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Characterizing Geospatial Dynamics of Application Usage in a 3G Cellular Data Network
Jeffrey Pang, Jia Wang, Lusheng Ji, Zubair Shafiq, Alex X. Liu
IEEE INFOCOM 2012,
2012.
[PDF]
[BIB]
IEEE Copyright
This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in IEEE INFOCOM 2012. , 2012-03-25
(c) ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Internet Measurement Conference 2011. , 2012-03-25.
{Recent studies on cellular network measurement have provided the evidence that significant geospatial correlations, in terms of traffic volume and application access, exist in cellular network usage. Such geospatial correlation patterns provide local optimization opportunities to cellular network operators for handling the explosive growth in the traffic volume observed in recent years. In this paper, we aim to characterize the geospatial dynamics of application usage in a 3G cellular data network. Our analysis is based on two simultaneously collected traces from the radio sub-network (containing location records) and the core sub-network (containing traffic records) of an operational cellular network in the United States. To better understand the application usage in our data, we first cluster cell locations based on their application distributions and then study the geospatial dynamics of application usage across different geographical regions. Our study reveals that the cell clustering results are significantly different for traffic volume in terms of byte or packet count, session count, and unique user count distributions across different geographical regions. The results of our measurement study present operators with fine-grained opportunities to tune network parameter settings. However, our results also suggest that care should be exercised so that cells are not optimized solely with respect to traffic volume based on byte or packet count, or session count because this may negatively impact other low volume applications that most users in those cells use.}

A First Look at Cellular Machine-to-Machine Traffic – Large Scale Measurement and Characterization
Zubair Shafiq, Lusheng Ji, Alex Liu, Jeffrey Pang, Jia Wang
SIGMETRICS,
2012.
[PDF]
[BIB]
ACM Copyright
(c) ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in 2012 , 2012-06-11.
{Cellular network based Machine-to-Machine (M2M) communication is fast becoming a market-changing force for a wide spectrum of businesses and applications such as telematics, smart metering, point-of-sale terminals, and home security and automation systems. In this paper, we aim to answer the following important question: Does traffic generated by M2M devices impose new requirements and challenges for cellular network design and management? To answer this question, we take a first look at the characteristics of M2M traffic and compare it with traditional smartphone traffic. We have conducted our measurement analysis using a week-long traffic trace collected from a tier-1 cellular network in the United States. We characterize M2M traffic from a wide range of perspectives, including temporal dynamics, device mobility, application usage, and network performance.
Our experimental results show that M2M traffic exhibits significantly different patterns than smartphone traffic in multiple aspects. For instance, M2M devices have a much larger ratio of uplink to downlink traffic volume, their traffic typically exhibits different diurnal patterns, they are more likely to generate synchronized traffic resulting in bursty aggregate traffic volumes, and are less mobile compared to smartphones. On the other hand, we also find that M2M devices are generally competing with smartphones for net- work resources in co-located geographical regions. These and other findings suggest that better protocol design, more careful spectrum allocation, modified pricing schemes, and careful structuring of quality of service profiles may be needed to accommodate the rise of M2M devices.}

Network Selection for Secondary Users in Cognitive Radio Systems
Chonggang Wang, Kazem Sohraby, Rittwik Jana, Lusheng Ji, Mahmoud Daneshmand
INFOCOM 2011,
2011.
[BIB]
{Measurement studies have shown that uneven and
dynamic usage patterns by the primary users of license based
wireless communication systems often lead to temporal and
spatial spectrum underutilization. This provides an opportunity
for secondary users (SU) to tap into underutilized frequency
bands provided that they are capable of cognitively accessing
the networks without colliding or impacting the performance of
the primary users (PU). When there are multiple networks with
spare spectrum, secondary users can opportunistically choose the
best network to access, subject to certain constraints. In cognitive
radio systems, this is referred to as the network selection problem
for secondary users.
This paper first formulate a Markov queuing model to obtain
the maximum allowable arrival rate of secondary users subject to
a target collision probability for the primary users. Based on this
model, a Collision-Constrained Network Selection (CCNS) method
is proposed to maximize secondary users throughput subject to
a given PU collision probability. Two more approaches, referred
as CCNS-Greedy and CCNS-Energy, are designed to furthermore
reduce collision probability and to decrease energy consumption
of secondary users, when the system is underloaded. However,
CCNS strictly relies on PU and SU traffic characteristics such as
inter-arrival time and service time. Then, MEAsurement-based
Networks Selection (MEANS) is proposed to perform network
selection for secondary users based on online measurement of
PU collision probability of each network, with the same objective
to regulate PU collision probability of each network below the
target value. Later, an enhanced MEANS (MEANS+) is designed
to improve SU throughput while not violating the target PU
collision probability. Simulation based extensive performance
evaluation has shown that the proposed schemes achieve the best
performance in terms of resulted PU collision probability, SU
throughput, and SU energy consumption, compared to Random
and Greedy strategies.}

Characterizing and Modeling Internet Traffic Dynamics of Cellular Devices
Lusheng Ji, Jia Wang, M. Zubair Shafiq, Alex X. Liu
ACM SIGMETRICS 2011,
2011.
[PDF]
[BIB]
ACM Copyright
(c) ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM SIGMetrics 2011, 2011-06-07
{Understanding Internet traffic dynamics in large cellular networks
is important for network design, troubleshooting, performance
evaluation, and optimization. In this paper, we
present the results from our study, which is based upon a
week-long aggregated flow level mobile device traffic data
collected from a major cellular operator�s core network. In
this study, we measured the spatial and temporal dynamics
of Internet traffic to characterize the behavior of mobile devices
used to access cellular networks. We distinguish our
study from other related work by conducting the measurement
at a larger scale and exploring device traffic patterns
along two new dimensions � device types and applications
carried by network traffic. Based on the findings of our measurement
analysis, we propose a Zipf-like model to capture
the distribution and a Markov model to capture the volume
dynamics of aggregate Internet traffic. We further customize
our models for different device types using an unsupervised
clustering algorithm to improve prediction accuracy.}

TowerDefense: Deployment Strategies for Battling against IP Prefix Hijacking
Jia Wang, Lusheng Ji, Dan Pei, Tongqing Qiu, Jun Xu
IEEE ICNP ,
2010.
[BIB]
{IP prefix hijacking is one of the top security threats targeting today�s Internet routing protocol. Several schemes have been proposed to either detect or mitigate prefix hijacking events. However, none of these approaches is adopted and deployed in large-scale on the Internet due to reasons such as scalability, economical practicality, or unrealistic assumptions about the collaborations among ISPs. Thus there are no actionable and deployable solutions for dealing with prefix hijacking.
In this paper, we study key issues related to deploying and operating an IP prefix hijacking detection and mitigation system. Our contributions include (i) deployment strategies for hijacking detection and mitigation system (named as TOWERDEFENSE ): a practical service model for prefix hijacking protection and effective algorithms for selecting agent locations for detecting and mitigating prefix hijacking attacks; and (ii) large scale experi- ments on PlanetLab and extensive analysis on the performance of TOWERDEFENSE .}
Method For QoS Data Delivery In Contention-Based Multi Hop Network,
Tue Dec 13 16:06:46 EST 2011
An arrangement and a method that, for a given pair of nodes that wish to intercommunicate with a high QoS measure, converts a portion of the contention-based network into a contention-less subnetwork by sending a reservation message and a confirmation message between the given pair of nodes. All nodes that are on the paths used for communicating between the pair of nodes are protected from interference by causing all nodes that potentially can interfere to enter a non-transmitting state.
Method And Apparatus For Detecting Computer-Related Attacks,
Tue Oct 18 16:06:18 EDT 2011
Disclosed is a method and apparatus for detecting prefix hijacking attacks. A source node is separated from a destination network at a first time via an original path. The destination network is associated with a prefix. At a second time, a packet is transmitted from the source node to the destination network to determine a current path between the source node and the destination network. A packet is also transmitted from the source node to a reference node to determine a reference node path. The reference node is located along the original path and is associated with a prefix different than the prefix associated with the destination network. The current path and the reference node path are then compared, and a prefix hijacking attack is detected when the reference node path is not a sub-path of the current path.
Signal Strength Guided Intra-Cell Upstream Data Forwarding,
Tue Jul 19 16:05:43 EDT 2011
Intra-cell upstream data forwarding is utilized in a wireless network such as a wireless local area network. A network forwarding path is determined based on the signal strength of an access point signal received at client stations within the network, referred to as the OASS. In particular embodiments, a station that is either originating or forwarding a frame inserts its own OASS into the frame before transmitting it and a client station that receives a frame forwards it only if its own OASS exceeds the frame-enclosed OASS, illustratively by at least a predetermined amount.
Method For Encoding Frame Data,
Tue May 10 16:05:05 EDT 2011
In applications where data is transmitted in frames of symbols and the transmission medium is such that the probability of correct reception of symbols is, on the average, not uniform for different symbols in a frame, transmission of test frames enables creation of information about the different probabilities of correct reception, and that information is employed by the transmitter to control the manner in which symbols are transmitted so as to ameliorate the effects of the different probabilities of correct reception.
Signal Strength Guided Intra-Cell Upstream Data Forwarding,
Tue Jan 26 15:03:18 EST 2010
Intra-cell upstream data forwarding is utilized in a wireless network such as a wireless local area network. A network forwarding path is determined based on the signal strength of an access point signal received at client stations within the network, referred to as the OASS. In particular embodiments, a station that is either originating or forwarding a frame inserts its own OASS into the frame before transmitting it and a client station that receives a frame forwards it only if its own OASS exceeds the frame-enclosed OASS, illustratively by at least a predetermined amount.