1. Dynamic SON-Enabled
Location Management in LTE Networks
Abstract: Wireless networks are
facing various challenges that demand continuous and rapid improvement.
Long-Term Evolution (LTE) is a preferred wireless technology because of its
satisfactory performance. Owing to an exponential increase in demand and new
potential applications, the core network of LTE, which is known as the Evolved
Packet Core (EPC), is affected by a surge in signaling caused by a variety of
control functions. The signaling overhead decreases the users’ Quality of
Experience (QoE). The current study attempts to improve the intelligence of
location management techniques. As an extension of our previous study, a
Self-Organizing Network (SON) that enables dynamic reconfiguration of cellto-
TAL/MME is introduced. Both centralized and distributed pooling schemes are
tested in terms of signaling overhead and user power consumption. A
decomposition model that reduces the original formulated problem to two
sub-problems is proposed, each of which is solved optimally. In addition, a
smart cell-to- TAL selection scheme is proposed to prioritize potential cells
that might be visited by a user equipment (UE). Our method is shown to
outperform several state-of-the-art methods presented in the literature.
Finally, a heuristic algorithm is presented to obtain a less complex
solution than the optimal one.
2. Dynamic Deployment and
Cost-Sensitive Provisioning for Elastic Mobile Cloud Service
Abstract: As mobile customers
gradually occupying the largest share of cloud service users, the effective and
cost-sensitive provisioning of mobile cloud services quickly becomes a main
theme in cloud computing. The key issues involved are much more than just
enabling mobile users to access remote cloud resources through wireless
networks. The resource limited and intermittent disconnection problems of
mobile environments have intrinsic conflict with the continuous connection
assumption of the cloud service usage patterns. We advocate that seamless
service provisioning in mobile cloud can only be achieved with full
exploitation of all available resources around mobile users. An elastic
framework is proposed to automatically and dynamically deploy cloud services on
data center, base stations, client units, even peer devices. The best
deployment location is dynamically determined based on a contextaware and
cost-sensitive evaluation model. To facilitate easy adoption of the proposed
framework, a service development model and associated semi-automatic tools are
provided such that cloud service developers can easily convert a service for
execution on different platforms without porting. Prototype implementation and
evaluation on the Google Cloud and Android platforms demonstrate that our
mechanism can successfully maintain seamless services with very low over head.
3. Energy-aware Dual-path
Geographic Routing to Bypass Routing Holes in Wireless Sensor Networks
Abstract: Geographic routing has
been considered as an attractive approach for resource-constrained wireless
sensor networks (WSNs) since it exploits local location information instead of
global topology information to route data. However, this routing approach often
suffers from the routing hole (i.e., an area free of nodes in the direction
closer to destination) in various environments such as buildings and obstacles
during data delivery, resulting in route failure. Currently, existing
geographic routing protocols tend to walk along only one side of the routing
holes to recover the route, thus achieving suboptimal network performance such
as longer delivery delay and lower delivery ratio. Furthermore, these protocols
cannot guarantee that all packets are delivered in an energy-efficient manner
once encountering routing holes. In this paper, we focus on addressing these
issues and propose an energy-aware dual-path geographic routing (EDGR) protocol
for better route recovery from routing holes. EDGR adaptively utilizes the
location information, residual energy, and the characteristics of energy
consumption to make routing decisions, and dynamically exploits two
node-disjoint anchor lists, passing through two sides of the routing holes, to
shift routing path for load balance. Moreover, we extend EDGR into
three-dimensional (3D) sensor networks to provide energy-aware routing for
routing hole detour. Simulation results demonstrate that EDGR exhibits higher
energy efficiency, and has moderate performance improvements on network
lifetime, packet delivery ratio, and delivery delay, compared to other
geographic routing protocols in WSNs over a variety of communication scenarios
passing through routing holes. The proposed EDGR is much applicable to
resource-constrained WSNs with routing holes.
4. Fast Cell Discovery in
mm-wave 5G Networks with Context Information
Abstract: The exploitation of
mm-wave bands is one of the key-enabler for 5G mobile radio networks. However,
the introduction of mm-wave technologies in cellular networks is not
straightforward due to harsh propagation conditions that limit the mm-wave
access availability. Mm-wave technologies require high-gain antenna systems to
compensate for high path loss and limited power. As a consequence, directional
transmissions must be used for cell discovery and synchronization processes:
this can lead to a non-negligible access delay caused by the exploration of the
cell area with multiple transmissions along different directions. The
integration of mm-wave technologies and conventional wireless access networks
with the objective of speeding up the cell search process requires new 5G
network architectural solutions. Such architectures introduce a functional
split between C-plane and U-plane, thereby guaranteeing the availability of a
reliable signaling channel through conventional wireless technologies that
provides the opportunity to collect useful context information from the network
edge.
In this article, we
leverage the context information related to user positions to improve the
directional cell discovery process. We investigate fundamental trade-offs of
this process and the effects of the context information accuracy on the overall
system performance. We also cope with obstacle obstructions in the cell area
and propose an approach based on a geo-located context database where
information gathered over time is stored to guide future searches. Analytic
models and numerical results are provided to validate proposed strategies.
5. Multi-objective
Optimization based Allocation of Heterogeneous Spatial Crowdsourcing Tasks
Abstract: With the rapid
development of mobile networks and the proliferation of mobile devices, spatial
crowdsourcing, which refers to recruiting mobile workers to perform
location-based tasks, has gained emerging interest from both research
communities and industries. In this paper, we consider a spatial crowdsourcing
scenario: in addition to specific spatial constraints, each task has a valid
duration, operation complexity, budget limitation and the number of required
workers. Each volunteer worker completes assigned tasks while conducting
his/her routine tasks. The system has a desired task probability coverage and
budget constraint. Under this scenario, we investigate an important problem,
namely heterogeneous spatial crowdsourcing task allocation (HSC-TA), which
strives to search a set of representative Pareto-optimal allocation solutions
for the multi-objective optimization problem, such that the assigned task
coverage is maximized and incentive cost is minimized
simultaneously. To accommodate the multi-constraints in
heterogeneous spatial crowdsourcing, we build a worker mobility behavior
prediction model to align with allocation process. We prove that the HSC-TA
problem is NP-hard. We propose effective heuristic methods, including
multi-round linear weight optimization and enhanced multi-objective particle
swarm optimization algorithms to achieve adequate Pareto-optimal allocation.
Comprehensive experiments on both real-world and synthetic data sets clearly
validate the effectiveness and efficiency of our proposed approaches.
6. MiLift: Efficient
Smartwatch-based Workout Tracking Using Automatic Segmentation
Abstract: The use of smart phones
and wear ables as sensing devices has created innumerable context inference
apps including a class of workout tracking apps. Workout data generated by
mobile tracking apps can assist both users and physicians in achieving better
health care, rehabilitation, and self-motivation. Previous approaches impose
extra burdens on users by requiring users to select types of exercises or to
start/stop sessions. In this paper we propose Mi Lift, a practical end-to-end
workout tracking system that performs automatic segmentation to remove user
burdens. Mi Lift uses commercial off-the-shelf smart watches to accurately and
efficiently track both cardio and weightlifting workouts without manual inputs
from users. For weightlifting tracking, Mi Lift supports both machine-based and
free weight exercises, and proposes a lightweight repetition detection
algorithm to ensure efficiency. A research study of 22 users shows that Mi Lift
can achieve above 90% average precision and recall for cardio workout
classification, weightlifting session detection, and weightlifting type
classification. Mi Lift can also count repetitions of weightlifting exercises
with an average error of 1.12 reps (out of an average of 9.65). Our empirical
app study on a Moto 360 watch suggests that Mi Lift can extend watch battery
lives by up to 8.25× (19.13h) compared with previous approaches.
7. Efficient
Privacy-Aware Authentication Scheme for Mobile Cloud Computing
Services
Abstract: With the
exponential increase of the mobile devices and the fast development
of cloud computing, a new computing paradigm called mobile cloud
computing (MCC) is put forward to solve the limitation of the
mobile device’s storage, communication, and computation. Through
mobile devices, users can enjoy various cloud computing services
during their mobility. However, it is difficult to ensure security
and protect privacy due to the openness of wireless communication
in the new computing paradigm. Recently, Tsai and Lo proposed a
privacy-aware authentication (PAA) scheme to solve the
identification problem in MCC services and proved that their scheme was able to
resist many kinds of existing attacks. Unfortunately, we found that Tsai and
Lo’s scheme cannot resist the service provider impersonation attack, i.e., an
adversary can impersonate the service provider to the user. Also, the adversary
can extract the user’s real identity during executing the service provider
impersonation attack. To address the above problems, in this paper, we
construct a new PAA scheme for MCC services by using an identity-based
signature scheme. Security analysis shows that the proposed PAA scheme is able
to address the serious security problems existing in Tsai and Lo’s scheme and
can meet security requirements for MCC services. The performance evaluation
shows that the proposed PAA scheme has less computation and communication costs
compared with Tsai and Lo’s PAA scheme.
8. Identifying On-site
Users f or Social Events: Mobility, Content, and Social Relationship
Abstract: The wide spread use of
social network services, especially location based services, has transformed
social networks into an important information source of real-world events. Many
event detection systems using geo- tagged posts from social networks have been
developed in recent years. Besides detecting real-world events, it is also
desirable for government officials, news media, and police etc. to identify
on-site users of an event, from whom we could gather valuable information
regarding the process of events and investigate suspects when an event is
associated with crime or terrorist. However, due to the high uncertainty of
human mobility patterns and the low probability of users sharing their location
information, it difficult to identify on-site users while a social event unfolds,
and research work in this area is still in its infancy. In this paper, we
propose a Fused feature Gaussian process Regression (FEGOR) model,
which exploits three influential factors in social networks for on-site user
identification: mobility influence, content similarity,
and social relationship. By integrating these factors, we are able to
estimate the distance between a user and a social event even when the user’s
location profile is unknown, thus identify on-site users. Experiments on a
real-world Twitter dataset demonstrate the effectiveness of our
model, achieving a minimum mean absolute error of 1.7km and outperforming
state-of-the-art methods.
9. Motivating
Human-enabled Mobile Participation for Data Offloading
Abstract: The exploding popularity
of mobile devices enables people to enjoy benefits brought by various
interesting mobile apps. However, the ever-increasing data traffic has
exacerbated the congestion on current cellular networks, which results in
users’ dissatisfaction, especially in crowded areas. Hence, how to alleviate
data traffic in cellular networks becomes a challenging problem. Traditional
methods rely on mobile offloading techniques to deviate the data traffic
originally targeted to cellular networks, such as the small cell, Wi-Fi, and
opportunistic communication. Unfortunately, mobile users still experience
severe congestion when a large number of users request for data. Facing these
challenges, we introduce the concept of mobile participation to assist data
offloading by leveraging the mobility of users and the social features among a
group of users. A mobile caching user, who pre-caches a certain amount of
contents, will roam around congested areas to participate in content
dissemination in order to satisfy users’ requests, which is expected to benefit
both himself and users in the crowd simultaneously. To motivate such
human-enabled mobile participation for data offloading, a Stackelberg game is
deployed with joint considerations on social effect and delay effect. Based on
detailed performance analysis, we demonstrate the feasibility and efficiency of
the proposed approach.
10. Motivating
Human-enabled Mobile Participation for Data Offloading
Abstract: The exploding popularity
of mobile devices enables people to enjoy benefits brought by various
interesting mobile apps. However, the ever-increasing data traffic has
exacerbated the congestion on current cellular networks, which results in
users’ dissatisfaction, especially in crowded areas. Hence, how to alleviate
data traffic in cellular networks becomes a challenging problem. Traditional
methods rely on mobile offloading techniques to deviate the data traffic
originally targeted to cellular networks, such as the small cell, Wi-Fi, and
opportunistic communication. Unfortunately, mobile users still experience
severe congestion when a large number of users request for data. Facing these
challenges, we introduce the concept of mobile participation to assist data
offloading by leveraging the mobility of users and the social features among a
group of users. A mobile caching user, who pre-caches a certain amount of
contents, will roam around congested areas to participate in content
dissemination in order to satisfy users’ requests, which is expected to benefit
both himself and users in the crowd simultaneously. To motivate such
human-enabled mobile participation for data offloading, a Stackelberg game is
deployed with joint considerations on social effect and delay effect. Based on
detailed performance analysis, we demonstrate the feasibility and efficiency of
the proposed approach.
11. Motivating
Human-enabled Mobile Participation for Data Offloading
Abstract: The exploding popularity
of mobile devices enables people to enjoy benefits brought by various
interesting mobile apps. However, the ever-increasing data traffic has
exacerbated the congestion on current cellular networks, which results in
users’ dissatisfaction, especially in crowded areas. Hence, how to alleviate
data traffic in cellular networks becomes a challenging problem. Traditional
methods rely on mobile offloading techniques to deviate the data traffic
originally targeted to cellular networks, such as the small cell, Wi-Fi, and
opportunistic communication. Unfortunately, mobile users still experience
severe congestion when a large number of users request for data. Facing these
challenges, we introduce the concept of mobile participation to assist data
offloading by leveraging the mobility of users and the social features among a
group of users. A mobile caching user, who pre-caches a certain amount of
contents, will roam around congested areas to participate in content
dissemination in order to satisfy users’ requests, which is expected to benefit
both himself and users in the crowd simultaneously. To motivate such human-enabled
mobile participation for data offloading, a Stackelberg game is deployed with
joint considerations on social effect and delay effect. Based on detailed
performance analysis, we demonstrate the feasibility and efficiency of the
proposed approach.
12. Recurring Contacts
Between Groups of Devices: Analysis and Application
Abstract: The capability to
anticipate a contact with another device can contribute to improve the
performance and user satisfaction of mobile social network applications and of
any other relying on some form of data harvesting or hoarding. This paper
presents a 9 year data set of wireless access logs produced by more than 70000
devices and 40000 users. Research on the recurring contact patterns observed
between groups of devices permitted to model the probabilities of occurrence of
a contact at a predefined date between pairs of devices. As an example, the
paper presents and evaluates an algorithm that provides daily contact
predictions, based on the history of past pairwise contacts and its application
on a reputation service.
13. Two-hop
Distance-Bounding Protocols: Keep your Friends Close
Abstract: Authentication in
wireless communications often depends on the physical proximity to a location.
Distance-bounding (DB) protocols are cross-layer authentication protocols that
are based on the round-trip-time of challenge-response exchanges and can be
employed to guarantee physical proximity and combat relay attacks. However,
traditional DB protocols rely on the assumption that the prover (e.g., user) is
in the communication range of the verifier (e.g., access point); something that
might not be the case in multiple access control scenarios in ubiquitous
computing environments as well as when we need to verify the proximity of our
two-hop neighbour in an ad-hoc network. In this paper, we extend traditional DB
protocols to a two-hop setting i.e. when the prover is out of the communication
range of the verifier and thus, they both need to rely on an untrusted
in-between entity in order to verify proximity. We present a formal framework that
captures the most representative classes of existing DB protocols and provide a
general method to extend traditional DB protocols to the two-hop case (three
participants). We analyse the security of two-hop DB protocols and identify
connections with the security issues of the corresponding one-hop case.
Finally, we demonstrate the correctness of our security analysis and the
efficiency of our model by transforming five existing DB protocols to the
two-hop setting and we evaluate their performance with simulated experiments.
14. Wireless Charger
Placement and Power Allocation for Maximizing Charging Quality
Abstract: Wireless power transfer
is a promising technology used to extend the lifetime of, and thus enhance the
usability of, energyhungry battery-powered devices. It enables energy to be
wirelessly transmitted from power chargers to energy-receiving devices.
Existing studies have mainly focused on maximizing network lifetime, optimizing
charging efficiency, minimizing charging delay, etc. In this paper, we consider
wireless charging service provision in a two-dimensional target area and focus
on optimizing charging quality, where the power of each charger is adjustable.
We first consider the charger Placement and Power allocation Problem with Stationary
rechargeable devices (SP3): Given a set of stationary devices and a set of
candidate locations for placing chargers, find a charger placement and a
corresponding power allocation to maximize the charging quality, subject to a
power budget. We prove that SP3 is NP-complete, and propose an approximation
algorithm. We also show how to deal with mobile devices (MP3), cost-constrained
power reconfiguration (CRP), and optimization with more candidate locations.
Extensive simulation results show that, the proposed algorithms perform very
closely to the optimum (the gap is no more than 4.5%, 4.4%, and 5.0% of OPT in
SP3, MP3, and CRP, respectively), and outperforms the baseline algorithms.
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