C # version of smooth weighted round-robin balancing

Nginx based on the implementation of the polling algorithm, it not only realizes the weight-based polling algorithm, but also realizes the smoothing algorithm.
The so-called smooth, that is, in a period of time, not only the server is selected by the number of distributions and their weights consistent, and the scheduling algorithm is also more evenly select the server, and will not concentrate for a period of time only select a high-weighted server.
If the use of random algorithm selection or ordinary weight-based polling algorithm, it is relatively easy to cause a service set is called too much pressure.

For example, for example, a group of servers with weights, {a:5, b:1, c:1) Nginx's smooth polling algorithm chooses a sequence of { a, a, b, a, c, a, a }
This is clearly { c, b, a, a, a, a, a } smoother and more reasonable than the sequence, and does not result in a centralized access to the server.

The C # version code is as follows:

/// <summary>2     ///Weight Object3     /// </summary>4      Public classWeightobject5     {6         /// <summary>7         ///Current Weight8         /// </summary>9          Public intCurrentweight {Set;Get; }Ten  One         /// <summary> A         ///effective -         /// </summary> -          Public intEffectiveweight {Set;Get; } the  -  -         /// <summary> -         ///Weights +         /// </summary> -          Public intWeight {Set;Get; } +  A  at     } -  -      Public classBalancingassignhelper -     { -  -         /// <summary> in         ///algorithm: -         ///On each peer selection we increase current_weight of each eligible peer by its weight, to         ///Select Peer with greatest current_weight and reduce their current_weight by total number of weight points distribute Da Mong Peers. +          Public StaticT next<t> (list<t> servers)whereT:weightobject -         { the             if(Servers = =NULL|| Servers. Count = =0) *             { $                 return NULL;Panax Notoginseng             } -             if(Servers. Count = =1) the             { +                 returnservers[0]; A             } the  +T best =NULL; -  $             //calculate the sum of weights $             intTotal =0; -              for(inti =0; I < servers. Count; i++) -             { the  -T W =Servers[i];Wuyi  the                 if(W = =NULL) -                 { Wu                     Continue; -                 } About  $W.currentweight + =W.effectiveweight; -Total + =W.effectiveweight; -  -                 if(W.effectiveweight <w.weight) A                 { +w.effectiveweight++; the                 } -  $                 if(Best = =NULL|| W.currentweight >Best . Currentweight) the                 { theBest =W; the                 } the  -             } in  the             if(Best = =NULL) the             { About                 return NULL; the             } the  theBest. Currentweight-=Total ; +             returnBest ; -         } the     }Bayi  the     //1. Declare an entity class that inherits Randomobject, such as: * the      Public classServerweightobject:weightobject - { -     /// <summary> the     ///name the     /// </summary> the      Public stringName {Set;Get; } the     /// <summary> -     ///Description the     /// </summary> the      Public stringDescription {Set;Get; } the     //... Other related fields/properties94  the      PublicServerweightobject () the     { theEffectiveweight =Weight;98     } About } - 101 102     /// <summary>103     ///DEMO104     /// </summary> the      Public classBalancingassigndemo106     {107 108          Public voidMain ()109         { the 111             //1. Initialize the call data, such as: thelist<serverweightobject> list =NewList<serverweightobject>();113List. ADD (Newserverweightobject {Name ="A", Weight =2 }); theList. ADD (Newserverweightobject {Name ="B", Weight =3 }); theList. ADD (Newserverweightobject {Name ="C", Weight =5}); the             //list. ADD (new Serverweightobject {Name = "D", Weight = 3});117             //list. ADD (new Serverweightobject {Name = "E", Weight = 4});118             //list. ADD (new Serverweightobject {Name = "F", Weight = 5});119             //list. ADD (new Serverweightobject {Name = "G", Weight = $); -              for(inti =0; I < -; i++)121             {122System.Diagnostics.Debug.Write (balancingassignhelper.next<serverweightobject>(list). Name);123             }124         } the}

C # version of smooth weighted round-robin balancing