Reservation based Resource Management for SDN-based UE Cloud

Sun, Guolin,Kefyalew, Dawit,Liu, Guisong Korean Society for Internet Information 2016 KSII Transactions on Internet and Information Syst Vol.10 No.12

Recent years have witnessed an explosive growth of mobile devices, mobile cloud computing services offered by these devices and the remote clouds behind them. In this paper, we noticed ultra-low latency service, as a type of mobile cloud computing service, requires extremely short delay constraints. Hence, such delay-sensitive applications should be satisfied with strong QoS guarantee. Existing solutions regarding this problem have poor performance in terms of throughput. In this paper, we propose an end-to-end bandwidth resource reservation via software defined scheduling inspired by the famous SDN framework. The main contribution of this paper is the end-to-end resource reservation and flow scheduling algorithm, which always gives priority to delay sensitive flows. Simulation results confirm the advantage of the proposed solution, which improves the average throughput of ultra-low latency flows.

Big Data Based Dynamic Flow Aggregation over 5G Network Slicing

( Guolin Sun ),( Bruce Mareri ),( Guisong Liu ),( Xiufen Fang ),( Wei Jiang ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.10

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

Reservation based Resource Management for SDN-based UE Cloud

( Guolin Sun ),( Dawit Kefyalew ),( Guisong Liu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.12

Recent years have witnessed an explosive growth of mobile devices, mobile cloud computing services offered by these devices and the remote clouds behind them. In this paper, we noticed ultra-low latency service, as a type of mobile cloud computing service, requires extremely short delay constraints. Hence, such delay-sensitive applications should be satisfied with strong QoS guarantee. Existing solutions regarding this problem have poor performance in terms of throughput. In this paper, we propose an end-to-end bandwidth resource reservation via software defined scheduling inspired by the famous SDN framework. The main contribution of this paper is the end-to-end resource reservation and flow scheduling algorithm, which always gives priority to delay sensitive flows. Simulation results confirm the advantage of the proposed solution, which improves the average throughput of ultra-low latency flows.

Dynamic Resource Reservation for Ultra-low Latency IoT Air-Interface Slice

( Guolin Sun ),( Guohui Wang ),( Prince Clement Addo ),( Guisong Liu ),( Wei Jiang ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.7

The application of Internet of Things (IoT) in the next generation cellular networks imposes a new characteristic on the data traffic, where a massive number of small packets need to be transmitted. In addition, some emerging IoT-based emergency services require a real-time data delivery within a few milliseconds, referring to as ultra-low latency transmission. However, current techniques cannot provide such a low latency in combination with a mice-flow traffic. In this paper, we propose a dynamic resource reservation schema based on an air-interface slicing scheme in the context of a massive number of sensors with emergency flows. The proposed schema can achieve an air-interface latency of a few milliseconds by means of allowing emergency flows to be transported through a dedicated radio connection with guaranteed network resources. In order to schedule the delay-sensitive flows immediately, dynamic resource updating, silence-probability based collision avoidance, and window-based re-transmission are introduced to combine with the frame-slotted Aloha protocol. To evaluate performance of the proposed schema, a probabilistic model is provided to derive the analytical results, which are compared with the numerical results from Monte-Carlo simulations.

Energy Efficient Cell Management by Flow Scheduling in Ultra Dense Networks

( Guolin Sun ),( Prince Clement Addo ),( Guohui Wang ),( Guisong Liu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.9

To address challenges of an unprecedented growth in mobile data traffic, the ultra-dense network deployment is a cost efficient solution to off-load the traffic over other small cells. However, the real traffic is often much lower than the peak-hour traffic and certain small cells are superfluous, which will not only introduce extra energy consumption, but also impose extra interference onto the radio environment. In this paper, an elastic energy efficient cell management scheme is proposed based on flow scheduling among multi-layer ultra-dense cells by a SDN controller. A significant power saving was achieved by a cell-level energy manager. The scheme is elastic for energy saving, adaptive to the dynamic traffic distribution in the office or campus environment. In the end, the performance is evaluated and demonstrated. The results show substantial improvements over the conventional method in terms of the number of active BSs, the handover times, and the switches of BSs.

MARS: Multiple Access Radio Scheduling for a Multi-homed Mobile Device in Soft-RAN

( Guolin Sun ),( Kongmaing Eng ),( Seng Yin ),( Guisong Liu ),( Geyong Min ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.1

In order to improve the Quality-of-Service (QoS) of latency sensitive applications in next-generation cellular networks, multi-path is adopted to transmit packet stream in real-time to achieve high-quality video transmission in heterogeneous wireless networks. However, multi-path also introduces two important challenges: out-of-order issue and reordering delay. In this paper, we propose a new architecture based on Software Defined Network (SDN) for flow aggregation and flow splitting, and then design a Multiple Access Radio Scheduling (MARS) scheme based on relative Round-Trip Time (RTT) measurement. The QoS metrics including end-to-end delay, throughput and the packet out-of-order problem at the receiver have been investigated using the extensive simulation experiments. The performance results show that this SDN architecture coupled with the proposed MARS scheme can reduce the end-to-end delay and the reordering delay time caused by packet out-of-order as well as achieve a better throughput than the existing SMOS and Round-Robin algorithms.

User Bandwidth Demand Centric Soft-Association Control in Wi-Fi Networks

( Guolin Sun ),( Sebakara Samuel Rene Adolphe ),( Hangming Zhang ),( Guisong Liu ),( Wei Jiang ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.2

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.