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The purpose of this study is to examine both the technical feasibility and the commercial viability of several demand-side integration (DSI) programs to utilize the charging flexibility of electric transport vehicles in a logistic facility. DSI is important for improving system reliability and assisting in integrating renewables into the energy system.

A pre-assessment of several DSI programs is performed by considering effort for implementation, costs and economic potential. Afterward, the most promising programs are compared economically on the basis of optimization methods and economic analysis. The analysis is based on a comprehensive electric mobility project dealing with electric transport vehicles operating in container terminals.

The pre-assessment of several potential DSI programs revealed that many of these programs are unsuitable, largely due to regulatory requirements. Although using DSI to optimize the company’s load is feasible, controlled charging based on variable prices is particularly advantageous because the implementation requires modest effort while identifying significant cost-saving potentials.

Based on the analysis, other companies using electric transport vehicles have a foundation for identifying the most promising demand-side management program.

While most research has focused on individually used electric vehicles, here commercial electric transport vehicles operating in closed systems were investigated as this area of application was found to be particularly suitable for participation in DSI programs.

A microcomputer‐based information management and capacity planning system for discrete parts manufacturing is described. The two primary components of the system are: (1) framework for information management and schedule generation, and (2) heuristic methods for workload balancing. The databases facilitate streamlining and standardisation of the information used on the production floor. The schedules generated by the system help the user in developing machine level capacity plans. The automatic workload balancing heuristics provide an effective way to refine the initial schedules to balance the workload and to satisfy user specified constraints.

The purpose of this paper is to construct a task assignment model for U-shaped production lines with collaborative task, which is optimized by minimizing the number of workers and balancing the workload of the operators. The ultimate goal is to increase productivity by increasing the U-line balance and balancing the load on the operators.

First, task selection and update mechanism are analyzed and the task selection mechanism suitable for collaborative task is proposed. Second, M-COMOSAL is obtained by improving the original COMOSAL. Finally, The M-COMOSAL algorithm and the COMAOSAL algorithm are used to perform job assignment on the double-acting clutch U-shaped assembly line.

According to the allocation scheme obtained by M-COMSOAL, the beat can be adjusted according to the change of order demand. The final allocation scheme is superior to the COMSOAL algorithm in terms of number of workers, working time, production tempo and balance rate. In particular, compared with the old scheme, the new scheme showed a decrease of 16.7% in the number of employees and a 18.8% increase in the production line balance rate. Thus, the method is helpful to reduce the number of operators and balance the workload.

The new algorithm proposed in this paper for the assignment of collaborative task can minimize the number of workers and balance the load of operators, which is of great significance for improving the balance rate of U-shaped production lines and the utilization of personnel or equipment.

This paper aims to propose a scheduling technique for parameter sweep workflows, which are used in parametric study and optimization. When executed in multiple parallel instances in the grid environment, it is necessary to address bottleneck and load balancing to achieve an efficient execution.

A bottleneck detection approach is based on commonly known performance metrics of grid resources. To address load balancing, a resource requirement similarity metric is introduced to determine the likelihood of the distribution of tasks across available grid resources, which is referred to as an execution context. The presence of a bottleneck and the execution context are used in the main algorithm, named ABeC, to schedule tasks selectively at run-time to achieve a better overall execution time or makespan.

According to the results of the simulations against four existing algorithms using several scenarios, the proposed technique performs, at least, similarly to the existing four algorithms in most cases and achieves better performance when scheduling workflows have a parallel structure.

The bottleneck detection and the load balancing proposed in this paper require only common resource and task information, rendering it applicable to most workflow systems. The proposed scheduling technique, through such selective behaviour, may help reduce the time required for the execution of multiple instances of a grid workflow that is to be executed in parallel.

Although proactive fault handling plans are widely spread, many unexpected data center outages still occurred. To rescue the jobs from faulty data centers, the authors propose a novel independent job rescheduling strategy for cloud resilience to reschedule the task from the faulty data center to other working-proper cloud data centers, by jointly considering job nature, timeline scenario and overall cloud performance.

A job parsing system and a priority assignment system are developed to identify the eligible time slots for the jobs and prioritize the jobs, respectively. A dynamic job rescheduling algorithm is proposed.

The simulation results show that our proposed approach has better cloud resiliency and load balancing performance than the HEFT series approaches.

This paper contributes to the cloud resilience by developing a novel job prioritizing, task rescheduling and timeline allocation method when facing faults.

Cloud users can access services at anytime from anywhere in the world. On average, Google now processes more than 40,000 searches every second, which is approximately 3.5 billion searches per day. The diverse and vast amounts of data are generated with the development of next-generation information technologies such as cryptocurrency, internet of things and big data. To execute such applications, it is needed to design an efficient scheduling algorithm that considers the quality of service parameters like utilization, makespan and response time. Therefore, this paper aims to propose a novel Efficient Static Task Allocation (ESTA) algorithm, which optimizes average utilization.

Cloud computing provides resources such as virtual machine, network, storage, etc. over the internet. Cloud computing follows the pay-per-use billing model. To achieve efficient task allocation, scheduling algorithm problems should be interacted and tackled through efficient task distribution on the resources. The methodology of ESTA algorithm is based on minimum completion time approach. ESTA intelligently maps the batch of independent tasks (cloudlets) on heterogeneous virtual machines and optimizes their utilization in infrastructure as a service cloud computing.

To evaluate the performance of ESTA, the simulation study is compared with Min-Min, load balancing strategy with migration cost, Longest job in the fastest resource-shortest job in the fastest resource, sufferage, minimum completion time (MCT), minimum execution time and opportunistic load balancing on account of makespan, utilization and response time.

The simulation result reveals that the ESTA algorithm consistently superior performs under varying of batch independent of cloudlets and the number of virtual machines’ test conditions.

The purpose of this paper is to present a methodology for parallel simulation that employs the discrete element method (DEM) and improves the cache performance using Hilbert space filling curves (HSFC).

The methodology is well suited for large-scale engineering simulations and considers modelling restrictions due to memory limitations related to the problem size. An algorithm based on mapping indexes, which does not use excessive additional memory, is adopted to enable the contact search procedure for highly scattered domains. The parallel solution strategy uses the recursive coordinate bisection method in the dynamical load balancing procedure. The proposed memory access control aims to improve the data locality of a dynamic set of particles. The numerical simulations presented here contain up to 7.8 millions of particles, considering a visco-elastic model of contact and a rolling friction assumption.

A real landslide is adopted as reference to evaluate the numerical approach. Three-dimensional simulations are compared in terms of the deposition pattern of the Shum Wan Road landslide. The results show that the methodology permits the simulation of models with a good control of load balancing and memory access. The improvement in cache performance significantly reduces the processing time for large-scale models.

The proposed approach allows the application of DEM in several practical engineering problems of large scale. It also introduces the use of HSFC in the optimization of memory access for DEM simulations.

This paper aims to deal with a modified-based approach for the evaluation of the steady state performances of three-phase self-excited induction generator (SEIG) feeding single-phase load.

Using the symmetrical components method, the proposed approach is based on a modified model of unbalanced three-phase SEIG, which is formulated similarly to the well-known model of balanced three-phase SEIG. Owing to this modified model, the determination of the SEIG operating point amounts to the resolution of two semi-decoupled nonlinear equations for two unknowns; the magnetizing reactance and the per-unit frequency. A simple resolution method based on an iterative two-step technique is used. The results obtained by the proposed approach are compared with those given by a conventional approach and are validated experimentally.

The proposed approach is as accurate as the conventional approach. Further, for the same accuracy degree, the proposed approach permits to speed up the resolution when compared to the conventional approach, as only few iterations are required for the convergence. The proposed approach was also successfully used for the steady state analysis of SEIG under generalized unbalanced loading conditions.

The determination of the operating point of the generator is based on a modified model of the generator and a simple iterative resolution method. The calculation technique can be implemented on low resource controller to provide online voltage control of the SEIG.

The paper contains two main originalities. The first one consists in a modified formulation of the SEIG model under unbalanced loading conditions. The modified formulation permits the use of the well-known model of balanced three-phase SEIG. Unlike previous ones reported in the literature, the proposed model does not require tedious algebraic manipulations. The second originality is the use of two-step technique to solve the equations, which permits to avoid laborious mathematical derivations and manipulating high-order polynomials.

With the rapid growth of wireless sensor networks (WSNs), they have become an integral and substantial part of people's life. As such WSN stands as an assuring outlook, but because of sensor's resource limitations and other prerequisites, optimal dual route discovery becomes an issue of concern. WSN along with central sink node is capable of handling wireless transmission, thus optimizing the network's lifetime by selecting the dual path. The major problem confronted in the application of security mechanisms in WSNs is resolving the issues amid reducing consumption of resources and increases security.

According to the proposed system, two metrics, namely, path length and packets delivery ratio are incorporated for identifying dual routes amid the source and destination. Thereafter by making use of the distance metric, the optimal dual route is chosen and data transmission is carried out amid the nodes. With the usage of the recommended routing protocol high packet delivery ratio is achieved with reduced routing overhead and low average end to end delay. It is clearly portrayed in the simulation output that the proposed on demand dual path routing protocol surpasses the prevailing routing protocol. Moreover, security is achieved make use of in accord the data compression reduces the size of the data. With the help of dual path, mathematical model of Finite Automata Theory is derived to transmit data from source to destination. Finite Automata Theory comprises Deterministic Finite Automata (DFA) that is being utilized for Dual Path Selection. In addition, data transition functions are defined for each input stage. In this proposed work, another mathematical model is 10; introduced to efficiently choose an alternate path between a receiver and transmitter for data transfer with qualified node as relay node using RR Algorithm. It also includes Dynamic Mathematical Model for Node Localization to improve the precision in location estimation using Node Localization Algorithm. As a result a simulator is built and various scenarios are elaborated for comparing the performance of the recommended dual path routing protocol with respect to the prevailing ones.

Reliability and fault-tolerance: The actual motive in utilizing the approach of multipath routing in sensor network was to offer path resilience in case of a node or link failures thus ascertaining reliable transmission of data. Usually in a fault tolerant domain, when the sensor node is unable to forward the data packets to the sink, alternative paths can be utilized for recovering its data packets during the failure of any link/node. Load balancing: Load balancing involves equalizing energy consumption of all the existing nodes, thereby degrading them together. Load balancing via clustering improves network scalability. The network's lifetime as well as reliability can be extended if varied energy level's nodes exist in sensor node. Quality of service (QoS): Improvement backing of quality of service with respect to the data delivery ratio, network throughput and end-to-end latency stands very significant in building multipath routing protocols for various network types. Reduced delay: There is a reduced delay in multipath routing since the backup routes are determined at the time of route discovery. Bandwidth aggregation: By dividing the data toward the same destination into multiple streams (by routing all to a separate path) can aggregate the effective bandwidth. The benefit being that, in case a node possesses many links with low bandwidth, it can acquire a bandwidth which is more compared to the individual link.

Few more new algorithms can be used to compare the QoS parameters.

Proposed mechanism with feedback ascertains improvised delivery ratio compared to the single path protocol since in case of link failure, the protocol has alternative route. In case there are 50 nodes in the network, the detection mechanism yields packet delivery of 95% and in case there are 100 nodes, the packet delivery is lowered to 89%. It is observed that the packet rate in the network is more for small node range. When the node count is 200, the packet ratio is low, which is lowered to 85%. With a node count of 400, the curve depicts the value of 87%. Hence, even with a decrease in value, it is superior than the existing protocols. The average end-to-end delay represents the transmission delay of the data packets that have been successfully delivered as depicted in Figure 6 and Table 3. The recommended system presents the queue as well as the propagation delay from the source to destination. The figure depicts that when compared to the single path protocol, the end-to-end delay can be reduced via route switching. End-to-end delay signifies the time acquired for the delay in the receival of the the retransmitted packet by each node. The comparison reveals that the delay was lower compared to the existing ones in the WSN. Proposed protocol aids in reducing consumption of energy in transmitter, receiver and various sensors. Comparative analysis of energy consumptions of the sensor in regard to the recommended system must exhibit reduced energy than the prevailing systems.

On demand dual path routing protocol. Hence it is verified that the on demand routing protocol comprises DFA algorithms determines dual path. Here mathematical model for routing between two nodes with relay node is derived using RR algorithm to determine alternate path and thus reduce energy consumption. Another dynamic mathematical model for node localization is derived using localization algorithm. For transmitting data with a secure and promising QoS in the WSNs, the routing optimization technique has been introduced. The simulation software environment follows the DFA. The simulation yields in improvised performance with respect to packet delivery ratio, throughput, average end-to-end delay and routing overhead. So, it is proved that the DFA possesses the capability of optimizing the routing algorithms which facilitates the multimedia applications over WSNs.

The purpose of this study is to eliminate voltage harmonics and instantly measure the positive sequence fundamental voltage during unbalanced grid conditions, the dual second-order generalized integrator-phase locked loop used in series hybrid filter structures is often used in grid synchronisation in three-phase networks. The preferred series active hybrid power filter simultaneously compensates for voltage balancing and current harmonics generated by non-linear loads.

This paper examines the use of renewable energy–based microgrid (MG) to support linear and non-linear loads. It is capable of synchronising with both the utility and the diesel generator unit. Power is transferred from the grid throughout a stable grid situation with minimum renewable energy generation and maximum load demand. It synchronises with diesel generator set to supply the load and form an AC MG during outages and minimum renewable power generation. In islanded and grid-connected mode, the voltage and power quality issues of the MG are controlled by static synchronous compensator and series hybrid filter.

Because of the presence of non-linear loads, reactive loads in the distribution system and the injection of wind power into the grid integrated system result power quality issues like current harmonics, voltage fluctuations, reactive power demand, etc.

The voltage at the load (linear and non-linear) is regulated, and the power factor and total harmonic distortions were improved with the help of the series hybrid filter.