Modeling Maintenance Productivity Measurement of Engineering Production Systems: Discrete Event Simulation Approach

Modeling and simulation of industrial information communication systems and networks is one of the major concerns of productivity engineers for the establishment of productivity standards in virtually all functional areas of an industrial organization. Maintenance function is one of such areas that have always engaged the attention of engineering productivity practitioners. However, one of the basic prob- lems is the difficulty in setting up integrated but easy and practical measurement schemes. Even where the measures are set up, the approaches to measurement sometimes are conflicting. Therefore the need for an integrated approach to optimize the basket of parameters measured remains. In this chapter the author attempts to identify approaches in integrated and systematic maintenance productivity measurement and create models for optimising total productivity in maintenance systems. Visual yardstick, utility, queuing systems and simulations approaches for measurement of maintenance productivity are all discussed with a particular focus on markov chain approach for stochastic break- downs in repairable systems.. The chapter also shows how understanding the impact of plant failure and repair/service distributions assists in providing measures for maintenance productivity using discrete event system simulation

Empirical analysis of dynamic load balancing techniques in cloud computing

Virtualization, dispersed registration, systems administration, programming, and web administrations are all examples of distributed computing. Customers, datacenters, and scattered servers are just a few of the components that make up a cloud. It includes things like internal failure adaption, high accessibility, flexibility, adaptability, lower client overhead, lower ownership costs, on-demand advantages, and so on. The basis of a feasible load adjusting computation is key to resolving these challenges. CPU load, memory limit, deferral, and system load are all examples of heaps. Burden adjustment is a method for distributing the load across the many hubs of a conveyance framework in order to optimize asset utilization and employment response time while avoiding a situation where some hubs are heavily loaded while others are idle or performing little work. Burden adjustment ensures that at any one time, each processor in the framework or each hub in the system does about the same amount of work. This method may be initiated by the sender, the collector, or the symmetric sort (the blend of sender-started and recipient started types). With some example data center loads, the goal is to create several dynamic load balancing techniques such as Round Robin, Throttled, Equally Spread Current Execution Load, and Shortest Job First algorithms

An effective transmit packet coding with trust-based relay nodes in VANETs

ehicular ad-hoc networks (VANETs) are characterized by limited network resources such as limited bandwidth and battery capacity. Hence, it is necessary that unnecessary use of network resources (such as unnecessary packet transfers) is reduced in such networks so that the available power can be conserved for efficient multicast communications. In this paper, we have presented a Transmit Packet Coding (TPC) Network Coding in VANET to ensure reliable and efficient multicasting. With network coding, the number of transmitted packets over the network can be reduced, ensuring efficient utilization of network devices and resources. Here, the trust-based graph optimization is performed using Cuckoo search algorithm to select the secure relay nodes. The experimental results showed the superiority of the presented approach compared to the existing techniques in terms of throughput, latency, hop delay, packet delivery ratio, network decoder outage probability, and block error rate

Clustering Algorithms for Scale-free Networks and Applications to Cloud Resource Management

In this paper we introduce algorithms for the construction of scale-free networks and for clustering around the nerve centers, nodes with a high connectivity in a scale-free networks. We argue that such overlay networks could support self-organization in a complex system like a cloud computing infrastructure and allow the implementation of optimal resource management policies.Comment: 14 pages, 8 Figurs, Journa

Cloud service analysis using round-robin algorithm for quality-of-service aware task placement for internet of things services

Round-robin (RR) is a process approach to sharing resources that requires each user to get a turn using them in an agreed order in cloud computing. It is suited for time-sharing systems since it automatically reduces the problem of priority inversion, which are low-priority tasks delayed. The time quantum is limited, and only a one-time quantum process is allowed in round-robin scheduling. The objective of this research is to improve the functionality of the current RR method for scheduling actions in the cloud by lowering the average waiting, turnaround, and response time. CloudAnalyst tool was used to enhance the RR technique by changing the parameter value in optimizing the high accuracy and low cost. The result presents the achieved overall min and max response times are 36.69 and 650.30 ms for running 300 min RR. The cost for the virtual machines (VMs) is identified from $0.5 to$3. The longer the time used, the higher the cost of the data transfer. This research is significant in improving communication and the quality of relationships within groups