Research on task scheduling and concurrent processing technology for energy internet operation platform

The energy Internet operation platform provides market entities such as energy users,energy enterprises,suppliers,and governments with the ability to interact,transact,and manage various operations.Owing to the large number of platform users,complex businesses,and large amounts of data-mining tasks,it is necessary to solve the problems afflicting platform task scheduling and the provision of simultaneous access to a large number of users.This study examines the two core technologies of platform task scheduling and multiuser concurrent processing,proposing a distributed task-scheduling method and a technical implementation scheme based on the particle swarm optimization algorithm,and presents a systematic solution in concurrent processing for massive user numbers.Based on the results of this study,the energy internet operation platform can effectively deal with the concurrent access of tens of millions of users and complex task-scheduling problems.

Concurrent processes scheduling with scarce resources in small and medium enterprises

Scarce resources,precedence and non-determined time-lag are three constraints commonly found in small and medium manufacturing enterprises(SMEs),which are deemed to block the application of workflow management system(WfMS). To tackle this problem,a workflow scheduling approach is proposed based on timing workflow net(TWF-net) and genetic algorithm(GA). The workflow is modelled in a form of TWF-net in favour of process simulation and resource conflict checking. After simplifying and reconstructing the set of workflow instance,the conflict resolution problem is transformed into a resource-constrained project scheduling problem(RCPSP),which could be efficiently solved by a heuristic method,such as GA. Finally,problems of various sizes are utilized to test the performance of the proposed algorithm and to compare it with first-come-firstserved(FCFS) strategy. The evaluation demonstrates that the proposed method is an overwhelming and effective approach for scheduling the concurrent processes with precedence and resource constraints.

PRODUCT MODELING AND PROCESS PLANNING WITHIN CONCURRENT ENGINEERING ENVIRONMENT

A prodouct modeling and a process planning that are two essential basses of realizing concurrent engineering are investigated , a logical modeling technique , grammar representation scheme of technology knowledge and architecture of expert system for process planning within con- current engineering environment are proposed. They have been utilized in a real reaserch project.

Modeling and Verifying Concurrent Programs with Finite Chu Spaces

Finite Chu spaces are proposed for the modeling and verification of concurrent programs.In order to model not only typical concurrent behaviors but also modern exception handling and synchronization mechanisms,we design an enriched process algebra of Chu spaces from a practical point of view.To illustrate the power of finite Chu spaces and the process algebra while abstracting away from language-specific details,an imaginary concurrent programming language（ICL） is designed.A denotational semantics of ICL is presented using finite Chu spaces and the enriched process algebra.The valuation functions are fairly straightforward since the carefully designed operators have done much of the job.The enriched process algebra is also used as the specification language for Chu spaces,with which process-algebraic properties can be specified.Verification algorithms are presented with their time complexities discussed.

Towards application-level elasticity on shared cluster： an actor-based approach

In current cluster computing, several distributed frameworks are designed to support elasticity for business services adapting to environment fluctuation. However, most existing works support elasticity mainly at the resource level, leaving application level elasticity support problem to domain-specific frameworks and applications. This paper proposes an actor-based general approach to support application-level elasticity for multiple cluster computing frameworks. The actor model offers scalability and decouples language-level concurrency from the runtime environment. By extending actors, a new middle layer called Unisupervisor is designed to ＂sit＂ between the resource management layer and application framework layer. Actors in Unisupervisor can automatically distribute and execute tasks over clusters and dynamically scale in/out. Based on Unisupervisor, high-level profiles （MasterSlave, MapReduce, Streaming, Graph, and Pipeline） for diverse cluster computing requirements can be supported. The entire approach is implemented in a prototype system called UniAS. In the evaluation, both benchmarks and real applications are tested and analyzed in a small scale cluster. Results show that UniAS is expressive and efficiently elastic.