IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 56, NO. 6, NOVEMBER 2007 3511
Minimum-Cost Data Delivery in Heterogeneous
Wireless Networks
Haining Chen, Student Member, IEEE, Hongyi Wu, Member, IEEE, Sundara Kumar, Student Member, IEEE,
and Nian-Feng Tzeng, Senior Member, IEEE
Abstract—With various wireless technologies developed over
the past few years, a ubiquitous and integrated architecture is
envisioned for future wireless communication. An important op-
timization issue in such an integrated system is how to minimize
the overall communication cost by intelligently utilizing the avail-
able heterogeneous wireless technologies while, at the same time,
meeting the quality-of-service requirements of mobile users. In
this paper, we first identify the cost-minimization (CM) problem
to be NP-hard. We then present an efficient minimum-cost data-
delivery algorithm based on linear programming (LP), with var-
ious constraints, such as channel bandwidth, link costs, delay
budgets, and user mobility, taken into consideration. In case of
insufficient bandwidth for communication with the core network,
prefetch is employed to fully utilize the wireless-network capacity.
If multiple routes are available, a probability-based approach is
taken for CM. Extensive simulations are carried out to evaluate
the proposed CM scheme. Our results show that the proposed
LP approach can effectively reduce the overall communication
cost, with small overhead (< 3%) for signaling, computing, and
handoff. We expect that minimum-cost data delivery will become
imperative for the future heterogeneous wireless networks and the
emerging 4G wireless systems.
Index Terms—Cost minimization (CM), heterogeneous wireless
networks, linear programming (LP), quality of service (QoS).
I. I NTRODUCTION
W
ITH VARIOUS network characteristics and commercial
concerns, a number of wireless technologies have been
developed over the past few years, and they are likely to coexist
for many years to come. For example, the cellular systems
[1]–[3] have evolved from the first-generation analog system
to the second-generation digital system, and they are presently
entering the era of 3G that supports not only voice but also
data traffic at a speed of up to 2 Mb/s, while the 4G system is
under development for achieving a data rate that is ten times
higher. On the other hand, a series of complementary IEEE
standards, including 802.20 [4], 802.16e [5], 802.16 [6], 802.11
[7], and 802.15 [8], have been developed or are currently under
development to effect data communication in mobile and fixed
broadband wireless-access networks, local- and metropolitan-
Manuscript received November 24, 2005; revised December 24, 2006 and
February 4, 2007. This work was supported in part by the U.S. Department of
Energy (DoE) under Award DE-FG02-04ER46136, by the Board of Regents,
State of Louisiana, under Contract DOE/LEQSF(2004-07)-ULL, and by the
National Science Foundation CAREER Award under Award CNS-0347686.
The review of this paper was coordinated by Prof. T. Hou.
The authors are with the Center for Advanced Computer Studies, University
of Louisiana, Lafayette, LA 70504 USA (e-mail: hxc5633@cacs.louisiana.edu;
wu@cacs.louisiana.edu; sxk6124@cacs.louisiana.edu; tzeng@cacs.louisiana.
edu).
Digital Object Identifier 10.1109/TVT.2007.901049
area networks, and personal-area networks, respectively. In
particular, 802.20 and 802.16e target at mobile broadband
wireless-access networks, providing users moving at vehicular
speed with a data rate from 1 to 30 Mb/s in a wide area. 802.16
offers fixed broadband wireless-access network with data rate
up to 75 Mb/s, which can be allotted to T1-level connections
for business customers and/or to the best effort DSL-speed
connections for home customers. 802.11 supports low-mobility
users in small cells, at the data rates varying from 1 to 54 Mb/s.
Recently, this cost-effective technology is being deployed ag-
gressively for establishing metro-scale “cellular WiFi” net-
works [9] to support seamless Internet access in urban areas. In
addition to aforementioned terrestrial communication systems,
the satellite [10] is a vital component in the wireless system,
providing global coverage and high-speed data transmission.
While most of these wireless technologies are deployed
independently for now, the service providers have most interest
to own and operate overlaid heterogeneous wireless systems,
which integrate multiple wireless technologies with partially
overlapped coverage areas and provide ubiquitous network ser-
vice to mobile users. For example, several mobile carriers such
as Verizon, Sprint PCS, and T-Mobile are anxious to include
wireless LAN (or WiFi) access among their service offerings.
In order to access various wireless networks/technologies, the
mobile host (MH) may be equipped with one or multiple
programmable wireless-interface card(s) (e.g., based on the
programmable radio technology [11], [12] or an approach
similar to mobile-access router [13]), resulting in twofold flex-
ibility that may enable the optimization of data delivery: 1) An
MH may select one of multiple available wireless-access tech-
nologies at a particular location, because one area may be
covered by multiple wireless networks with different costs,
data rates, and mobility-support capabilities, and 2) an MH
may use different access technologies when it travels in the
network and arrives at different locations covered by various
wireless networks. From the standpoint of the service provider,
it is an important issue to minimize the overall communication
cost by intelligently using the available heterogeneous wireless
technologies.
In this paper, we consider a typical scenario where an
MH X is involved in massive data transmission while travel-
ing (or staying, as a special case). For example, MH X may
participate in a large peer-to-peer (P2P) network, where the
members share resources such as movie files [14], [15]. Given
the large data volume and the limited link capacity, a long data-
transmission time (e.g., up to hours) may be expected, during
which MH X needs to serve as either a receiver or a data
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