通讯机构：
[Kuang, Zhufang] C;Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha, Peoples R China.
关键词：
long non-coding RNA;Environmental factor;heterogenous network;HeteSim score;Gradient boosting decision tree;random walk with restart
摘要：
Interactions between genetic factors and environmental factors (EFs) play an important role in many diseases. Many diseases result from the interaction between genetics and EFs. The long non-coding RNA (lncRNA) is an important non-coding RNA that regulates life processes. The ability to predict the associations between lncRNAs and EFs is of important practical significance. However, the recent methods for predicting lncRNA-EF associations rarely use the topological information of heterogenous biological networks or simply treat all objects as the same type without considering the different and subtle semantic meanings of various paths in the heterogeneous network. In order to address this issue, a method based on the Gradient Boosting Decision Tree (GBDT) to predict the association between lncRNAs and EFs (GBDTL2E) is proposed in this paper. The innovation of the GBDTL2E integrates the structural information and heterogenous networks, combines the Hetesim features and the diffusion features based on multi-feature fusion, and uses the machine learning algorithm GBDT to predict the association between lncRNAs and EFs based on heterogeneous networks. The experimental results demonstrate that the proposed algorithm achieves a high performance.
期刊：
IEEE INTERNET OF THINGS JOURNAL,2020年7(12):11701-11712 ISSN：2327-4662
通讯作者：
Deng, Xiao-Heng
作者机构：
[Deng, Xiao-Heng; Wang, Lei-Lei; Zeng, Feng; Gui, Jin-Song] Cent South Univ, Sch Comp Sci & Engn, Changsha 410075, Peoples R China.;[Kuang, Zhu-Fang] Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha 410004, Peoples R China.
通讯机构：
[Deng, Xiao-Heng] C;Cent South Univ, Sch Comp Sci & Engn, Changsha 410075, Peoples R China.
关键词：
Routing;Trajectory;Routing protocols;Internet of Things;Prediction algorithms;Gaussian distribution;Vehicular ad hoc networks;Geographic routing;Internet of Vehicles (IoV);vehicle position analysis;vehicle prediction trajectory
摘要：
Geographic routing is a research hotspot of the Internet of Vehicles (IoV) and intelligent traffic system (ITS). In practice, the vehicle movement is not only affected by its characteristics and the relationship between the vehicle and position but also affected by some implicit factors. Pointing to this problem, we combine the vehicle moving position probability matrix, the vehicle position association matrix, and the implicit factors to study the influence of vehicle position potential features and vehicle association potential features and propose a routing algorithm based on vehicle position (RAVP) analysis, which can obtain the more accurate vehicle prediction trajectory. Then, the vehicle distance is obtained based on the vehicle prediction trajectory. By the normalization of vehicle distance and cache, the vehicle data forwarding capability is obtained and the transmission decision is made. Simulation results show that the proposed algorithm outperforms the other three routing algorithms in terms of packet delivery ratio, average end-to-end delay, and routing overhead ratio.
作者机构：
[赵佳豪; 邝祝芳] School of Computer and Information Engineering, Central South University of Forestry & Technology, Changsha;410004, China;[邓晓衡] School of Computer Science and Engineering, Central South University, Changsha;410083, China;[赵佳豪; 邝祝芳] 410004, China
摘要：
Mobile edge computing (MEC) is a promising technique to enhance computation capacity at the edge of mobile networks. The joint problem of partial offloading decision, offloading scheduling, and resource allocation for MEC systems is a challenging issue. In this paper, we investigate the joint problem of partial offloading scheduling and resource allocation for MEC systems with multiple independent tasks. A partial offloading scheduling and power allocation (POSP) problem in single-user MEC systems is formulated. The goal is to minimize the weighted sum of the execution delay and energy consumption while guaranteeing the transmission power constraint of the tasks. The execution delay of tasks running at both MEC and mobile device is considered. The energy consumption of both the task computing and task data transmission is considered as well. The formulated problem is a nonconvex mixed-integer optimization problem. In order to solve the formulated problem, we propose a two-level alternation method framework based on Lagrangian dual decomposition. The task offloading decision and offloading scheduling problem, given the allocated transmission power, is solved in the upper level using flow shop scheduling theory or greedy strategy, and the suboptimal power allocation with the partial offloading decision is obtained in the lower level using convex optimization techniques. We propose iterative algorithms for the joint problem of POSP. Numerical results demonstrate that the proposed algorithms achieve near-optimal delay performance with a large energy consumption reduction.
摘要：
Energy harvesting (EH) from ambient energy sources can potentially reduce the dependence on the supply of grid or battery energy, providing many benefits to green communications. In this paper, we investigate the device-to-device (D2D) user equipments (DUEs) multiplexing cellular user equipments (CUEs) downlink spectrum resources problem for EH-based D2D communication heterogeneous networks (EH-DHNs). Our goal is to maximize the average energy efficiency of all D2D links, in the case of guaranteeing the quality of service of CUEs and the EH constraints of the D2D links. The resource allocation problems contain the EH time slot allocation of DUEs, power and spectrum resource block (RB) allocation. In order to tackle these issues, we formulate an average energy efficiency problem in EH-DHNs, taking into consideration EH time slot allocation, power and spectrum RB allocation for the D2D links, which is a nonconvex problem. Furthermore, we transform the original problem into a tractable convex optimization problem. We propose joint the EH time slot allocation, power and spectrum RB allocation iterative algorithm based on the Dinkelbach and Lagrangian constrained optimization. Numerical results demonstrate that the proposed iterative algorithm achieves higher energy efficiency for different network parameters settings.
通讯机构：
[Kuang, Zhufang] C;[Kuang, Zhufang] U;Cent South Univ Forestry & Technol, Sch Comp & Informat Engn, Changsha, Hunan, Peoples R China.;Cent S Univ, Sch Software, Changsha, Hunan, Peoples R China.;Univ Victoria, Dept Comp Sci, Victoria, BC, Canada.
关键词：
CR-VANETs;Spectrum access;Energy efficiency;Orthogonal frequency division multiple access (OFDMA)
摘要：
Cognitive radio (CR) is a state-of-the-art technology to solve the spectrum shortage problem for emerging wireless services, which include the CR-enabled vehicular ad hoc networks (CR-VANETs) for vehicle-to-road side unit (RSU) communications. With the increasing demands for high data rate and more reliable mobile services, orthogonal frequency division multiple access (OFDMA) has been often used in such systems. Energy efficiency is an important issue in OFDMA CR-VANETs due to the concern of green communications to transmit the required data in the shortest time, without affecting primary users. In this paper, we proposed an adaptive solution to minimize the overall energy consumption of CR-VANETs as well as maintaining the service quality of Vehicle-to-RSU uplink communications. This goal has been achieved by the means of dynamically selecting different spectrum access schemes for CR-enabled vehicles with relays. Considering the inter-vehicle distances and location information, we formulated a mixed-integer nonlinear constrained optimization problem. A heuristic algorithm based on the greedy strategy and bisection method is then used to solve the formulated problem and it has been evaluated through extensive simulations for different upload data sizes and available communication durations. The acquired results substantiate the efficiency of the proposed solution in terms of energy consumption.
作者机构：
[Gongqiang Li] School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China;Author to whom correspondence should be addressed.;[Zhigang Chen 0001] School of Software, Central South University, Changsha 410083, China;[Junshan Tan] School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Author to whom correspondence should be addressed.;[Zhufang Kuang] School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>School of Software, Central South University, Changsha 410083, China
通讯机构：
[Junshan Tan] S;School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Author to whom correspondence should be addressed.
摘要：
The link failure due to the secondary users exiting the licensed channels when primary users reoccupy the licensed channels is very important in cognitive wireless mesh networks (CWMNs). A multipath routing and spectrum allocation algorithm based on channel interference and reusability with Quality of Service (QoS) constraints in CWMNs (MRIR) was proposed. Maximizing the throughput and the acceptance ratio of the wireless service is the objective of the MRIR. First, a primary path of resource conservation with QoS constraints was constructed, then, a resource conservation backup path based on channel interference and reusability with QoS constraints was constructed. The MRIR algorithm contains the primary path routing and spectrum allocation algorithm, and the backup path routing and spectrum allocation algorithm. The simulation results showed that the MRIR algorithm could achieve the expected goals and could achieve a higher throughput and acceptance ratio.
摘要：
Cognitive wireless mesh networks (CWMNs) were developed to improve the utilization ratio of licensed spectrum. Since the spectrum opportunities for users vary over time and location, enhancing the spectrum effectiveness is a goal and also a challenge for CWMNs. Multimedia applications have recently generated much interest in CWMNs supporting quality-of-service (QoS) communications. Multicast routing and spectrum allocation is an important challenge in CWMNs. In this paper, we study to design an effective multicast routing algorithm based on diversity rate with respect to load balancing and the number of transmissions for CWMNs. In this paper, a load balancing wireless links weight computing function and computing algorithm based on diversity rate (DRLB) are proposed, and a load balancing channel and rate allocating algorithm based on diversity rate (DR2CS) is proposed. On this basis, a load balancing joint multicast routing, channel and rate allocation algorithm based on diversity rate with QoS constraints for CWMNs (LMR2D) is proposed. Balancing the load of node and channel, and minimizing the number of transmissions of multicast tree are the objectives of LMR2D. Firstly, LMR2D computes the weight of wireless links using DRLB and Dijkstra for constructing the load balancing multicast tree step by step. Secondly, LMR2D uses DR2CS to allocate channel and rate of channel to links which is based on the wireless broadcast advantage. Simulation results show that LMR2D can achieve the expected goal. It can not only balance the load of node and channel, but also need lower number of transmissions for multicast tree.
期刊：
International Journal of Communication Networks and Distributed Systems,2017年18(1):58-82 ISSN：1754-3916
通讯作者：
Kuang, Zhufang(zfkuangcn@csu.edu.cn)
作者机构：
[Zhufang Kuang] School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha, 410004, China;[Zhufang Kuang; Zhigang Chen 0001] School of Software, Central South University, Changsha, 410083, China
摘要：
A channel utility value computing (CUVC) algorithm is proposed. The channel utility value contains channel usage probability and channel stability. A high reliability and low latency wireless link weight computing algorithm (RL2W) is proposed. On this basis, a high reliability and low latency routing and spectrum allocation algorithm based on dynamic programming in cognitive wireless mesh networks (HRL2A) is proposed. High reliability and low latency route is the objective of HRL2A. Firstly, HRL2A computes the channel utility value using CUVC for constructing the high reliability route. Secondly, HRL2A uses the algorithm RL2W computing wireless link weight. Thirdly, the route of high reliability and low latency is constructed based on dynamic programming, and the wireless link channel is allocated. Simulation results show that HRL2A algorithm can achieve expectation goal. The construction route not only has higher reliability, but also has lower latency. The throughput has been increased.
摘要：
针对认知无线Ad Hoc网络(Cognitive Radio Ad Hoc Networks, CRAHNs)下垫式(Underlay)频谱接入模型,次用户节点对主用户干扰功率过高,以及次用户节点能量过早耗尽的问题,提出了基于粒子群优化算法的联合功率控制的路由与频谱分配算法PRSA,以最小化次用户对主用户的干扰功率与延长网络生存时间为目标,包括粒子编码与粒子初始化、适应度函数、粒子飞行。设计了包含信道与发射功率等级二元组的邻接矩阵粒子编码结构,以及重新定义了粒子的3种运算规则。仿真结果表明,PRSA能在最小化对主用户的干扰功率的同时,延长网络生存时间。
摘要：
认知无线AdHoc网络(Cognitive Radio Ad Hoc Networks,CRAHNs)中某一链路的SINR低于门限值时,将导致端到端路径中断,针对该问题,以最小化路径的中断概率为目标,研究次用户节点总发射功率受限,以及次用户对主用户干扰功率受限的情况下,联合功率控制的路由与频谱分配策略. 联合功率控制的路由与频谱分配问题非常复杂,是NP问题,为了有效求解该问题,提出基于遗传算法的联合功率控制的路由与频谱分配算法JPCRA. 通过大量的仿真发现,我们提出的JPCRA算法能达到预定目标,构造的路径不仅具有较低的中断概率,而且有效地降低了对主用户节点的干扰功率.
作者机构：
[邝祝芳] School of Computer and Information Engineering, Central South University of Forestry &, Technology, Changsha , China;[刘蕙] Department of Computer Science, Missouri State University, Springfield , MO, United States;[陈志刚; 邝祝芳; 王国军] School of Software, Central South University, Changsha , China
通讯机构：
School of Computer and Information Engineering, Central South University of Forestry & Technology, Changsha, China
作者机构：
[邝祝芳] School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China;[邝祝芳; 陈志刚] School of Information Science and Engineering, Central South University, Changsha 410083, China
通讯机构：
School of Computer and Information Engineering, Central South University of Forestry and Technology, China
