Workshop on Advances in Intelligent Mobile Networks for Smart Cities

Session AINSC

AINSC

Conference
10:00 AM — 12:00 PM JST
Local
Dec 16 Wed, 8:00 PM — 10:00 PM EST

A Traffic Engineering Technology Based on Segment Routing in Software Defined Network

Yuantao Teng, Zhengyou Xia (Nanjin University of Aeronautics and Astronautics, China)

0
In recent years, the network urgently needs a lot
of bandwidth resources to meet the explosive growth of traffic
demands. Network operators are also constantly speeding up the
routing ports and expanding the link bandwidth, but the network
resource utilization rate is still very low, so through traffic
engineering technology to optimize the utilization of network
resources is of great significance. Therefore, focusing on the traffic
engineering technology based on segment routing in Software-
Defined Networking, we propose the SRTE-L model, and a
traffic scheduling scheme. We propose to set a path decision
variable L and a path constraint to limit the length of SR path
and the number of intermediate nodes, thereby minimizing the
maximum link utilization and reducing computation time, and we
investigate the trade-off between link utilization and computation
time. Finally, the difference between the proposed method and the
existing methods in terms of computation time and maximum link
utilization is compared. Through extensive simulations,we indeed
experimentally show that our method can reduce the computation
time while retaining comparable maximum link utilization.

An Ensemble Learning Approach for Extracting Concept Prerequisite Relations from Wikipedia

Yang Zhou, Kui Xiao, Yan Zhang (Hubei University, China)

1
Online educational resources usually provided by different people, and the dependency relations between resources are always not clear, which bring challenges for self-directed learners, since they don’t know where to begin when they have a collection of resources. Concept prerequisite relations play an important role in educational resources sequencing and curriculum planning tasks. In this paper, we treat Wikipedia as an educational resource corpus and propose an ensemble learning approach for extracting concept prerequisite relations from Wikipedia. In experiments, we evaluate our approach on two existing datasets, the CMU and AL-CPL datasets, and validate that our approach can achieve better performance than baseline methods.

Boosting Cooperative Game with Complete Information in Multi-UAV Mesh Router Networks

Wei Zhao, Taoyang Zhou, Xuangou Wu, Xiujun Wang, Ruilin Pan (Anhui University of Technology, China); Xun Shao (Kitami Institute of Technology, Japan)

0
It is an inspiring way to provide emergence communication
services in natural disaster areas by deploying wireless
routers on the ground and multiple unmanned aerial vehicles
(UAVs) in the air. The wireless routers serve as access points.
UAVs relay data from routers and themselves to a remote base
station in a safe place. Thus, people can communicate with others
outside the disaster. The network lifetime is restricted to battery
lifetime of routers which are scattered over a complex postdisaster
area. There is a potential to prolong the network lifetime
by utilizing UAV mobility. We consider the trajectory planning of
UAVs with the goal of maximizing the network lifetime, which is
modeled as a cooperative game with complete information. However,
the time complexity of the problem increases exponentially
with the number of UAVs as well as UAV candidate strategies. In
our proposal, we boost the game process by excluding some of
candidates from the strategy space for each UAV. Specifically,
there is no influence for a given UAV, taking the strategies
excluded, over the other UAVs. In addition, these strategies are
dominated by another strategy at least. Our proposed model
is verified through simulations that show its advantage on time
complexity over others.

Community Preference-Based Information-Centric Networking Cache

Xiao Yang (Shanghai Jiao Tong University, China); Chaofeng Zhang (Advanced Institute of Industrial Technology, Japan); Caijuan Chen (National Institute of Informatics, Japan); Haozhe Liang (Pinduoduo Inc., China)

0
Information-centric networking (ICN) framework
has been proposed to connect data content and network users
together, which leads to great efficiency in comparison to conventional
network. Cache policy performances as an essential
part of ICN, and many studies have been conducted to research
this. However, there are still two problems remaining unsolved,
1) ignoring the network user community features, 2) without
considering the correlations between users and data content.
To optimize these shortcomings, a community preference-based
ICN cache policy was proposed. This policy will comprehensively
consider the data content features and user community
preference and then utilize recommendation system to cache the
data into corresponding servers. Moreover, policy advantages and
simulation will also be evaluated in this paper.

Design and Analysis of Decentralized Interactive Cyber Defense Approach based on Multi-agent Coordination

Ming Liu, Lu Ma, Chao Li, Weiling Chang, Yuanjie Wang (National Computer Network Emergency Response Technical Team/Coordination Center of China, China); Jianming Cui (Chang’an University, China), Yingying Ji (National Computer Network Emergency Response Technical Team/Coordination Center of China, China)

2
Since the current cyberspace is becoming changeable
and complex over times, the situation of cyber security is
becoming increasingly severe, and one of the important issues is
that there is still lack of a general applicability defense model
for open and dynamic networks. Recent research suggests that
the evolutionary game methods have the advantage of improving
the defensive capabilities based on the internal decision and
learning mechanisms. In this paper, by exploiting the advantage
of collaborative decision-making in multi-agent system, we constructed
the dynamic cyber defense problem into a decentralized
multi-agent cooperative decision framework, whose core idea is
the initiative decentralized interactions among defense agents.
Then, we contributed a heuristic imprecise probabilistic based
interaction decision algorithm, HIDS, that is, which utilizes the
multidimensional semantic relevance among observation, tasks
and agents, so that agents can continuously improve cognition
and optimize decision-making by learning interactive records. In
addition, we analyzed the equivalence and the transformation
conditions between the proposed model and the existing decision
models, and combined the evolutionary game with the nonlinear
stochastic theory, then the evolution process of the defense
policies are analyzed. Finally, the performance comparison of
the proposed algorithm and the influence of different intensity
random disturbances on the evolution process are analyzed.

Improving the Response Time of SDN Controllers Based on Vertical Handover

Modhawi Alotaibi (University of Ottawa, Canada and Taibah University, Saudi Arabia); Liu Dandan (Wuhan University, China and University of Ottawa, Canada); Amiya Nayak (University of Ottawa, Canada)

1
Incorporating the Software-Defined Networking
(SDN) paradigm into mobile networking has its strengths and
weaknesses. Aside from the promising benefits that SDN brings
to the realm of networking, there are still some challenging
issues. For instance, the drastic increase in using real-time
demanding applications, combined with mobility, have led to
a significant increase in the control traffic and can burden
managing controllers. Therefore, we need dynamic adjustments
and a redistribution of the load among the controllers to
maintain acceptable levels of QoS to be delivered to mobile
users. In this work, we propose a load balancing framework
that employs vertical handovers to enable load balancing among
a set of controllers managing heterogeneous wireless networks.
Our main metric is the controller response time, since it affects
the completion of any procedure associated with mobile users.
Through simulation, our framework has shown as much decrease
as a 36% decrease in response time.

Session Chair

Chaofeng Zhang (Advanced Institute of Industrial Technology, Japan)

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