Network and traffic engineering in emerging distributed computing applications

This book focuses on network management and traffic engineering for Internet and distributed computing technologies, as well as present emerging technology trends and advanced platform

Joint optimization of rule placement and traffic engineering for QoS provisioning in software defined network

Software-Defined Network (SDN) is a promising network paradigm that separates the control plane and data plane in the network. It has shown great advantages in simplifying network management such that new functions can be easily supported without physical access to the network switches. However, Ternary Content Addressable Memory (TCAM), as a critical hardware storing rules for high-speed packet processing in SDN-enabled devices, can be supplied to each device with very limited quantity because it is expensive and energy-consuming. To efficiently use TCAM resources, we propose a rule multiplexing scheme, in which the same set of rules deployed on each node apply to the whole flow of a session going through but towards different paths. Based on this scheme, we study the rule placement problem with the objective of minimizing rule space occupation for multiple unicast sessions under QoS constraints. We formulate the optimization problem jointly considering routing engineering and rule placement under both existing and our rule multiplexing schemes. Via an extensive review of the state-of-the-art work, to the best of our knowledge, we are the first to study the non-routing-rule placement problem. Finally, extensive simulations are conducted to show that our proposals significantly outperform existing solutions.

An experimental study on the failure tolerant control of a redundant planar serial manipulator via pseudo-inverse approach

In this paper, fault-tolerant control of redundant planar serial manipulators has been investigated experimentally via an offline method called psuedo-inverse reconfiguration method. Minimizing the end-effector's velocity jump via an optimal mapping of joint failures into healthy joints velocity space can be regarded as the main contribution of this reconfiguration approach. This algorithm has been simulated and implemented on a four-link serial manipulator named as TaArm. It should be mentioned that for simulation and practical tests, C++ programming language in QtCreator environment has been used which provided high computational speed. Two scenarios has been selected for simulation and implementation studies and results shows that the algorithm considerably removes the velocity jump of the end-effector in both simulation and experimetal studies.

Control layer resource management in SDN-IoT networks using multi-objective constraint

Software Defined Networking (SDN) and Internet of Things (IoT) integration has thrown many critical challenges. Specifically, in heterogeneous SDN-IoT ecosystem, optimized resources utilization and effective management at the control layer is very difficult. This mainly affects the application specific Quality of Service (QoS) and energy consumption of the IoT network. Motivated from this, we propose a new Resource Management (RM) method at the control layer, in distributed SDN-IoT networks. This paper starts with reasons that why at control layer RM is more complex in the SDN-IoT ecosystem. After-that, we highlight motivated examples that necessitate to investigate new RM methods in SDN-IoT context. Further, we propose a novel method to compute controller performance. Theoretical analysis is conducted to prove that the proposed method is better than the existing methods.

Aggregation on the fly: Reducing traffic for big data in the cloud

As a leading framework for processing and analyzing big data, MapReduce is leveraged by many enterprises to parallelize their data processing on distributed computing systems. Unfortunately, the all-to-all data forwarding from map tasks to reduce tasks in the traditional MapReduce framework would generate a large amount of network traffic. The fact that the intermediate data generated by map tasks can be combined with significant traffic reduction in many applications motivates us to propose a data aggregation scheme for MapReduce jobs in cloud. Specifically, we design an aggregation architecture under the existing MapReduce framework with the objective of minimizing the data traffic during the shuffle phase, in which aggregators can reside anywhere in the cloud. Some experimental results also show that our proposal outperforms existing work by reducing the network traffic significantly.

Software engineering for multi-tenancy computing challenges and implications

Multi-tenancy is a cloud computing phenomenon. Multiple instances of an application occupy and share resources from a large pool, allowing different users to have their own version of the same application running and coexisting on the same hardware but in isolated virtual spaces. In this position paper we survey the current landscape of multi-tenancy, laying out the challenges and complexity of software engineering where multi-tenancy issues are involved. Multitenancy allows cloud service providers to better utilise computing resources, supporting the development of more exible services to customers based on economy of scale, reducing overheads and infrastructural costs. Nevertheless, there are major challenges in migration from single tenant applications to multi-tenancy. These have not been fully explored in research or practice to date. In particular, the reengineering effort of multi-tenancy in Software-as-a-Service cloud applications requires many complex and important aspects that should be taken into consideration, such as security, scalability, scheduling, data isolation, etc. Our study emphasizes scheduling policies and cloud provisioning and deployment with regards to multi-tenancy issues. We employ CloudSim and MapReduce in our experiments to simulate and analyse multi-tenancy models, scenarios, performance, scalability, scheduling and reliability on cloud platforms.

Longitudinal study of computer usage in flexible engineering education

A longitudinal analysis of computer usage by commencing students in Deakin University's undergraduate engineering and technology programs over the period 1998 to 2001 revealed that; access to computers was at high levels; mean computer usage for off campus students had not changed significantly, but had risen significantly for on campus students; while access to the Internet / WWW had not increased significantly, reported regular use of the Internet / WWW had risen significantly; while most students continued to report their source of Internet / WWW access as either home or university, the proportion reporting home as their source of access had risen significantly; and the reported regular use of email rose significantly. Other results are also presented.

These results imply that commencing engineering and technology students are well placed to adopt online delivery and support of teaching and learning. However, while it might now be reasonable to assume that all students have access to computers and the Internet, the experiences of on campus students in computer laboratories with broadband network access will be different from off campus students accessing the Internet via a dialup modem connection. A small proportion of commencing students were unaware of the computing facilities provided by the university; an orientation program covering computing facilities and services would benefit all commencing students.

Foundation software engineering practices for capstone projects and beyond

This paper outlines an introductory course in software engineering undertaken by computing students at Deakin University. The course focuses on areas of that are often not emphasized in introductory software engineering. These areas include formal problem solving, management of software development, communication, and working in groups. The approach includes the application of concepts in a collaborative group setting. Enhancements to the course have been made over a number of semesters and evidence suggests that our overall approach is working. The skills acquired by students taking this course can be applied to later courses in software engineering, particularly the capstone project course, and to professional life

The design and development of an integrated system for object-oriented finite element computing

Finite Element Method (FEM) is widely used in Science and Engineering since 1960’s. The vast majority of FEM software is procedure-oriented. However, this conventional style of designing FEM software encounters problems in maintenance, reuse, and expansion of the software. Recently the object-oriented finite element method attracts the attention of lots of researchers, and now there is a growing interest in this method. In this paper, the object-oriented finite element (OOFE) is briefly introduced. Then the design and development of an integrated OOFE system is described. A comparison of the integrated OOFE system and a procedure-oriented system shows that our OOFE system has many advantages.

Parallel I/O scheduling in the presence of data duplication on multiprogrammed cluster computing systems

The widespread adoption of cluster computing as a high performance computing platform has seen the growth of data intensive scientific, engineering and commercial applications such as digital libraries, climate modeling, computational chemistry, computational fluid dynamics and image repositories. However, I/O subsystem performance has not been keeping pace with processor and memory performance, and is fast becoming the dominant factor in overall system performance.  Thus, parallel I/O has become a necessity in the face of performance improvements in other areas of computing systems. This paper addresses the problem of parallel I/O scheduling on cluster computing systems in the presence of data replication.  We propose two new I/O scheduling algorithms and evaluate the relative performance of the proposed policies against two existing approaches.  Simulation results show that the proposed policies perform substantially better than the baseline policies.

Conceptions of teaching with integrity online in higher education: a case in the field of engineering

The viewpoints of academic teaching staff take centre stage in the analysis of the changing conceptions of what it means to act with integrity when teaching online. To teach with integrity in contemporary online-supported environments in higher education is not necessarily to teach the same as if one would in teaching regularly face-to-face in the classroom. The paper argues that to teach with integrity online is to teach differently. With integrity both enhanced and in some respects diminished in teaching online, the apparent contradiction can only be resolved through developing conceptions of what teaching with integrity means in the contemporary world of higher education. Implications are drawn in the context of teaching extended and wholly online units in the field of engineering.

An evolutionary computing approach to minimize dynamic hedging error

The objective of our present paper is to derive a computationally efficient genetic pattern learning algorithm to evolutionarily derive the optimal rebalancing weights (i.e. dynamic hedge ratios) to engineer a structured financial product out of a multiasset, best-of option. The stochastic target function is formulated as an expected squared cost of hedging (tracking) error which is assumed to be partly dependent on the governing Markovian process underlying the individual asset returns and partly on
randomness i.e. pure white noise. A simple haploid genetic algorithm is advanced as an alternative numerical scheme, which is deemed to be
computationally more efficient than numerically deriving an explicit solution to the formulated optimization model. An extension to our proposed scheme is suggested by means of adapting the Genetic Algorithm parameters based on fuzzy logic controllers.

An autonomic management system for service oriented enterprise grid computing

Grid computing and service oriented architectures improve the way computational tasks are performed. Through this research a management system, utilising the autonomic characteristics of self discovery and negotiation, self configuration and self healing, was designed and implemented, ultimately removing the need for users to know the intricacies of these systems.