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Energy efficient and robust allocation of interdependent tasks on mobile ad hoc computational grid
Author(s) -
Shah Sayed Chhattan
Publication year - 2014
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3297
Subject(s) - computer science , distributed computing , wireless ad hoc network , resource allocation , computer network , mobile ad hoc network , energy consumption , optimized link state routing protocol , grid , vehicular ad hoc network , data transmission , routing (electronic design automation) , routing protocol , network packet , wireless , engineering , telecommunications , geometry , mathematics , electrical engineering
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.