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    FEATURE TOPIC: FUTURE INTERNET ARCHITECTURE AND TESTBEDS
  • FEATURE TOPIC: FUTURE INTERNET ARCHITECTURE AND TESTBEDS
    Migration to Software-Defined Networks: the Customers’ View
    Tingting Yuan, Xiaohong Huang, Maode Ma, Pei Zhang
    2017, 14(10): 1-11.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    Software Defined Networking (SDN) provides a flexible and convenient way to support fine-grained traffic-engineering (TE). Besides, SDN also provides better Quality of Experience (QoE) for customers. However, the policy of the evolution from legacy networks to the SDNs overemphasizes the controllability of the network or TE while ignoring the customers’ benefit. Standing in the customers’ position, we propose an optimization scheme, named as Optimal Migration Schedule based on Customers’ Benefit (OMSB), to produce an optimized migration schedule and maximize the benefit of customers. Not only the quality and quantity of paths availed by migration, but also the number of flows from the customers that can use these multi-paths are taken into consideration for the scheduling. We compare the OMSB with other six migration schemes in terms of the benefit of customers. Our results suggest that the sequence of the migration plays a vital role for customers, especially in the early stages of the network migration to the SDN.
  • FEATURE TOPIC: FUTURE INTERNET ARCHITECTURE AND TESTBEDS
    Software De?ned Tra?c Engineering for Improving Quality of Service
    Xiaoming Li, Jinyao Yan, Hui Ren
    2017, 14(10): 12-25.
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    The Software Defined Networking (SDN) paradigm separates the control plane from the packet forwarding plane, and provides applications with a centralized view of the distributed network state. Thanks to the flexibility and efficiency of the traffic flow management, SDN based traffic engineering increases network utilization and improves Quality of Service (QoS). In this paper, an SDN based traffic scheduling algorithm called CATS is proposed to detect and control congestions in real time. In particular, a new concept of aggregated elephant flow is presented. And then a traffic scheduling optimization model is formulated with the goal of minimizing the variance of link utilization and improving QoS. We develop a chaos genetic algorithm to solve this NP-hard problem. At the end of this paper, we use Mininet, Floodlight and video traces to simulate the SDN enabled video networking. We simulate both the case of live video streaming in the wide area backbone network and the case of video file transferring among data centers. Simulation results show that the proposed algorithm CATS effectively eliminates network congestions in subsecond. In consequence, CATS improves the QoS with lower packet loss rate and balanced link utilization.
  • FEATURE TOPIC: FUTURE INTERNET ARCHITECTURE AND TESTBEDS
    Towards a Dynamic Controller Scheduling-Timing Problem in Software-Defined Networking
    Zhenping Lu, Fucai Chen, Guozhen Cheng, Chao Qi, Jianjian Ai
    2017, 14(10): 26-38.
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    Controller vulnerabilities allow malicious actors to disrupt or hijack the Software-Defined Networking. Traditionally, it is static mappings between the control plane and data plane. Adversaries have plenty of time to exploit the controller’s vulnerabilities and launch attacks wisely. We tend to believe that dynamically altering such static mappings is a promising approach to alleviate this issue, since a moving target is difficult to be compromised even by skilled adversaries. It is critical to determine the right time to conduct scheduling and to balance the overhead afforded and the security levels guaranteed. Little previous work has been done to investigate the economical time in dynamic-scheduling controllers. In this paper, we take the first step to both theoretically and experimentally study the scheduling-timing problem in dynamic control plane. We model this problem as a renewal reward process and propose an optimal algorithm in deciding the right time to schedule with the objective of minimizing the long-term loss rate. In our experiments, simulations based on real network attack datasets are conducted and we demonstrate that our proposed algorithm outperforms given scheduling schemes.
  • FEATURE TOPIC: FUTURE INTERNET ARCHITECTURE AND TESTBEDS
    Efficient Virtual Network Embedding Algorithm Based on Restrictive Selection and Optimization Theory Approach
    Haotong Cao, Zhicheng Qu, Yishi Xue, Longxiang Yang
    2017, 14(10): 39-60.
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    Network virtualization (NV) is widely considered as a key component of the future network and promises to allow multiple virtual networks (VNs) with different protocols to coexist on a shared substrate network (SN). One main challenge in NV is virtual network embedding (VNE). VNE is a NP-hard problem. Previous VNE algorithms in the literature are mostly heuristic, while the remaining algorithms are exact. Heuristic algorithms aim to find a feasible embedding of each VN, not optimal or sub-optimal, in polynomial time. Though presenting the optimal or sub-optimal embedding per VN, exact algorithms are too time-consuming in small-scaled networks, not to mention moderately sized networks. To make a trade-off between the heuristic and the exact, this paper presents an effective algorithm, labeled as VNE-RSOT (Restrictive Selection and Optimization Theory), to solve the VNE problem. The VNE-RSOT can embed virtual nodes and links per VN simultaneously. The restrictive selection contributes to selecting candidate substrate nodes and paths and largely cuts down on the number of integer variables, used in the following optimization theory approach. The VNE-RSOT fights to minimize substrate resource consumption and accommodates more VNs. To highlight the efficiency of VNE-RSOT, a simulation against typical and state-of-art heuristic algorithms and a pure exact algorithm is made. Numerical results reveal that virtual network request (VNR) acceptance ratio of VNE-RSOT is, at least, 10% higher than the best-behaved heuristic. Other metrics, such as the execution time, are also plotted to emphasize and highlight the efficiency of VNE-RSOT.
  • FEATURE TOPIC: FUTURE INTERNET ARCHITECTURE AND TESTBEDS
    A Fast and Memory-Efficient Approach to NDN Name Lookup
    Dacheng He, Dafang Zhang, Ke Xu, Kun Huang, Yanbiao Li
    2017, 14(10): 61-69.
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    For name-based routing/switching in NDN, the key challenges are to manage large-scale forwarding Tables, to lookup long names of variable lengths, and to deal with frequent updates. Hashing associated with proper length-detecting is a straightforward yet efficient solution. Binary search strategy can reduce the number of required hash detecting in the worst case. However, to assure the searching path correct in such a schema, either backtrack searching or redundantly storing some prefixes is required, leading to performance or memory issues as a result. In this paper, we make a deep study on the binary search, and propose a novel mechanism to ensure correct searching path without neither additional backtrack costs nor redundant memory consumptions. Along any binary search path, a bloom filter is employed at each branching point to verify whether a said prefix is present, instead of storing that prefix here. By this means, we can gain significantly optimization on memory efficiency, at the cost of bloom checking before each detecting. Our evaluation experiments on both real-world and randomly synthesized data sets demonstrate our superiorities clearly
  • FEATURE TOPIC: FUTURE INTERNET ARCHITECTURE AND TESTBEDS
    Energy-Efficient Joint Content Caching and Small Base Station Activation Mechanism Design in Heterogeneous Cellular Networks
    Renchao Xie, Zishu Li, Tao Huang, Yunjie Liu
    2017, 14(10): 70-83.
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    Heterogeneous cellular networks (HCNs), by introducing caching capability, has been considered as a promising technique in 5G era, which can bring contents closer to users to reduce the transmission delay, save scarce bandwidth resource. Although many works have been done for caching in HCNs, from an energy perspective, there still exists much space to develop a more energy-efficient system when considering the fact that the majority of base stations are under-utilized in the most of the time. Therefore, in this paper, by taking the activation mechanism for the base stations into account, we study a joint caching and activation mechanism design to further improve the energy efficiency, then we formulate the optimization problem as an Integer Linear Programming problem (ILP) to maximize the system energy saving. Due to the enormous computation complexity for finding the optimal solution, we introduced a Quantum-inspired Evolutionary Algorithm (QEA) to iteratively provide the global best solution. Numerical results show that our proposed algorithm presents an excellent performance, which is far better than the strategy of only considering caching without deactivation mechanism in the actual, normal situation. We also provide performance comparison among our QEA, random sleeping algorithm and greedy algorithm, numerical results illustrate our introduced QEA performs best in accuracy and global optimality.
    • COMMUNICATIONS THEORIES & SYSTEMS
  • COMMUNICATIONS THEORIES & SYSTEMS
    Dual Power Allocation Optimization Based on Stackelberg Game in Heterogeneous Network with Hybrid Energy Supplies
    Shiyu Ji, Liangrui Tang, Mengxi Zhang, Shimo Du
    2017, 14(10): 84-94.
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    In heterogeneous network with hybrid energy supplies including green energy and on-grid energy, it is imperative to increase the utilization of green energy as well as to improve the utilities of users and networks. As the difference of hybrid energy source in stability and economy, thus, this paper focuses on the network with hybrid energy source, and design the utility of each user in the hybrid energy source system from the perspective of stability, economy and environment pollution. A dual power allocation algorithm based on Stackelberg game to maximize the utilities of users and networks is proposed. In addition, an iteration method is proposed which enables all players to reach the Stackelberg equilibrium (SE). Simulation results validate that players can reach the SE and the utilities of users and networks can be maximization, and the green energy can be efficiently used.
  • COMMUNICATIONS THEORIES & SYSTEMS
    A Distributed User Association and Resource Allocation Method in Cache-Enabled Small Cell Networks
    Gongye Ren, Hua Qu, Jihong Zhao, Shuyuan Zhao, Zhirong Luan
    2017, 14(10): 95-107.
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    Cache-enabled small cell networks have been regarded as a promising approach for network operators to cope with the explosive data traffic growth in future 5G networks. However, the user association and resource allocation mechanism has not been thoroughly studied under given content placement situation. In this paper, we formulate the joint optimization problem of user association and resource allocation as a mixed integer nonlinear programming (MINLP) problem aiming at deriving a balance between the total utility of data rates and the total data rates retrieved from caches. To solve this problem, we propose a distributed relaxing-rounding method. Simulation results demonstrate that the distributed relaxing-rounding method outperforms traditional max-SINR method and range-expansion method in terms of both total utility of data rates and total data rates retrieved from caches in practical scenarios. In addition, effects of storage and backhaul capacities on the performance are also studied.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Multi-Core Virtual Concatenation Scheme Considering Inter-Core Crosstalk in Spatial Division Multiplexing Enabled Elastic Optical Networks
    Yongli Zhao, Liyazhou Hu, Chunhui Wang, Ruijie Zhu, Xiaosong Yu, Jie Zhang
    2017, 14(10): 108-117.
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    Spatial division multiplexing enabled elastic optical networks (SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmission capacity in single-mode fiber and single-core fiber. However, spectrum fragmentation issue becomes more serious in SDM-EONs compared with simple elastic optical networks (EONs) with single mode fiber or single core fiber. In this paper, multi-core virtual concatenation (MCVC) scheme is first proposed considering inter-core crosstalk to solve the spectrum fragmentation issue in SDM-EONs. Simulation results show that the proposed MCVC scheme can achieve better performance compared with the baseline scheme, i.e., single-core virtual concatenation (SCVC) scheme, in terms of blocking probability and spectrum utilization.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Two-Stage Resource Allocation Scheme for Three-Tier Ultra-Dense Network
    Junwei Huang, Pengguang Zhou, Kai Luo, Zhiming Yang, Gongcheng He
    2017, 14(10): 118-129.
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    In 5G Ultra-dense Network (UDN), resource allocation is an efficient method to manage inter-small-cell interference. In this paper, a two-stage resource allocation scheme is proposed to supervise interference and resource allocation while establishing a realistic scenario of three-tier heterogeneous network architecture. The scheme consists of two stages: in stage I, a two-level sub-channel allocation algorithm and a power control method based on the logarithmic function are applied to allocate resource for Macrocell and Picocells, guaranteeing the minimum system capacity by considering the power limitation and interference coordination; in stage II, an interference management approach based on K-means clustering is introduced to divide Femtocells into different clusters. Then, a prior sub-channel allocation algorithm is employed for Femtocells in diverse clusters to mitigate the interference and promote system performance. Simulation results show that the proposed scheme contributes to the enhancement of system throughput and spectrum efficiency while ensuring the system energy efficiency.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Delay-Based User Association in Heterogeneous Networks with Backhaul
    Wenchao Xia, Jun Zhang, Shi Jin, Hongbo Zhu
    2017, 14(10): 130-141.
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    The Internet of things (IoT) as an important application of future communication networks puts a high premium on delay issues. Thus when IoT applications meet heterogeneous networks (HetNets) where macro cells are overlaid with small cells, some traditional problems need rethinking. In this paper, we investigate the delay-addressed association problem in two-tier HetNets considering different backhaul technologies. Specifically, millimeter wave and fiber links are used to provide high-capacity backhaul for small cells. We first formulate the user association problem to minimize the total delay which depends on the probability of successful transmission, the number of user terminals (UTs), and the number of base stations (BSs). And then two algorithms for active mode and mixed mode are proposed to minimize the network delay. Simulation results show that algorithms based on mutual selection between UTs and BSs have better performance than those based on distance. And algorithms for mixed modes have less delay than those for active mode when the number of BSs is large enough, compared to the number of UTs.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Energy-Efficient Resource Allocation for Small-Cell Networks: A Stable Queue Perspective
    Hongxin Wei, Wei Feng, Yunzhou Li, Shidong Zhou
    2017, 14(10): 142-150.
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    The small-cell technology is promising for spectral-efficiency enhancement. However, it usually requires a huge amount of energy consumption. In this paper, queue state information and channel state information are jointly utilized to minimize the time average of overall energy consumption for a multi-carrier small-cell network, where the inter-cell interference is an intractable problem. Based on the Lyapunov optimization theory, the problem could be solved by dynamically optimizing the problem of user assignment, carrier allocation and power allocation in each time slot. As the optimization problem is NP-hard, we propose a heuristic iteration algorithm to solve it. Numerical results verify that the heuristic algorithm offers an approximate performance as the brute-force algorithm. Moreover, it could bring down the overall energy consumption to different degrees according to the variation of traffic load. Meanwhile, it could achieve the same sum rate as the algorithm which focuses on maximizing system sum rate.
    • NETWORKS & SECURITY
  • NETWORKS & SECURITY
    Modeling and Analysis of Data Dependencies in Business Process for Data-Intensive Services
    Yuze Huang, Jiwei Huang, Budan Wu, Junliang Chen
    2017, 14(10): 151-163.
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    With the growing popularity of data-intensive services on the Internet, the traditional process-centric model for business process meets challenges due to the lack of abilities to describe data semantics and dependencies, resulting in the inflexibility of the design and implement for the processes. This paper proposes a novel data-aware business process model which is able to describe both explicit control flow and implicit data flow. Data model with dependencies which are formulated by Linear-time Temporal Logic (LTL) is presented, and their satisfiability is validated by an automaton-based model checking algorithm. Data dependencies are fully considered in modeling phase, which helps to improve the efficiency and reliability of programming during developing phase. Finally, a prototype system based on jBPM for data-aware workflow is designed using such model, and has been deployed to Beijing Kingfore heating management system to validate the flexibility, efficacy and convenience of our approach for massive coding and large-scale system management in reality.
  • NETWORKS & SECURITY
    Robust Virtual Network Embedding Based on Component Connectivity in Large-Scale Network
    Xiaojuan Wang, Mei Song, Deyu Yuan, Xiangru Liu
    2017, 14(10): 164-179.
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    Virtual network embedding problem which is NP-hard is a key issue for implementing software-defined network which is brought about by network virtualization. Compared with other studies which focus on designing heuristic algorithms to reduce the hardness of the NP-hard problem we propose a robust VNE algorithm based on component connectivity in large-scale network. We distinguish the different components and embed VN requests onto them respectively. And k-core is applied to identify different VN topologies so that the VN request can be embedded onto its corresponding component. On the other hand, load balancing is also considered in this paper. It could avoid blocked or bottlenecked area of substrate network. Simulation experiments show that compared with other algorithms in large-scale network, acceptance ratio, average revenue and robustness can be obviously improved by our algorithm and average cost can be reduced. It also shows the relationship between the component connectivity including giant component and small components and the performance metrics.
  • NETWORKS & SECURITY
    Design and Implementation of Cloud Platform for Intelligent Logistics in the Trend of Intellectualization
    Mengke Yang, Movahedipour Mahmood, Xiaoguang Zhou, Salam Shafaq, Latif Zahid
    2017, 14(10): 180-191.
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer (SaaS), platform layer (PaaS) and infrastructure (IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-win logistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.
  • NETWORKS & SECURITY
    Energy-Efficient Framework for Virtual Machine Consolidation in Cloud Data Centers
    Kejing He, Zhibo Li, Dongyan Deng, Yanhua Chen
    2017, 14(10): 192-201.
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    With the advent of the era of cloud computing, the high energy consumption of cloud computing data centers has become a prominent problem, and how to reduce the energy consumption of cloud computing data center and improve the efficiency of data center has become the research focus of researchers all the world. In a cloud environment, virtual machine consolidation (VMC) is an effective strategy that can improve the energy efficiency. However, at the same time, in the process of virtual machine consolidation, we need to deal with the tradeoff between energy consumption and excellent service performance to meet service level agreement (SLA). In this paper, we propose a new virtual machine consolidation framework for achieving better energy efficiency-Improved Underloaded Decision (IUD) algorithm and Minimum Average Utilization Difference (MAUD) algorithm. Finally, based on real workload data on PlanetLab, experiments have been done with the cloud simulation platform CloudSim. The experimental result shows that the proposed algorithm can reduce the energy consumption and SLA violation of data centers compared with existing algorithms, improving the energy efficiency of data centers.
  • NETWORKS & SECURITY
    Internet Multimedia Traffic Classification from QoS Perspective Using Semi-Supervised Dictionary Learning Models
    Zaijian Wang, Yuning Dong, Shiwen Mao, Xinheng Wang
    2017, 14(10): 202-218.
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    ATo address the issue of fine-grained classification of Internet multimedia traffic from a Quality of Service (QoS) perspective with a suitable granularity, this paper defines a new set of QoS classes and presents a modified K-Singular Value Decomposition (K-SVD) method for multimedia identification. After analyzing several instances of typical Internet multimedia traffic captured in a campus network, this paper defines a new set of QoS classes according to the difference in downstream/upstream rates and proposes a modified K-SVD method that can automatically search for underlying structural patterns in the QoS characteristic space. We define bag-QoS-words as the set of specific QoS local patterns, which can be expressed by core QoS characteristics. After the dictionary is constructed with an excess quantity of bag-QoS-words, Locality Constrained Feature Coding (LCFC) features of QoS classes are extracted. By associating a set of characteristics with a percentage of error, an objective function is formulated. In accordance with the modified K-SVD, Internet multimedia traffic can be classified into a corresponding QoS class with a linear Support Vector Machines (SVM) classifier. Our experimental results demonstrate the feasibility of the proposed classification method.
    • SIGNAL PROCESSING FOR COMMUNICATIONS
  • SIGNAL PROCESSING FOR COMMUNICATIONS
    Joint Spectrum Sensing Based on Variance and Correlation Analysis
    Junsheng Mu, Xiaojun Jing, Hai Huang, Ning Gao
    2017, 14(10): 219-227.
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    In this paper, a novel detection criterion is proposed to decide whether primary user (PU) exists based on joint analysis of the variance and correlation for observation signal, considering a correlation within the observed signal. Simultaneously, the corresponding detection thresholds are also designed. Simulation experiments verify the proposed method suits for the observation signal in Additive White Gaussian Noise (AWGN), Rayleigh, Rician channel and the detection performance is improved greatly.
  • SIGNAL PROCESSING FOR COMMUNICATIONS
    An SNR-Adaptive Relaying Algorithm for Multi-Antenna Cooperative Networks
    Shuangshuang Han, Peng Zhang, Feijin Shi, Fei-Yue Wang
    2017, 14(10): 228-236.
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    Multiple-input multiple-output (MIMO) and cooperative communications have been attracted great attention for the improvements of communication capacity, power consumption, and transmission coverage. The conventional fixed relaying protocols, amplify-and-forward (AF) and decode-and-forward (DF), have their own advantages and disadvantages, i.e. AF performs better than DF for low signal-to-noise ratio (SNR) region, while the reverse is true for high SNR region. Therefore, this paper proposes an SNR-adaptive forward (SAF) relaying scheme obtaining the advantages of both AF and DF. Furthermore, the proposed SAF does not need to switch between AF and DF when SNR changes. The main idea is to adaptively derive the soft information at the cooperative relay nodes based on the information of the received signal and the SNR. Besides, based on the theoretical analysis and the simulation results, it is affirmed that the proposed SAF achieves superior performance than both AF and DF for all SNRs. Moreover, the performance gain would be improved with the increasing number of parallel cooperative relay nodes.