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Cross-Layer Resource Optimization for Wireless Relay Networks Under Dynamic Node Selfishness
Li, Jinglei,Yang, Qinghai,Kwak, Kyung Sup,Rao, Ramesh R. IEEE 2017 IEEE Transactions on Vehicular Technology VT Vol.66 No.8
<P>In this paper, we investigate the cross-layer resource optimization for wireless relay networks with dynamic node-selfishness information. The degree of intrinsic selfishness (DeIS) and the degree of extrinsic selfishness (DeES) of the relay node (RN) are defined as the effects of its own residual energy resource and the incentive in an incentive mechanism, respectively. A model of two-timescale node-selfishness dynamics is constructed to describe the time-varying characteristics of the RN's DeIS and DeES. Based on the two-timescale node-selfishness dynamics of the RNs, a two-timescale resource-optimization dynamical algorithm (TRODA) is employed to control the transmit powers of both RNs and end users (EU), as well as the flow rates of the data packets injected by all EUs. Meanwhile, the stability and the tracking error of the TRODA under the two-timescale node-selfishness dynamics are analyzed by Lyapunov theory. Our simulation results demonstrate that the two-timescale optimization algorithm is stable and has trivial tracking error.</P>
Neural-Network Based Optimal Dynamic Control of Delivering Packets in Selfish Wireless Networks
Jinglei Li,Qinghai Yang,Kyung Sup Kwak IEEE 2015 IEEE communications letters Vol.19 No.12
<P>In this letter, we investigate the dynamic packet delivery through a specific path in selfish wireless networks (SeWNs) with cascaded selfish relay nodes (RN). A dynamic node-selfishness model is designed to formulate the variation of the RN's degree of node-selfishness (DeNS) with both its own resource and the incentive controlled by the source. When the node-selfishness dynamics are unknown, using the neural network (NN), we further identify the node-selfishness model and then approximate the optimal incentives for maximizing the infinite-horizon utility, namely the tradeoff between the path reliability and the incentive cost in the long term. Simulation results demonstrate the effectiveness of the proposed scheme.</P>
Dynamic Rate Allocation and Forwarding Strategy Adaption for Wireless Networks
Feng, Li,Yang, Qinghai,Kim, Kyehyun,Kwak, Kyungsup IEEE Signal Processing Society 2018 IEEE signal processing letters Vol.25 No.7
<P>In this letter, we investigate the dynamic rate allocation and forwarding strategy adaption scheme for wireless networks with potential selfish nodes. Aided by an incentive mechanism, we develop a stochastic differential equation (SDE) to portray the dynamic node selfishness in terms of node's energy resource and incentives. Then, a stochastic optimization model is employed to maximize the average network utility while bounding the node selfishness. Based on the continuous-time Lyapunov optimization theory, we solve the optimization problem and propose a dynamic rate allocation and forwarding strategy update (DRAF) algorithm to accommodate the dynamic network state. We further analyze the tracking errors between the output of DRFA algorithm and the optimal solution. Then, an adaptive-compensation rate allocation and forwarding strategy update (ACRAF) algorithm is designed, which iterates only once when network state changes. Finally, we provide a sufficient condition that the ACRAF algorithm asymptotically tracks the moving equilibrium point with no tracking errors. Simulation results validate the theoretical analysis.</P>
Profit-Maximizing Virtual Machine Provisioning Based on Workload Prediction in Computing Cloud
( Qing Li ),( Qinghai Yang ),( Qingsu He ),( Kyung Sup Kwak ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.12
Cloud providers now face the problem of estimating the amount of computing resources required to satisfy a future workload. In this paper, a virtual machine provisioning (VMP) mechanism is designed to adapt workload fluctuation. The arrival rate of forthcoming jobs is predicted for acquiring the proper service rate by adopting an exponential smoothing (ES) method. The proper service rate is estimated to guarantee the service level agreement (SLA) constraints by using a diffusion approximation statistical model. The VMP problem is formulated as a facility location problem. Furthermore, it is characterized as the maximization of submodular function subject to the matroid constraints. A greedy-based VMP algorithm is designed to obtain the optimal virtual machine provision pattern. Simulation results illustrate that the proposed mechanism could increase the average profit efficiently without incurring significant quality of service (QoS) violations.
Jinglei Li,Qinghai Yang,Peng Gong,Kyung Sup Kwak IEEE 2016 IEEE TRANSACTIONS ON COMMUNICATIONS Vol.64 No.3
<P>In this paper, we investigate the multiservice delivery between the source-destination pairs in distributed selfish wireless networks (SeWN), where selfish relay nodes (RN) expose their selfish behaviors, i.e., forwarding or dropping multiservices. Owing to the effect of the RNs' node-selfishness on the multiservices, a distributed framework of the node-selfishness management is constructed to manage the RN's node-selfishness information (NSI) in terms of its available resources, the employed incentive mechanism and the quality-of-service (QoS) requirements, and the other RNs' NSI in terms of their historical behaviors. In this framework, the RNs' NSI includes the degree of node-selfishness (DeNS), the degree of intrinsic selfishness (DeIS) and the degree of extrinsic selfishness (DeES). Under the distributed node-selfishness management, a path selection criterion is designed to select the most reliable and shortest path in terms of RNs' DeISs affected by their available resources, and the optimal incentives are determined by the source to stimulate forwarding multiservices of the RNs in the selected path. Our simulation results demonstrate that this framework effectively manages the RNs' NSI, and the optimal strategies of both the path selection and the incentives are determined.</P>
Weihua Wu,Qinghai Yang,Bingbing Li,곽경섭 한국통신학회 2016 Journal of communications and networks Vol.18 No.5
In this paper, we investigate the resource allocation prob-lemin time-varying heterogeneous wireless networks (HetNet) withmulti-homing user equipments (UE). The stochastic optimizationmodel is employed tomaximize the network utility, which is definedas the difference between the HetNet’s throughput and the total en-ergy consumption cost. In harmony with the hierarchical architec-ture of HetNet, the problem of stochastic optimization of resourceallocation is decomposed into two subproblems by the Lyapunovoptimization theory, associated with the flow control in transportlayer and the power allocation in physical (PHY) layer, respec-tively. For avoiding the signaling overhead, outdated dynamic in-formation, and scalability issues, the distributed resource alloca-tion method is developed for solving the two subproblems based onthe primal-dual decomposition theory. After that, the adaptive re-source allocation algorithm is developed to accommodate the time-varying wireless network only according to the current networkstate information, i.e. the queue state information (QSI) at radioaccess networks (RAN) and the channel state information (CSI) ofRANs-UE links. The tradeoff between network utility and delay isderived, where the increase of delay is approximately linear in Vand the increase of network utility is at the speed of 1/V with acontrol parameter V . Extensive simulations are presented to showthe effectiveness of our proposed scheme.
Cao, Ke,Li, Jingjing,Zhao, Yong,Wang, Qi,Zeng, Qinghai,He, Siqi,Yu, Li,Zhou, Jianda,Cao, Peiguo Korean Society for Molecular and Cellular Biology 2016 Molecules and cells Vol.39 No.2
miR-101 is considered to play an important role in hepatocellular carcinoma (HCC), but the underlying molecular mechanism remains to be elucidated. Here, we aimed to confirm whether Girdin is a target gene of miR-101 and determine the tumor suppressor of miR-101 through Girdin pathway. In our previous studies, we firstly found Girdin protein was overexpressed in HCC tissues, and it closely correlated to tumor size, T stage, TNM stage and Edmondson-Steiner stage of HCC patients. After specific small interfering RNA of Girdin was transfected into HepG2 and Huh7.5.1 cells, the proliferation and invasion ability of tumor cells were significantly inhibited. In this study, we further explored the detailed molecular mechanism of Girdin in HCC. Interestingly, we found that miR-101 significantly low-expressed in HCC tissues compared with that in matched normal tissues while Girdin had a relative higher expression, and miR-101 was inversely correlated with Girdin expression. In addition, after miR-101 transfection, the proliferation, migration and invasion abilities of HepG2 cells were weakened. Furthermore, we confirmed that Girdin is a direct target gene of miR-101. Finally we confirmed Talen-mediated Girdin knockout markedly suppressed cell proliferation, migration and invasion in HCC while downregulation of miR-101 significantly restored the inhibitory effect. Our findings suggested that miR-101/Girdin axis could be a potential application of HCC treatment.