Hierarchical Load Balancing Model by Optimal Resource Utilization

Powerful computational capabilities and resource availability at a low cost is the utmost demand for high performance computing. The resources for computing can viewed as the edges of an interconnected grid. It can attain the capabilities of grid computing by balancing the load at various levels. Since the nature of resources are heterogeneous and distributed geographically, the grid computing paradigm in its original form cannot be used to meet the requirements, so it can use the capabilities of the cloud and other technologies to achieve the goal. Resource heterogeneity makes grid computing more dynamic and challenging. Therefore, in this article the problem of scalability, heterogeneity and adaptability of grid computing is discussed with a perspective of providing high computing, load balancing and availability of resources.

Unique Taxonomy for Evaluating Fog Computing Services

Cloud computing has slowly but surely become the foremost service provider for information technology applications and platform delivery. However, Cloud issues continue to exist, like cyberattacks, slow last mile latency, and clouds lack client-centric and location-aware applications to process real time data for efficient and customized application delivery. As an alternative, Fog Computing has the potential to resolve these issues by extending the Cloud service provider's reach to the edge of the Cloud network model, right up to the Cloud service consumer. This enables a whole new state of applications and services which increases the security, enhances the cloud experience and keeps the data close to the user. This research article presents a review on the academic literature research work on Fog Computing, introduces a novel taxonomy to classify cloud products based on Fog computing elements and then determine the best fit Fog Computing product to choose for the Cloud service consumer.

A Study on Recent Trends in Cloud-Based Data Processing for IoT Era

Cloud computing has become one of the most important technologies in our day-to-day lives. The computing resources are delivered to the customers based on subscription basis via internet. Big data storage and processing are main application of cloud. Furthermore, the development of internet of things provides the platform for interconnecting devices over internet. This includes everything from mobile phones, washing machines, lamps, headphones, wearable devices, and everything else we never think of. This enables machine-to-machine communication, also applies to the components of the machine. The main objective of this chapter is to give an overview of cloud computing, big data, and internet of things and the advance research topics.

Security of Wireless Sensor Networks

Wireless sensor networks (WSNs) are comprised of large collections of small devices having low operating power, low memory space, and limited processing capabilities referred to as sensor nodes. The nodes in WSNs are capable of sensing, recording, and monitoring environmental conditions. Nowadays, a variety of WSNs applications can be found in many areas such as in healthcare, agriculture, industries, military, homes, offices, hospitals, smart transportation, and smart buildings. Though WSNs offer many useful applications, they suffer from many deployment issues. The security issue is one of them. The security of WSNs is considerable because of the use of unguided medium and their deployment in harsh, physically unprotected, and unattended environments. This chapter aims to discuss various security objectives and security attacks on WSNs and summarizes the discussed attacks according to their categories. The chapter also discusses different security protocols presented to prevent, detect, and recover the WSNs from various security attacks.

A Novel Trust Model for Secure Group Communication in Distributed Computing

Distributed networks are networks in which each node can act as a server or client and hence any node can provide service to any other node. In such a scenario, establishing a trust model between the service providing user and the service utilizing user is a challenging task. At present, only a few approaches are available in the past literature to provide this facility. Moreover, the existing approaches do not provide high trust accuracy. Therefore,a novel efficient trust model has been proposed in this article to support the secure dynamic group communication in distributed networks. The main advantage of the proposed work is that it provides higher trust accuracy. Moreover, the proposed work takes less memory for maintaining the trust values and increases the packet delivery ratio in comparison with other existing works which are in the literature.

Adaptive Threshold Based Scheduler for Batch of Independent Jobs for Cloud Computing System

Distributed systems are efficient means of realizing high-performance computing (HPC). They are used in meeting the demand of executing large-scale high-performance computational jobs. Scheduling the tasks on such computational resources is one of the prime concerns in the heterogeneous distributed systems. Scheduling jobs on distributed systems are NP-complete in nature. Scheduling requires either heuristic or metaheuristic approach for sub-optimal but acceptable solutions. An adaptive threshold-based scheduler is one such heuristic approach. This work proposes adaptive threshold-based scheduler for batch of independent jobs (ATSBIJ) with the objective of optimizing the makespan of the jobs submitted for execution on cloud computing systems. ATSBIJ exploits the features of interval estimation for calculating the threshold values for generation of efficient schedule of the batch. Simulation studies on CloudSim ensures that the ATSBIJ approach works effectively for real life scenario.

Impact of E-HRM Strategies on Organizational Innovation by Knowledge Repository as Mediating Role

The current study is intended to provide the analysis of the direct and indirect relationships between (E-HRM) strategies and organizational innovation through a knowledge repository as a mediation construct. From various previous studies, five (E-HRM) strategies constructs were adopted for this study. These include e-recruitment, e-selection, e-training, e-performance appraisal, and e-compensations, and used the mediating role of a knowledge repository for these constructs to improve organizational innovation. The study applied the Smart Partial Least Square (PLS) software to analyze the underlying relationships amongst the most relevant constructs between (E-HRM) strategies, knowledge repositories, and organizational innovation with a total of seven constructs. As a result of analysis of the findings from middle managers (n = 94) working for the Royal Jordanian airline. It was found that there was a strong and statistically positive significant relationship between several (E-HRM) strategies and organizational innovation by using the knowledge repository as a mediation construct.

Architecture for Big Data Storage in Different Cloud Deployment Models

Cloud Computing is a new computing model that distributes the computation on a resource pool. The need for a scalable database capable of expanding to accommodate growth has increased with the growing data in web world. More familiar Cloud Computing vendors such as Amazon Web Services, Microsoft, Google, IBM and Rackspace offer cloud based Hadoop and NoSQL database platforms to process Big Data applications. Variety of services are available that run on top of cloud platforms freeing users from the need to deploy their own systems. Nowadays, integrating Big Data and various cloud deployment models is major concern for Internet companies especially software and data services vendors that are just getting started themselves. This chapter proposes an efficient architecture for integration with comprehensive capabilities including real time and bulk data movement, bi-directional replication, metadata management, high performance transformation, data services and data quality for customer and product domains.

Novel Taxonomy to Select Fog Products and Challenges Faced in Fog Environments

This article describes how the rise of fog computing to improve cloud computing performance and the acceptance of smart devices is slowly but surely changing our future and shaping the computing environment around us. IoT integrated with advances in low cost computing, storage and power, along with high speed networks and big data, supports distributed computing. However, much like cloud computing, which are under constant security attacks and issues, distributed computing also faces similar challenges and security threats. This can be mitigated to a great extent using fog computing, which extends the limits of Cloud services to the last mile edge near to the nodes and networks, thereby increasing the performance and security levels. Fog computing also helps increase the reach and comes across as a viable solution for distributed computing. This article presents a review of the academic literature research work on the Fog Computing. The authors discuss the challenges in Fog environment and propose a new taxonomy.

The Optimal Checkpoint Interval for the Long-Running Application

For the distributed computing system, excessive or deficient checkpointing operations would result in severe performance degradation. To minimize the expected computation execution of the long-running application with a general failure distribution, the optimal equidistant checkpoint interval for fault tolerant performance optimization is analyzed and derived in this paper. More precisely, the optimal checkpointing period to determine the proper checkpoint sequence is proposed, and the derivation of the expected effective rate of the defined computation cycle is introduced. Corresponding to the maximal expected effective rate, the constraint of the optimal checkpoint sequence can be obtained. From the constraint of optimality, the optimal equidistant checkpoint interval can be obtained according to the minimal fault tolerant overhead ratio. By the numerical results, the proposal is practical to determine a proper equidistant checkpoint interval for fault tolerant performance optimization.