Optimal Scheduling for Real-Time Jobs in Energy Harvesting Computing Systems

Abstract

International audienceIn this paper, we study a scheduling problem, in which every job is associated with a release time, deadline, required computation time, and required energy. We focus on an important special case where the jobs execute on a uniprocessor system that is supplied by a renewable energy source and use a rechargeable storage unit with limited capacity. Earliest deadline first (EDF) is a class one online algorithm in the classical real-time scheduling theory where energy constraints are not considered. We propose a semi-online EDF-based scheduling algorithm theoretically optimal (i.e., processing and energy costs neglected). This algorithm relies on the notions of energy demand and slack energy, which are different from the well known notions of processor demand and slack time. We provide an exact feasibility test. There are no restrictions on this new scheduler: each job can be one instance of a periodic, aperiodic, or sporadic task with deadline

Resource Allocation in Green Dense Cellular Networks: Complexity and Algorithms

“…Next, they develop a constant-factor approximation algorithm to solve the problem. Other related work include packet or job scheduling in the context of scheduling theory [17,18]. For example, [17] study the problem of real-time job scheduling in an energy harvesting system.…”

“…In the worst-case, x is increased by 1 every time, i.e., Now, to solve RAED-SCSB-COMMON with energy constraints, we reduce it, in polytime, to an 17 unweighted knapsack problem with cumulative capacity; that is, the capacity of the knapsack is not fixed to T but changes from one slot to another depending on the energy arrivals. Therefore, knowing the maximum accumulated capacity, we can apply PACK to obtain an optimal solution to RAED-SCSB-COMMON.…”

Efficient Energy Consumption Scheduling: Towards Effective Load Leveling

“…the number of customers. Chetto [25] studied the scheduling for real-time jobs, which are executed on a uniprocessor system supplied by a renewable energy source. Wang et al [26] studied the energy-aware data allocation and task scheduling problem on multiprocessor system for real-time applications.…”

SMEH: Stochastic Method of Energy Harvesting for Powering up Mobile Phones

“…The studies toward scheduling as well as provisioning problem was investigated by Chetto et al [7], as it is directly associated with the drainage of energy supply. The author commented that if the scheduling is not performed effectively, the storage module depletes unnecessary power to perform a task.…”