Mobile and Wireless Networks:
Retrospective and Remaining Challenges
Jie Wu
Department of Computer and Information Sciences
Temple University
Wireless and Mobile Networks

Dead-end or the Dawn of a New Ear?


Not dead-end
Greatest Opportunities Ahead
 Theory


Mobility: model and applications
Applications

Mobile video and mobile cloud
Mobility: Friend or Foe

Routing capability

Foe in dense mode (MANETs)

Friend in sparse mode (DTNs)

Network capacity

Security

Sensor coverage

Information dissemination (mobile pub/sub)

Reducing uncertainty in reputation systems
PSU
Graph Models for Dynamic Networks

Movement-Assisted Routing in DTNs
 Store

Carry

Forward
ICCCN 2011 Panel
Applications

Node movement



Vehicular networks (VANETs)
Social contact networks (SCNs)
Edge dynamic


Wireless sensor networks (WSNs)
• duty cycle
u
Cognitive radio networks (CRNs)
v
• primary users (PU) and secondary users (SU)
pu: {c}
su1: {1, 2}
su2: {1, 2, c}
Connectivity
(u,v) - connectivity under time-space view
View window
• All i, (u(i), v(i))
Time
Space
• Exist i, (u(i), v(i))
u
View(i)
• Exist i, j, (u(i), v(j))
ICCCN 2011 Panel
v
View(i+1)
View(j)
Evolving Graph and Extensions

Time sequence: t1, t2, ..., tL

Gi = (Vi, Ei): subgraph in [ti, ti+ Δ]

Evolving graph: (V, E), where
(u,v) = {i | (u, v) є Ei} (i: label)
ICCCN 2011 Panel

Weighted evolving graph
(u, v) = {(i, wi) | (u, v) є Ei}
where weight wi: bandwidth,
reliability, and latency
Optimization Problems
Optimization

Minimum-hop

Earliest-completion

Maximum-bandwidth

Fastest

Maximum-reliability
ICCCN 2011 Panel
Solution: Slicing and Virtualization


Slicing
 Partition G into G1, G2, …, Gi
 Select the best among i solutions for Gi
Virtualization
Enlarge G to G’ through virtualization
 Solve G’ which includes a solution for G

Mobile video

Popularity of mobile devices



Smartphones (Android and iPhone platforms)
Netbooks and tablets
Popularity of mobile video



…
From 2009 – 2014, mobile traffic is predicted to increase 39
times
66% of this traffic expected to be video by 2014
Key technologies and players
 WiMax. Clearwire/Sprint, Korean Telecom, and UQ/KDDI
(Japanese)

LTE. NTT, DoCoMo, Verizon, T-Mobile, AT&T, China TelecomUnicom, and KDDI
Wireless at Temple University

Metropolitan WiMax deployment

Joint project with Drexel University and City of Philadelphia.

Our goal:


Provide wireless coverage for downtown Philadelphia.
Various projects (later).
Research projects

Tourist applications using city-wide WiMax

WiMax centric bodynet for telemedicine

Content delivery network using WiMax

WiMax mobile surveillance for law enforcement

WiMax enhanced mobile urban sensing
Wireless at Temple University


Why WiMax?

Only choice within GENI.

Need vendor support. Currently, only NEC.
Why Philadelphia?

Digital Philadelphia. Gigabit city vision.

Existing/proposed wireless infrastructure. e.g. 4.9
GHz Wimax video surveillance, 700 MHz LTE citywide
overlay.