Ubiquitous Computing

Max Mühlhäuser, Iryna Gurevych (Editors)

Part II : ConnectivityChapter 9: Opportunistic Networks

Andreas Heinemann

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UbiquitousComputing

Opportunistic Networks:

Motivation

new network type called Opportunistic Networks emerges based on spontaneous interaction and collaboration among

devices and users

Short/medium range wireless communication technologiescapture the mass-market, e.g.

• Bluetooth enabled mobile phones• WiFi enabled PDAs• WiFi enabled mobile phones

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Opportunistic Networks:

Application Example

Opportunistic Networks help to make people aware of each other

Support data dissemination similar to word-of-mouth communication

At a computer science conference site, researchers from all around the world stay together for 2 – 3 days to discuss recent advances in their fields. Due to the limited time, each attendee tries to make his stay as beneficial as possible, for example, by talking to colleagues during coffee breaks. For novices in research there might be the question “Who should I talk to?” or “Which other attendees are working on similar research problems?”

By carrying a Bluetooth enabled mobile phone, the device is able to communicate with nearby devices carried by others in order to look for interesting conversational partners. Once the devices have discovered a match in research interests, the devices notify their owners and the owners are able to switch to a face-to-face communication due to the short communication range.

The devices might also exchange information, for example, paper reading lists, without user notification. By this, each attendee would learn about what other researchers are currently working on.

After the conference is over, this information is carried back home and the attendee might share this information with colleagues at his research institute, again, by using his mobile phone and without notice.

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Opportunistic Networks:

Underlying Ideas and Concepts

• User vicinity exploitation

• Profile based user interest expression

• Data dissemination

• Open and unrelated user group

• Unpredictable communication pattern

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Opportunistic Networks:

A Definition for Opportunistic Networks

Definition (Opportunistic Network) An opportunistic network is a network of wireless connected nodes. Nodes may be either mobile or fixed. Communication range between two connected nodes is within walking distance, i.e., 100–300 meters. The network topology may change due to node mobility or node activation and node deactivation. The nodes provide the following functionality:

– Node Discovery: A network node is able to discover other network nodes in direct communication range.

– One-hop Message Exchange: A node is able to send and receive arbitrary data in form of a message to or from any other node in direct communication range.

Definition (Opportunistic Network Node) An opportunistic network node consists of a device with short-range wireless communication capabilities. The device operates an opportunistic network application that uses a data sharing protocol for data dissemination. The data sharing protocol uses i) node discovery and ii) one-hop message exchange.

Definition (Mobile Node) A mobile node (or node for short) consists of a user carrying a mobile device that acts as an opportunistic network node.

Definition (Information Sprinkler) An Information Sprinkler (abbreviated IS) is a fixed opportunistic network node within the network. It is a device placed at a dedicated location, thus it is not mobile and not under direct user control. The Information Sprinkler uses the same data sharing protocol as other opportunistic network nodes.

Opp. Net.Node

MobileNode

Infor.Sprinkler

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Opportunistic Networks:

Vertical Architecture

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Opportunistic Networks:

MANETs for anonymous groups of humans?

• What is an incentive for B to route messages between A and C?

• Why should A and C trust and rely on node B for their communication?

A C

B

?

• MANET = multi-hop ad-hoc network• Sample application domains: Military, sensor networks, rescue scenarios• Key characteristic: Common goal, strong relationship

Opportunistic Networks:• One-hop communication to share information

– augmented with constrained propagation based on user profiles– mimics word-of-mouth communication between humans

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Opportunistic Networks:

P2P vs. MANET vs. Opp. Networks

Network Type

Layer Routing/Msg. Forwarding

Focus Node Mobility

Network Size

Community Dynamics

Node Relationship

P2P Application YES NO HIGH HIGH LOW

MANET Network YES YES LOW – MEDIUM

MEDIUM HIGH

Opp. Network

Application NO YES LOW MEDIUM LOW

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Opportunistic Networks:

Opportunistic Networks Applications – Two Types

Active Collaboration

• exploits physical proximity of users in order to support a face-to-face conversation

• device act as a link to the user• Examples: Lovegety (Iwatani, 1998), SpotMe (Shockfish SA

Switzerland, 2003), Nokia Sensor (Nokia, 2005)

Passive Collaboration

• disseminate data among nearby users without any user interaction

• digital form of word-of-mouth communiation• Examples: Datta, Quarteroni, and Aberer (2004), Görgen et al.

(2005), Khelil, Becker, Tian, and Rothermel (2002)

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Opportunistic Networks:

Opportunistic Network Example: iClouds

• Spontaneous one-hop network of humans

• Combines publish/subscribe with localized P2P networking

• Communication in user's vicinity– no infrastructure needed– spontaneous face-to-face meeting possible

• Digital items to share– by interest – using incentives – no a-priori need for user's attention

• more info: http://iClouds.tk.informatik.tu-darmstadt.de

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Opportunistic Networks:

Profile based data dissemination – Idea (iClouds)

• Information wish list (iWish)

• Information have list(iHave)

Looking for …

Offer…

Offer…

Looking

for …

Two basic data structures

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Opportunistic Networks:

iWish iHaveiWish iHave iWish iHave

User B User CUser A

t1 , L1≠most cases: to , L0

user profile

Multi-Hop Information Dissemination (iClouds)

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Opportunistic Networks:

Human Factors

Recall: Opportunistic Networks are formed by humans carrying a personal device and potentially pass sensitive information without notice.

Privacy Issues

Q: How to protect a a user's privacy?

Incentive Issues

Q: Why should a user contribute with a personal device to a network? What is his benefit?

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Opportunistic Networks:

Privacy – Degrees of User Identifiability

• Identity: A user that communicates with others and reveals any piece of information that can be used to clearly identify him, is said to work under his identity.

• Pseudonymity: This is the ability to prove a consistent identity without revealing a user’s real identity, instead using a pseudonym. (The harder it is to reveal the pseudonym of a user, the closer we are to the state of not being identifiable at all, thus acting anonymously)

• Anonymity: Anonymity is the ability to remain unidentifiable within a set. A user acts anonymously if it is impossible to reveal his identity.

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Opportunistic Networks:

Privacy Preservation in iClouds

• Attention: All network layers need to be taken into account

Appl. layera number of self generated aliases

TCP/IP dynamic IP Addresses

802.11 WIFI dynamic MAC AddressesTyp

ical

net

wor

k st

ack

B CA my ID is Dmy ID is B D

• Make use of dynamtic IDs during communication• Idea

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UbiquitousComputing

Opportunistic Networks:

An Incentive Scheme Example

Basic Idea• The incentive scheme rewards users (bearers) who

partly help to carry a piece of information from an information producer to an information consumer.

Roles• Information Producer• Information Bearer• Information Consumer

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Opportunistic Networks:

Incentive Scheme Implementation: AdPASS(Straub & Heinemann, 2004)

• AdPASS is a concrete Opportunistic Network application based on iClouds

• Disseminates digital advertisements according to user preferences (iWish/iHave)

• Bonus point reward for all peoplecarrying the ad to a buyer

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Opportunistic Networks:

CA B

CB

A

vendors disseminate digital ads via radio to customerscustomers pass on the ad when meeting in the streetcustomer returns to store and buys the productvendor informs mediator about bonus pointscustomers sync their bonus points via internet

customer A B C

bonus 2 5 3

AdPASS: Participants & Communication Model

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Opportunistic Networks:

Security Goals in AdPASS

Authentication• assure that the information was issued by the claimed

information producer and not forged

Non-repudiation• prevent an information producer from denying that he has

issued a certain piece of information

Integrity• information integrity• integrity of the bearer chain

Anonymity• of information bearers in order to prevent an attacker from

creating user profiles

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Opportunistic Networks:

Security Solutions in AdPASS (Overview)

Goal Technique

Integrity Digital signature operation

Authentication Certificates

Non-Repudiation Qualified signatures and certificates

Anonymity Multiple key pairs as aliases

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Opportunistic Networks:

signed by A-

signed by P-

AdPASS: Integrity Protection of the Bearer Chain

• Make use of public key pairs (X+,X-) – X+ user alias

– X- for signature operation

P B

Sender.: A+

Receiver.: B+

Information

Sender.: P+

Receiver.: A+

P A B

signed by P-

Information

Sender.: P+

Receiver.: B+

10p

8p 2p

10p

10p

B's Attack: Remove A from chain

can't be forged by C without

knowledge of P-

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Opportunistic Networks:

• Iwatani, Y. (1998). Love: Japanese Style. Retrieved February 2, 2007 from http://www.wired.com/news/culture/0,1284,12899,00.html

• Shockfish SA Switzerland. (2003). The SpotMe Homepage. Retrieved February 2, 2007 from http://www.spotme.ch Nokia. (2005). Nokia Sensor. Retrieved February 2, 2007 from http://www.nokia.com/sensor

• Datta, A., Quarteroni, S., & Aberer, K. (2004). Autonomous Gossiping: A Self-Organizing Epidemic Algorithm for Selective Information Dissemination in Wireless Mobile Ad-Hoc Networks. Lecture Notes in Computer Science, 3226, 126–143.

• Görgen, D., Frey, H., & Hutter, C. (2005). Information Dissemination Based on the En-Passent Communication Pattern. In Kommunikation in verteilten systemen (kivs 2005) (pp. 129–141).

• Khelil, A., Becker, C., Tian, J., & Rothermel, K. (2002). An Epidemic Model for Information Diffusion in MANETs. In Mswim ’02: Proceedings of the 5th acm international workshop on modeling, analysis, and simulation of wireless and mobile systems (pp. 54–60). New York, NY, USA: ACM Press.

• Straub, T., & Heinemann, A. (2004). An Anonymous Bonus Point System For Mobile Commerce Based On Word-Of-Mouth Recommendation. In L. M. Liebrock (Ed.), Applied computing 2004. proceedings of the 2004 acm symposium on applied computing (pp. 766–773). New York, NY, USA: ACM Press.

• Heinemann. A (2007) Collaboration in Opportunistic Networks Ph.D. Thesis, University of Technology, Darmstadt, 2007. http://elib.tu-darmstadt.de/diss/000834

Literature