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About this book

This book constitutes the refereed post-conference proceedings of the 14th EAI International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2018, held in Ho Chi Minh City, Vietnam, in December 2018. The 13 revised full papers were carefully reviewed and selected from 28 submissions. The papers are organized thematically in tracks, starting with security and privacy, telecommunication systems and networks, networks and applications.

Table of Contents


Improving Privacy for GeoIP DNS Traffic

Many authoritative nameservers today support GeoIP feature. EDNS Client Subnet (ECS) extension helps GeoIP authoritative nameserver to address the public recursive resolver’s proximity IP problem. However, ECS raises some privacy concerns since recursive resolver leaks client subnet information on the resolution path to the authoritative nameserver. In this paper we introduce an EDNS ISP Location (EIL) extension, to make privacy improvement for GeoIP DNS traffic while preserve the ECS optimization on the end-user experience, reduce response latency, and increase cache-hit rate. We analysis 910.9K Chinese IPv4 CIDR/24 subnets, find that 479.9K TEL subnets, 234.0K UNI subnets, and 66.3K MOB subnets can enable EIL to optimize DNS traffic.
Lanlan Pan, Xuebiao Yuchi, Xin Zhang, Anlei Hu, Jian Wang

Deep Reinforcement Learning Based QoS-Aware Routing in Knowledge-Defined Networking

Knowledge-Defined networking (KDN) is a concept that relies on Software-Defined networking (SDN) and Machine Learning (ML) in order to operate and optimize data networks. Thanks to SDN, a centralized path calculation can be deployed, thus enhancing the network utilization as well as Quality of Services (QoS). QoS-aware routing problem is a high complexity problem, especially when there are multiple flows coexisting in the same network. Deep Reinforcement Learning (DRL) is an emerging technique that is able to cope with such complex problem. Recent studies confirm the ability of DRL in solving complex routing problems; however, its performance in the network with QoS-sensitive flows has not been addressed. In this paper, we exploit a DRL agent with convolutional neural networks in the context of KDN in order to enhance the performance of QoS-aware routing. The obtained results demonstrate that the proposed approach is able to improve the performance of routing configurations significantly even in complex networks.
Tran Anh Quang Pham, Yassine Hadjadj-Aoul, Abdelkader Outtagarts

Throughput Optimization for Multirate Multicasting Through Association Control in IEEE 802.11 WLAN

Multicasting in wireless local area network is an efficient way to deliver message from a source user to a specified group of destination users simultaneously. In unirate multicasting, all users belonging to a particular group receive their services at the same basic rate. This may underutilize network resources as users requirements are generally heterogeneous in nature. To resolve this limitation, multirate multicasting is introduced, where different users belonging to a particular group may receive their services at different rates. Often dense deployment of access points (APs) is required for coverage and capacity improvement. Thus an station (STA) may come under the coverage range of several APs and hence there may exists many possible associations between the STAs and the APs. Hence finding an efficient association is very important as individual throughput of the STAs as well as the overall system throughput depend on it. We have developed an efficient algorithm to find an appropriate association for multirate multicasting. The objective is to maximize overall system throughput while respecting the user fairness. Through simulations, we have evaluated and compared the performance of our proposed algorithm with other well-known metrics such as received signal strength indicator, minimum hop-distance, in-range STA number and normalized cost. Results show that the proposed algorithm significantly improves the overall system throughput in comparison to these metrics.
Dhrubajyoti Bhaumick, Sasthi C. Ghosh

An ns-3 MPTCP Implementation

Multipath TCP (MPTCP) achieves greater throughput by sending packets from a single byte stream across multiple interfaces and thus, potentially exploits multiple available network paths. This allows end hosts to aggregate bandwidth and network resources. Network simulators such as ns-3 [1] provide researchers with a convenient tool to evaluate protocols and architectures and their importance can not be overemphasized. There are currently 3 existing implementations of MPTCP in ns-3. We evaluate these implementations and find that they lack several key features and are therefore, inadequate for furthering research. We implement MPTCP in ns-3-dev (Developer’s version) and introduce multiple path managers namely default, ndiffports and fullmesh creating an MPTCP patch for ns-3 [2]. The simulation results show improvements in throughput and Flow Completion Times (FCTs) in comparison with previous work. Our implementation [3] is compatible with the current version (ns-3.29).
Kashif Nadeem, Tariq M. Jadoon

A Novel Security Framework for Industrial IoT Based on ISA 100.11a

This paper proposes a security assurance technology of IoT devices using their relevant standard, focusing on ISA100.11a, one of the ICS wireless communication protocols. The proposed security assurance technology is divided broadly into communication test and security function assessment. In detail, the communication test is divided into baseline operation test, resource robustness testing, and packet manipulation testing. The security function assessment conducted with the devices that have passed communication testing is proposed differing the required items, divided by the components of ISA100.11a, such as a field device, backbone router, and host so that an assessment appropriate for the hardware specifications and roles of each component is achieved. In addition, the paper seeks to facilitate the implementation and application of the proposed security assurance technology by proposing concrete methods or criteria for communication testing and security function assessment. Finally, this paper attempts to verify the conformance of the proposed security assurance by testing the security assurance technology in a test-bed with a network environment where the standard ISA100.11a can work network environment.
Hyunjin Kim, Sungjin Kim, Sungmoon Kwon, Wooyeon Jo, Taeshik Shon

Social-Aware Caching and Resource Sharing Optimization for Video Delivering in 5G Networks

The proliferation demand of mobile users (MUs) for video contents, which will occupy up to 78% of data traffic by 2021, poses a serious challenge of system delivery capacity to the macro base stations (MBSs) and the small cell base stations, e.g., femtocell base stations (FBSs), in 5G networks. In this paper, we propose a social-aware caching and resource sharing (SCS) scheme that can help the MBSs and the FBSs relax the backhaul links and provide the MUs with high system delivery capacity. Particularly, we formulate an SCS optimization problem under the constraints on the number of replicas of each video cached in the FBSs and the target signal to interference plus noise ratio (SINR) of the cellular users (CUs) that share the downlink resources. This problem is then solved for maximum system delivery capacity by finding the best placements to cache the videos in the FBSs and the best device-to-device (D2D) pairs shared the same downlink resources with the CUs to offload the videos over D2D communications. Importantly, the behavior of MUs to access the videos and the social relationship of each D2D pair are considered in the SCS optimization problem to efficiently improve the system performance. Simulation results are shown to demonstrate the benefits of the proposed SCS scheme compared to other conventional schemes.
Minh-Phung Bui, Nguyen-Son Vo, Tien-Thanh Nguyen, Quang-Nhat Tran, Anh-Tuan Tran

Energy Efficiency in QoS Constrained 60 GHz Millimeter-Wave Ultra-Dense Networks

Millimeter-Wave (mmWave) communication in ultra-dense networks (UDNs) has been considered as a promising technology for future wireless communication systems. Exploiting the benefits of mmWave and UDNs, we introduce a new approach for jointly optimizing small-cell base station (SBS) - user (UE) association and power allocation to maximize the system energy efficiency (EE) while guaranteeing the quality of service (QoS) constraints for each UE. The SBS-UE association problem poses a new challenge since it reflects as a complex mixed-integer non-convex problem. On the other hand, the power allocation problem is in non-convexity structure, which is impossible to handle with the association problem concurrently. An alternating descent method is thus introduced to divide the primal optimization problem into two subproblems and handle one-by-one at each iteration, where the SBS-UE association problem is reformulated using the penalty approach. Then, path-following algorithms are developed to convert non-convex problem into the simple convex quadratic functions at each iteration. Numerical results are provided to demonstrate the convergence and low-complexity of our proposed schemes.
Huy Thanh Nguyen, Homare Murakami, Kien Nguyen, Kentaro Ishizu, Fumihide Kojima, Jong-Deok Kim, Sang-Hwa Chung, Won-Joo Hwang

Priority-Based Device Discovery in Public Safety D2D Networks with Full Duplexing

Device-to-device (D2D) services are gaining popularity in public safety (PS) applications. The existing half-duplex (HD) D2D discovery has the constraint that the devices sending beacon cannot be discovered at the same time, resulting in large time delays. To counter this problem, in-band full duplex (IB-FD) communications can be used to discover the user quickly by enabling simultaneous transmission and reception during same time-frequency block. In this paper, we exploit the benefits of IB-FD system where PS users are given priority in resource allocation. Moreover, to efficiently utilize the spectrum, we propose a time-efficient device discovery resource allocation (TE-DDRA) scheme where a user can switch the transmission mode from HD to IB-FD when the demand exceeds the available resources in HD mode. The simulation results prove that in comparison with random mode, the PS priority mode saves around \(37\%\) discovery time.
Zeeshan Kaleem, Muhammad Yousaf, Syed Ali Hassan, Nguyen-Son Vo, Trung Q. Duong

Modified Direct Method for Point-to-Point Blocking Probability in Multi-service Switching Networks with Resource Allocation Control

This article proposes a simplified approach to the internal blocking probability calculation in switching networks with mechanisms controlling resource allocation for offered multi-service traffic streams. This resource allocation control can be executed using the so-called threshold and resource reservation mechanisms, according to which the volume of resources admitted depends on a traffic class and on the occupancy state of the interstage and outgoing links of the switching network. The developed method is of generic nature and allows one to model switching systems regardless of the implemented resource allocation control mechanism. However, despite its generic character, the method provides better accuracy as compared to the methods worked out earlier.
Mariusz Głąbowski, Maciej Sobieraj, Maciej Stasiak

Inconsistencies Among Spectral Robustness Metrics

Network robustness plays a critical role in the proper functioning of modern society. It is common practice to use spectral metrics, to quantify the robustness of networks. In this paper we compare eight different spectral metrics that quantify network robustness. Four of the metrics are derived from the adjacency matrix, the others follow from the Laplacian spectrum. We found that the metrics can give inconsistent indications, when comparing the robustness of different synthetic networks. Then, we calculate and compare the spectral metrics for a number of real-world networks, where inconsistencies still occur, but to a lesser extent. Finally, we indicate how the concept of the \(R^*\)-value, a weighted sum of robustness metrics, can be used to resolve the found inconsistencies.
Xiangrong Wang, Ling Feng, Robert E. Kooij, Jose L. Marzo

QoS Criteria for Energy-Aware Switching Networks

This article proposes a method to determine the QoS parameters for energy-aware multiservice switching networks. The initial assumption is that a decrease in the power uptake by the network can be achieved by a temporary switch-off of a certain number of switches. To this end, the article develops methods for a determination of the blocking probability in switching networks with a variable number of switches. The results of the analytical calculations are then compared with the results of simulation experiments for a selected number of structures of switching networks. The study reveals the good accuracy of the proposed model. The results obtained in the study can be applied in constructing energy-aware switching networks.
Mariusz Głąbowski, Maciej Stasiak, Michał D. Stasiak

Modelling Overflow Systems with Queuing in Primary Resources

This article proposes a new method to determine the characteristics of multiservice overflow systems with queueing systems. A number of methods have been developed that have the advantage of determining the parameters of traffic directed to secondary resources as well as providing a way to model these resources. The accompanying assumption is that queues with limited capacities are used in primary resources. The results of analytical calculations are compared with the results of simulation experiments for a number of selected structures of overflow systems with queueing in primary resources. The results of the study confirm high accuracy of the proposed method and, in consequence, the accuracy of the theoretical assumptions adopted for the proposed method.
Mariusz Głąbowski, Damian Kmiecik, Maciej Stasiak

Exploring YouTube’s CDN Heterogeneity

In this paper, we set up measurements and make performance and geographic analysis of YouTube CDN video platform. We use large distributed testbeds, like PlatnetLab and EdgeNet, to grasp the heterogeneity of client situations. Those facilities can work as real clients without any simulation. From these infrastructures, we generate numerous requests to YouTube video servers. Using a reduced initial set of nodes in different geographic location, we continuously measure information related to YouTube homepage websites and video servers, and calculate the latency from clients to cache servers. We also look at the geographical location of YouTube servers. This enables a better understanding of cache mapping strategy and draws the map of the system. Our first result focus on distance between users and data centers before studying dynamic aspect of the system. The information we collect can be of interest to e.g. ISP network operators who need to improve their network architecture to minimize costs and optimize quality for the user.
Anh-Tuan Nguyen, Olivier Fourmaux, Christophe Deleuze


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