Adaptive Delay Optimization of Multicast-Enabled Coded Caching in Device-to-Device Networks

This letter investigates a delay optimization problem in device-to-device(D2D)networks where users have pre-downloaded subfiles following a coded caching rule.Due to acquiring rest subfiles,users may suffer both receiving and transmitting delays.To achieve the delay minimization,we first propose a delay-aware mode-selection strategy to adaptively choose multicast or D2D communications mode to reduce the receiving-caused delay.By matching these transmit modes with distinct subfile sizes,we further formulate a min-max optimization problem to minimize the delivery delay.Finally,numerical results prove that the proposed scheme outperforms existing ones in terms of both receiving and transmitting delays.

Defect-Tolerant Mapping of CMOL Circuit Targeting Delay Optimization

In view of the significant number of defective nanodevices in the Cmos/nanowire/MOLecular hybrid(CMOL)circuit,defect-tolerant mapping is an essential step to achieve correct logic operations in defective CMOL circuits.However,less effort has been made to improve circuit delay by defect-tolerant strategies.In this paper,the factors affecting the delay of mapped circuits are analyzed,and the path-tree based defect-tolerant mapping method for the delay optimization is proposed.From the logic-domain,the terminology of the path tree is presented,and the logic circuit is first partitioned into multiple path trees.Then,the mapping areas in the physic-domain are pre-planned for(near)critical path trees.During the mapping process,the specific mapping modes and an updating strategy are formulated to map the path trees:inputs are mapped based on input sorting;(near)critical path trees are mapped with priority,while the others are mapped in a hierarchical way.Finally,an improved tabu search algorithm is employed to verify the validity of the proposed defect-tolerant mapping method.Experimental evaluations on the ISCAS benchmarks show that the proposed method can reduce circuit delay by 15.22%.

Joint Allocation of Wireless Resource and Computing Capability in MEC-Enabled Vehicular Network

In MEC-enabled vehicular network with limited wireless resource and computation resource,stringent delay and high reliability requirements are challenging issues.In order to reduce the total delay in the network as well as ensure the reliability of Vehicular UE(VUE),a Joint Allocation of Wireless resource and MEC Computing resource(JAWC)algorithm is proposed.The JAWC algorithm includes two steps:V2X links clustering and MEC computation resource scheduling.In the V2X links clustering,a Spectral Radius based Interference Cancellation scheme(SR-IC)is proposed to obtain the optimal resource allocation matrix.By converting the calculation of SINR into the calculation of matrix maximum row sum,the accumulated interference of VUE can be constrained and the the SINR calculation complexity can be effectively reduced.In the MEC computation resource scheduling,by transforming the original optimization problem into a convex problem,the optimal task offloading proportion of VUE and MEC computation resource allocation can be obtained.The simulation further demonstrates that the JAWC algorithm can significantly reduce the total delay as well as ensure the communication reliability of VUE in the MEC-enabled vehicular network.

Efficiency analysis of numerical integrations for finite element substructure in real-time hybrid simulation

Finite element（FE） is a powerful tool and has been applied by investigators to real-time hybrid simulations（RTHSs）. This study focuses on the computational efficiency, including the computational time and accuracy, of numerical integrations in solving FE numerical substructure in RTHSs. First, sparse matrix storage schemes are adopted to decrease the computational time of FE numerical substructure. In this way, the task execution time（TET） decreases such that the scale of the numerical substructure model increases. Subsequently, several commonly used explicit numerical integration algorithms, including the central difference method（CDM）, the Newmark explicit method, the Chang method and the Gui-λ method, are comprehensively compared to evaluate their computational time in solving FE numerical substructure. CDM is better than the other explicit integration algorithms when the damping matrix is diagonal, while the Gui-λ（λ = 4） method is advantageous when the damping matrix is non-diagonal. Finally, the effect of time delay on the computational accuracy of RTHSs is investigated by simulating structure-foundation systems. Simulation results show that the influences of time delay on the displacement response become obvious with the mass ratio increasing, and delay compensation methods may reduce the relative error of the displacement peak value to less than 5% even under the large time-step and large time delay.

Joint Beamforming for Delay Optimal Transmission in Cache-Enabled Wireless Backhaul Networks

This paper considers the problem of joint beamformer design for a two-tier wireless network,whereby a set of cache-enabled access points(APs)are connected to the base station(BS)via wireless backhaul links.The APs can prefetch and store the files requested by users,to serve users directly in the access links.Thus low-latency transmissions are enabled as the transmission in the backhaul links is saved.However,due to the limited cache capacity,not all requested files can be stored in the APs,some of the non-cached APs then should be utilized as long as their transmission delays in the access and backhaul links can be well addressed.Two delay optimal beamformer design(DOBD)problems are formulated to minimize the overall delay incurred in the backhaul and access link transmissions via a joint optimization of the beamformer at the BS and APs.We consider the DOBD problem under non-fragment and fragment caching policies,both involving nonconvex link rate constraints.The semi-definite relaxation(SDR)and sequential convex approximation(SCA)schemes are adopted to approximate the nonconvex problems into convex ones,which are then iteratively solved.Numerical results demonstrate the convergence and improved transmission delay performance of the proposed scheme under various network settings.

Reducing the Upper Bound Delay by Optimizing Bank-to-Core Mapping

Nowadays, inter-task interferences are the main difficulty in analyzing the timing behavior of multicores. The timing predictable embedded multicore architecture MERASA, which allows safe worst-case execution time （WCET） estimations, has emerged as an attractive solution. In the architecture, WCET can be estimated by the upper bound delay （UBD） which can be bounded by the interference-aware bus arbiter （IABA） and the dynamic cache partitioning such as columnization or bankization. However, this architecture faces a dilemma between decreasing UBD and efficient shared cache utilization. To obtain tighter WCET estimation, we propose a novel approach that reduces UBD by optimizing bank-to-core mapping on the multicore system with IABA and the two-level partitioned cache. For this, we first present a new UBD computation model based on the analysis of inter-task interference delay, and then put forward the core-sequence optimization method of bank-to-core mapping and the optimizing algorithms with the minimum UBD. Experimental results demonstrate that our approach can reduce WCET from 4% to 37%.

Harmonic balance-based approach for optimal time delay to control unstable periodic orbits of chaotic systems

As a classical technique for chaos suppression,the time-delayed feedback controlling strategy has been widely developed by stabilizing unstable periodic orbits(UPOs)embedded in chaotic systems.A critical issue for achieving high controlling precision is to search for an appropriate time delay.This paper proposes a simple yet effective approach,based on incremental harmonic balance method,to determine the optimal time delay in the delayed feedback controller.The time delay is adjusted within the iterative scheme provided by the proposed method,and finally converges to the period of the target UPO.As long as the optimal time delay is fixed,moreover,the attained solution makes it quite convenient to analyze its stability according to the Floquet theory,which further provides the effective interval of the feedback gain.

State Prediction of Chaotic System Based on ANN Model

The choice of time delay and embedding dimension is very important to the phase space reconstruction of any chaotic time series. In this paper, we determine optimal time delay by computing autocorrelation function of time series. Optimal embedding dimension is given by means of the relation between embedding dimension and correlation dimension of chaotic time series. Based on the methods above, we choose ANN model to appoximate the given true system. At the same time, a new algorithm is applied to determine the network weights. At the end of this paper, the theory above is demonstrated through the research of time series generated by Logistic map.