A heuristic resource scheduling scheme in time-constrained networks. (August 2016)

• Record Type: Journal Article
• Authors: Kim, Yang G.; Wang, Yu; Park, ByoungSeob; Choi, Hyo Hyun
• Is Part Of: Computers & electrical engineering. Volume 54(2016)
• Page Start: 1
• Page End: 15
• Publication Date: 2016-08
• Subjects: Multi-channel -- Multi-timeslot -- Multi-hop -- Scheduling algorithms -- End-to-end delay -- Wireless sensor networks; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.06.001
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Multi-channel multi-time slot scheduling algorithms in a multi-hop wireless network. End-to-end delay requirement based meta-heuristic and greedy heuristic resource scheduling algorithms in a realistic factory network. A trade-off study performs in a meta-heuristic scheduling in terms of the complexity and greedy heuristic scheduling in terms of the solution quality in a time-constrained network. A sub-optimal value within a range of end-to-end delay requirements rather than an optimal value due to the complexity is acceptable. Abstract: Sensor device is emerging as a promising enabler for the development of new solutions in a plethora of Internet of Things (IoT) applications. With the explosion of connected devices, it is essential for conversion gateway between the Internet and sensor nodes to support end-to-end (e2e) interoperability because the current Internet Protocol (IT) does not support end-to-end delay in IEEE 802.15.4e. As part of IoT, we propose a scheduling scheme of multiple channels and multiple timeslots to minimize the e2e delay in multi-hop environments. The proposed greedy heuristic approach is compared with the meta-heuristics in terms of the given end-to-end delay bound. Although the meta-heuristics is more accurate in finding a global optimum or sub-optimal values than the greedy heuristic approach, this advantage comes at the expense of high complexity. The simulation results show that the proposed scheme reduces the complexity by obtaining suboptimal solutions that satisfy the e2e delay requirement.