针对iSLIP(iterative round robin matching with slip)算法在处理突发业务时性能严重恶化的问题,在iSLIP算法的基础上提出了一种流量自适应的时隙间迭代算法TA-iSLIP(traffic adaptive iSLIP)．该算法根据队列长度智能判断当前流量情况...针对iSLIP(iterative round robin matching with slip)算法在处理突发业务时性能严重恶化的问题,在iSLIP算法的基础上提出了一种流量自适应的时隙间迭代算法TA-iSLIP(traffic adaptive iSLIP)．该算法根据队列长度智能判断当前流量情况,采取不同的调度策略,充分利用已经匹配的资源,使系统的匹配开销尽可能减小．并给出了TA-iSLIP的算法描述和性能评价,与iSLIP算法、FIRM(fcfs in round-robin matching)算法进行了比较．仿真结果表明,TA-iSLIP在均匀和非均匀流量下都达到了较好的性能,在非均匀流量下的吞吐率达到97％以上．展开更多
In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barr...In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barrier term. Iteration bounds both for large-and small-update methods are derived, namely, O（nlog（n/c）） and O（√nlog（n/ε））. This new kernel function has simple algebraic expression and the proximity function has not been used before. Analogous to the classical logarithmic kernel function, our complexity analysis is easier than the other pri- mal-dual interior-point methods based on logarithmic barrier functions and recent kernel functions.展开更多
文摘针对iSLIP(iterative round robin matching with slip)算法在处理突发业务时性能严重恶化的问题,在iSLIP算法的基础上提出了一种流量自适应的时隙间迭代算法TA-iSLIP(traffic adaptive iSLIP)．该算法根据队列长度智能判断当前流量情况,采取不同的调度策略,充分利用已经匹配的资源,使系统的匹配开销尽可能减小．并给出了TA-iSLIP的算法描述和性能评价,与iSLIP算法、FIRM(fcfs in round-robin matching)算法进行了比较．仿真结果表明,TA-iSLIP在均匀和非均匀流量下都达到了较好的性能,在非均匀流量下的吞吐率达到97％以上．
基金Supported by the Natural Science Foundation of Hubei Province (2008CDZD47)
文摘In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barrier term. Iteration bounds both for large-and small-update methods are derived, namely, O（nlog（n/c）） and O（√nlog（n/ε））. This new kernel function has simple algebraic expression and the proximity function has not been used before. Analogous to the classical logarithmic kernel function, our complexity analysis is easier than the other pri- mal-dual interior-point methods based on logarithmic barrier functions and recent kernel functions.
