Task allocation in volunteer computing networks under monetary budget constraints

et al. 2020

Symmetry

As a type of distributed computing, volunteer computing (VC) has provided unlimited computing capacity at a low cost in recent decades. The architecture of most volunteer computing platforms (VCPs) is a master–worker model, which defines a master–slave relationship. Therefore, VCPs can be considered asymmetric multiprocessing systems (AMSs). As AMSs, VCPs are very promising for providing computing services for users. Users can submit tasks with deadline constraints to the VCPs. If the tasks are completed within their deadlines, VCPs will obtain the benefits. For this application scenario, this paper proposes a new task assignment problem with the maximum benefits in VCPs for the first time. To address the problem, we first proposed a list-based task assignment (LTA) strategy, and we proved that the LTA strategy could complete the task with a deadline constraint as soon as possible. Then, based on the LTA strategy, we proposed a maximum benefit scheduling (MBS) algorithm, which aimed at maximizing the benefits of VCPs. The MBS algorithm determined the acceptable tasks using a pruning strategy. Finally, the experiment results show that our proposed algorithm is more effective than current algorithms in the aspects of benefits, task acceptance rate and task completion rate.

Section: Dynamic Task Assignment Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on the Task Assignment Problem with Maximum Benefits in Volunteer Computing Platforms

et al. 2020

Symmetry

“…This type of algorithms is called throughput driven task scheduling algorithm, which has been extensively studied in previous work. For example, Guler et al [26] proposed a task allocation algorithm to maximize the number of task completions under monetary budget constraint. They also verify the effectiveness of their algorithm under the price of the electricity consumed by their peers.…”

Section: Task Scheduling Algorithms In Volunteer Computing Platformsmentioning

confidence: 99%

Dynamic Task Scheduling Algorithm with Deadline Constraint in Heterogeneous Volunteer Computing Platforms

et al. 2019

Future Internet

Volunteer computing (VC) is a distributed computing paradigm, which provides unlimited computing resources in the form of donated idle resources for many large-scale scientific computing applications. Task scheduling is one of the most challenging problems in VC. Although, dynamic scheduling problem with deadline constraint has been extensively studied in prior studies in the heterogeneous system, such as cloud computing and clusters, these algorithms can’t be fully applied to VC. This is because volunteer nodes can get offline whenever they want without taking any responsibility, which is different from other distributed computing. For this situation, this paper proposes a dynamic task scheduling algorithm for heterogeneous VC with deadline constraint, called deadline preference dispatch scheduling (DPDS). The DPDS algorithm selects tasks with the nearest deadline each time and assigns them to volunteer nodes (VN), which solves the dynamic task scheduling problem with deadline constraint. To make full use of resources and maximize the number of completed tasks before the deadline constraint, on the basis of the DPDS algorithm, improved dispatch constraint scheduling (IDCS) is further proposed. To verify our algorithms, we conducted experiments, and the results show that the proposed algorithms can effectively solve the dynamic task assignment problem with deadline constraint in VC.

“…Because the donated resources of VN are not available all the time, the completion time (makspan) of a task is usually hours or days. Therefore, the goal of many task assignment algorithms in prior studies [6][7][8][9] was to maximize the rate of task completion. However, as mentioned in References [10,11], minimizing the turnaround time of a task or batches of tasks was very meaningful for some special VC applications.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, many prior studies [7,9,14] about task assignment focused on independent tasks. However, the tasks of some VC applications in practice are precedence-constrained.…”

Section: Introductionmentioning

confidence: 99%

Task Assignment Algorithm Based on Trust in Volunteer Computing Platforms

et al. 2019

Information

In volunteer computing (VC), the expected availability time and the actual availability time provided by volunteer nodes (VNs) are usually inconsistent. Scheduling tasks with precedence constraints in VC under this situation is a new challenge. In this paper, we propose two novel task assignment algorithms to minimize completion time (makespan) by a flexible task assignment. Firstly, this paper proposes a reliability model, which uses a simple fuzzy model to predict the time interval provided by a VN. This reliability model can reduce inconsistencies between the expected availability time and actual availability time. Secondly, based on the reliability model, this paper proposes an algorithm called EFTT (Earliest Finish Task based on Trust, EFTT), which can minimize makespan. However, EFTT may induce resource waste in task assignment. To make full use of computing resources and reduce task segmentation rate, an algorithm IEFTT (improved earliest finish task based on trust, IEFTT) is further proposed. Finally, experimental results verify the efficiency of the proposed algorithms.