下面給出2021華為軟體精英挑戰賽參與的整個程序，雖然成績不是很好，但是也是花了一些時間的，希望后面多多學習，多多進步，
代碼已經上傳到了Github上：https://github.com/myFrank/huawei_test，代碼給出了簡易的虛擬機遷移思路和服務器初始化購買及服務器的擴容實作，
1、賽題簡介
區域初賽賽題的考核內容，要求選手根據賽題的相關條件，進行云資源的合理規劃與調度，在滿足用戶所有請求的前提下，減少運營、硬體成本開銷，2、題目定義
2.1、服務器
2.1.1、服務器型別
在公有云的運營場景中，我們的資料中心可以選購的服務器型別有多種，以下是目前公有云常用的一些服務器型別，
2.1.2、NUMA 架構
目前主流的服務器都采用了非統一記憶體訪問（NUMA）架構，你可以理解為每臺服務器內部都存在兩個 NUMA 節點：A 和 B（下文中提到的節點均指 NUMA 節點），服務器擁有的資源（CPU 和記憶體）均勻分布在這兩個節點上，以 NV603 為例，其 A、B 兩個節點分別包含 46C 和 162G 的資源，保證服務器的CPU 核數和記憶體大小均為偶數，2.1.3、服務器成本
資料中心使用每臺服務器的成本由兩部分構成：硬體成本和能耗成本，硬體成本是在采購服務器時的一次性支出，能耗成本是后續服務器使用程序中的持續支出，為了便于計算，我們以天為單位計算每臺服務器的能耗成本，若一臺服務器在一天內處于關機狀態，則其不需要消耗任何能耗成本，否則我們需要支出其對應的能耗成本，2.1.4、虛擬機型別
我們面向用戶提供了多種型別的虛擬機售賣服務，用戶可以根據自己的需求來自由選購，以下是一些常用的虛擬機型別，
2.1.5、單節點/雙節點部署
由于服務器存在兩個節點，對應的虛擬機也存在兩種部署方式：單節點部署或雙節點部署，單節點部署指的是一臺虛擬機所需的資源（CPU和記憶體）完全由主機上的一個節點提供；雙節點部署指的是一臺虛擬機所需的資源（CPU 和記憶體）必須由一臺服務器的兩個節點同時提供，并且每個節點提供總需求資源的一半，例如：c3.8xlarge.2 型別的虛擬機需要被部署在一臺服務器的 A和 B 兩個節點上，A、B 節點分別提供 16C，32G 資源，請注意，一種型別的虛擬機是單節點部署還是雙節點部署與其規格沒有必然聯系，但是雙節點部署的虛擬機保證其 CPU 和記憶體需求量都是偶數，2.2、 資源規劃和調度
2.2.1、容量約束
服務器可以用來容納用戶的虛擬機，但是服務器上的任意一個節點(A和 B)上的資源負載(CPU 和記憶體)均不能超過其容量上限，2.2.2、請求型別
用戶的請求共分為兩種型別：創建請求和洗掉請求，創建請求表示用戶向公有云平臺提交的一個創建虛擬機的請求；洗掉請求表示用戶提交的洗掉一臺之前創建的虛擬機的請求，2.2.3、請求序列
由一系列請求構成的序列，題目會給出接下來若干天中每一天用戶的請求序列，根據每天的請求序列，你需要進行相應的資源規劃和調度，2.2.4、資料中心擴容
在得知了一天的請求序列后，你可以在實際進行調度前進行一次資料中心擴容，即購買一些新的服務器來容納后續用戶請求的虛擬機，同時你需 要付出所購買服務器相應的硬體成本，你需要指定購買哪些型別的服務器以及購買的數量，初始時你沒有任何服務器，2.2.5、虛擬機遷移
在完成擴容后，在處理每一天的新請求之前，你還可以對當前存量虛擬機進行一次遷移，即把虛擬機從一臺服務器遷移至另一臺服務器，對于單節 點部署的虛擬機，將其從一臺服務器的 A 節點遷移至 B 節點(或反之)也是允許的，遷移的目的服務器和節點必須有足夠的資源容納所遷移的虛擬機，遷移的虛 擬機總量不超過當前存量虛擬機數量的千分之五，即假設當前有 n 臺存量虛擬機，每天你可以遷移的虛擬機總量不得超過 5n/1000 向下取整，2.2.6、部署虛擬機
在完成擴容和遷移之后，你需要按順序處理當天所有的新請求，對于每一個創建虛擬機的新請求，你要為虛擬機指定一臺服務器進行部署，若虛擬機是單節點部署的，你還需要指明部署在服務器的 A 節點還是 B 節點，處理請求的程序中，任意一臺服務器上每個節點容納的虛擬機資源總和都不能超出節點本身的資源容量（指 CPU 和記憶體兩個維度），3、賽題實作（C/C++實作）
由于服務器的資源是NUMA均勻分布，所以我們每個服務器CPU核數 service_cpu和記憶體大小 service_mem，則它在A，B兩個節點均分后，各有service_cpu/2 個cpu核數和 service_mem/2 大小的記憶體，
3.1、下面給出賽題定義的結構體資料型別：
1 /* 2 記錄每天添加/刪減的虛擬機CPU及記憶體數量及單雙核數量-分單雙節點部署(用結構體) 3 */ 4 struct _per_day_VmTotal_info { 5 6 int deployed_Vm_number = 0; 7 8 int Per_Day_VmTotal_CPU = 0; 9 int Per_Day_VmTotal_MEM = 0; 10 11 int Per_Day_VmTotal_DoubleNodeCPU = 0; 12 int Per_Day_VmTotal_DoubleNodeMEM = 0; 13 14 15 int Per_Day_VmTotal_SingeNode = 0; 16 int Per_Day_VmTotal_DoubleNode = 0; 17 18 }per_day_VmTotal_info; 19 20 21 /* 22 記錄每天購買的服務器型別，包括 23 購買服務器的型別 24 服務器ID(編號從0開始，每增加一臺編號增加1 25 服務器用途(目前用于為虛擬機單雙節點部署flag，0表示此編號服務器用于單節點部署 26 1表示此編號服務器用于雙節點部署 27 服務器A節點的剩余CPU核數(初始為total cpu/2) 28 服務器B節點的剩余CPU核數 29 服務器A節點的剩余MEM(初始為total mem/2) 30 服務器B節點的剩余MEM 31 32 還需要記錄每個服務器上所負載的虛擬機的ID，為了migration 33 */ 34 struct _purchase_service_info { 35 string purchase_service_type; 36 37 int purchased_Service_number; 38 39 /*除了記錄服務器ID（注意服務器ID對應的資訊可以從其他引數匯出） 40 還需要記錄每個服務器上所負載的虛擬機的ID，為了migration*/ 41 unordered_map<int, vector<int>> purchase_service_ID_Info; 42 /* 43 purchase_service_ID_Info[i][j] :s 44 其中i表示 購買的服務器序號，目前是和服務器ID一致 45 其中j = 0時，存盤服務器ID ; j = 1 2 3 時，表示搭建的虛擬機編號 46 */ 47 48 //vector<int> purchase_service_ID; 49 vector<int> purchase_service_useflag; 50 vector<int> purchase_service_nodeA_remainCPU; 51 vector<int> purchase_service_nodeB_remainCPU; 52 vector<int> purchase_service_nodeA_remainMEM; 53 vector<int> purchase_service_nodeB_remainMEM; 54 55 }purchase_service_info; 56 57 58 /* 59 決議txt檔案時，將可供購買的服務器型別資訊決議保存 60 (型號，cpu，記憶體大小，硬體成本，每日能耗成本) 61 */ 62 struct _server_info_stu { 63 string serverType; 64 string cpuCores; 65 string memorySize; 66 string serverCost; 67 string powerCost; 68 }; 69 70 /* 71 決議txt檔案時，將可售賣虛擬機型別資訊決議保存 72 (型號，cpu核數，記憶體大小，是否雙節點部署) 73 */ 74 struct _vm_info_stu { 75 string vmType; 76 string vmCpuCores; 77 string vmMemory; 78 string vmTwoNodes; 79 }; 80 81 struct _userVm_requestAdd_info { 82 string op; 83 string reqVmType; 84 string reqId; 85 }; 86 87 struct _userVm_requestDel_info { 88 string op; 89 string reqId; 90 };
3.2、服務器虛擬機資料處理
我采用的是unordered_map來存盤每種NUMA服務器的資訊，虛擬機為了方便匹配服務器，設計的資料結構如下：
1 // 服務器資訊 2 unordered_map<string,vector<int>> serverInfos; 3 // 虛擬機資訊 4 unordered_map<string,vector<int>> vmInfos;
在決議training-1/2.txt檔案時，將可供購買的服務器型別和用戶可以創建的虛擬機型別資訊決議保存，
1 void generateServer(_server_info_stu *server_info_stu) 2 { 3 string _serverType = ""; 4 for (int i = 1; i < server_info_stu->serverType.size() - 1; i++) { 5 _serverType += server_info_stu->serverType[i]; 6 } 7 8 int _cpuCores = 0, 9 _memorySize = 0, 10 _serverCost = 0, 11 _powerCost = 0; 12 13 for (int i = 0; i < server_info_stu->cpuCores.size() - 1; i++) 14 { 15 _cpuCores = 10 * _cpuCores + server_info_stu->cpuCores[i] - '0'; 16 } 17 18 for (int i = 0; i < server_info_stu->memorySize.size() - 1; i++) 19 { 20 _memorySize = 10 * _memorySize + server_info_stu->memorySize[i] - '0'; 21 } 22 23 for (int i = 0; i < server_info_stu->serverCost.size() - 1; i++) 24 { 25 _serverCost = 10 * _serverCost + server_info_stu->serverCost[i] - '0'; 26 } 27 28 for (int i = 0; i < server_info_stu->powerCost.size() - 1; i++) 29 { 30 _powerCost = 10 * _powerCost + server_info_stu->powerCost[i] - '0'; 31 } 32 33 serverInfos[_serverType] = vector<int>{ _cpuCores / 2 , 34 _cpuCores / 2, 35 _memorySize / 2, 36 _memorySize / 2, 37 _serverCost, 38 _powerCost }; 39 }
1 /* 決議txt檔案時，將可售賣虛擬機型別資訊決議保存 2 (型號，cpu核數，記憶體大小，是否雙節點部署) 3 */ 4 void generateVm(_vm_info_stu *vm_info_stu) 5 { 6 string _vmType; 7 8 for (int i = 1; i < vm_info_stu->vmType.size() - 1; i++) { 9 _vmType += vm_info_stu->vmType[i]; 10 } 11 12 int _vmCpuCores = 0, _vmMemory = 0, _vmTwoNodes = 0; 13 for (int i = 0; i < vm_info_stu->vmCpuCores.size() - 1; i++) { 14 _vmCpuCores = _vmCpuCores * 10 + vm_info_stu->vmCpuCores[i] - '0'; 15 } 16 for (int i = 0; i < vm_info_stu->vmMemory.size() - 1; i++) { 17 _vmMemory = _vmMemory * 10 + vm_info_stu->vmMemory[i] - '0'; 18 } 19 if (vm_info_stu->vmTwoNodes[0] == '1') { 20 _vmTwoNodes = 1; 21 } 22 else { 23 _vmTwoNodes = 0; 24 } 25 vmInfos[_vmType] = vector<int>{ _vmCpuCores, 26 _vmMemory, 27 _vmTwoNodes }; 28 }
在讀取檔案時，采用freopen進行重定向到txt檔案，采用cin標準輸入讀入服務器、虛擬機資料，并讀人每天虛擬機請求，具體代碼如下：
1 //在讀取檔案時，采用freopen進行重定向到txt檔案，采用cin標準輸入讀取資料 2 #ifdef TEST 3 std::freopen(filePath.c_str(), "rb", stdin); 4 #endif 5 int serverNum; 6 7 scanf("%d", &serverNum); 8 9 for (int i = 0; i < serverNum; i++) 10 { 11 cin >> server_info_stu.serverType >> server_info_stu.cpuCores >> server_info_stu.memorySize >> server_info_stu.serverCost >> server_info_stu.powerCost; 12 13 generateServer(&server_info_stu); 14 } 15 16 int vmNumber = 0; 17 scanf("%d", &vmNumber); 18 19 20 21 for (int i = 0; i < vmNumber; i++) { 22 cin >> vm_info_stu.vmType >> vm_info_stu.vmCpuCores >> vm_info_stu.vmMemory >> vm_info_stu.vmTwoNodes; 23 24 generateVm(&vm_info_stu); 25 26 } 27 28 int requestdays = 0, 29 dayRequestNumber = 0; 30 31 scanf("%d", &requestdays);
3.3、服務器購買初始化
服務器購買初始化非常重要，需要依據服務的性價比及分析前面天數的虛擬機CPU、MEM需求，來選擇服務器，之后分單雙節點分別實作，代碼如下：
1 // 初始化server，如何初始化購買的服務器是一個大的優化 2 void Init_BuyServer() 3 { 4 5 string serverType; 6 bool flag = 0; 7 8 findVm_CM_max(); 9 analyzeServerInfo(); 10 11 for (int i = 0; i < 4000; i++) 12 { 13 NodeOnServerInfo[i] = vector<int>{ 0, 0 }; 14 PreNodeOnServerInfo[i] = vector<int>{ 0, 0 }; 15 } 16 17 for (auto it = vec.begin(); it != vec.end(); ++it) 18 { 19 if (flag == 0) 20 { 21 if (serverInfos[it->second][0] >= VM_max_Core && serverInfos[it->second][2] >= VM_max_Mem) //服務器內核和記憶體是最大虛擬需求的2倍，且性價比高 22 { 23 serverType = it->second; 24 flag = 1; 25 } 26 } 27 } 28 29 flag = 0; 30 31 //serverType = "hostUY41I"; hostTUL1P 32 //(hostTUL1P, 286, 858, 142387, 176) 33 serverType = "hostQ0Y9D"; 34 int n = 700; //目前700最佳 35 36 int server_numberID = 0; 37 38 serverRunVms.resize(4000, 0); 39 string initBuy = "(purchase, "; 40 initBuy += to_string(2) + ")\n"; 41 42 //vector<string> res; 43 res.push_back(initBuy); //(purchase, 2) 44 45 string pauseInfo = "(" + serverType + ", "; 46 pauseInfo += std::to_string(n / 2) + ")\n"; 47 48 res.push_back(pauseInfo); //(hostUY41I, 1250) 49 day_BuyServers_res.push_back((serverType + std::to_string(0) + "," + std::to_string(n / 2))); 50 for (int i = 0; i < n / 2; i++) 51 { 52 //unordered_map<int,vector<int>> sysServerResource; 53 sysServerResource[serverNumber++] = serverInfos[serverType]; 54 SERVERCOST += serverInfos[serverType][4]; 55 56 //記錄購買的虛擬機資訊，為后面遷移做準備 57 purchase_service_info.purchase_service_ID_Info[server_numberID][0] = server_numberID; //存盤服務器節點 58 purchase_service_info.purchase_service_nodeA_remainCPU[server_numberID] = serverInfos[serverType][0]; 59 purchase_service_info.purchase_service_nodeB_remainCPU[server_numberID] = serverInfos[serverType][1]; 60 purchase_service_info.purchase_service_nodeA_remainMEM[server_numberID] = serverInfos[serverType][2]; 61 purchase_service_info.purchase_service_nodeB_remainMEM[server_numberID] = serverInfos[serverType][3]; 62 63 // 1-->記錄總的CPU 2->記錄總的MEM 64 purchase_service_info.purchase_service_ID_Info[server_numberID][1] = serverInfos[serverType][0] + serverInfos[serverType][1]; 65 purchase_service_info.purchase_service_ID_Info[server_numberID][2] = serverInfos[serverType][2] + serverInfos[serverType][3]; 66 67 server_numberID++; 68 69 Total_Server_ID[serverNumber - 1] = string{ serverType + std::to_string(0) + "," + std::to_string(serverNumber - 1) }; 70 } 71 //Total_Server_NameID[serverType] = int{ n / 2 - 1}; 72 //ServerTypeBuyOrder[serverType] = int{ 1 }; 73 //(host78BMY, 996, 332, 246869, 310) 74 //(hostUY41I, 676, 994, 243651, 305) 75 serverType = "hostC039T"; 76 pauseInfo = "(" + serverType + ", "; 77 pauseInfo += std::to_string(serverNumber) + ")\n";//(host78BMY, 1250) 78 79 day_BuyServers_res.push_back((serverType + std::to_string(0) + "," + std::to_string(n / 2))); 80 res.push_back(pauseInfo); 81 82 for (int i = 0; i < n / 2; i++) 83 { 84 sysServerResource[serverNumber++] = serverInfos[serverType]; 85 SERVERCOST += serverInfos[serverType][4]; 86 87 //記錄購買的虛擬機資訊，為后面遷移做準備 88 purchase_service_info.purchase_service_ID_Info[server_numberID][0] = server_numberID; //存盤服務器節點 89 purchase_service_info.purchase_service_nodeA_remainCPU[server_numberID] = serverInfos[serverType][0]; 90 purchase_service_info.purchase_service_nodeB_remainCPU[server_numberID] = serverInfos[serverType][1]; 91 purchase_service_info.purchase_service_nodeA_remainMEM[server_numberID] = serverInfos[serverType][2]; 92 purchase_service_info.purchase_service_nodeB_remainMEM[server_numberID] = serverInfos[serverType][3]; 93 94 // 1-->記錄CPU 2->記錄MEM 95 purchase_service_info.purchase_service_ID_Info[server_numberID][1] = serverInfos[serverType][0] + serverInfos[serverType][1]; 96 purchase_service_info.purchase_service_ID_Info[server_numberID][2] = serverInfos[serverType][2] + serverInfos[serverType][3]; 97 98 99 Total_Server_ID[serverNumber - 1] = string{ serverType + std::to_string(0) + "," + std::to_string(serverNumber - 1 - n / 2) }; 100 } 101 //Total_Server_NameID[serverType] = int{ n / 2 - 1 }; 102 //ServerTypeBuyOrder[serverType] = int{ 2 }; 103 }
3.4、虛擬機遷移
虛擬機遷移主要是利用了之前的結構體，結合虛擬機的add及del函式，對結構體引數進行處理，服務器遷移大策略就是編號末尾的服務器剩余CPU/MEM比較多的的遷移到前面服務器上去，盡量占滿，為了減少服務器作業成本：
1 for (int _count = (purchase_service_info.purchased_Service_number - 1); _count >= 0; _count--) 2 { 3 //if (purchase_service_info.purchase_service_nodeA_remainCPU[_count] >= 0) 4 //{ 5 float remain_cpu = (purchase_service_info.purchase_service_nodeA_remainCPU[_count] 6 + purchase_service_info.purchase_service_nodeB_remainCPU[_count])*1.0f 7 / purchase_service_info.purchase_service_ID_Info[_count][1] * 1.0f; 8 9 float remain_mem = (purchase_service_info.purchase_service_nodeA_remainMEM[_count] 10 + purchase_service_info.purchase_service_nodeB_remainMEM[_count])*1.0f 11 / purchase_service_info.purchase_service_ID_Info[_count][2] * 1.0f; 12 13 if ((remain_cpu > 0.8f) && (remain_cpu < 0.99f) && (remain_mem > 0.8f) && (remain_mem < 0.99f)) 14 //if ((remain_cpu > 0.8f) && (remain_mem > 0.8f)) 15 { 16 //for (int vm_tra = 3; purchase_service_info.purchase_service_ID_Info[_count][vm_tra] != 0; vm_tra= vm_tra+4) 17 for (int vm_tra = 3; vm_tra <= 239; vm_tra = vm_tra + 4) //30 -- 119 and 40 --159 18 { 19 if (purchase_service_info.purchase_service_ID_Info[_count][vm_tra] > 100) 20 { 21 for (int service_tra = 0; service_tra < 2600; service_tra++) 22 { 23 if (service_tra != _count) //服務器不能自己遷移到自己本身 24 { 25 //if (purchase_service_info.purchase_service_ID_Info[service_tra][vm_tra + 1]) //如果是雙節點 26 if (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1] == 1) //如果是雙節點 27 { 28 if ((purchase_service_info.purchase_service_nodeA_remainCPU[service_tra] >= (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] / 2)) 29 && (purchase_service_info.purchase_service_nodeB_remainCPU[service_tra] >= (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] / 2)) 30 && (purchase_service_info.purchase_service_nodeA_remainMEM[service_tra] >= (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] / 2)) 31 && (purchase_service_info.purchase_service_nodeB_remainMEM[service_tra] >= (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] / 2)) 32 ) 33 { 34 #ifdef My_PRINT 35 cout << "nodeA_remain cpu:" << purchase_service_info.purchase_service_nodeA_remainCPU[_count] << " 1 " << purchase_service_info.purchase_service_ID_Info[_count][1] << endl; 36 cout << "nodeB_remain cpu:" << purchase_service_info.purchase_service_nodeB_remainCPU[_count] << " 1 " << purchase_service_info.purchase_service_ID_Info[_count][1] << endl; 37 cout << "nodeA_remain mem:" << purchase_service_info.purchase_service_nodeA_remainMEM[_count] << " 1 " << purchase_service_info.purchase_service_ID_Info[_count][2] << endl; 38 cout << "nodeB_remain mem:" << purchase_service_info.purchase_service_nodeB_remainMEM[_count] << " 1 " << purchase_service_info.purchase_service_ID_Info[_count][2] << endl; 39 #endif 40 41 purchase_service_info.purchase_service_nodeA_remainCPU[service_tra] -= (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] / 2); 42 purchase_service_info.purchase_service_nodeB_remainCPU[service_tra] -= (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] / 2); 43 purchase_service_info.purchase_service_nodeA_remainMEM[service_tra] -= (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] / 2); 44 purchase_service_info.purchase_service_nodeB_remainMEM[service_tra] -= (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] / 2); 45 46 //需要補充選定服務器移出去的虛擬機的CPU和MEM 47 purchase_service_info.purchase_service_nodeA_remainCPU[_count] += (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] / 2); 48 purchase_service_info.purchase_service_nodeB_remainCPU[_count] += (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] / 2); 49 purchase_service_info.purchase_service_nodeA_remainMEM[_count] += (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] / 2); 50 purchase_service_info.purchase_service_nodeB_remainMEM[_count] += (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] / 2); 51 52 #ifdef My_PRINT 53 cout << "nodeA_remain cpu:" << purchase_service_info.purchase_service_nodeA_remainCPU[_count] << " 2 " << purchase_service_info.purchase_service_ID_Info[_count][1] << endl; 54 cout << "nodeB_remain cpu:" << purchase_service_info.purchase_service_nodeB_remainCPU[_count] << " 2 " << purchase_service_info.purchase_service_ID_Info[_count][1] << endl; 55 cout << "nodeA_remain mem:" << purchase_service_info.purchase_service_nodeA_remainMEM[_count] << " 2 " << purchase_service_info.purchase_service_ID_Info[_count][2] << endl; 56 cout << "nodeB_remain mem:" << purchase_service_info.purchase_service_nodeB_remainMEM[_count] << " 2 " << purchase_service_info.purchase_service_ID_Info[_count][2] << endl; 57 #endif 58 59 //vmOnServer[vmId] = vector<int>{ serverId,vmCores,vmMemory,1,2 }; 60 61 vmOnServer[std::to_string(purchase_service_info.purchase_service_ID_Info[_count][vm_tra])] = vector<int>{ 62 purchase_service_info.purchase_service_ID_Info[service_tra][0], 63 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2], 64 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3],1,2 }; 65 66 67 68 assert(purchase_service_info.purchase_service_nodeA_remainCPU[service_tra] >= 0 69 && purchase_service_info.purchase_service_nodeB_remainCPU[service_tra] >= 0 70 && purchase_service_info.purchase_service_nodeA_remainMEM[service_tra] >= 0 71 && purchase_service_info.purchase_service_nodeB_remainMEM[service_tra] >= 0); 72 73 74 assert((purchase_service_info.purchase_service_ID_Info[_count][1] / 2) >= purchase_service_info.purchase_service_nodeA_remainCPU[_count] 75 && (purchase_service_info.purchase_service_ID_Info[_count][1] / 2) >= purchase_service_info.purchase_service_nodeB_remainCPU[_count] 76 && (purchase_service_info.purchase_service_ID_Info[_count][2] / 2) >= purchase_service_info.purchase_service_nodeA_remainMEM[_count] 77 && (purchase_service_info.purchase_service_ID_Info[_count][2] / 2) >= purchase_service_info.purchase_service_nodeB_remainMEM[_count]); 78 79 string s; 80 string _migration = "migration"; 81 s = "(" + _migration + ", "; 82 s += std::to_string(1) + ")\n";//(migration, count_migration) 83 res.push_back(s); 84 #ifdef My_PRINT 85 cout << s << endl; 86 #endif 87 88 s = "(" + std::to_string(purchase_service_info.purchase_service_ID_Info[_count][vm_tra]) + ", "; 89 s += std::to_string(purchase_service_info.purchase_service_ID_Info[service_tra][0]) + ")\n";//(虛擬機ID, 目的服務器ID)*/ 90 91 res.push_back(s); 92 93 //添加移入服務器上虛擬機的資訊 94 for (int load_vm = 0; load_vm < 60; load_vm++) //因為del的原因，需要解決洗掉資訊的方面 95 { 96 if (purchase_service_info.purchase_service_ID_Info[service_tra][3 + 4 * load_vm] == 0) 97 { 98 purchase_service_info.purchase_service_ID_Info[service_tra][3 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra]; 99 purchase_service_info.purchase_service_ID_Info[service_tra][4 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1]; //Nodes 100 purchase_service_info.purchase_service_ID_Info[service_tra][5 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]; //CPU 101 purchase_service_info.purchase_service_ID_Info[service_tra][6 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3]; //MEM 102 103 break; 104 } 105 106 107 } 108 109 //需要洗掉從服務器移走虛擬機的資訊 110 purchase_service_info.purchase_service_ID_Info[_count][vm_tra] = 0; 111 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1] = 0; //Nodes 112 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] = 0; //CPU 113 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] = 0; //MEM 114 115 #ifdef My_PRINT 116 cout << s << endl; 117 #endif 118 119 //計算功耗需要 扣除服務器的虛擬機數量 120 serverRunVms[_count]--; 121 serverRunVms[service_tra]++; 122 123 124 count_migration--; 125 126 //break; //如果判斷是可以移植的話，即進行移植，移植完之后 立馬進行下一個虛擬機 127 return 0; 128 } 129 else 130 { 131 //否則判斷下一個服務器 CPU和MEM（從小號往大號） 132 } 133 } 134 else if (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1] == 2)//需要對A節點點進行選擇移植 不需要除/2 135 { 136 if ((purchase_service_info.purchase_service_nodeA_remainCPU[service_tra] >= purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]) 137 && (purchase_service_info.purchase_service_nodeA_remainMEM[service_tra] >= purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3])) 138 { 139 140 purchase_service_info.purchase_service_nodeA_remainCPU[service_tra] -= purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]; 141 purchase_service_info.purchase_service_nodeA_remainMEM[service_tra] -= purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3]; 142 143 //需要補充選定服務器移出去的虛擬機的CPU和MEM 144 purchase_service_info.purchase_service_nodeA_remainCPU[_count] += purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]; 145 purchase_service_info.purchase_service_nodeA_remainMEM[_count] += purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3]; 146 147 148 vmOnServer[std::to_string(purchase_service_info.purchase_service_ID_Info[_count][vm_tra])] = vector<int>{ 149 purchase_service_info.purchase_service_ID_Info[service_tra][0], 150 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2], 151 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3],1 }; 152 153 154 assert(purchase_service_info.purchase_service_nodeA_remainCPU[service_tra] >= 0 155 && purchase_service_info.purchase_service_nodeA_remainMEM[service_tra] >= 0); 156 157 158 assert(purchase_service_info.purchase_service_ID_Info[_count][1] / 2 >= purchase_service_info.purchase_service_nodeA_remainCPU[_count] 159 && purchase_service_info.purchase_service_ID_Info[_count][2] / 2 >= purchase_service_info.purchase_service_nodeA_remainMEM[_count]); 160 161 string s; 162 string _migration = "migration"; 163 s = "(" + _migration + ", "; 164 s += std::to_string(1) + ")\n";//(migration, count_migration) 165 res.push_back(s); 166 #ifdef My_PRINT 167 cout << s << endl; 168 #endif 169 170 s = "(" + std::to_string(purchase_service_info.purchase_service_ID_Info[_count][vm_tra]) + ", "; 171 string _AA_A = "A"; 172 s += std::to_string(purchase_service_info.purchase_service_ID_Info[service_tra][0]) + ", ";//(虛擬機ID, 目的服務器ID, A) 173 s += _AA_A + ")\n"; 174 res.push_back(s); 175 176 //添加移入服務器上虛擬機的資訊 177 for (int load_vm = 0; load_vm < 60; load_vm++) //因為del的原因，需要解決洗掉資訊的方面 178 { 179 if (purchase_service_info.purchase_service_ID_Info[service_tra][3 + 4 * load_vm] == 0) 180 { 181 purchase_service_info.purchase_service_ID_Info[service_tra][3 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra]; 182 purchase_service_info.purchase_service_ID_Info[service_tra][4 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1]; //Nodes 183 purchase_service_info.purchase_service_ID_Info[service_tra][5 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]; //CPU 184 purchase_service_info.purchase_service_ID_Info[service_tra][6 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3]; //MEM 185 186 break; 187 } 188 189 190 } 191 192 //需要洗掉從服務器移走虛擬機的資訊 193 purchase_service_info.purchase_service_ID_Info[_count][vm_tra] = 0; 194 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1] = 0; //Nodes 195 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] = 0; //CPU 196 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] = 0; //MEM 197 #ifdef My_PRINT 198 cout << s << endl; 199 #endif 200 201 //計算功耗需要 扣除服務器的虛擬機數量 202 serverRunVms[_count]--; 203 serverRunVms[service_tra]++; 204 205 206 count_migration--; 207 208 //break; //如果判斷是可以移植的話，即進行移植，移植完之后 立馬進行下一個虛擬機 209 return 0; 210 } 211 else 212 { 213 ; 214 } 215 } 216 else if (purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1] == 3)//需要對B節點點進行選擇移植 不需要除/2 217 { 218 if ((purchase_service_info.purchase_service_nodeB_remainCPU[service_tra] >= purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]) 219 && (purchase_service_info.purchase_service_nodeB_remainMEM[service_tra] >= purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3])) 220 { 221 222 223 purchase_service_info.purchase_service_nodeB_remainCPU[service_tra] -= purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]; 224 purchase_service_info.purchase_service_nodeB_remainMEM[service_tra] -= purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3]; 225 226 #ifdef TEST 227 cout << purchase_service_info.purchase_service_nodeB_remainCPU[_count] << purchase_service_info.purchase_service_ID_Info[_count][1] << endl; 228 #endif 229 //需要補充選定服務器移出去的虛擬機的CPU和MEM 230 purchase_service_info.purchase_service_nodeB_remainCPU[_count] += purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]; 231 purchase_service_info.purchase_service_nodeB_remainMEM[_count] += purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3]; 232 233 234 vmOnServer[std::to_string(purchase_service_info.purchase_service_ID_Info[_count][vm_tra])] = vector<int>{ 235 purchase_service_info.purchase_service_ID_Info[service_tra][0], 236 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2], 237 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3],2 }; 238 239 240 #ifdef TEST 241 cout << purchase_service_info.purchase_service_nodeB_remainCPU[_count] << endl; 242 #endif 243 244 assert(purchase_service_info.purchase_service_nodeB_remainCPU[service_tra] >= 0 245 && purchase_service_info.purchase_service_nodeB_remainMEM[service_tra] >= 0); 246 247 248 assert(purchase_service_info.purchase_service_ID_Info[_count][1] / 2 >= purchase_service_info.purchase_service_nodeB_remainCPU[_count] 249 && purchase_service_info.purchase_service_ID_Info[_count][2] / 2 >= purchase_service_info.purchase_service_nodeB_remainMEM[_count]); 250 251 string s; 252 string _migration = "migration"; 253 s = "(" + _migration + ", "; 254 s += std::to_string(1) + ")\n";//(migration, count_migration) 255 res.push_back(s); 256 #ifdef My_PRINT 257 cout << s << endl; 258 #endif 259 260 s = "(" + std::to_string(purchase_service_info.purchase_service_ID_Info[_count][vm_tra]) + ", "; 261 string _BB_B = "B"; 262 s += std::to_string(purchase_service_info.purchase_service_ID_Info[service_tra][0]) + ", ";//(虛擬機ID, 目的服務器ID, B) 263 s += _BB_B + ")\n"; 264 res.push_back(s); 265 266 //添加移入服務器上虛擬機的資訊 267 for (int load_vm = 0; load_vm < 60; load_vm++) //因為del的原因，需要解決洗掉資訊的方面 268 { 269 if (purchase_service_info.purchase_service_ID_Info[service_tra][3 + 4 * load_vm] == 0) 270 { 271 purchase_service_info.purchase_service_ID_Info[service_tra][3 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra]; 272 purchase_service_info.purchase_service_ID_Info[service_tra][4 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1]; //Nodes 273 purchase_service_info.purchase_service_ID_Info[service_tra][5 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2]; //CPU 274 purchase_service_info.purchase_service_ID_Info[service_tra][6 + 4 * load_vm] = purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3]; //MEM 275 276 break; 277 } 278 279 280 } 281 282 //需要洗掉從服務器移走虛擬機的資訊 283 purchase_service_info.purchase_service_ID_Info[_count][vm_tra] = 0; 284 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 1] = 0; //Nodes 285 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 2] = 0; //CPU 286 purchase_service_info.purchase_service_ID_Info[_count][vm_tra + 3] = 0; //MEM 287 288 289 #ifdef My_PRINT 290 cout << s << endl; 291 #endif 292 293 //計算功耗需要 扣除服務器的虛擬機數量 294 serverRunVms[_count]--; 295 serverRunVms[service_tra]++; 296 297 298 count_migration--; 299 300 //break; //如果判斷是可以移植的話，即進行移植，移植完之后 立馬進行下一個虛擬機 301 return 0; 302 } 303 else 304 { 305 ; 306 } 307 } 308 309 if (count_migration == 0) 310 { 311 return 0; 312 } 313 } 314 else 315 { 316 ; 317 } 318 } 319 } 320 else 321 { 322 ; 323 } 324 } 325 //不移動 326 /* 327 if (no_shift == 1) 328 { 329 string s = "(migration, 0)\n"; 330 res.push_back(s); 331 332 no_shift = 0; 333 } 334 */ 335 336 } 337 else 338 { 339 //否則判斷上一個服務器 CPU和MEM（從大號往小號） 340 } 341 342 if (count_migration == 0) 343 { 344 return 0; 345 } 346 //} 347 }View Code
3.4、后期優化方向
如何初始化購買服務器，如何進行虛擬機的遷移，還有擴容策略是優化的重要方面，可能這是個NP-Hard問題，我在這版代碼下，只是實作了虛擬機遷移的一大點，初始化購買服務器和擴容策略是由師兄一起討論，從最后結果來看，我遷移的演算法層面還是欠缺，沒有做好程式的高效移植性，c++功底還是偏弱，和師兄的討論還是少了，對任務的分配還是沒有非常明確，個人對工程演算法實作層面弱，Debug能力弱，希望后面多多學習，
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標籤：C++
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