Energy efficient and robust allocation of interdependent tasks on mobile ad hoc computational grid

Abstract

Summary A mobile ad hoc computational grid is a distributed computing infrastructure that allows mobile nodes to share computing resources in a mobile ad hoc environment. Compared to traditional distributed systems such as grids and clouds, resource allocation in mobile ad hoc computational grids is not straightforward because of node mobility, limited battery power and an infrastructure‐less network environment. The existing schemes are either based on a decentralized architecture that results in poor allocation decisions or assume independent tasks. This paper presents a scheme that allocates interdependent tasks and aims to reduce task completion time and the amount of energy consumed in transmission of data. This scheme comprises two key algorithms: resource selection and resource allocation. The resource selection algorithm is designed to select nodes that remain connected for a longer period, whereas the resource assignment or allocation algorithm is developed to allocate interdependent tasks to the nodes that are accessible at the minimum transmission power. The scheme is based on a hybrid architecture that results in effective allocation decisions, reduces the communication cost associated with the exchange of control information, and distributes the processing burden among the nodes. The paper also investigates the relationship between the data transfer time and transmission energy consumption and presents a power‐based routing protocol to reduce data transfer costs and transmission energy consumption. Copyright © 2014 John Wiley & Sons, Ltd.

Private mobile edge cloud for 5G network applications

“…However, energy‐efficient protocols designed for battery‐powered nodes and network layers may not fully utilize other network layer resources. A detailed analysis of existing energy aware protocols and algorithms is provided in References .…”

“…Determining which of these two options should be used requires an estimation of task completion time, which is not straightforward for data‐oriented applications due to the complex, heterogeneous multinetwork environment. Existing cost estimation models are designed for homogenous network environments and therefore assume data transmission via a single communication link …”

“…A summary of existing systems is given in Table . A detailed analysis of existing resource management systems is provided in References .…”

“…The new models should consider mobility history, link quality, link lifetimes, energy consumption, central processing unit overhead, operating system overhead, and task dispatch times. To manage application failure, Markov‐chain‐based failure avoidance mechanisms developed in References should be used.…”

A quantum‐inspired binary gravitational search algorithm–based job‐scheduling model for mobile computational grid

“…Shah, in his work, proposed an approach that schedules the interdependent tasks to the best resources to minimize the total completion time and the amount of energy consumed in data transmission. 30 In another work, Shah and Park 31 proposed a hybrid power-based resource allocation scheme for interdependent tasks to nodes within mobile ad hoc computational grid while minimizing the transmission power. Also, a power-based algorithm is proposed to search the closest nodes to allocate a set of interdependent tasks so that energy consumption and communication cost can be reduced.…”