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EECS 122: Introduction to Computer Networks Evolution of the Internet. Computer Science Division Department of Electrical Engineering and Computer Sciences University of California, Berkeley Berkeley, CA 94720-1776. R U RDY 4 WOTS NXT?. 93 Million. Internet Computers. Today’s Internet.

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eecs 122 introduction to computer networks evolution of the internet

EECS 122: Introduction to Computer Networks Evolution of the Internet

Computer Science Division

Department of Electrical Engineering and Computer Sciences

University of California, Berkeley

Berkeley, CA 94720-1776

x internet beyond the pc


Internet Computers

Today’s Internet

Internet Users

407 Million


663 Million


1.5 Billion


Electronic Chips

30 Billion

“X-Internet” Beyond the PC

Forrester Research, May 2001

x internet beyond the pc1






“X-Internet” Beyond the PC

Forrester Research, May 2001

the old days
Shape of Things Today: Diverse Appliances and Devices

Game Consoles

Personal Digital Assistants

Digital VCRs


Smart Telephones


The Old Days

All will demand broadband

Internet connectivity

… and 10BaseT won’t be sufficient

future of the internet
Future of the Internet
  • Mobile IP
  • Networked Everything: Sensor Nets
  • Internet Economics
why mobile ip
Why Mobile IP?
  • Need a protocol that maintains network connectivity while hosts move between nets
  • Must avoid massive changes to router software, etc.
  • Must be compatible with large installed base of IPv4 networks/hosts
  • Confine changes to mobile hosts and a few support hosts that enable mobility

G. G. Richard III, UNO

mobile ip basics
Mobile IP: Basics
  • Proposed by IETF (Internet Engineering Task Force)
    • Standards development body for the Internet
  • Allows a mobile host (MH) to move about without changing its permanent IP address
  • Each mobile host has a home agent (HA) on its home network
  • MH establishes a care-of address when it's away from home

G. G. Richard III, UNO

mobile ip basics1
Mobile IP: Basics
  • Correspondent host (CH) is a host that wants to send packets to the MH
  • CH sends packets to the MH’s IP permanent home address
  • Packets routed to the MH’s home network
  • HA forwards IP packets for MH to current care-of address
  • MH sends packets directly to correspondent, using permanent home IP as source IP

G. G. Richard III, UNO

mobile ip basics2
Mobile IP: Basics

correspondent host

home agent

G. G. Richard III, UNO

mobile ip care of addresses
Mobile IP: Care-of Addresses
  • When MH connects to a remote network:
    • Care-of can be the address of a foreign agent (FA) on the remote network
      • FA delivers packets forwarded from HA to MA
    • Care-of can be a temporary, foreign IP address obtained through, e.g., DHCP
      • HA tunnels packets directly to the temporary IP address
  • Care-of address must be registered with HA

G. G. Richard III, UNO

ip in ip tunneling
IP header

IP header



IP-in-IP Tunneling
  • Packet to be forwarded is encapsulated in a new IP packet
  • In the new header:
    • Destination = care-of-address
    • Source = address of home agent
    • Protocol number = IP-in-IP

IP header

G. G. Richard III, UNO

at the other end
At the Other End...
  • Depending on type of care-of address:
    • FA or
    • MH
  • … strips outer IP header of tunneled packet, which is then fed to the MH

G. G. Richard III, UNO

routing inefficiency
Routing Inefficiency

MH and CH may even be on the same network!!

correspondent host

home agent

G. G. Richard III, UNO

route optimizations
Route Optimizations
  • Possible Solution:
    • HA sends current care-of address to CH
    • CH caches care-of address
    • Future packets tunneled directly to care-of address
  • But …
    • Cache consistency problem arises ...
    • Cached care-of address becomes stale when the MH moves
    • Potential security issues with providing care-of address to correspondent

G. G. Richard III, UNO

future of the internet1
Future of the Internet
  • Mobile IP
  • Networked Everything: Sensor Nets
  • Internet Economics
Embedded Sensor Nets: Enabling Technologies

Embednumerous distributed devices to monitor and interact with physical world

Networkdevices tocoordinate and perform higher-level tasks




Sensing, action

Control system w/

Small form factor

Untethered nodes


Tightly coupled to physical world

Exploit spatially/temporally dense, in situ/remote, sensing/actuation

Jim Kurose, UMass

sensor nets new design themes
Sensor Nets: New Design Themes
  • Self configuring systems that adapt to unpredictable environment
    • Dynamic, messy (hard to model) environments preclude pre-configured behavior
  • Leverage data processing inside the network
    • Exploit computation near data to reduce communication
    • Collaborative signal processing
    • Achieve desired global behavior with localized algorithms (distributed control)
  • Long-lived, unattended, untethered, low duty cycle systems
    • Energy a central concern
    • Communication primary consumer of scarce energy resource

Jim Kurose, UMass

from embedded sensing to embedded control
From Embedded Sensing to Embedded Control
  • Embedded in unattended “control systems”
    • Control network, and act in environment
  • Critical apps extend beyond sensing to control & actuation
    • Transportation, precision agriculture, medical monitoring and drug delivery, battlefield apps
    • Concerns extend beyond traditional networked systems and apps: usability, reliability, safety
  • Need systems architecture to manage interactions
    • Current system development: one-off, incrementally tuned, stove-piped
    • Repercussions for piecemeal uncoordinated design: insufficient longevity, interoperability, safety, robustness, scaling

Jim Kurose, UMass

why not simply adapt internet protocols end to end architecture
Why Not Simply Adapt Internet Protocols, “End-to-End” Architecture?
  • Internet routes data using IP Addresses in Packets and Lookup tables in routers
    • Humans get data by “naming data” to a search engine
    • Many levels of indirection between name and IP address
    • Embedded, energy-constrained (un-tethered, small-form-factor), unattended systems cant tolerate communication overhead of indirection
  • Special purpose system function(s): don’t need want Internet general purpose functionality designed for elastic applications

Jim Kurose, UMass

sample layered architecture
Sample Layered Architecture

User Queries, External Database

Resource constraints call for more tightly integrated layers

Open Question:

What are defining



In-network: Application processing, Data aggregation, Query processing

Data dissemination, storage, caching

Adaptive topology, Geo-Routing

MAC, Time, Location

Phy: comm, sensing, actuation, SP

Jim Kurose, UMass

  • Passive elements: seismic, acoustic, infrared, strain, salinity, humidity, temperature, etc.
  • Passive Arrays: imagers (visible, IR), biochemical
  • Active sensors: radar, sonar
    • High energy, in contrast to passive elements
  • Technology trend: use of IC technology for increased robustness, lower cost, smaller size
    • COTS adequate in many of these domains; work remains to be done in biochemical

Jim Kurose, UMass

fine grained time and location
Fine Grained Time and Location
  • Unlike Internet, node time/space location essential for local/collaborative detection
    • Fine-grained localization and time sync to detect events in 3D and compare detections across nodes
  • GPS provides solution where available (with diff-GPS providing finer granularity)
    • GPS not always available, too “costly,” too bulky
    • Other approaches under study
  • Localization of sensor nodes has many uses
    • Beamforming for localization of targets and events
    • Geographical forwarding
    • Geographical addressing

Jim Kurose, UMass

coverage measures
Area coverage: fraction of area covered by sensors

Detectability: probability sensors detect moving objects

Node coverage: fraction of sensors covered by other sensors


Where to add new nodes for max coverage

How to move existing nodes for max coverage

Coverage Measures




Given: sensor field (either known sensor locations, or spatial density)

Jim Kurose, UMass

in network processing
In-Network Processing
  • Communication expensive when limited
    • Power
    • Bandwidth
  • Perform (data) processing in network
    • Close to (at) data
    • Forward fused/synthesized results
    • e.g., find max. of data
  • Distributed data, distributed computation

Jim Kurose, UMass

distributed representation and storage












Distributed Representation and Storage
  • Data Centric Protocols, In-network Processing goal:
    • Interpretation of spatially distributed data (Per-node processing alone is not enough)
    • Network does in-network processing based on distribution of data
    • Queries automatically directed towards nodes that maintain relevant/matching data
  • Pattern-triggered data collection
    • Multi-resolution data storage and retrieval
    • Distributed edge/feature detection
    • Index data for easy temporal and spatial searching
    • Finding global statistics (e.g., distribution)

Jim Kurose, UMass

directed diffusion data centric routing
Directed Diffusion: Data Centric Routing
  • Basic idea
    • Name data (not nodes) with externally relevant attributes: data type, time, location of node, SNR,
    • Diffuse requests and responses across network using application driven routing (e.g., geo sensitive or not)
    • Support in-network aggregation and processing
  • Data sources publish data, data clients subscribe to data
    • However, all nodes may play both roles
      • Node that aggregates/combines/processes incoming sensor node data becomes a source of new data
      • Node that only publishes when combination of conditions arise, is client for triggering event data
    • True peer to peer system?

Jim Kurose, UMass

future of the internet2
Future of the Internet
  • Mobile IP
  • Networked Everything: Sensor Nets
  • Internet Economics
the big picture
The Big Picture


Structure &






Producer Surplus

Consumer Surplus

Social Surplus

Welfare (surplus)

John Chueng