HDU4570:Multi-bit Trie(区间DP)

本文讨论了路由器中IP查找的简化方法,通过最长前缀匹配(LPM)问题来实现高效的路径查找。利用多比特尝试技术,减少查找过程中对内存单元的访问次数,同时保持查找效率。详细解释了从单一比特尝试到多比特尝试的转换过程,并提供了实例说明其应用效果。

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Problem Description
IP lookup is one of the key functions of routers for packets forwarding and classifying. Generally, IP lookup can be simplified as a Longest Prefix Matching (LPM) problem. That's to find the longest prefix in the Forwarding Information Base (FIB) that matches the input packet's destination address, and then output the corresponding Next Hop information.

Trie-based solution is the most wildly used one to solve LPM. As shown in Fig.1(b), an uni-bit trie is just a binary tree. Processing LPM on it needs only traversing it from the root to some leaf, according to the input packet's destination address. The longest prefix along this traversing path is the matched one. In order to reduce the memory accesses for one lookup, we can compress some consecutively levels of the Uni-bit Trie into one level, transforming the Uni-bit Trie into a Multi-bit Trie.
For example, suppose the strides array is {3, 2, 1, 1}, then we can transform the Uni-bit Trie shown in Fig.1(b) into a Multi-bit Trie as shown in Fig.1(c). During the transforming process, some prefixes must be expanded. Such as 11(P2), since the first stride is 3, it should be expanded to 110(P2) and 111(P2). But 110(P5) is already exist in the FIB, so we only store the longer one 110(P5).
Multi-bit Trie can obviously reduce the tree level, but the problem is how to build a Multi-bit Trie with the minimal memory consumption (the number of memory units). As shown in Fig.1, the Uni-bit Trie has 23 nodes and consumes 46 memory units in total, while the Multi-bit Trie has 12 nodes and consumes 38 memory units in total.
 

 

Input
The first line is an integer T, which is the number of testing cases.
The first line of each case contains one integer L, which means the number of levels in the Uni-bit Trie.
Following L lines indicate the nodes in each level of the Uni-bit Trie.
Since only 64 bits of an IPv6 address is used for forwarding, a Uni-bit Trie has maximal 64 levels. Moreover, we suppose that the stride for each level of a Multi-bit Trie must be less than or equal to 20.
 

 

Output
Output the minimal possible memory units consumed by the corresponding Multi-bit Trie.
 

 

Sample Input
1 7 1 2 4 4 5 4 3
 

 

Sample Output
38
 


 

题意:这题题意确实有点难懂,起码对于我这个英语渣渣来说是这样,于是去别人的博客看了下题目意思,归纳起来如下:

给出一个长度为n的数列,将其分成若干段,要求最小,其中ai是每一段数列的第一项,bi是每一段的长度,l为将数列分成l段。

比如样例:n=7,A={1 2 4 4 5 4 3},将其分成1 2 4| 4 5| 4| 3,则其所用空间为1*2^3+4*2^2+4*2^1+3*2^1=38,而如果分成1 2| 4 4 5| 4 3,则其所用空间为1*2^2+4*2^3+4*2^2=52,比38大。

 

思路:区间DP,

dp[i][j]表示i--j层最小的内存;

初始条件:全压缩或全不压缩

因为压缩不能超过20层,所以在小于20层时初始条件:

dp[i][j]=num[i]*pow(j-i)*2;

大于20层是只能不压缩

dp[i][j]=(sum[j]-sum[i-1])*2; 

然后循环

dp[i][j]=min(dp[i][k]+dp[k+1][j],dp[i][j]); k:i...j;

 

 

#include <stdio.h>
#include <string.h>
#include <algorithm>
using namespace std;

int n;
__int64 dp[70][70],a[70],sum[70];

__int64 pow(__int64 n)
{
    __int64 ans= 1;
    int i;
    for(i = 1; i<=n; i++)
        ans*=2;
    return ans;
}

int main()
{
    int t,i,j,k,s;
    scanf("%d",&t);
    while(t--)
    {
        scanf("%d",&n);
        memset(sum,0,sizeof(sum));
        for(i = 1; i<=n; i++)
        {
            scanf("%I64d",&a[i]);
            sum[i] = sum[i-1]+a[i];
        }
        memset(dp,0,sizeof(dp));
        for(s = 0; s<=n; s++)
        {
            for(i = 1; i<=n && i+s<=n; i++)
            {
                j = i+s;
                if(s<=19)//小于20层,全压缩
                    dp[i][j] =a[i]*pow(j-i)*2;
                else//多于20,全不压缩
                    dp[i][j] = (sum[j]-sum[i-1])*2;
                for(k = i; k<=j; k++)//区间dp
                    dp[i][j] = min(dp[i][j],dp[i][k]+dp[k+1][j]);
            }
        }
        printf("%I64d\n",dp[1][n]);
    }

    return 0;
}


内容概要:本文探讨了在MATLAB/SimuLink环境中进行三相STATCOM(静态同步补偿器)无功补偿的技术方法及其仿真过程。首先介绍了STATCOM作为无功功率补偿装置的工作原理,即通过调节交流电压的幅值和相位来实现对无功功率的有效管理。接着详细描述了在MATLAB/SimuLink平台下构建三相STATCOM仿真模型的具体步骤,包括创建新模型、添加电源和负载、搭建主电路、加入控制模块以及完成整个电路的连接。然后阐述了如何通过对STATCOM输出电压和电流的精确调控达到无功补偿的目的,并展示了具体的仿真结果分析方法,如读取仿真数据、提取关键参数、绘制无功功率变化曲线等。最后指出,这种技术可以显著提升电力系统的稳定性与电能质量,展望了STATCOM在未来的发展潜力。 适合人群:电气工程专业学生、从事电力系统相关工作的技术人员、希望深入了解无功补偿技术的研究人员。 使用场景及目标:适用于想要掌握MATLAB/SimuLink软件操作技能的人群,特别是那些专注于电力电子领域的从业者;旨在帮助他们学会建立复杂的电力系统仿真模型,以便更好地理解STATCOM的工作机制,进而优化实际项目中的无功补偿方案。 其他说明:文中提供的实例代码可以帮助读者直观地了解如何从零开始构建一个完整的三相STATCOM仿真环境,并通过图形化的方式展示无功补偿的效果,便于进一步的学习与研究。
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