamental part of a distributed system Have to plan for bandwidth, latency, etc Wed like to think of the network as an abstraction Sockets = pipes RPC looks l
39、ike a normal procedure call, handles tricky stuff under the hood Still have to plan for failures of all kinds,Distributed Filesystems,The network allows us to make data available across many machines Network file systems can hook into existing infrastructure Specialized file systems (like GFS) can o
40、ffer better performance with loss of generality Raises issues of concurrency, process isolation, and how to combat stale data,And finally,There are lots of distributed systems out there MapReduce, BOINC, MPI, several other architectures, styles, problems to solve You might be designing an important one soon yourself!,
