Jie Wu

1
COT 6930 Ad Hoc Networks (Part III)

• Jie Wu
• Department of Computer Science and Engineering
• Florida Atlantic University
• Boca Raton, FL 33431

2
Table of Contents

• Introduction
• Infrastructured networks
• Handoff
• location management (mobile IP)
• channel assignment

3
Table of Contents (contd.)

• Infrastructureless networks
• Wireless MAC (IEEE 802.11 and Bluetooth)
• Security
• Ad Hoc Routing Protocols
• Multicasting and Broadcasting

4
Table of Contents (contd.)

• Infrastructureless networks (contd.)
• Power Optimization
• Applications
• Sensor networks and indoor wireless environments
• Pervasive computing
• Sample on-going projects

5
Security

• Availability
• Survivability of network services despite DoS
  attacks
• Confidentiality
• information is never disclosed to unauthorized
  entities
• Integrity
• Message being transferred is never corrupted
• Authentication
• Enables a node to ensure that the identity of the
  peer node it is communicating with.
• Non-repudiation
• The origin cannot deny having sent the message

6
Security Challenges

• The nodes are constantly mobile
• The protocols implemented are co-operative in
  nature
• There is a lack of a fixed infrastructure to
  collect audit data
• No clear distinction between normalcy and anomaly
  in ad hoc networks

7
Types of Attack

• External attack
• An attack caused by nodes that do not belong to
  the network.
• Internal attack
• An attack from nodes that belong to the network
  due to them getting compromised or captured.

8
Sample Security Attacks

• Routing attacks
• Action of advertising routing updates that does
  not follow the specifications
• Examples add/delete a node in the path,
  advertise a route with smaller (larger) distance
  metric (timestamp)
• Packet forwarding attacks
• Packets are not delivered consistently based on
  routing states.
• Examples drop the packet, inject junk packets

9
Security Problems in DSR and AODV

• Remote redirection
• Sequence number (AODV)
• Hop count (AODV)
• Source route (DSR)
• Spoofing (impersonation) (AODV and DSR)
• Fabrication
• Error message (AODV and DSR)
• Source route (DSR)

10
Security Solutions

• Routing attacks
• Traditional cryptography (preventive)
• message authentication primitives
• secured ad hoc routing
• Challenges cost, key management
• Packet forwarding attacks
• Watchdog (detective)
• Challenges blackmail attacks

11
Sample Solutions

• Property Techniques
• Timeliness Timestamp
• Ordering Sequence Number
• Authenticity Password, Certificate
• Authorization Credential
• Integrity Digest, Digital Signature
• Confidentiality Encryption
• Non-repudiation Chaining of digital signatures

12
Sample Distance Metric

• Hop count hash chain (Hu et al03)
  h0,h1,hn
• hiH(hi-1) and H is a known one-way hash function
• hn is added to the routing message and the ith
  node along a path has hi
• When a node receives an RREQ or RREP with
  (Hop_Count, hx), it checks
• hn Hn-Hop_Count(hx)
• Hm(.) means applying the H function m times

13
(V) Special Challenges

• Survivability
• Ad hoc networks should have a distributed
  architecture with no central entities to achieve
  high survivability
• Scalability
• Security mechanisms should be scalable to handle
  a large network
• Trust
• Because of frequent changes in topology, trust
  relationship among nodes in ad hoc networks also
  changes

14
Sample Survivability Solution

• Threshold cryptography (Zhou and Haas99)
• The public key is known to all whereas the
  private key is divided into n shares
• Decentralized CA to distribute key pairs
• The private key can be constructed with any
  subset of shares of certain sizes
• Proactive security Share refreshing
• Servers compute new shares from old ones in
  collaboration without disclosing the service
  private key to any server

15
Scalable Design

• Partition the network into groups
• Each group group head group members
• Group heads form a dominating set (DS)
• Also an independent set (IS) to guarantee a
  constant bound
• Also connected (CDS) to ensure routing within the
  heads.

16
Scalable Design (Cont)
17
Scalable Design (Cont)

• Resurrecting duckling transition association
  (Stajano and Anderson99) within a group
• A duckling considers the first moving object it
  sees as its mother
• Transient master-slave relationship
• When a node is deactivated, it goes back to the
  pre-birth stage and can be reborn through another
  imprint (resurrection)

18
Trust Building (Zhou and Wu03)

• An ad hoc network cannot succeed without trust
  within
• Nodes are trustworthy if they have
• integrity, and
• proper capability

19
Trust between entities

• CA certification authority

20
Trust between entities

• Trust is the conjunction of integrity and
  capability
• Integrity, capability, and trust can be
  recommended

21
Group Trust

• A group G for task x is functional if there is a
  mutual trust within the group
• Where two groups trust each other, then the join
  group is functional

22
A Terrorist Network

• From Krebs Mapping Networks of Terrorist Cells
  (Connections, 24(3) 43-52, 2002)

23
A Terrorist Network (Cont)
24
A Terrorist Network (Cont)
25
A Terrorist Network (Prior Contacts Meeting
ties shortcuts)
26
A Terrorist Network (Network Neighborhood)
27
Operation Policy

• Information sharing
• Minimum information was shared to other members
  whose tasks necessitated their knowledge.
• Knowledge of a lower-level task group was a
  subset of that of a higher-level task group.
• Communication
• Confidential and authentic within the group.
• Three type of inter-group communications.
• Redundancy

28
Subjective Logic (Josang01)

• Subjective logic as a trust model
• A logic which operates on subjective beliefs
  about the world, and uses the term opinion to
  denote the representation of a subjective belief
• ?A(B) (bA(B), dA(B), uA(B))
• view of A on B, with bdu 1, where b is
  belief, d disbelief, and u uncertain

29
Subjective Logic (Cont)

• Trust represention and manipulations
• Opinion, Mapping, Discounting Combination,
  Consensus Combination, etc.
• Discounting combination
• If ?A(B) (bA(B), dA(B), uA(B)) and ?B(C)
  (bB(C), dB(C), uB(C)) then ?AB(C) (bAB(C),
  dAB(C), uAB(C))
• bAB(C) bA(B) bB(C),
• dAB(C), bA(B) dB(C), and
• uAB(C) dA(B) uA(B) bA(B) uB(C)
• As opinon about C as a result of Bs
  advice to A

30
Open Problems and Opportunities

• Can preventive methods (cryptography) provide a
  cost-effective solution?
• Hybrid approach cryptography trust model.
• Multi-fence security solution resiliency-oriented
  design.
• Multi-level approach application, transport,
  network, link, and physical
• (link layer jam-resistant communications using
  spread-spectrum and frequency-hopping)

31
Open Problems and Opportunities (Cont)

• New approach incentive-based approaches (to
  avoid free riders)
• Credit mechanism (micro payment)
• Exchange or barter economy (n-way exchange)
• Game theory (Prisoners Dilemma game)

32
Conclusions

• Research in secured routing in ad hoc networks is
  still in its early stage.
• Is security in ad hoc networks a problem with no
  technical solution?
• Technical solution one that requires a
  change only in the techniques of the natural
  sciences, demanding little or nothing
• in the way of change in human values or
  ideas of morality.
• From Hardins The Tragedy of the Commons,
  1968

33
Power Optimization

• Network Longevity (Wieselthier, Infocom 2002)
• Time at which first node runs out of energy
• Time at which first node degrades below an
  acceptable level
• Time until the network becomes disconnected
• High throughput volume
• High total number of bits delivered

34
Power Optimization

• Two related goals (Toh, IEEE Comm. Mag. 2001)
• Saving overall energy consumptions in the
  networks
• Prolong life span of each individual node

35
Power Optimization

• Source of Power Consumption (Singh et al, MobiCom
  1998)
• Communication cost
• Transmit
• Receive
• Standby
• Computation cost

36
Power-Aware Routing

• Wu et als Power-aware marking process (Wu et al,
  ICPP 2001)
• Use energy level as priority in Rule 1 and Rule 2
  of marking process
• Balance the overall energy consumption and the
  lifespan of each node

37
Location-Based Routing

• Let P(dis) represent the power consumption of
  transmitting with distance dis
• Stojmenovic et als greedy method (Stojmenovic et
  al, IPDPS 2001)
• Each node knows the location of destination and
  all its neighbors
• Source s selects a neighbor n to reach
  destination d with minimum P(dis(s,n))P(dis(n,d))
  

38
Adjustable Transmission Ranges

• Power level of a transmission can be chosen
  within a given range of values
• Transmission cost
• where a2 or 4.

39
Power Optimization

• Problem Each node selects a minimum transmission
  range subject to a global constraint (i.e.
  network connectivity)
• Heterogeneous most problems are NP-complete
• Homogeneous polynomial solutions exist

40
Uniform Transmission Range

• Problem Use a minimum uniform transmission range
  to connect a given set of points
• Greedy algorithms
• Binary search
• Kruskals MST (Ramanathan Rosales-Hain, ICC
  2000)
• Prims MST (Dai Wu, FAU 2002)

41
Power Optimization

• Kruskals MST
• Each node is initialized as a separate connected
  component
• Edges are sorted and traversed in non-decreasing
  order
• An edge is added to the MST whenever it connects
  any two connected components.

42
Power Optimization

• Prims algorithm
• The approach starts from an arbitrary root and
  grow a single tree until it spans all the
  vertices.
• At each step, an edge of lightest possible weight
  is added.

43
Non-uniform transmission range

• Wireless multicast advantage (Wieselthier,
  Infocom 2000)
• where is power needed between node i and
  node j

44
Non-uniform transmission range

• S broadcasts to two destinations D1 and D1
  (r1dis(s, D1), and r2dis(s, D2)).
• Direct S broadcasts to both at the same time
• Indirect S sends the packet to D1 which then
  relays the packet to D2

45
Non-uniform transmission range

• Use direct if
• angle between

46
Non-uniform transmission range

• Broadcast incremental power algorithm
  (Wieselthier Infocom 2000)
• Standard Prims algorithm
• Pair i, j that results in the minimum
  incremental power for i to reach j is selected,
  where i is in the tree and j is outside the tree.

47
Non-uniform transmission range

• Other algorithms
• Broadcast least-unicast-cost algorithm
• Broadcast link-based MST algorithm
• The sweep removing unnecessary transmissions

48
Non-uniform transmission range

• Extensions to directional antennas
• (Wieselthier, Infocom 2002)
• Energy consumption
• Extended power incremental algorithm

49
Non-uniform transmission range

• Possible extensions
• Fixed beamwidth
• Single beam per node
• Multiple beams per node
• Limited multiple beams per node
• Directional receiving antennas

50
Non-uniform transmission range

• Incorporation of resource limitation
• Bandwidth limitation
• Greedy frequency assignment, but cannot ensure
  coverage (when running out of frequencies)
• Energy limitation

51
Sensor Networks

• Sensor networks (Estrin, Mobicom 1999)
• Information gathering and processing
• Data centric data is requested based on certain
  attributes
• Application specific
• Energy constraint
• Data aggregation (also data fusion)

52
Sensor Networks

• Military applications
• (4Cs) Command, control, communications,
  computing
• Intelligence, surveillance, reconnaissance
• Targeting systems

53
Sensor Networks

• Health care
• Monitor patients
• Assist disabled patients
• Commercial applications
• Managing inventory
• Monitoring product quality
• Monitoring disaster areas

54
Sensor Networks

• Design factors (Akyildiz et al, IEEE Comm. Mag.
  Aug. 2002)
• Fault Tolerance (sustain functionalities)
• Scalability (hundreds or thousands)
• Production Cost (now 10, near future 1)
• Hardware Constraints
• Network Topology (pre-, post-, and re-deployment)
• Transmission Media (RF (WINS), Infrared
  (Bluetooth), and Optical (Smart Dust))
• Power Consumption (with lt 0.5 Ah, 1.2 V)

55
Sensor Networks

• Sample problems
• Coverage and exposure problems
• Data dissemination and gathering

56
Coverage and Exposure Problems

• Coverage problem (Meguerdichian, Infocom 2001)
• Quality of service (surveillance) that can be
  provided by a particular sensor network
• Related to to Art Gallery Problem (solved
  optimally in 2D, but NP-hard in 3D)
• Exposure problem (Meguerdichian, Mobicom 2001)
• A measure of how well an object, moving on an
  arbitrary path, can be observed by the sensor
  network over a period of time

57
Coverage and Exposure Problems

• Voronoi diagram of a set of points
• Partitions the plane into a set of convex
  polygons with such that all points inside a
  polygon are closest to only one point.

58
Coverage and Exposure Problems

• A sample Voronoi diagram

59
Coverage and Exposure Problems

• Delaunay triangulation
• Obtained by connecting the sites in the Voronoi
  diagram whose polygons share a common edge.
• It can be used to find the two closest points by
  considering the shortest edge in the
  triangulation.

60
Coverage and Exposure Problems

• Maximal breach path (worst case coverage)
• A path p connecting two end points such that the
  distance from p to the closest sensor is
  maximized
• Fact The maximal breach path must lie on the
  line segments of the Voronoi diagram.
• Solution binary search breadth-first search

61
Coverage and Exposure Problems

• Maximal Support Path (Best Case Coverage)
• A path p with the distance from p to the closest
  sensor is minimized
• The maximal support path must lie on the lines of
  the Delaunay triangulation

62
Coverage and Exposure Problems

• Exposure problem
• Expected average ability of serving a target in
  the sensor field
• General sensing model
• where s is the sensor and p the point.

63
Coverage and Exposure Problems

• Exposure problem integral of the sensing
  function

64
Coverage and Exposure Problems

• Minimal Exposure Path
• Transform the continuous problem domain to a
  discrete one.
• Apply graph-theoretic abstraction.
• Compute the minimal exposure path using
  Dijkstras algorithm.

65
Coverage and Exposure Problems

• First, second, and third-order generalized 22
  grid

66
Data Dissemination and Gathering

• Two different approaches
• Traditional reverse multicast/broadcast tree with
  BS as the sink (root).
• Three-phase protocol sinks broadcast the
  interest, and sensor nodes broadcast an
  advertisement for the available data and wait for
  a request from the interested nodes.

67
Data Dissemination and Gathering

• Energy-efficient route (Akyildiz, 2002)
• Maximum total available energy route
• Minimum energy consumption route
• Minimum hop route
• Maximum minimum available energy node route

68
Data Dissemination and Gathering

• Sample data aggregation protocols
• SMECN (Li and Halpern, ICC01)
• SPIN (Heinzelman et al, MobiCom99)
• SAR (Sohrabi, IEEE Pers. Comm., Oct. 2000)
• Directed Diffusion(Intanagonwiwat et al,
  MobiCom00)
• Linear Chain (Lidsey and Raghavendra, IEEE TPDS,
  Sept. 2002)
• LEACH (Heinzelman et al, Hawaii Conf. 2000)

69
Data Dissemination and Gathering

• SMECN
• Create a subgraph of the sensor network that
  contains the minimum energy path
• SPIN
• Sends data to sensor nodes only if they are
  interested has three types of messages (ADV,
  REQ, and DATA)
• SAR
• Creates multiple trees where the root of each
  tree is one hop neighbor from the sink select a
  tree for data to be routed back to the sink
  according to the energy resources and additive
  QoS metric

70
Data Dissemination and Gathering

• Directed diffusion
• Sets up gradients for data to flow from source to
  sink during interest dissemination (initiated
  from the sink)
• Linear Chain
• A linear chain with a rotating gathering point.
• LEACH
• Clusters with clusterheads as gathering points
  again clusterheads are rotated to balance energy
  consumption

71
Data Dissemination and Gathering

• Directed diffusion with several elements
  interests, data messages, gradients, and
  reinforcements
• Interests a query (what a user wants)
• Gradients a direction state created in each node
  that receives an interests
• Events flow towards the originator's of interests
  along multiple gradient paths
• The sensor network reinforces one, or a small
  number of these paths.

72
Data Dissemination and Gathering

• SPIN (Sensor Protocols for Information via
  Negotiation) efficient dissemination of
  information among sensors
• ADV new data advertisement containing meta-data
• REQ request for data when a node wishes to
  receive some actual data.
• DATA actual sensor data with a meta-data header

73
Data Dissemination and Gathering

• Sequential gathering in a linear chain

74
Data Dissemination and Gathering

• Parallel gathering (recursive double)

75
Data Dissemination and Gathering

• Enhancement
• Multiple chain
• Better linear chain formation
• New node always the new head of the linear chain
• New node can be inserted into the existing chain

76
Data Dissemination and Gathering

• Multiple Chains

77
Data Dissemination and Gathering

• Simple chain (new node as head of chain)

78
Data Dissemination and Gathering

• Simple chain (new node inserted in the chain)

79
Data Dissemination and Gathering

• LEACH

80
Data Dissemination and Gathering

• Extended LEACH (energy-based)

81
Sensor Coverage

• How well do the sensors observe the physical
  space
• Sensor deployment random vs. deterministic
• Sensor coverage point vs. area
• Coverage algorithms centralized, distributed, or
  localized
• Sensing communication range
• Additional requirements energy-efficiency and
  connectivity
• Objective maximum network lifetime or minimum
  number of sensors

82
Sensor Coverage

• Area (point)-dominating set
• A small subset of sensor nodes that covers the
  monitored area (targets)
• Nodes not belonging to this set do not
  participate in the monitoring they sleep
• Localized solutions
• With and without neighborhood information

83
Area-dominating set

• With neighborhood info (Tian and Geoganas, 2002)
• Each node knows all its neighbors positions.
• Each node selects a random timeout interval.
• At timeout, if a node sees that neighbors who
  have not yet sent any messages together cover its
  area, it transmits a withdrawal and goes to
  sleep
• Otherwise, the node remains active but does not
  transmit any message

84
Point-dominating set

• With neighborhood info based on Dai and Wus Rule
  k (Carle and Simplot-Ryl, 2004)
• Each node knows either 2- or 3-hop neighborhood
  topology information
• A node u is fully covered by a subset S of its
  neighbors iff three conditions hold
• The subset S is connected.
• Any neighbor of u is a neighbor of S.
• All nodes in S have higher priority than u.

85
Coverage without neighborhood info

• PEAS probabilistic approach (F. Ye et al, 2003)
• A node sleeps for a while (the period is
  adjustable) and decides to be active iff there
  are no active nodes closer than r.
• When a node is active, it remain active until it
  fails or runs out of battery.
• The probability of full coverage is close to 1 if
  
• r (1 ) r
• where r is the sensing (transmission) range

86
Indoor Environments

• Three popular technologies
• Wireless LANs (IEEE 802.11 standard)
• HomeRF (http//www.homerf.org/tech/, Negus et al,
  IEEE Personal Comm. Feb. 2000)
• Bluetooth (http//www.bluetooth.com/)

87
Indoor Environments

• Network topology
• Straightforward for 802.11WLAN and HomeRF (e.g.,
  In TDMA-based MAC protocol, a central entity is
  used to assign slots to the stations).
• The Bluetooth topology poses interesting
  challenges.

88
Bluetooth

• Bluetooth Special Interest Group (formed in July
  1997 with now 1200 companies).
• Major technology for short-range wireless
  networks and wireless personal area network.
• An enabling technology for multi-hop ad hoc
  networks.
• Low cost of Bluetooth chips (about 5 per chip).

89
Bluetooth

• Basic facts
• Operates in the unlicensed Industrial-Science-Medi
  cal (ISM) band at 2.45 GHz.
• Adopts frequency-hop transceivers to combat
  interference and fading.
• The nominal radio range 10 meters with a
  transmit power of 0 dBm.
• The extended radio range 100 meters with
  amplified transmit power of 20 dBm.

90
Bluetooth Basic Structure

• Piconet
• A simple on-hop star-like network
• A master unit
• Up to 7 active slave units
• Unlimited number of passive slave units.
• Scatternet
• A group of connected piconets
• A unit serves as a bridge between the overlapping
  piconets in proximity.

91
Bluetooth Basic Structure

• Open problem a method for forming an efficient
  scatternet under a practical networking scenario.
• Two methods Bluetree and Bluenet

92
Bluetooth Basic Structure

• Scatternet formation
• Connected scatternet
• Resilience to disconnections in the network
• Routing robustness (multiple paths)
• Limited route length
• Selection of gateway slaves (a salve being a
  neighbor of two maters)
• Small number of roles per node
• Self-healing (converge to a new scatternet after
  a topology change)

93
Bluetree (Zaruba, ICC 2001)

• Blueroot Grown Bluetrees
• The blueroot starts paging its neighbors one by
  one.
• If a paged node is not part of any piconet, it
  accepts the page (thus becoming the slave of the
  paging node).
• Once a node has been assigned the role of slave
  in a piconet, it initiates paging all its
  neighbors one by one, and so on.

94
Bluetree (Zaruba, ICC 2001)

• Blueroot Grown Bluetrees (sample)

95
Bluetree (Zaruba, ICC 2001)

• Limiting the number of slaves
• Observations if a node has more than five
  neighbors, then there are at least two nodes that
  are neighbors themselves.
• The paging number obtains the neighbor set of
  each neighbor.
• Balanced Bluetree (Dong and Wu, 2003)
• Using neighbors neighbor sets.
• Using neighbor locations.

96
Bluetree (Zaruba, ICC 2001)

• Distributed Bluetrees
• Speed up the scatternet formation process by
  selecting more than one root (phase 1).
• Then by merging the trees generated by each root
  (phase 2).

97
Bluetree (Zaruba, ICC 2001)

• Phase 1
• Each slave will be informed about the root of the
  tree.
• When paging nodes are in the tree, information of
  respective roots are exchanged.
• Each node having roles from the set M, S, (MS),
  where M for master and S for slave.

98
Bluetree (Zaruba, ICC 2001)

• Phase 2
• Merge bluetrees (pairwise)
• Each node can only receive at most one additional
  M, S, or MS.
• Each node having roles from the set M, S, (MS),
  (SS), (MSS) (note that (MM)M).

99
Bluetree (Zaruba, ICC 2001)

• Distributed bluetree (sample)

100
Bluetree (Zaruba, ICC 2001)

• Overflow problem (Wu)
• Solution slot reservation (up to 6 slaves)

101
Bluenet (Wang et al, Hawaii Conf. 2002)

• Drawbacks of bluetrees
• Lacks of reliability
• Lacks of efficient routing
• Parents nodes are likely to become communication
  bottleneck.
• Three types of nods in Bluenet
• Master (M), Slave (S), Bridge (M/S or S/S)

102
Bluenet (Wang et al, Hawaii Conf. 2002)

• Rule 1 Avoid forming further piconets inside a
  piconet.
• Rule 2 For a bridge node, avoid setting up more
  than one connections to the same piconet.
• Rule 3 Inside a piconet, the master tries to
  acquire some number of slaves (not too many or
  too few).

103
Bluenet (Wang et al, Hawaii Conf. 2002)

• Phase 1 Initial piconets formed with some
  separate Bluetooth nodes left.
• Phase 2 Separate Bluetooth nodes get connected
  to initial piconets.
• Phase 3 Piconets get connected to form a
  scatternet (slaves set up outgoing links).
• Dominating-set-based bluenet?

104
BlueStars (Petrioli et al, IEEE TR 2003)

• BlueStars (i.e., piconet) formation phase
• Clustering-based approach for master selection
• The formation of disjoint piconets
• Selection of gateway devices to connect multiple
  piconets
• Yao construction phase
• Yao procedure is used to ensuring the max number
  of node degree by removing links without losing
  connectivity
• BlueStars over the Yao topology

105
NeuRFon (Motorola Research Lab., ICCCN 2002)

• Build a reverse shortest path tree (w.r.t. a
  given root) through paging.
• Self-healing find a new parent with a
  lowest-level number (cloested to the root).

106
On-going projects

• Internet P2P applications (http//www.p2pwg.org)
• Distributed systems in which nodes of equal roles
  and capabilities exchanges information and
  services directly with each other.
• Servant for both server/client.
• Major issue efficient techniques for search and
  retrieval of data.
• Sample systems Gnutella, Napster, and Morpheus.

107
On-going projects

• Basics of P2P protocols
• Searching query-source sends query-send with
  file id through controlled flooding
• Network dynamic A peer joins the network through
  broadcast-send to select logical neighbors
  (neighborhood with short session duration, 2
  hours per day on average).
• Transferring files The query-source servant
  establishes the end-to-end communication with the
  file-source (datagram transmission after the file
  is fragmented in small pieces).

108
On-going projects

• Basics of P2P protocols (contd)
• Controlled flooding caches (query-id,
  query-source) to avoid duplicate query processing
  and uses TTL to prevents a message being
  forwarded infinitely.
• Neighborhood control uses the ping-pong
  protocol for maintaining up-to-date neighbors
  and issues broadcast-send to find another
  neighbor when the current one is lost.

109
On-going projects

• Sample P2P search protocols (ICDCS 2002)
• Iterative deepening multiple breadth-first
  searches with successively large depth limits.
• Directed BFS sending query messages to just a
  subset of its neighbors.
• Local indices each node maintaining an index
  over the data of all nodes.
• Mobile agents swarm intelligence the
  collection of simple ants achieve intelligent
  collective behavior.

110
On-going projects

• Sensor nodes
• Smart dust (http//robotics.eecs.berkeley.edu/pis
  ter/SmartDust)
• Autonomous sensing and communication in a cubic
  millimeter
• Macro motes 20 meter comm. range, one week
  lifetime in continuous op. and 2 years with 1
  duty cycling.

111
On-going projects

• Sensor nodes
• Smart dust (http//robotics.eecs.berkeley.edu/pis
  ter/SmartDust)
• Autonomous sensing and communication in a cubic
  millimeter
• Macro motes 20 meter comm. range, one week
  lifetime in continuous op. and 2 years with 1
  duty cycling.
• PicoRadio (http//bwrc.eecs.berkeley.edu/Research/
  Pico_Radio/PN3/)

112
On-going projects

• Power-Aware Ad Hoc and Sensor Networks
• µAMPS (µ-Adaptive Multi-domain Power aware
  Sensors) (http//www-mtl.mitedu/research/icsystems
  /uamps)
• Innovative energy-optimized solution at all
  levels of the system hiearchy
• PACMAN (http//pacman.usc.edu)

113
On-going projects

• Sensor Networks
• WINS (Wireless Integrated Network Sensors)
  (http//www.janet.ucla/WINS)
• Distributed network and internet access to
  sensors, controls, and processors that are deeply
  embedded in equipment.
• SensoNet (http//www.ece.gatech.edu/research/labs/
  bwn)

114
On-going projects

• Distributed Algorithms
• SCADDS (Scalable Coordination Architectures for
  Deeply Distributed Systems) (http//www.isi.edu/sc
  adds)
• Directed diffusion, adaptive fidelity,
  localization, time synchronization,
  self-configuration, and sensor-MAC

115
On-going projects

• Power conservation algorithms
• Span (Chen et al, MIT).
• PAMAS (Power Aware Multi Access protocol with
  Signaling for Ad Hoc Net works) (Singh, SIGCOMM,
  1999).

116
On-going projects

• Distributed query processing
• COUGAR device database project (http//www.cs.corn
  ell.edu/database/cougar/index.htm)
• Database (http//cs.rutgers.edu/dataman/)

117
On-going projects

• Security for Sensor Networks
• SPINS (Security Protocols for Sensor Networks)
  (http//www.ece.cmu.edu/adrian/project.html)