CN104270322A - Self-adaptive load balance scheduling mechanism for internet-of-things device access processing platform - Google Patents
Self-adaptive load balance scheduling mechanism for internet-of-things device access processing platform Download PDFInfo
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Abstract
The invention relates to the technical field of computer networks, in particular to a self-adaptive load balance scheduling mechanism for an internet-of-things device access processing platform. The invention provides a novel scheduling algorithm framework in which a routing policy and a routing algorithm are independently separated, the routing policy can be replaced, the evaluation indicator is expandable, the routing algorithm is open-ended, and three routing policies including a single algorithm policy, a combined algorithm policy and an adaptive algorithm policy, are also provided to deal with the abruptness and the randomness of a device connection request in a real application environment. With the adoption of the self-adaptive load balance scheduling mechanism, an internet-of-things device access system effectively adjusts the distribution condition of the device connection request according to the performance difference and the load conditions of various nodes in a cluster, so that the overall performance of a cluster system is improved. Compared with the prior art, the self-adaptive load balance scheduling mechanism for the internet-of-things device access processing platform has the advantages of novel thought, flexibility in use, and good convenience for expansion, fully meets the scheduling requirements of the connection request of an internet-of-things gateway, and effectively breaks the limitations that the single router is not applicable to all scenes.
Description
Technical field
The present invention relates to technical field of the computer network, particularly relate to the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform.
Background technology
Along with the arrival in Internet of Things epoch, increasing awareness apparatus needs access platform system, and obtains Internet of Things data message quickly and easily by network.In order to solve the concurrent access platform system of large number quipments, adopting distributed type assemblies to dispose becomes commonplace solution.
Load-balancing technique occurs along with the appearance of cluster, and it is one of key technology realizing group system, and its quality directly affects the performance of whole system.Effect Dynamic Load-Balancing Strategy relatively is preferably gone so far as from early stage static load balancing strategy, and from centerized fusion (passive type cluster) to distributed AC servo system (active concentrating) etc.
The design philosophy of Dynamic Load-Balancing Strategy the load characteristic of automatic adaptation system parameter variations and the unknown can carry out control load distribution, and control algolithm difference develops and occurred that passive type clustered control and active concentrating control.
According to the different phase of task matching, load-balancing algorithm can be divided into two classes, static load balancing algorithm and Dynamic Load-balancing Algorithm.First be the task requests stage, system, according to the allocation algorithm pre-set, is distributed to certain node in cluster, i.e. original allocation, is called static scheduling algorithm at this stage allocation algorithm.Next is in cluster running, and when there is node failure or node overload, task by sub-distribution again, namely can be reallocated, and is called dynamic dispatching algorithm at this stage allocation algorithm.
Summary of the invention
The present invention overcomes above-mentioned weak point, object is the self-adapted load balance scheduling mechanism providing internet of things oriented equipment access processing platform, the novel dispatching algorithm framework adopting routing policy to be separated with routing algorithm, overcomes single routing algorithm in existing group system and cannot be suitable for the defect of all scenes.
The present invention achieves the above object by the following technical programs: the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform, comprises the following steps:
1) routing node arranges routing policy according to cluster current operating environment, and routing algorithm required under associating this routing policy, this configuration comes into force;
2) processing node obtains the loading level measurement index of this node, by loading level measurement index with to have distributed linking number periodicity of pack and sent to routing node;
3) routing node receives new gateway device connection request, performs corresponding routing algorithm and obtains candidate target, then produce destination node from candidate target, connection request is dispensed to destination node according to routing policy;
4) routing node receives the loading level measurement index of processing node transmission and distribution linking number, judge each node whether overload, the distribution that routing node takes out on overload node connects, and again carries out reallocation work according to routing policy, keeps the dynamic load leveling of cluster;
5) when running environment changes, step 1 is jumped to).
As preferably, described routing policy and routing algorithm independent separate, routing policy is upper layer module, and routing algorithm is lower module.
As preferably, routing policy is: single algorithm policy or combinational algorithm strategy or adaptation algorithm strategy;
Single algorithm policy is used for equipment access situation and stablizes and have the running environment of adaptable specific routing algorithm;
Combinational algorithm strategy is used for the running environment of equipment access situation the unknown;
Adaptation algorithm strategy is used for equipment access situation, and to replace rule obvious and have specific routing algorithm to be suitable for the running environment of corresponding situation.
As preferably, cluster is according to loading condition and distribute connection and be divided into different mode of operations, and adaptation algorithm strategy selects the routing algorithm of fit optimum according to the mode of operation of cluster.
As preferably, described loading level measurement index is loading level saturation value, is calculated by following steps:
(1) the load information sampling period arranged is obtained during processing node initialization;
(2) processing node gathers the multiple machine performance index of current the machine when sampling time node arrives, and comprises CPU usage, memory usage, disk utilization rate and bandwidth utilization rate, and is normalized each desired value;
(3) processing node is to the smoothing filtering process of multiple machine performance index, reduces " noise " impact in measured data;
(4) multiple machine performance index obtains the scalar of a scope from 0 to 1 as input parameter by multiple input single output calculated with mathematical model, and this scalar is expressed as loading level saturation value.
As preferably, the determination methods of overload is: the load that loading level saturation value the is greater than setting difference controlled in threshold value or loading level saturation value and cluster between minimum load degree saturation value is greater than the threshold value of setting.
Beneficial effect of the present invention is: the novel dispatching algorithm framework that (1) adopts routing policy to be separated with routing algorithm, and make the division of labor of routing algorithm and routing policy definitely, responsibility is more clear; (2) routing algorithm can carry out combining and adaptation as unit member, changes the limitation that routing algorithm effectively can evade single algorithm the time of running; (3) three kinds of routing policies complement each other, and can adapt to environment of internet of things complicated and changeable, and the Pre-Evaluation mechanism adding the survival of the fittest of distribution target carries out better adaptive scheduling, keeps cluster dynamic load leveling; (4) platform can light integrated new routing algorithm, and evaluation function also can spread, reaches the requirement of open type software architecture design completely.
Accompanying drawing explanation
Fig. 1 is theory structure schematic diagram of the present invention;
Fig. 2 is the schematic flow sheet that the present invention realizes the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform;
Fig. 3 is the renewal schematic flow sheet that processing node obtains loading level measurement index;
Fig. 4 is the schematic flow sheet carrying out dispatching distribution after routing node accepting device connection request of the present invention;
Fig. 5 is the single algorithm policy schematic flow sheet in routing policy of the present invention;
Fig. 6 is the combinational algorithm strategic process schematic diagram in routing policy of the present invention;
Fig. 7 is the adaptation algorithm strategic process schematic diagram in routing policy of the present invention;
Fig. 8 is the schematic flow sheet that routing node of the present invention keeps cluster dynamic load leveling;
Fig. 9 is expansion adaptation algorithm strategic process schematic diagram of the present invention.
Embodiment
Below in conjunction with specific embodiment, the present invention is described further, but protection scope of the present invention is not limited in this:
Embodiment 1: as shown in Figure 1, self-adapted load balance scheduling of the present invention is realized by routing node, processing node, routing node is responsible for the load balancing between the dispatching distribution of newly-built equipment connection request and clustered node, and processing node is responsible for monitoring in real time the load state of this node and is carried out the Business Processing of all access devices of this section point.When gateway device access platform, dispatching distribution to carry out data and business process to certain processing node is responsible for by routing node, when cluster load imbalance, routing node is responsible for the equipment connection on heavier loads node being migrated to the enterprising row relax of the lighter processing node of other loads.
As shown in Figure 2, the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform, routing node is adopted to monitor the load condition of cluster processing node in real time and the thought that is separated with algorithm of the distribution condition of self-adaptative adjustment equipment access process, strategy, scheduling mechanism can carry out in the mode of best-fit running environment the work safeguarding cluster load balance on higher abstraction hierarchy, thus ensures overall performance and the stable operation of platform.
Realize above-mentioned self-adapted load balance scheduling mechanism, comprise the following steps:
1) routing node arranges routing policy according to cluster current operating environment, and routing algorithm required under associating this routing policy, this configuration comes into force;
2) processing node obtains the loading level measurement index of this node, by loading level measurement index with to have distributed linking number periodicity of pack and sent to routing node;
3) routing node receives new gateway device connection request, performs corresponding routing algorithm and obtains candidate target, then produce destination node from candidate target, connection request is dispensed to destination node according to routing policy;
4) routing node receives the loading level measurement index of processing node transmission and distribution linking number, judge each node whether overload, the distribution that routing node takes out on overload node connects, and again carries out reallocation work according to routing policy, keeps the dynamic load leveling of cluster;
5) when running environment changes, step 1 is jumped to).
Processing node mainly from but be not limited to the load condition that following four kinds of performance index investigate this node, this load condition is called loading level measurement index, comprise: CPU usage, memory usage, disk utilization rate, network bandwidth utilization rate, and loading level saturation value is calculated to unify the current load information weighing computing node by function model, namely loading level measurement index loading level saturation value represents.
CPU usage, the CPU usage of present sample timing node.
Memory usage, the CPU usage of present sample timing node.
Disk utilization rate, the disk utilization rate of present sample timing node.
Network bandwidth utilization rate, the network bandwidth utilization rate of present sample timing node.
Loading level saturation value, the abstract representation of the machine loading information of present sample timing node, span [0,1], 0 represents completely non-loaded, and 1 represents complete full load.
As shown in Figure 3, loading level measurement index is by processing node by periodically obtaining, and more new technological process detailed process comprises the following steps:
Step 301: processing node initialization is connected with the TCP of routing node is long, and arranges the load information sampling period;
Step 302: processing node regularly performs step 303 to step 306 according to the sampling period;
Step 303: processing node gathers the multiple machine performance index of current the machine when sampling time node arrives, and is normalized each desired value;
Step 304: processing node carries out low-pass filtering treatment to multiple machine performance index, reduces " noise " impact in measured data, obtains level and smooth data and export;
Step 305: multiple machine performance index calculates load information as input parameter by the load function model of multiple input single output, this load information be a scope from 0 to 1 scalar, this scalar is expressed as loading level saturation value, load function model can be used but not limited to by positive inverse function to performance index value is converted to multiple median then linear weighted function obtain unique output valve;
Step 306: loading level saturation value is reported to routing node by the long connection of TCP by processing node;
The present invention samples the novel dispatching algorithm framework of routing policy and routing algorithm independent separate, and namely by two-layer design module, lower module is routing algorithm, and upper layer module is routing policy.Routing algorithm mainly performs the evaluation work of candidate allocation target when gateway device accesses, and the unification of final distribution target is carried out assessment by routing policy and obtained.Provide the sudden and randomness that three kinds of routing policies tackle equipment connection request in true applied environment, comprise single algorithm policy, combinational algorithm strategy and adaptation algorithm strategy.Routing algorithm comprises multiple current main-stream routing algorithm, comprises weighting Smallest connection and figures method, polling algorithm, distributed AC servo system algorithm and ant group algorithm, can carry out free expansion in platform.
When routing node receives new gateway device connection request, perform corresponding routing algorithm according to routing policy and obtain candidate target, then produce destination node from candidate target, connection request is dispensed to destination node.Detailed process comprises the following steps, as shown in Figure 4:
Step 401: new gateway device access or have distributing equipment and connect when again distributing, routing node starts allocating task;
Step 402: routing node to obtain in configuration file routing policy and associates the configuration informations such as routing algorithm, and this configuration information can change at any time;
Step 403: routing node produces according to different routing policy patterns and distributes target accordingly:
The use number of single algorithm policy limit algorithm is 1 but does not limit to adopt which kind of algorithm, can carry out replacing used specific algorithm the time of running at platform, is applicable to equipment access situation and stablizes and cause the adaptable scene of certain special algorithm.As shown in Figure 5, single algorithm policy performs the algorithm A1 arranged to single algorithm policy schematic flow sheet, and the distribution target of generation is candidate target, and this candidate target is final destination node.When cluster running environment changes, the inapplicable current environment of algorithm A1, replaces algorithm A1 by arranging by the algorithm B1 adapting to current operating environment.
The number that combinational algorithm strategy uses algorithm and kind all do not limit, and can replace wherein one or more algorithms the time of running at platform, are applicable to equipment access situation unknown and to the scene causing single algorithm effectively to adapt to.As shown in Figure 6, each algorithm produces a candidate target and calculates corresponding evaluation index value simultaneously combinational algorithm strategic process schematic diagram, and evaluation index is worth maximum candidate target as distribution target, and this distribution target is destination node, and algorithm can be replaced at any time.
Adaptation algorithm strategy belongs to empirical mode, and as shown in Figure 7, adaptation algorithm strategy chooses the best algorithm of fit according to current cluster mode of operation, and the candidate target that algorithm produces is distribution target, and synchronization only exists an algorithm and not replaceable.Typical mode of operation includes but not limited to following two kinds: active mode and inactive pattern.Active mode represents that the gateway device connection request of new platform is less or more stable, and the business data processing motion frequency of access device is higher.The data processing activity frequency of inactive modal representation platform access device is lower, and new gateway device connection request is more or situation is unknown.
Step 404: gateway device connection is dispensed on destination node by routing node;
Step 405: judge that in allocating task, whether all devices connection request is disposed, if process terminates, enters next step, otherwise is back to step 402.
Step 406: routing node continues listening port and waits for new allocating task.
In order to keep cluster dynamic load leveling, routing node receives the loading level measurement index of processing node transmission and distribution linking number, judge each node whether overload, the distribution that routing node takes out on overload node connects, again reallocation work is carried out according to routing policy, as shown in Figure 8, specifically comprise the following steps:
Step 801: routing node is monitored by TCP long connection and received loading level saturation value that each processing node reports and distributed the information such as linking number, concrete loading level saturation value more new technological process see Fig. 3;
Step 802: routing node upgrades cluster state and mode of operation, and sorts to all processing nodes according to loading level saturation value size, finds out the processing node (namely the load saturation angle value of this node is maximum) of pack heaviest;
Step 803: routing node judges whether current cluster meets the condition of state transition, if met, enter next step, otherwise be back to step 801, Rule of judgment is the threshold value that the load difference controlled in threshold value or loading level saturation value and cluster between minimum load degree saturation value that loading level saturation value is greater than setting is greater than setting.
Step 804: routing node activates the sub-thread of process, starts connection migration task, arranges migration and connects the relevant informations such as node that source, place target is pack heaviest and required migration linking number;
Step 805: obtain gateway device from source target and connect, and connect the facility information of association and business contexts information etc. therewith;
Step 806: according to the equipment connection dispatching distribution workflow of Fig. 4 by this connection migration in new distribution target;
Step 807: the contextual information of this connection and facility information are synchronized in new distribution node;
Step 808: judge in migration task, whether required migration connection is all disposed, if process terminates, paulospore thread (i.e. step 809), otherwise be back to step 805.
Illustrate how to carry out flexible expansion to novel dispatching algorithm framework of the present invention with newly-increased adaptation algorithm strategy, expansion flow process is see Fig. 9, and detailed process comprises the following steps:
Step 901: platform, first through the testing results of combinational algorithm strategy and single algorithm policy, finds out the algorithm that the corresponding fit of characteristic sum of working platform pattern is best;
Step 902: judge whether to need to add new routing algorithm to produce candidate target, if need, realize interface RouteStrategyService, otherwise enter next step;
Step 903: judge whether to need to change the cluster mode realization dividing mode of operation according to operation characteristic, if need, realize interface FamilyClusterStatus<T extends Object>, otherwise enter next step;
Step 904: judge whether that the candidate target evaluation criterion needing to change acquiescence realizes, if need, realize interface ScoreVoter, otherwise enter next step;
Step 905: realize interface PolicyVoter and complete traffic control that routing policy does, selects the traffic control of best-fit algorithm and the candidate target produced according to evaluation criterion filtering algorithm under namely realizing different mode;
Step 906: all classes that realizes are carried out packing and are re-deployed in platform running environment, in amendment configuration file, routing algorithm and routing policy are up-to-date realize class, the adaptation algorithm strategy that platform dynamic load is newly-increased.
The know-why being specific embodiments of the invention and using described in above, if the change done according to conception of the present invention, its function produced do not exceed that specification and accompanying drawing contain yet spiritual time, must protection scope of the present invention be belonged to.
Claims (6)
1. the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform, is characterized in that, comprise the following steps:
1) routing node arranges routing policy according to cluster current operating environment, and routing algorithm required under associating this routing policy, this configuration comes into force;
2) processing node obtains the loading level measurement index of this node, by loading level measurement index with to have distributed linking number periodicity of pack and sent to routing node;
3) routing node receives new gateway device connection request, performs corresponding routing algorithm and obtains candidate target, then produce destination node from candidate target, connection request is dispensed to destination node according to routing policy;
4) routing node receives the loading level measurement index of processing node transmission and distribution linking number, judge each node whether overload, the distribution that routing node takes out on overload node connects, and again carries out reallocation work according to routing policy, keeps the dynamic load leveling of cluster;
5) when running environment changes, step 1 is jumped to).
2. the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform according to claim 1, it is characterized in that, described routing policy and routing algorithm independent separate, routing policy is upper layer module, and routing algorithm is lower module.
3. the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform according to claim 2, it is characterized in that, routing policy is: single algorithm policy or combinational algorithm strategy or adaptation algorithm strategy;
Single algorithm policy is used for equipment access situation and stablizes and have the running environment of adaptable specific routing algorithm;
Combinational algorithm strategy is used for the running environment of equipment access situation the unknown;
Adaptation algorithm strategy is used for equipment access situation, and to replace rule obvious and have specific routing algorithm to be suitable for the running environment of corresponding situation.
4. the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform according to claim 3, it is characterized in that, cluster is divided into different mode of operations according to loading condition and distribution connection, and adaptation algorithm strategy selects the routing algorithm of fit optimum according to the mode of operation of cluster.
5. the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform according to claim 1, it is characterized in that, described loading level measurement index is loading level saturation value, is calculated by following steps:
(1) the load information sampling period arranged is obtained during processing node initialization;
(2) processing node gathers the multiple machine performance index of current the machine when sampling time node arrives, and comprises CPU usage, memory usage, disk utilization rate and bandwidth utilization rate, and is normalized each desired value;
(3) processing node is to the smoothing filtering process of multiple machine performance index, reduces " noise " impact in measured data;
(4) multiple machine performance index obtains the scalar of a scope from 0 to 1 as input parameter by multiple input single output calculated with mathematical model, and this scalar is expressed as loading level saturation value.
6. the self-adapted load balance scheduling mechanism of internet of things oriented equipment access processing platform according to claim 5, it is characterized in that, the determination methods of overload is: the load difference controlled in threshold value or loading level saturation value and cluster between minimum load degree saturation value that loading level saturation value is greater than setting is greater than the threshold value of setting.
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