cot 6930 ad hoc networks (part iii)

Jie WuDepartment of Computer Science and EngineeringFlorida Atlantic UniversityBoca Raton, FL 33431

COT 6930 Ad Hoc Networks (Part III)

Table of Contents

Introduction Infrastructured networks

Handoff location management (mobile IP) channel assignment

Table of Contents (cont’d.)

Infrastructureless networksWireless MAC (IEEE 802.11 and Bluetooth)SecurityAd Hoc Routing ProtocolsMulticasting and Broadcasting

Table of Contents (cont’d.) Infrastructureless networks (cont’d.)

Power Optimization Applications

Sensor networks and indoor wireless environments

Pervasive computing Sample on-going projects

SecuritySecurity goals (Zhou and Hass, IEEE Network,

1999): Availability

Survivability of network services despite denial of service attacks

Confidentiality Certain information is never disclosed to

unauthorized entities Integrity

Message being transferred is never corrupted

Security Authentication

• Enables a node to ensure that the identity of the peer node it is communicating with.

Non-repudiation• The origin of a message cannot deny

having sent the message

Security Challenges in ad hoc network

security 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

Security Type 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.

Security Some objectives:

Ad hoc networks should have a distributed architecture with no central entities to achieve high survivability

Because of frequent changes in topology, trust relationship among nodes in ad hoc networks also changes.

Security mechanisms should be scalable to handle a large network.

Security

Sample security attacks: Passive eavesdropping Active impersonation Message reply Message distortion

Security Traditional approaches

Authentication protocols Digital signature Encryption

Security Secure key management

Threshold cryptography• The public key is known to all whereas the

private key is divided into n shares.• Decentralized Certification Authority to

distribute key pairs.• The private key can be constructed with

any subset of shares of certain sizes.

Security Proactive security

• Share refreshing: servers compute new shares from old ones in collaboration without disclosing the service private key to any server

Asynchrony• Cannot distinguish a compromised server from a

correct but slow one• Weak consistency: do not require that the correct

servers to be consistent after each operation; instead, only enough correct servers need to be up-to-date.

Security Secure routing

External attack: injecting erroneous routing information or distorting routing information

Internal attack: compromised node advertise incorrect routing information (similar to the Byzantine general problem)

SecuritySecurity problems in AODV and DSR

(Dahill, UM-CS-2001-037) 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)

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

Power Optimization

Two related goals (Toh, IEEE Comm. Mag. 2001)

Saving overall energy consumptions in the networks

Prolong life span of each individual node

Power Optimization

Source of Power Consumption (Singh et al, MobiCom 1998) Communication cost

• Transmit• Receive• Standby

Computation cost

Power-Aware Routing Wu et al’s 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

Location-Based Routing Let P(dis) represent the power

consumption of transmitting with distance dis

Stojmenovic et al’s 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))

Adjustable Transmission Ranges Power level of a transmission can be

chosen within a given range of values

Transmission cost: where a=2 or 4.

ddisP )(

Uniform Transmission Range

Problem: Use a minimum uniform transmission range to connect a given set of points

Greedy algorithms Binary search Kruskal’s MST (Ramanathan & Rosales-Hain,

ICC 2000) Prim’s MST (Dai & Wu, FAU 2002)

Power Optimization

Kruskal’s 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.

Power Optimization

Prim’s 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.

Non-uniform transmission range

Wireless multicast advantage (Wieselthier, Infocom 2000):

where is power needed between node i and node j

},max{),,( ijikkji PPP

ijP

Non-uniform transmission range

S broadcasts to two destinations: D1 and D1 (r1=dis(s, D1), and r2=dis(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

Non-uniform transmission range Use “direct” if angle between

whererr ,cos21

21 randr

Non-uniform transmission range Broadcast incremental power

algorithm (Wieselthier Infocom 2000) Standard Prim’s 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.

Non-uniform transmission range Other algorithms

Broadcast least-unicast-cost algorithm Broadcast link-based MST algorithm

The sweep: removing unnecessary transmissions

Non-uniform transmission range Extensions to directional antennas (Wieselthier, Infocom 2002)

Energy consumption:

Extended power incremental algorithm

300

r

Non-uniform transmission range Possible extensions

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

Non-uniform transmission range Incorporation of resource limitation

Bandwidth limitation• Greedy frequency assignment, but cannot

ensure coverage (when running out of frequencies)

Energy limitation

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EPP

i

iijij

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)

Sensor Networks

Military applications: (4C’s) Command, control,

communications, computing Intelligence, surveillance,

reconnaissance Targeting systems

Sensor Networks Health care

• Monitor patients• Assist disabled patients

Commercial applications• Managing inventory• Monitoring product quality• Monitoring disaster areas

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 < 0.5 Ah, 1.2 V)

Sensor Networks Sample problems

Coverage and exposure problems Data dissemination and gathering

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

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.

Coverage and Exposure Problems A sample Voronoi diagram

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.

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

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

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.

),(

),(psdis

psS

Coverage and Exposure Problems Exposure problem: integral of the sensing

function

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

Dijkstra’s algorithm.

Coverage and Exposure Problems First, second, and third-order generalized 2*2 grid

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.


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

route


Sample data aggregation protocols SMECN (Li and Halpern, ICC’01) SPIN (Heinzelman et al, MobiCom’99) SAR (Sohrabi, IEEE Pers. Comm., Oct. 2000) Directed Diffusion (Intanagonwiwat et al,

MobiCom’00) Linear Chain* (Lidsey and Raghavendra, IEEE

TPDS, Sept. 2002) LEACH * (Heinzelman et al, Hawaii Conf. 2000)


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


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


Sequential gathering in a linear chain


Parallel gathering (recursive double)


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


Multiple Chains


Simple chain (new node as head of chain)


Simple chain (new node inserted in the chain)


LEACH


Extended LEACH (energy-based)

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/)

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.

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).

Bluetooth

Basic facts Operates in the unlicensed Industrial-Science-

Medical (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.

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.

Bluetooth: Basic Structure

Open problem: a method for forming an efficient scatternet under a practical networking scenario.

Two methods: Bluetree and Bluenet

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.


Blueroot Grown Bluetrees (sample)


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 (Wu and ?, 2003) Using neighbors’ neighbor sets. Using neighbor locations.


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).


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.


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).


Distributed bluetree (sample)


Overflow problem (Wu)

Solution: slot reservation (up to 6 slaves)

u v

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)


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 aquire some number of slaves (not too many or too few).


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?

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).

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.

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).

On-going projects Basics of P2P protocols (cont’d)

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.

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.

On-going projects Sensor nodes

Smart dust (http://robotics.eecs.berkeley.edu/~pister/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.

On-going projects Sensor nodes

Smart dust (http://robotics.eecs.berkeley.edu/~pister/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/)

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)

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)

On-going projects Distributed Algorithms

SCADDS (Scalable Coordination Architectures for Deeply Distributed Systems) (http://www.isi.edu/scadds)• Directed diffusion, adaptive fidelity,

localization, time synchronization, self-configuration, and sensor-MAC

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).

On-going projects Distributed query processing

COUGAR device database project (http://www.cs.cornell.edu/database/cougar/index.htm)

Database (http://cs.rutgers.edu/dataman/)

On-going projects Security for Sensor Networks

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

cot 6930 ad hoc networks (part iii)

Documents

ieee network

service private key

network securitythe

key pairs

large network

compromised node

correct servers

erroneous routing information