Open Access
ARTICLE
TSLBS: A Time-Sensitive and Load Balanced Scheduling Approach to Wireless Sensor Actor Networks
Morteza Okhovvat, Mohammad Reza Kangavari*
School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
E-mail: morteza.okhovvat@gmail.com
* Corresponding Author: E-mail:
Computer Systems Science and Engineering 2019, 34(1), 13-21. https://doi.org/10.32604/csse.2019.34.013
Abstract
Existing works on scheduling in Wireless Sensor Actor Networks (WSANs) are mostly concerned with energy savings and ignore time constraints and thus
increase the make-span of the network. Moreover, these algorithms usually do not consider balance of workloads on the actor nodes and hence, sometimes
some of the actors are busy when some others are idle. These problem causes the actors are not utilized properly and the actors’ lifetime is reduced. In
this paper we take both time awareness and balance of workloads on the actor in WSANs into account and propose a convex optimization model (TAMMs)
to minimize make-span. We also propose a protocol called LIBP to improve load balancing that allocates tasks to actors according to their measured
capabilities in such a way to enhance balances of workloads on the actors. Finally, by combination of TAMMs and LIBP, a time-sensitive and load balanced
scheduling approach (TSLBS) is proposed. TSLBS considers both local and global tasks and the distribution requirements of WSANs (i.e. WSANs with hybrid
architecture). The results of simulations on typical scenarios shows that TSLBs is more efficient in terms of both the make-span and load balancing compared
to stochastic task scheduling algorithm (STSA). We also show that TSLBs performs significantly better than STSA in terms of actor’s lifetime.
Keywords
Cite This Article
M. Okhovvat and M. Reza Kangavari, "Tslbs: a time-sensitive and load balanced scheduling approach to wireless sensor actor networks,"
Computer Systems Science and Engineering, vol. 34, no.1, pp. 13–21, 2019. https://doi.org/10.32604/csse.2019.34.013
Citations