A Trusted Multi-Task Distribution Mechanism for Internet of Vehicles Based on Smart Contract

In this paper,a trusted multi-task distribution mechanism for Internet of Vehicles based on smart contract is proposed to improve the security and efficiency for the task distribution in Internet of Vehicles.Firstly,a three-tier trusted multi-task distribution framework is presented based on smart contract.The smart contract will be triggered by the task request.As the important part of the smart contract,the task distribution algorithm is stored on the blockchain and run automatically.In the process of the task distribution,the cost of the task distribution and the system stability play a critical role.Therefore,the task distribution problem is formulated to minimize the cost of the task distribution whilst maintaining the stability of the system based on Lyapunov theorem.Unfortunately,this problem is a mixed integer nonlinear programming problem with NP-hard characteristics.To tackle this,the optimization problem is decomposed into two sub problems of computing resource allocation and task distribution decision,and an effective task distribution algorithm is proposed.Simulation results show that the proposed algorithm can effectively improves system performance.

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.

A Homogeneous Cloud Task Distribution Method Based on an Improved Leapfrog Algorithm

Cloud manufacturing is a new manufacturing model with crowd-sourcing characteristics,where a cloud alliance composed of multiple enterprises,completes tasks that a single enterprise cannot accomplish by itself.However,compared with heterogeneous cloud tasks,there are relatively few studies on cloud alliance formation for homogeneous tasks.To bridge this gap,a novel method is presented in this paper.First,a homogeneous cloud task distribution model under cloud environment was constructed,where services description,selection and combination were modeled.An improved leapfrog algorithm for cloud task distribution(ILA-CTD)was designed to solve the proposed model.Different from the current alternatives,the initialization operator and the leapfrog operator in ILA-CTD can ensure that the algorithm always searches the optimal solution in the feasible space.Finally,the processing of task allocation for 1000 pieces of medical labeling machine bottom plates was studied as a case to show the feasibility of the proposed method.The superiority of ILA-CTD was also proven based on more optimal solutions found,compared with the three other methods.

Distributed cooperative task planning algorithm for multiple satellites in delayed communication environment

Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.

A Theory for the Initial Allocating of Real Time Tasks in Distributed Systems

Referring to a set of real time tasks with arriving time,executing time and deadline,this paperdiscusses the problem of polynomial time initial-allocating approximation algorithms in a distributedsystem and five new results are gained which provide a theory for the designing of initial-allocating algorithmsof real time tasks.