Automatic Scaling Mechanism of Intermodal EDI System under Green Cloud Computing

Algorithm 3

XDRF algorithm.

	Algorithm name: XDRFforPOD
	/^∗The number of nodes is n, and the resource dimension is m^∗/
	Input: R = < = < to >, …,  = < to >, …,  = < to >>: total resource collection; collection<POP>: POD optimization scheme collection;
	Output: none
	Define variable z = collection<POP>.size: the number of PODs to be calculated; Define variable : the set of allocated resources, represents the number of resources of type j that has been allocated by POD(i) on node k; Define variable : unallocated resource set, represents the number of resources of type j on node k that can be allocated; Define variable : The weight set of POD to be optimized;
	for (i from 1 to z) {
	Calculate the weight of the POD in the collection<POP> according to formula (10) and fill the collection W;
	}
	for (k from 1 to n) {
	Calculate the cluster nodes according to formula (10) and arrange them in ascending order;
	}
	do {
	for (i from 1 to z) {
	For R and Ru sets, calculate the dominant share Si of POD(i) according to formulas (11) and (12), and update the collection<POP> collection, sorted by Si in ascending order;
	}
	//Get the POD with the smallest dominant share (i)
	picking POP(i), the first element of collection<POP>;
	POD(i) = POP(i).POD;
	//Get POD(i) resource requirements such as CPU and memory
	calculate resource demand of POD(i) as Di;
	Calculate the resource Predicates set Npre(i) of POD(i) according to formula (14);
	if () {
	According to formulas (13) or (14), a copy resource r is allocated to POD(i), where r = = Di;
	//Load and run the copy instance
	let replication as result of loading and running POD(i).replicationConfig with r;
	//Register the copy, monitor the data queue and participate in data processing services
	register this replication as consumer to kafka with POP(i).topic;
	//Update resource usage
	; ;
	//Refresh the dominant share of POD(i) according to formulas (12) and (13)
	refresh dominant share for POD(i);
	if (POP(i).dPR-- == 0) {
	//The POD has been expanded and deleted from collection<POP>, and no longer enters //the subsequent allocation process
	POD(i) scaling-up done;
	}}
	//The cluster node resources are exhausted, record the POD information that has not been
	//allocated and exit DRF
	else {
	get unsatisfied POPs as collection<UPOP> from collection<POP>;
	report collection<UPOP> to CAdvisor;
	terminate XDRF;
	}
	/ When collection<POP> is empty, all POD allocation is completed
	If (allocation done for all pod in collection<POP>) {
	report to XTuning allocation done with R and collection<POP>;
	terminate XDRF;
	}} while (true)