Task assignment is one of the most fundamental combinatorial optimization problems. Solving the Task Assignment Problem is very important for many real time and computational scenarios where a lot of small tasks need to be solved by multiple processors simultaneously. In this paper a Heuristic and Parallel Algorithm for Task Assignment Problem is proposed. Results obtained for certain cases are...

We study the problem of task allocation in heterogeneous distributed systems. The objective is the minimization of the sum of processor execution and intertask communication costs. We transform the problem to a maximization one, where we try to determine and avoid large communication costs and inefficient allocations. After an appropriate graph transformation, we propose two fast algorithms, th...

This Cloud computing is a latest new computing paradigm where applications, data and IT services are provided across dynamic and geographically dispersed organization. Job scheduling system problem is a nucleus and demanding issue in Cloud Computing. How to utilize Cloud computing resources proficiently and gain the maximum profits with job scheduling system is one of the Cloud computing servic...

—We consider the problem of assigning tasks to homogeneous nodes in the distributed system, so as to minimize the amount of communication, while balancing the processors' loads. This issue can be posed as the graph partitioning problem. Given an undirected graph G=(nodes, edges), where nodes represent task modules and edges represent communication, the goal is to divide n, the number of process...

The popularity of Online To Offline (O2O) service platforms has spurred the need for online task assignment in real-time spatial data, where streams of spatially distributed tasks and workers are matched in real time such that the total number of assigned pairs is maximized. Existing online task assignment models assume that each worker is either assigned a task immediately or waits for a subse...