scholarly journals HAGP: A Heuristic Algorithm Based on Greedy Policy for Task Offloading with Reliability of MDs in MEC of the Industrial Internet

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3513
Author(s):  
Min Guo ◽  
Xing Huang ◽  
Wei Wang ◽  
Bing Liang ◽  
Yanbing Yang ◽  
...  
Keyword(s):  
Heuristic Algorithm ◽  
Residual Energy ◽  
Mixed Integer ◽  
Mobile Environment ◽  
Cycle Frequency ◽  
Industrial Internet ◽  
Battery Capacity ◽  
System Overhead ◽  
Greedy Policy ◽  
Task Offloading

In the Industrial Internet, computing- and power-limited mobile devices (MDs) in the production process can hardly support the computation-intensive or time-sensitive applications. As a new computing paradigm, mobile edge computing (MEC) can almost meet the requirements of latency and calculation by handling tasks approximately close to MDs. However, the limited battery capacity of MDs causes unreliable task offloading in MEC, which will increase the system overhead and reduce the economic efficiency of manufacturing in actual production. To make the offloading scheme adaptive to that uncertain mobile environment, this paper considers the reliability of MDs, which is defined as residual energy after completing a computation task. In more detail, we first investigate the task offloading in MEC and also consider reliability as an important criterion. To optimize the system overhead caused by task offloading, we then construct the mathematical models for two different computing modes, namely, local computing and remote computing, and formulate task offloading as a mixed integer non-linear programming (MINLP) problem. To effectively solve the optimization problem, we further propose a heuristic algorithm based on greedy policy (HAGP). The algorithm achieves the optimal CPU cycle frequency for local computing and the optimal transmission power for remote computing by alternating optimization (AP) methods. It then makes the optimal offloading decision for each MD with a minimal system overhead in both of these two modes by the greedy policy under the limited wireless channels constraint. Finally, multiple experiments are simulated to verify the advantages of HAGP, and the results strongly confirm that the considered task offloading reliability of MDs can reduce the system overhead and further save energy consumption to prolong the life of the battery and support more computation tasks.

scholarly journals Lifetime and Energy Efficiency Improvement Techniques for Hierarchical Networks

2019 ◽  
Vol 9 (1S6) ◽  
pp. 62-72
Keyword(s):  
Cost Effective ◽  
Residual Energy ◽  
Efficiency Improvement ◽  
Hierarchical Networks ◽  
Energy Efficiency Improvement ◽  
Battery Capacity ◽  
Time Scheduling ◽  
Network Operation ◽  
Simulation Results ◽  
Hole Detection

The detection points are the detection points in the space of network. The properties of detection points include cost effective materials and longer battery capacity. WSN can span variety of applications like sensing of data related to environment entities, detection of enemy vehicles. Lifetime ratio defines the efficiency of the WSN network operation. There are multiple techniques which can help in improvement of Network Lifetime (NL) spanning from transmission nature, data connections, formation of System and time scheduling. This paper provides the analysis of how energy consumption happens and its effect on lifetime ratio. LEACH and CHEF algorithms responsible for hierarchical kind of routing are discussed in detail with simulation results. The parameters used for comparison includes delay, hops, consumption of energy. Non-Hole detection points, Hole detection points, Non-Hole to Hole Ratio, residual energy, routing overhead and throughput.

scholarly journals A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6610
Author(s):  
Raka Jovanovic ◽  
Islam Safak Bayram ◽  
Sertac Bayhan ◽  
Stefan Voß
Keyword(s):  
Public Transport ◽  
High Speed ◽  
Large Scale ◽  
Integer Program ◽  
Mixed Integer ◽  
Transport Systems ◽  
Mixed Integer Program ◽  
Scheduling Problems ◽  
Electric Bus ◽  
Battery Capacity

Electrifying public bus transportation is a critical step in reaching net-zero goals. In this paper, the focus is on the problem of optimal scheduling of an electric bus (EB) fleet to cover a public transport timetable. The problem is modelled using a mixed integer program (MIP) in which the charging time of an EB is pertinent to the battery’s state-of-charge level. To be able to solve large problem instances corresponding to real-world applications of the model, a metaheuristic approach is investigated. To be more precise, a greedy randomized adaptive search procedure (GRASP) algorithm is developed and its performance is evaluated against optimal solutions acquired using the MIP. The GRASP algorithm is used for case studies on several public transport systems having various properties and sizes. The analysis focuses on the relation between EB ranges (battery capacity) and required charging rates (in kW) on the size of the fleet needed to cover a public transport timetable. The results of the conducted computational experiments indicate that an increase in infrastructure investment through high speed chargers can significantly decrease the size of the necessary fleets. The results also show that high speed chargers have a more significant impact than an increase in battery sizes of the EBs.

An Efficient Heuristic Algorithm for Solving Crane Scheduling Problem

2013 ◽  
Vol 442 ◽  
pp. 443-449
Author(s):  
Xie Xie ◽  
Yan Ping Li ◽  
Yong Yue Zheng ◽  
Xiao Li Li
Keyword(s):  
Heuristic Algorithm ◽  
Mixed Integer Linear Programming ◽  
Numerical Experiments ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Crane Scheduling ◽  
Technological Requirement ◽  
Iron And Steel ◽  
Analytical Properties ◽  
Upper Level

This paper focuses on a single crane scheduling problem which is motivated by cooled-rolling material warehouse in the iron and steel enterprise. As storage technological requirement, coils have been stored on the pre-specified position in two levels. If a demanded coil is in the upper level, it can be picked up directly. If a demanded coil in the lower level is blocked by un-demanded coils, the coil can not be transported until all the blocking coils are shuffled to another position. Our problem combines transportation and shuffling simultaneously for crane to pick up all demanded coils as early as possible to designated place (makespan). We first propose a mixed integer linear programming (MILP) model. Some analytical properties are further provided. Based on these properties, we propose a polynomial-time heuristic algorithm. Numerical experiments are carried out to confirm our proposed methods can provide high quality solutions.

scholarly journals A Risk-Sensitive Task Offloading Strategy for Edge Computing in Industrial Internet of Things

2021 ◽  
Author(s):  
Xiaoyu Hao ◽  
Ruohai Zhao ◽  
Tao Yang ◽  
Yulin Hu ◽  
Bo Hu ◽  
...  
Keyword(s):  
At Risk ◽  
Internet Of Things ◽  
Value At Risk ◽  
Communication Systems ◽  
Edge Computing ◽  
Conditional Value At Risk ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
End To End ◽  
Task Offloading

Abstract Edge computing has become one of the key enablers for ultra-reliable and low-latency communications in the industrial Internet of Things in the fifth generation communication systems, and is also a promising technology in the future sixth generation communication systems. In this work, we consider the application of edge computing to smart factories for mission-critical task offloading through wireless links. In such scenarios, although high end-to-end delays from the generation to completion of tasks happen with low probability, they may incur severe casualties and property loss, and should be seriously treated. Inspired by the risk management theory widely used in finance, we adopt the Conditional Value at Risk to capture the tail of the delay distribution. An upper bound of the Conditional Value at Risk is derived through analysis of the queues both at the devices and the edge computing servers. We aim to find out the optimal offloading policy taking into consideration both the average and the worst case delay performance of the system. Given that the formulated optimization problem is a non-convex mixed integer non-linear programming problem, a decomposition into sub-problems is performed and a two-stage heuristic algorithm is proposed. Simulation results validate our analysis and indicate that the proposed algorithm can reduce the risk in both the queueing and end-to-end delay.

The Value of Energy Flexibility: Integrating Wind Resources in New York State

2018 ◽  
Author(s):  
Terence M. Conlon ◽  
Vijay Modi ◽  
Michael B. Waite
Keyword(s):  
New York ◽  
Energy Storage ◽  
New York State ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
York State ◽  
Average Load ◽  
Battery Capacity ◽  
Wind Potential ◽  
Wind Resources

This paper explores the effects of energy system flexibility on the contribution of wind generation to the New York State (NYS) electricity generation mix. First, the benefits of NYS-specific flexible hydropower are investigated. For all simulations, a mixed integer linear program minimizes net load to determine the maximum aggregate capacity factor for the installed wind power. A similar routine explores the benefits of three different types of energy flexibility: flexible supply, flexible demand, and bidirectional flexibility (i.e. energy storage). To compare across technologies, a novel method of standardizing flexibility inputs, Potential Flexible Energy (PFE), is introduced. With 30 GW wind capacity in NYS (average electricity demand of 18.7 GW), introducing electric vehicles with an average load of 1.44 GW and daily available battery capacity of 34.5 GWh (roughly equivalent to the daily use of 3.4 million passenger EVs) increases statewide wind utilization by 840 MW (9.0% of wind potential and 4.5% of average load). Added flexibility in the form of energy storage yields similar results: with 3.2 GW charge/discharge capability and 76.8 GWh storage capacity, statewide wind utilization increases by an average of 660 MW (7.0% of wind potential and 3.5% of average load). Because of transmission constraints and the geographic distribution of high-potential wind resources, increased wind utilization is only achieved when flexibility is added in the region where 86% of the 30 GW simulated wind capacity is located.

Designing a scheduling decision support system for the skin pass line: A case study of the steel finishing line

2020 ◽  
Vol 234 (13) ◽  
pp. 1640-1655 ◽  
Author(s):  
Parinaz Vaez ◽  
Armin Jabbarzadeh ◽  
Nader Azad
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Heuristic Algorithm ◽  
Production Scheduling ◽  
Mixed Integer ◽  
Total Production ◽  
Steel Company ◽  
Manual Method ◽  
Skin Pass

In this paper, we investigate the scheduling policies in the iron and steel industry, and in particular, we formulate and propose a solution to a complicated problem called skin pass production scheduling in this industry. The solution is to generate multiple production turns for the skin pass coils and, at the same time, determine the sequence of these turns so that productivity and product quality are maximized, while the total production scheduling cost, including the costs of tardiness, flow of material, and the changeover cost between adjacent and non-adjacent coils, is minimized. This study has been prompted by a practical problem in an international steel company in Iran. In this study, we present a new mixed integer programming model and develop a heuristic algorithm, as the commercial solvers would have difficulty in solving the problem. In our heuristic algorithm, initial solutions are obtained by a greedy constraint satisfaction algorithm, and then a local search method is developed to improve the initial solution. The experimental results tested on the data collected from the steel company show the efficiency of the proposed heuristic algorithm by solving a large-sized instance in a reasonable computation time. The average deviation between the manual method and the heuristic algorithm is 30%. Also, in all the components of the objective function, the algorithm performs better compared to the manual method. The improved values are greater than 15. In addition, we develop a commercial decision support system for the implementation of the proposed algorithm in the steel company.

scholarly journals Electric vehicle routing problem with backhauls considering the location of charging stations and the operation of the electric power distribution system

TecnoLógicas ◽  
2019 ◽  
Vol 22 (44) ◽  
pp. 1-20 ◽  
Author(s):  
Luis Carlos Cubides ◽  
Andrés Arias Londoño ◽  
Mauricio Granada Echeverri
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Power Distribution ◽  
Vehicle Routing Problem ◽  
Distribution Network ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Routing Problem ◽  
Battery Capacity ◽  
Charging Stations

Logistics companies are largely encouraged to make greener their operations through an efficient solution with electric vehicles (EVs). However, the driving range is one of the limiting aspects for the introduction of EVs in logistics fleet, due to the low capacity provided by the batteries to perform the routes. In this regards, it is necessary to set up a framework to virtually increase this battery capacity by locating EV charging stations (EVCSs) along the transportation network for the completion of their routes. By the other side, the Distribution Network Operators (DNOs) express the concern associated with the inclusion of new power demands to be attended (installation of EVCSs) in the Distribution Network (DN), without reducing the optimal power supply management for the end-users. Under these circumstances, in this paper the Electric Vehicle Routing Problem with Backhauls and optimal operation of the Distribution Network (EVRPB-DN) is introduced and formulated as a mixed-integer linear programming model, considering the operation of the DN in conditions of maximum power demand. Different candidate points for the EVs charging are considered to recharge the battery at the end of the linehaul route or during the backhaul route. The problem is formulated as a multi-objective approach where the transportation and power distribution networks operation are modeled. The performance and effectiveness of the proposed formulation is tested in VRPB instance datasets and DN test systems from the literature. Pareto fronts for each instance are presented, using the ε-constraint methodology.

scholarly journals Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 999 ◽  
Author(s):  
Holger Hesse ◽  
Volkan Kumtepeli ◽  
Michael Schimpe ◽  
Jorn Reniers ◽  
David Howey ◽  
...  
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Mixed Integer ◽  
Time Variability ◽  
Data Set ◽  
Electricity Cost ◽  
Battery Capacity ◽  
Battery Degradation ◽  
Installed Capacity

To achieve maximum profit by dispatching a battery storage system in an arbitrage operation, multiple factors must be considered. While revenue from the application is determined by the time variability of the electricity cost, the profit will be lowered by costs resulting from energy efficiency losses, as well as by battery degradation. In this paper, an optimal dispatch strategy is proposed for storage systems trading on energy arbitrage markets. The dispatch is based on a computationally-efficient implementation of a mixed-integer linear programming method, with a cost function that includes variable-energy conversion losses and a cycle-induced battery capacity fade. The parametrisation of these non-linear functions is backed by in-house laboratory tests. A detailed analysis of the proposed methods is given through case studies of different cost-inclusion scenarios, as well as battery investment-cost scenarios. An evaluation with a sample intraday market data set, collected throughout 2017 in Germany, offers a potential monthly revenue of up to 8762 EUR/MWh cap installed capacity, without accounting for the costs attributed to energy losses and battery degradation. While this is slightly above the revenue attainable in a reference application—namely, primary frequency regulation for the same sample month (7716 EUR/MWh cap installed capacity)—the situation changes if costs are considered: The optimisation reveals that losses in battery ageing and efficiency reduce the attainable profit by up to 36% for the most profitable arbitrage use case considered herein. The findings underline the significance of considering both ageing and efficiency in battery system dispatch optimisation.

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