Resource Allocation and Distributed Uplink Offloading Mechanism in Fog Environment

Linna Ruan,Zhoubin Liu,Xuesong Qiu,Zixiang Wang,Shaoyong Guo,Feng Qi 한국통신학회 2018 Journal of communications and networks Vol.20 No.3

Applying fog computing technology to the shared patternhas two problems to cope with. One is to formulate a rational mechanismfor resource allocation, and the other is to design computationoffloading strategy of tasks based on resource allocation result. For solving these problems, we construct a three-layer F-RAN architecturefirst, which consists of terminal layer, access layer andnetwork layer. Second, we adopt differential game and bipartitegraph multiple matching algorithm to solve bandwidth resource allocationproblemof fog node (FN)-access point (AP) and AP-sharedterminal (ST), respectively. Third, Lyapunov theory and proposeddeviation update decision algorithm (DUDA) are used to solve computationoffloading decision-making and offloading update ordermaking. At last, simulation results show that our strategy can save30%-60% system consumption, and the resource demand satisfactionrate can be guaranteed to reach 80% or more.

Resource Allocation and Distributed Uplink Offloading Mechanism in Fog Environment

Ruan, Linna,Liu, Zhoubin,Qiu, Xuesong,Wang, Zixiang,Guo, Shaoyong,Qi, Feng The Korean Institute of Communications and Informa 2018 Journal of communications and networks Vol.20 No.3

Applying fog computing technology to the shared pattern has two problems to cope with. One is to formulate a rational mechanism for resource allocation, and the other is to design computation offloading strategy of tasks based on resource allocation result. For solving these problems, we construct a three-layer F-RAN architecture first, which consists of terminal layer, access layer and network layer. Second, we adopt differential game and bipartite graph multiple matching algorithm to solve bandwidth resource allocation problem of fog node (FN)-access point (AP) and AP-shared terminal (ST), respectively. Third, Lyapunov theory and proposed deviation update decision algorithm (DUDA) are used to solve computation offloading decision-making and offloading update order-making. At last, simulation results show that our strategy can save 30%-60% system consumption, and the resource demand satisfaction rate can be guaranteed to reach 80% or more.

Stochastic Optimization of Multipath TCP for Energy Minimization and Network Stability over Heterogeneous Wireless Network

( Zulfiqar A. Arain ),( Xuesong Qiu ),( Lujie Zhong ),( Mu Wang ),( Xingyan Chen ),( Yongping Xiong ),( Kiran Nahida ),( Changqiao Xu ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.1

Multipath Transport Control Protocol (MPTCP) is a transport layer protocol that enables multiple TCP connections across various paths. Due to path heterogeneity, it incurs more energy in a multipath wireless network. Recent work presents a set of approaches described in the literature to support systems for energy consumption in terms of their performance, objectives and address issues based on their design goals. The existing solutions mainly focused on the primary system model but did not discourse the overall system performance. Therefore, this paper capitalized a novel stochastically multipath scheduling scheme for data and path capacity variations. The scheduling problem formulated over MPTCP as a stochastic optimization, whose objective is to maximize the average throughput, avoid network congestion, and makes the system more stable with greater energy efficiency. To design an online algorithm that solves the formulated problem over the time slots by considering its min-drift-plus penalty form. The proposed solution was examined under extensive simulations to evaluate the anticipated stochastic optimized MPTCP (so-MPTCP) outcome and compared it with the base MPTCP and the energy-efficient MPTCP (eMPTCP) protocols. Simulation results justify the proposed algorithm's credibility by achieving remarkable improvements, higher throughput, reduced energy costs, and lower-end to end delay.

Clustering and Recommendation for Semantic Web Service in Time Series

( Yu Lei ),( Wang Zhili ),( Meng Luoming ),( Qiu Xuesong ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.8

Promoted by cloud technology and new websites, plenty and variety of Web services are emerging in the Internet. Meanwhile some Web services become outdated even obsolete due to new versions, and a normal phenomenon is that some services work well only with other services of older versions. These laggard or improper services are lowering the performance of the composite service they involved in. In addition, using current technology to identify proper semantic services for a composite service is time-consuming and inaccurate. Thus, we proposed a clustering method and a recommendation method to deal with these problems. Clustering technology is used to classify semantic services according to their topics, functionality and other aspects from plenty of services. Recommendation technology is used to predict the possible preference of a composite service, and recommend possible component services to the composite service according to the history information of invocations and similar composite services. The experiments show that our clustering method with the help of Ontology and TF/IDF technology is more accurate than others, and our recommendation method has less average error than others in the series of missing rate.

Providing survivability for virtual networks against substrate network failure

( Ying Wang ),( Qingyun Chen ),( Wenjing Li ),( Xuesong Qiu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.9

Network virtualization has been regarded as a core attribute of the Future Internet. In a network virtualization environment (NVE), multiple heterogeneous virtual networks can coexist on a shared substrate network. Thus, a substrate network failure may affect multiple virtual networks. In this case, it is increasingly critical to provide survivability for the virtual networks against the substrate network failures. Previous research focused on mechanisms that ensure the resilience of the virtual network. However, the resource efficiency is still important to make the mapping scheme practical. In this paper, we study the survivable virtual network embedding mechanisms against substrate link and node failure from the perspective of improving the resource efficiency. For substrate link survivability, we propose a load-balancing and re-configuration strategy to improve the acceptance ratio and bandwidth utilization ratio. For substrate node survivability, we develop a minimum cost heuristic based on a divided network model and a backup resource cost model, which can both satisfy the location constraints of virtual node and increase the sharing degree of the backup resources. Simulations are conducted to evaluate the performance of the solutions. The proposed load balancing and re-configuration strategy for substrate link survivability outperforms other approaches in terms of acceptance ratio and bandwidth utilization ratio. And the proposed minimum cost heuristic for substrate node survivability gets a good performance in term of acceptance ratio.

A New Traffic Congestion Detection and Quantification Method Based on Comprehensive Fuzzy Assessment in VANET

( Lanlan Rui ),( Yao Zhang ),( Haoqiu Huang ),( Xuesong Qiu ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.1

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.

Modeling and Analysis of Load-Balancing Based on Base-Station CoMP with Guaranteed QoS

( Lei Feng ),( Wenjing Li ),( Mengjun Yin ),( Xuesong Qiu ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.9

With the explosive deployment of the wireless communications technology, the increased QoS requirement has sparked keen interest in network planning and optimization. As the major players in wireless network optimization, the BS`s resource utilization and mobile user`s QoS can be improved a lot by the load-balancing technology. In this paper, we propose a load-balancing strategy that uses Coordinated Multiple Points (CoMP) technology among the Base Stations (BS) to effectively extend network coverage and increase edge users signal quality. To use universally, different patterns of load-balancing based on CoMP are modeled and discussed. We define two QoS metrics to be guaranteed during CoMP load balancing: call blocking rate and efficient throughput. The closed-form expressions for these two QoS metrics are derived. The load-balancing capacity and QoS performances with different CoMP patterns are evaluated and analyzed in low-dense and high-dense traffic system. The numerical results present the reasonable CoMP load balancing pattern choice with guaranteed QoS in each system.

Multi-Devices Composition and Maintenance Mechanism in Mobile Social Network

WenJing Li,Yifan Ding,Shaoyong Guo,Xuesong Qiu 한국통신학회 2015 Journal of communications and networks Vol.17 No.2

In mobile social network, it is a critical challenge to select an optimal set of devices to supply high quality service constantly under dynamic network topology and the limit of device capacity in mobile ad-hoc network (MANET). In this paper, a multi-devices composition and maintenance problem is proposed with ubiquitous service model and network model. In addition, a multi-devices composition and maintenance approach with dynamic planning is proposed to deal with this problem, consisting of service discovery, service composition, service monitor and service recover. At last, the simulation is implemented with OPNET andMATLAB and the result shows this mechanism is better applied to support complex ubiquitous service.

Low-Complexity Energy Efficient Base Station Cooperation Mechanism in LTE Networks

( Peng Yu ),( Lei Feng ),( Zifan Li ),( Wenjing Li ),( Xuesong Qiu ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.10

Currently Energy-Saving (ES) methods in cellular networks could be improved, as compensation method for irregular Base Station (BS) deployment is not effective, most regional ES algorithm is complex, and performance decline caused by ES action is not evaluated well. To resolve above issues, a low-complexity energy efficient BS cooperation mechanism for Long Time Evolution (LTE) networks is proposed. The mechanism firstly models the ES optimization problem with coverage, resource, power and Quality of Service (QoS) constraints. To resolve the problem with low complexity, it is decomposed into two sub-problems: BS Mode Determination (BMD) problem and User Association Optimization (UAO) problem. To resolve BMD, regional dynamic multi-stage algorithms with BS cooperation pair taking account of load and geographic topology is analyzed. And then a distributed heuristic algorithm guaranteeing user QoS is adopted to resolve UAO. The mechanism is simulated under four LTE scenarios. Comparing to other algorithms, results show that the mechanism can obtain better energy efficiency with acceptable coverage, throughput, and QoS performance.

EHMM-CT: An Online Method for Failure Prediction in Cloud Computing Systems

( Weiwei Zheng ),( Zhili Wang ),( Haoqiu Huang ),( Luoming Meng ),( Xuesong Qiu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.9

The current cloud computing paradigm is still vulnerable to a significant number of system failures. The increasing demand for fault tolerance and resilience in a cost-effective and device-independent manner is a primary reason for creating an effective means to address system dependability and availability concerns. This paper focuses on online failure prediction for cloud computing systems using system runtime data, which is different from traditional tolerance techniques that require an in-depth knowledge of underlying mechanisms. A `failure prediction` approach, based on Cloud Theory (CT) and the Hidden Markov Model (HMM), is proposed that extends the HMM by training with CT. In the approach, the parameter ω is defined as the correlations between various indices and failures, taking into account multiple runtime indices in cloud computing systems. Furthermore, the approach uses multiple dimensions to describe failure prediction in detail by extending parameters of the HMM. The likelihood and membership degree computing algorithms in the CT are used, instead of traditional algorithms in HMM, to reduce computing overhead in the model training phase. Finally, the results from simulations show that the proposed approach provides very accurate results at low computational cost. It can obtain an optimal tradeoff between `failure prediction` performance and computing overhead.