CSEN 503 Introduction to Communication Networks

Transcription

1 CSEN 503 Introduction to Communication Networks 1-1 Mervat AbuElkheir Hana Medhat Ayman Dayf ** Slides are attributed to J. F. Kurose

2 Roadmap: Application layer Cookies and User-Server State Web caches (proxy server) DNS 2

3 User-server state HTTP is stateless So how do web servers keep track of your preferences? 3

4 User-server state: cookies Many major Web sites use cookies Four components: 1) cookie header line of HTTP response message 2) cookie header line in HTTP request message 3) cookie file kept on user s host, managed by user s browser 4) back-end database at Web site Example: Susan always access Internet always from PC visits specific e-commerce site for first time when initial HTTP requests arrives at site, site creates: unique ID entry in backend database for ID 4

5 Cookies: keeping state (cont.) client server ebay 8734 cookie file ebay 8734 amazon 1678 one week later: ebay 8734 amazon 1678 usual http request msg usual http response Set-cookie: 1678 usual http request msg cookie: 1678 usual http response msg usual http request msg cookie: 1678 usual http response msg Amazon server creates ID 1678 for user create entry cookiespecific action cookiespectific action access access backend database 5

6 Cookies (continued) What cookies can bring: authorization shopping carts recommendations user session state (Web e- mail) How to keep state : protocol endpoints: maintain state at sender/receiver over multiple transactions cookies: http messages carry state aside Cookies and privacy: cookies permit sites to learn a lot about you you may supply name and to sites 6

7 Web caches (proxy server) Goal: satisfy client request without involving origin server user sets browser: Web accesses via cache origin server browser sends all HTTP requests to cache object in cache: cache returns object client Proxy server else cache requests object from origin server, then returns object to client client origin server 7

8 More about Web caching cache acts as both client and server typically cache is installed by ISP (university, company, residential ISP) Why Web caching? reduce response time for client request reduce traffic on an institution s access link. Internet dense with caches: enables poor content providers to effectively deliver content (but so does P2P file sharing) 8

9 Caching example Assumptions average object size = 1Mbits avg. request rate from institution s browsers to origin servers = 15 req/sec delay from internet router to any origin server and back to router = 2 sec Consequences utilization on LAN = (15 requests/sec). (1Mbits/request)/(100Mbps) = 15% utilization on access link = (15 requests/sec). (1Mbits/request)/(15Mbps) = 100% total delay = Internet delay + access delay + LAN delay = 2 sec + minutes + milliseconds Internet router institutional network public Internet 15 Mbps access link 100 Mbps LAN institutional cache origin servers 9

10 Caching example (cont) possible solution increase bandwidth of access link to, say, 100 Mbps consequence utilization on LAN = 15% utilization on access link = 15% Total delay = Internet delay + access delay + LAN delay = 2 sec + msecs + msecs often a costly upgrade Internet router institutional network public Internet 100 Mbps access link 100 Mbps LAN origin servers 10

11 Caching example (cont) possible solution: install cache suppose hit rate is 0.4 consequence 40% requests will be satisfied almost immediately 60% requests satisfied by origin server utilization of access link reduced to 60%, resulting in negligible delays (say 10 msec) total avg delay = Internet delay + access delay + LAN delay =.6*(2) secs +.4*milliseconds < 1.4 secs Internet router institutional network public Internet 15 Mbps access link 100 Mbps LAN origin servers institutional cache 11

12 Conditional GET Goal: don t send object if cache has up-to-date cached version cache: specify date of cached copy in HTTP request If-modified-since: <date> server: response contains no object if cached copy is up-to-date: cache HTTP request msg If-modified-since: <date> HTTP response HTTP/ Not Modified server object not modified HTTP/ Not Modified HTTP request msg If-modified-since: <date> HTTP response HTTP/ OK <data> object modified 12

13 DNS: Domain Name System People: many identifiers: SSN, name, passport # Internet hosts, routers: IP address (32 bit) - used for addressing datagrams name, e.g., ww.yahoo.com - used by humans Q: map between IP addresses and name? Domain Name System: distributed database implemented in hierarchy of many name servers application-layer protocol host, routers, name servers to communicate to resolve names (address/name translation) note: core Internet function, implemented as applicationlayer protocol complexity at network s edge 13

14 DNS 14 DNS services Hostname-to-IP-address translation host aliasing Canonical, alias names mail server aliasing load distribution replicated Web servers: set of IP addresses for one canonical name Why not centralize DNS? single point of failure traffic volume distant centralized database Maintenance: update huge DB doesn t scale!

15 Distributed, Hierarchical Database 15 Root DNS Servers com DNS servers org DNS servers edu DNS servers yahoo.com DNS servers amazon.com DNS servers pbs.org DNS servers poly.edu umass.edu DNS serversdns servers Client wants IP for 1 st approx: client queries a root server to find com DNS server client queries com DNS server to get amazon.com DNS server client queries amazon.com DNS server to get IP address for

16 DNS: Root name servers contacted by local name server that can not resolve name root name server: contacts authoritative name server if name mapping not known gets mapping returns mapping to local name server e NASA Mt View, CA f Internet Software C. Palo Alto, CA (and 36 other locations) a Verisign, Dulles, VA c Cogent, Herndon, VA (also LA) d U Maryland College Park, MD g US DoD Vienna, VA h ARL Aberdeen, MD j Verisign, ( 21 locations) k RIPE London (also 16 other locations) i Autonomica, Stockholm (plus 28 other locations) m WIDE Tokyo (also Seoul, Paris, SF) b USC-ISI Marina del Rey, CA l ICANN Los Angeles, CA 13 root name servers worldwide 16

17 TLD and Authoritative Servers 17 Top-level domain (TLD) servers: responsible for com, org, net, edu, etc, and all toplevel country domains uk, fr, ca, jp. Network Solutions maintains servers for com TLD Educause for edu TLD Authoritative DNS servers: organization s DNS servers, providing authoritative hostname to IP mappings for organization s servers (e.g., Web, mail). can be maintained by organization or service provider

18 Local Name Server 18 does not strictly belong to hierarchy each ISP (residential ISP, company, university) has one. also called default name server when host makes DNS query, query is sent to its local DNS server acts as proxy, forwards query into hierarchy

19 DNS name resolution example root DNS server Host at cis.poly.edu wants IP address for gaia.cs.umass.edu TLD DNS server iterated query: contacted server replies with name of server to contact I don t know this name, but ask this server local DNS server dns.poly.edu 1 8 requesting host cis.poly.edu 7 6 authoritative DNS server dns.cs.umass.edu gaia.cs.umass.edu 19

20 20 DNS name resolution example root DNS server recursive query: puts burden of name resolution on contacted name server heavy load? TLD DNS server local DNS server dns.poly.edu requesting host cis.poly.edu authoritative DNS server dns.cs.umass.edu gaia.cs.umass.edu

21 DNS: caching and updating records once (any) name server learns mapping, it caches mapping cache entries timeout (disappear) after some time (often 48 hours) TLD servers typically cached in local name servers Thus root name servers not often visited 21

22 DNS Problem 1-22 Consider the network diagram on the right depicting three hosts H1, H2 and H3, as well as three levels of hierarchical DNS-Servers. The three hosts perform a large number of domain-name lookups over the course of a day. When a given DNS-request is in the zone of a name-server, this means the server can resolve the domain-name directly, in other words it doesn't have to propagate the request to the next level. Imagine for example host H3 is issuing DNS-requests to DNS3. We say that the probability (Pz) of that request being in DNS3's zone is 17% when the expected number of requests DNS3 can resolve directly is 0.17 of the total number of requests. This in turn means that 0.83 of all the requests to DNS3 have to be propagated to DNS2. Furthermore, DNS2 and DNS3 perform caching. If for example the hitrate of a certain cache (denoted CHR) is 1/10, this means that on the average, 1 in 10 requests can be resolved from that server's cache (the other 9 have to be resolved by propagation). Consider the table containing the probabilities and CHRs for the three name-servers. What is the overall average RTT for domain-name lookups, if RTT1, RTT2 and RTT3 denote the round-trip time from Hx to servers DNS1, DNS2 and DNS3 respectively? Server Pz CHR DNS1 100% - DNS2 43% 2/7 DNS3 17% 4/5

23 Solution 1-23 Suppose 100 requests are sent to DNS3, consider the following: Of the 100 requests, how many will be resolved at server DNS3? n3 = 17 + (4/5) (100-17) = 83.4 (1) Of the 100 requests, how many will be resolved at DNS2? Here we need to remember, that out of the 100 original packets, only some will be propagated to DNS2: i2 = (100 - n3) = 16.6 where i2 is the number of requests propagated to DNS2. The number of requests found in DNS2 zone out of the i2 packets: z2= i2 *(43/100) = The number of requests resolved at DNS2 can now be calculated as follows: n2 = z2 + (2/7)*(i2-z2) = (2/7) * ( ) =9.84 (2) Since DNS1 has Pz = 100%, all the remaining packets will be resolved at DNS1, namely: n1 = i1 = n3 - n2 (3) Now we can calculate the weighted-average of the total RTT: RTT =(1/100)* (RTT1*n1 + RTT2*n2 + RTT3* n3) (4)

24 Solution 1-24 DNS# # requests processed in-zone in-cache up DNS1 n1= DNS n2 = DNS n3 =

25 Next Lecture 1-25 Transport Layer